The MixCommander product meets a number of objectives:

• Tracking the overall performance of your campaigns.

• Understanding your customers’ journeys before they convert on your site.

• Simulating new attribution models and comparing their impact on your ROI (return on investment) analysis.

• Analyzing the ROI of your campaigns and understanding what the most effective paid or natural levers are.

Customer Journey

Before a visitor converts on your site, they come into contact with it through campaigns or natural levers. The total sum of these points of contact (or touchpoints) is called the customer journey. Each touchpoint contains a “channel“, a “source” and a “lookback window“.

The conversion can be attributed to different touchpoints depending on which attribution model is selected.

The “customer journey” contains all the touchpoints concerning a visitor until they convert on the site.

Touchpoints

The above diagram represents a visitor’s customer journey. It consists of 5 touchpoints leading the user to conversion on the site:

1. Display Hi-Media

2. SEM Google

3. Retargeting Criteo

4. SEO Bing

5. Direct access

Diagram interpretation

The visitor has seen a display banner without going to the site, then clicked on an SEM link, a Retargeting banner, or an SEO link without converting to the site, and, in the end, accessed the site directly to finalize the conversion. The visitor came into contact with the brand 5 times and went to the site 4 times before converting.

Please note: A touchpoint always contains a Channel and may contain a Source.

Channels

The Channel denotes the type of traffic source. There are two types of channels:

1) – Paid channels: these types of traffic sources generate traffic on your site through campaigns. A budget is thus allocated to them.

The paid channels offered in the MixCommander product by default are:

• Affiliation: “Affiliation” is also called “performance-based marketing”. In this system the affiliates are often paid for each generated conversion (purchase or lead).

• Display: “Display” is a channel that displays banners, links, logos, etc. to promote a brand.

• ShopBot: the “ShopBot” channel denotes shopping robots (a.k.a. price comparison services, shopping robots or smart shopping agents).

• SEM: the “SEM” channel denotes sponsored links on search engines.

• Branded SEM: the “Branded SEM” channel denotes sponsored links on search engines for which the keyword is the brand name.

• Email: the “Email” channel denotes commercial emails sent to a group of people.

• Retargeting: “Retargeting” denotes the retargeting of visitors who have already been in contact with the brand or visited the site without converting.

• Ad Exchange: “Ad Exchange” is a channel that aggregates RTB (Real Time Bidding) display campaigns.

• Social ads: “Social Ads” are ads displayed on social media.

• Mobile channel: the “Mobile channel” denotes ads displayed on mobile apps (smartphones and tablets).

• Partners: the “Partners” channel aggregates traffic generated by partner sites.

2) – Organic (or Natural) Channels: these are types of traffic sources that are not bound by purchasing advertising space in a given medium.

Please note: You may need to allocate a non-media budget to organic channels (e.g.: SEO firm fees for improving your site’s search engine listing, email routing fees, etc.).

The natural channels offered in the MixCommander product by default are:

• SEO: the “SEO” channel denotes natural searches on search engines (unsponsored links).

• Brand: the “Brand” channel denotes natural searches (SEO) on search engines when the search keyword is the brand name.

• Direct Access: “Direct access” denotes access to the site via the browser’s navigation bar or “favorites” menu.

• Referrer: the “Referrer” denotes traffic from sites containing a link to your site.

• Social Networks: the “Social Networks” channel aggregates traffic generated by free campaigns on social media.

• Loyalty email: the “Loyalty email” channel aggregates emails sent to visitors already in the company’s contacts database.

• Service emailing: the “Service emailing” channel denotes service emails sent to visitors (e.g.: notifications, passwords resent, etc.).

• Social media animation: the “Social media animation” channel denotes traffic from social media that is not included in “Social Ads” or “Social Networks”. This may for instance concern a dedicated campaign run on social media by your community manager.

Sources

The Source denotes the partner who generated traffic on the site. A channel may not have a source (that is the case for direct access, which is not generated by any outside provider).

Here are a few examples of sources: Google, Criteo, Tradedoubler, Zanox, Facebook, YouTube, etc.

In the above diagram the visitor went through 5 different channels before converting:

1. Display

2. SEM

3. Retargeting

4. SEO

5. Direct access

Again in the above diagram, the visitor went through 4 sources before converting:

1. Hi-Media

2. Google

3. Criteo

4. Bing

Post-click, post-impression & lookback window

Post-click, Post-Impression

When a visitor gets to a site, they go through certain steps called touchpoints. These touchpoints can correspond to 2 types of actions:

• A click

• An impression or a view (means a banner posted on a third-party site)

Lookback window

It defines the period of validity of a channel click/impression and a source in the customer journey and is specific to an attribution model. If a channel’s lookback window is exceeded, the touchpoint is ignored when the conversion is attributed.

The lookback window is thus specific to the type of action (click/impression), the channel/source and depends on the selected attribution model.

The most commonly used lookback window for impression is “24 hours Post–Impression“. This means that if the banner impression occurred 24 hours before the conversion, it is taken into account by the attribution model. It is ignored otherwise.

The most commonly used lookback window for click is “30 days Post–Click“. This means that if the banner impression occurred 30 days before the conversion, it is taken into account by the attribution model, otherwise it is ignored.

In the above diagram, if the lookback window is the same for all channels, namely “30 days Post-Click” and “24 hours Post-Impression”:

• The touchpoints whose action type is the click (namely “SEM Google”, “Retargeting Criteo”, “SEO Bing”, “Direct Access”) are deemed valid because they were all made less than 30 days before the sale.

• The touchpoint whose action type is the impression (namely “Display – Hi-Media”) on the other hand is deemed invalid because it was made more than 24 hours before the sale.

It is then the attribution model that defines which channel(s) and source(s) will be attributed the sale.

Examples

An “attribution model” is a particular “view” of the customer journeys of the site’s visitors.

It attributes the conversion to one or more channels that played a part in the conversion.

The most commonly used attribution model nowadays is the “Last paid click” model. This model consists in attributing the sale to the last channel in the customer journey before conversion.

Commanders Act’s MixCommander product lets you transcend the “Last click” model and analyze other attribution models, such as “First click“, which consists in attributing the sale to the first touchpoint on the customer journey, the “U Model“, or the “linear model“, which consist in attributing the conversion to all the touchpoints that played a part and vary the conversion amount attributed to each touchpoint.

Eleven databases for creating your attribution models are available in MixCommander, including the “U model“, the “First Click“, the “Last Click“, the “Linear” and the “Exponential“, among others.

Last Paid Click

Scenario 1: the selected attribution model is “Last Paid Click”, so the conversion is attributed to the last click on a paid channel before conversion.

In our example, the conversion is attributed to Retargeting for the 3 represented conversions, and Retargeting recovers 100% of the conversion amount.

First Touchpoint

Scenario 2: the selected attribution model is “First touchpoint” (click or impression/paid or natural), so the conversion is attributed to the first paid or natural channel on the customer journey. In our example, 2 conversions are attributed to Display, and one conversion is attributed to Social Ads. Each winning channel recovers 100% of the conversion amount.

Contribution

Scenario 3: the selected attribution model is one that focuses on the contribution conversion levers: each channel is thus taken into account as long as it played a part in the customer journey.

In our example, the conversion is attributed to all the channels on the 3 customer journeys, and the conversion amount share attributed to each of them depends on the type of attribution model selected (with the attribution model “U model“, the first and last touchpoint receive a bigger share of the sale than the others; with the linear attribution model, each touchpoint gets the same share of the sale, etc.).

These 3 diagrams show that the customer journey is interpreted in a totally different way depending on which attribution model is selected:

• In the first scenario the most effective one appears to be Retargeting.

• In the second scenario the impression is exploited and the Display and Social Ads channels appear to be more effective.

• In the third scenario, each channel that at some point played a part in the conversion is taken into account.

So it is important to test as many attribution models as possible to fully understand your users’ journeys before conversion and the role your partner solutions play.

MixCommander provides numerous out-of-the-box attribution reports and has over 40 metrics and attributes to choose from when designing custom reports. Additionally, CRM and device filters can be applied to these reports to isolate campaign performance by specific audience segments.

Reports can easily be shared among your team and with your third-party vendors, and dashboards can be created using drag-and-drop functionality.

The MixCommander product meets a number of objectives:

• Tracking the overall performance of your campaigns.

• Understanding your customers’ journeys before they convert on your site.

• Simulating new attribution models and comparing their impact on your ROI (return on investment) analysis.

• Analyzing the ROI of your campaigns and understanding what the most effective paid or natural levers are.

The MixCommander module is set up by the consultant in charge of your account.

The articles in this section explain the configuration process for your site to generate the attribution reports you can access through the interface.

The Setup consists of two–steps:

• Identification of sources of traffic on your site.

• Data collection on your site.

We also explain what data is collected on the Commanders Act servers when you install the MixCommander product.

The first stage of the configuration process consists in identifying sources of visitor traffic. Commanders Act can track two elements:

Clicks on links and banners: clicks are tracked by means of the Commanders Act redirect URL.

Banner impression: impressions are tracked thanks to a tracking pixel integrated into your banners.

Click tracking

Commanders Act offers you redirect URLs to track clicks and banner impressions.

This method allows you to capture very detailed information, as the click is tracked by the Commanders Act servers when the web users click a link or banner, and before they reach your site, as the following diagram shows:

The redirect URL can be enriched with numerous parameters to capture as much information as possible about your campaigns (e.g.: channel, source, campaign, format, keyword, affiliate ID, etc.). So tracking your campaigns with Commanders Act redirection lets you access a great deal of information and analyses besides the channel and the source.

TagCommander redirections should be set up on all your campaigns by your traffic manager, agency or the person in charge of campaign trafficking.

Two elements are at your disposal to help you construct Commanders Act redirection URLs:

• An Excel deliverable provided by the consultant in charge of setup, which lists all the redirect URLs needed for each of your channels.

• A URL builder, available in the MixCommander interface.

Structure of the click redirection URL

This is Commanders Act’s redirection URL and its structure:

• $subdomain$.commander1.com: this part of the URL is your sub-domain + the Commanders Act domain name. This sends a hit to the Commanders Act servers. The sub-domain is configured and communicated by the Commanders Act consultant at the beginning of the project. It is usually your brand or site name.

• c3: this ID tells Commanders Act that the user action was a click (“c” for “click”). Conversely, impressions are identified with the v3 parameter (“v” for “view”).

• $siteID$: $siteID$ must be completed with your customer site ID at Commanders Act’s (this parameter is communicated by the Commanders Act consultant).

• $channel$ and $source$: “chn” lets you specify the Channel (= marketing lever) and “src” the Source (= partner). These 2 parameters must be provided for all implemented campaigns.

You can add other parameters of your choice in the redirect URL: these parameters are important because they let you track more information and analyze more elaborate elements than merely the “channel” and “source” (e.g.: keyword, campaign, etc.). If you want to add more parameters to your campaigns, seek advice from the consultant in charge of your account or from the Commanders Act support agents.

Parameters should be added in the following format: “&param=value”.

E.g.:

No accents or special characters can be used in these parameter values.

• $URL$: the landing page URL must always be included to enable Commanders Act to redirect web users to the right page when the click is logged on our servers.

Impression tracking

Impressions can be tracked by inserting a Commanders Act impression pixel in your banners. This lets you capture the fact that a visitor has viewed the banner of one of your campaigns without necessarily clicking on it and therefore without visiting your site there and then, as the following diagram shows:

The Commanders Act impression pixel can be enriched with numerous parameters enabling you to capture as much information as possible about your campaigns (e.g.: channel, source, campaign, format, keyword, affiliate ID, etc.). Tracking your campaigns with a Commanders Act impression pixel lets you access a great deal of information and analyses (besides the channel and the source) concerning banner impressions.

TagCommander impression pixels should be set up on all your campaigns by your traffic manager, agency or the person in charge of campaign trafficking.

Two elements are at your disposal to help you construct Commanders Act impression pixels:

• An Excel deliverable provided by the consultant in charge of setup, which lists all the redirect URLs needed for each of your channels.

• A URL builder, available in the MixCommander interface.

Impression pixel structure

• $subdomain$.commander1.com: this part of the URL is your sub-domain + the TagCommander domain name. This sends a hit to the TagCommander servers.The sub-domain is configured and communicated by the TagCommander consultant at the beginning of the project. It is usually your brand or site name.

• v3: this ID tells TagCommander that the user action was an impression (“v” for “view”). Conversely, clicks are identified with the c3 parameter (“c” for “click”).

• $siteID$: $siteID$ must be completed with your customer site ID at TagCommander (this parameter is communicated by the TagCommander consultant).

• $channel$ and $source$: “chn” lets you specify the Channel (= marketing lever) and “src” the Source (= partner). These 2 parameters must be provided for all implemented campaigns.

You can add other parameters of your choice in the redirect: these parameters are important because they let you track more information and analyze more elaborate elements than merely the “channel” and “source” (e.g.: keyword, campaign, etc.). If you want to add more parameters to your campaigns, seek advice from the consultant in charge of your account or from TagCommander support. Parameters should be added in the following format: “&param=value”.

E.g.:

No accents or special characters can be used in these parameter values.

• $CACHEBUSTER$: a random number or timestamp is required to avoid caching and to log the precise number of banner views.

Channels Calculation algorithm

focus on commanders mix hits

The “Conversion Details” report shows the winning channel(s) and source(s) for each conversion according to the selected attribution model.

The attribution model selected by default is “Last Touch Point” (= the conversion is attributed to the last channel in the customer journey, just before conversion). So the “Attribution” column shows the name of the winning channel with the “Last Touch Point” vision (1):

You can view the customer journey of your conversion in greater detail by clicking the magnifying glass next to the order ID.

A window pops up, listing the following elements:

– The “Conversion Details” section: it gives the date and user agent of the conversion (1).

– The “Customer journey” tab itemizes the contents of the customer journey to conversion (2):

• The “Position” column indicates the position of the touchpoint in the customer journey.

• The “Type” column indicates whether the touchpoint is a click or an impression.

• The “Touch point” column mentions the name of the channel and the source.

• The “Date event” column indicates the date and time of the touchpoint.

• The “Weight attribution” indicates the percentage of the sale the touchpoint is given.

Note: The “Touchpoint” on the first row (1) indicates the winning touchpoint according to the selected attribution model. In the screenshot below, given that the selected attribution model is “Last Click”, the winner of the conversion is the last touchpoint on the customer journey, namely the “SEO/google” click of 13/12/2015 at 00:44:03

To show attribution results conversion by conversion according to another attribution model, select the model of your choice in the “Attribution Model” dropdown menu (1).

If a single channel/source pair wins the conversion, you see it directly in the “Attribution” column. Otherwise, a message tells you how many channels/sources won the conversion (2):

The Conversion Details area allows you to:

Filter your data on the order ID (1)., and choose several other filters (below)

Click “PREVIEW” to apply your filters(2):

When the filter is applied, the five boxes to the right and the conversion details data underneath will automatically refresh and yield the filtered results.

Exporting the “conversion details” report:

Click the “Export” button to transfer all data from the report as an Excel file:

These are the options available:

1) – You can create a “simple” report that will contain the following elements:

• Identifier ID: TCID cookie (user identifier)

• Order ID: conversion ID

• Date: conversion date

• Amount: conversion amount

• Fraud Score: fraud score to measure the conversions reliability

• Winner channel: channel the conversion is allocated to according to the selected attribution model

• Winner source: source the conversion is allocated to according to the selected attribution model

• Winner campaign: campaign the conversion is allocated to according to the selected attribution model

• Winner device: device the purchase was made on (detected automatically)

• Click: number of clicks in the customer journey prior to the conversion

• Impression: number of touchpoints in the customer journey prior to the conversion

• Touchpoint: number of touchpoints in the customer journey

• Time to convert: time elapsed since the first touchpoint in the customer journey and the conversion

• Browser: browser used when the conversion happened

• IP: conversion IP

• Conversion segments: segment(s) associated to(s) the conversion (ex: “known/new client”, “pays”, etc.)

2) – You can create an “advanced” report containing data from “simple” reports and new information related to the customer journey’s touchpoints:

• Date: conversion OR touchpoint time and date

• Channel: touchpoint’s channel

• Source: touchpoint’s source

• Campaign: touchpoint’s campaign

• Device: Touchpoint’s device (detected automatically)

• Type: touchpoint’s contact (click or view)

• Page views: number of page views generated after the touchpoint intervened

• Win %: winning (“1”) or losing (“0”) touchpoints according to the selected attribution model.

3) – You can include duplicated conversions (conversions we received the same order ID for more than once) and excluded conversions (those the IP addresses are excluded for) in your exports.

4) – You can choose to create a “one shot” export or a scheduled export.

There are additional metrics available in the “Conversion Details” report, whose purpose is to give you a deeper understanding of your conversions.

Conversion metrics

The metrics are displayed in the table under the main Conversion Details area (1).

The “Conversion” metrics available are:

• Order ID: ID of the conversion.

• Date: Date of the conversion.

• Amount: Amount of the conversion.

• Fraud Score: Fraud score. This indicator identifies conversions that were potentially generated fraudulently. The detection criteria used are: IP address, User Agent, conversion ID and the date and time. 10 (maximum score) means that the sale is very reliable and 1 (minimum) means that the conversion may be fraudulent.

The “Customer journey” metrics available are:

• Attribution: Conversion attributed to one or more channel(s)/source(s).

• Click number: Number of clicks logged in the customer journey before conversion (the default data retention period is 90 rolling days).

• View number: Number of impressions logged in the customer journey before conversion (the default data retention period is 90 rolling days).

• Touchpoint number: Number of touchpoints in the customer journey before conversion (the default data retention period is 90 rolling days).

• Time to convert: Time elapsed between the first touchpoint of the customer journey and the conversion (the default data retention period is 90 rolling days).

• Post click/Post view:Conversion attributed as Post-Click or Post-Impression.

The “Visitor” metrics available are:

• Browser : Name and version of the browser used for conversion.

• IP: IP address of the conversion.

What are the additional metrics in the “Conversion Details” report used for?

The additional metrics in the “Detailed conversions” report let you track data concerning a particular conversion.

The “Fraud score” metric for instance can be very useful for sites where the conversion is lead-generated, because providers can more easily create fictitious leads fraudulently. An analysis of this metric lets you ascertain that the conversions on the provider’s site are reliable, and where applicable, apprise your partner of the problem.

The “Clicks”, “Views” and “Touchpoints” metrics let you analyze the contents of the customer journey by conversion. These metrics give you an idea of the length and composition of customer journeys (mainly “click” or “impression” actions).

The “Time to convert” metric lets you analyze how long users take to convert on your site from the first point of contact with your brand. You can thus see whether the purchase cycle on your site is fast or slow. If it is very slow and your products impose too many restrictions, this may highlight campaigns that are rather weak.

Finally, the “Browser” metric tells you what browsers are used for conversions. If a very popular browser is under-represented, that may point to a browsing problem on your site for that particular browser.

You can access the “Customer journey type” report by clicking the “Attribution” > “Customer journey type” tab:

This report shows you the types of customer journey that generate the most conversions on your site. There are three types of customer journey:

• “Natural”: all the conversions made with customer journeys comprising only natural touchpoints.

• “Paid”: all the conversions made with customer journeys comprising only paid touchpoints.

• “Mixed”: all the conversions made with customer journeys comprising both natural and paid touchpoints.

This report is divided into three parts:

1) – Two key metrics in the report header:

• “Top customer journey type in terms of turnover”: the type of customer journey generating the most revenue overall (1).

• “Best touchpoint number”: length and type of customer journey generating the most conversions on the site (example of an interpretation of the metric: most conversions were generated with customer journeys containing only one paid touchpoint) (2).

2) – A Graph part showing the performance of the different types of customer journey.

By default the graphs show the following metrics:

• “Conversion”: number of conversions by type of customer journey

• “Average basket”: average basket by type of customer journey

• “Turnover”: turnover by type of customer journey

You can click the “Metrics” (1) dropdown menu to display two other metrics:

• “Conversion share”: conversions share by type of customer journey

• “Turnover share”: turnover share by type of customer journey

3) – A Table part presenting detailed figures for each type of customer journey, “Full Natural“, “Full Paid” and “Mixed“.

By default the tables show the following metrics:

• “Touchpoint number“: length of customer journey (= number of touchpoints on the customer journey)

• “Conversion“: number of conversions by type of customer journey

• “Average basket“: average basket by type of customer journey

• “Turnover“: turnover by type of customer journey

You can click the “Metrics” (1) dropdown menu to display two other metrics:

• “Conversion share“: conversions share by type of customer journey

How to generate the “Customer journey type” report?

The “Customer journey type” report helps you understand the composition of your customer journeys, and the breakdown of conversions between customer journeys containing only paid channels, only natural channels or paid + natural channels.

In the following example, we see that most conversions are made with customer journeys containing only paid touchpoints (1).

This means that your natural channels alone do not generate enough conversions on your site, so you are highly reliant on the performance of your paid campaigns.

On that basis, you can take several courses of action: improve the search engine optimization of your site, raise the profile of your brand to acquire a reputation with your potential buyers (through offline campaigns like television or poster campaigns for instance), or even invest more in your paid campaigns to generate yet more paid traffic on your site. This configuration also means that if you cut your paid campaign budgets, conversions on your site may well suffer.

Conversely, in the following example we see that not just the majority of conversions are made through customer journeys only comprising natural touchpoints (1), but also that the average spend generated by natural customer journeys is much higher than that generated by paid customer journeys (2).

This configuration shows that this brand enjoys an excellent natural share of mind, which means that many conversions are generated only through natural touchpoints. However, the reports also show that paid campaigns are not very effective, as they generate little traffic and very small average spends. In this case, several courses of action are open to you: more investment in paid channels, tests with new paid partners (because the current ones are not effective enough), or even enhanced advertising messages to generate more interest in the products and a bigger average spend.

What is Live Report Builder ?

MixCommander offers you a new reporting module for your marketing campaigns. Live Report Builder is the result of long R&D work and implementation of new technical components. You can create and use customized reports update in real-time. Designed to be more granular than previous reports, it also allows you to cross-reference dimensions at your convenience and choose customized data range with a set of custom filters.

Create a report

The first step is to create reports that you can build yourself, then view, share and export.

Open the creation interface - which is also the editing interface. This screen give you access to several different options’ areas in addition to the drag&drop side panel:

• Header containing the report's title and informations

• Data Set (grey bar at the top of the report)

• Filters

• Table

• 1. Header

Header contains every useful information to manage and sort reports:

• Title: Visible in general reports’ listing and every page which concerning this report.

• Category: Classification unit in Live Report Builder organization.

• Description: We recommend that you use this field to explicit why you created the report and what is this kind of analysis. This will make it easier for your employees to understand the reason for each report and avoids duplication.

Category’s managing:

You can manage category on the homepage of Live Report Builder.

Categorys are created, and deleted in this pop-in, then usable in report’s edition. When a category is associated to a report, it is visible in the general listing and report’s details.

• 1. Data Set and filters

Although the result on the data is essentially the same, there is a fundamental difference between Data Set and filters:

• Data Set reduces the data scope used in the report. It cannot be disabled during consultation and is considered as an axiom of the report. It makes updates and generation easier.

  eg : I want a report that only concerns French market. I will set my Data Set to take only into account informations sent by tags whose country is "fr".

• Filters can be activated and deactivated directly on the view page. They allow to quickly reorganize the data of the table in the same way as the calendar which is a time filter.

  eg : I want to be able to sort my report by device to see if there is a lot of difference between phone and computer users.

Data Set can be edited from the grey band at the top of the editing screen. The button opens the screen dedicated to editing the Data Set.

This Data Set screen is a drag&drop side panel with some logical rule fields. You can see a summary of these rules in the grey area of the editing screen once you have saved your rules in the Data Set screen.

Rule creation is made by simple logic rules, explained directly in the interface, except for the rules linking the different rules:

• In each rules’ field, there is a logical OR between each line.

• Between each rules’ field, there is a logical AND.

Eg : I want to keep my report scope on mobile users who have made their purchase in a French-speaking country:

• Drag and drop dimension « country (conversion) » in the first field

• Create rules « equal to » for French-speaking coutrys (fr, qc, be…)

• Drag and drop dimension « device (traffic) » in the second field

• Create rule « equal to mobile »

Data Set will summarize the scope as :

Filters are defined directly on the report editing screen. All you have to do is drag and drop the filters you want into the field indicated in all letters. They will be used in the consultation page.

Creation of the table

The most important part of the report is the data table. The information on the rows is called Dimensions and the information on the column headers is called Metrics.

Dimensions are sorted between three different univers:

• Traffic: data reported by users' actions during their web browsing

• On Site: data reported by users' actions during their navigation on the customer's site

• Conversion: data catch by conversion’s tags at the time of order validation.

This makes it possible to monitor purchase actions and navigation actions in a differentiated way, which makes it easier to segment the population, particularly the behaviour of border residents.

Metrics are sorted by type:

• Ads: Based on clicks and impressions, they directly concern advertising actions.

• Analytics: Based on sessions and type of visitors, they concern the behaviour of users when they arrive and navigate on the customer's site.

• Attribution: Processing the number of conversions and the associated revenue. They differ according to the allocation model chosen.

Choose your metrics

To create the table of your choice, simply drag and drop the metrics and dimensions into the locations indicated.

For example display "new_customer" as column

By displaying this metric as a column will allow you to compare the number of new customers against total orders

NB :

• Metrics can be deleted by pressing the cross at the top right of each insert.

• Dimensions cannot be reorganized by drag&drop. To change their level, or delete them, click on the three points symbolizing the options.

Apply your attribution models

Once metrics and dimensions have been selected and arranged as desired, you can choose all attribution models you want by clicking on the cog on the right of the default attribution model.

When your table is finished, you can click on "Publish" to switch your report to view mode. You can then play with filters, calendar, export your document and allow your read-only collaborators to access it easily.

For users used to custom reports

Even if they are close, the "Session" metric is not equivalent to the "Visit" metric.

Use a report

Live Report Builder is not just a list of real-time reports. It is also a module which can administer your report list in order to remain as efficient as possible.

• 1. Report details

From the Live Report Builder homepage (the general list) you have access to a lot of information about the reports:

• Title

• Last edition

• Category

• Status

  • Published : published version visible directly in View mode. Read only user can view it.

  • Draft : unpublished version keep in draft mode. You can only access the editing screen. Read only users can view it in the list but they cannot access the data.

• Owner

But all information about a report can also be found in the Details panel (button on the right of its listing line or in the options).

In addition to the information available directly on the homepage:

• Data Set rules

• Filters

• Dimension’ levels

• Description

• Reports’ options:

  • View

  • Edit

  • Duplication

  • Archive

• 1. Archive, restore and delete

In Live Report Builder, reports could be separately disable or deleted.

• Archived: The report is no longer viewable, but its settings are stored for possible restoration.

• Deleted: The report, its settings and history are completely deleted from the databases. There is no way to recover the datas.

To archive, click on the option on the right of the line corresponding to the target report. The archiving option appears but not the deletion option. Restore and delete are the only options available for reports that are already archived.

When you get on the interface, you are directly located on the general list of active reports, yet by clicking on the "Archive" tab you have access to all your archived reports.

• 1. Rapport View

The report view screen allows you to browse through the data table and the different levels of dimensions provided. You can also use the filters that were defined during editing.

• • 1. Period Time

The calendar is located at the top right of the interface. You can define the period you need in three different ways:

• Directly in the input field

• By the shortlist

• By the start and end of period calendars

Within the input field, the format to be respected is : yyyy-mm-dd – yyyy-mm-dd

Nota Bene :

Within the pre-selection list, "Last X days" current day is not taken into account by the suggestions

Within the pre-selection list, "X to date" current day is not taken into account by the suggestions.

Compare 2 periods

Custom : choose 2 periods manually

• Directly in the input field

• By the start and end of period calendars

Predifined comparison periods

You can also apply predifined periods :

Export

The export button is located at the top right of the interface.

Be careful: At the moment, only the first 3 dimension levels of the table are available to export.

You have two types of exports available :

• One shot :The report that appears on the screen is sent with all its activated filters and the selected time period. It is sent via e-mail, once only, to the address registered in the user's profile..

• Scheduled : The user can specify a period, a sending frequency and a sending method (either by mail or by FTP server).

In the forecasting possibilities, you can define three different frequencies:

• Daily: the export will be sent every day before 10:00 a.m..

• Weekly: the export will be sent every week and you can choose the day of the export.

• Monthly: the export will be sent on the first Monday of each month.

By choosing send via email, you can add as many addresses as you wish in the field provided for this purpose, but only the addresses of employees registered on the platform are allowed.

By choosing send via FTP server, you can only choose an FTP server already configured in the options and add a path to store the export in the folder of your choice.

Synergy with DataCommander

Focus on Segments

if you are both DataCommander and MixCommander customer you will automatically see in LRB data set the DataCommander segments !

They are available in data set in traffic and conversion sections. You can display the name and the ID of the segments.

You can analyse the traffic and the conversions of DataCommander segments

You can use them as filters

Then you can choose the value you want to filter.

Then you can analyse the data. The segments are only available on last 90 days

FAQ

What is "missing Dimension"?

• new users (that don't have yet segments calculated)

• fresh campaign-only users (clicks) : means user that has never visited the website (before this click) and only comes from a new campaign

Specifically on Sessions

• Because of Safari, it seems very often a page seen generates a new session.

Specifically on Conversions

• Example : It varies between 30% and 80% depending on the attribution models. A First Touch Point will have 80% because the new user will not have his segments calculated depending of segments. A Last Touch Point will have 30% because the User's segments have been calculated in the meantime.

What is the difference between traffic and conversion dimension ?

Having the segments in the conversion universe allows you to filter on conversion-specific data (segments in wich the user was at the moment he converts), in addition to being able to filter on attribution data (i.e. the winning TPs that are in the traffic universe. It means segments in wich was the user when the winning touchpoint occurs in the past)

EXAMPLE :

If you launch a campaign to sell garden furniture.

Imagine a user that has seen the campaign in January (first touch point) but he was living in appartment. He did not buy. The user came back in March, he moved to the countrysiden now he is living in a house, he has bought garden furniture. In your LRB reports, you want first to analyse Segments of users based on campaigns (winning touchpoints) and you will see :

Then, it appears strange to you so you want to see in wich segment was the users the day they bought, so you choose the dimension "Segment (conversion)", and you will see :

And then you understand that users only buy if they are in house, so you'll change your campaign targetting or maybe keep it but look at a last touchpoint attribution model that feets better to your business.

The second stage consists in collecting two types of data on your site:

• Browsing data

• Conversion data

Browsing data is collected using two TagCommander tags called “MIX - Click and Site Tracking” and “MIX –Site Tracking Only“. These tags, set up by your consultant at the beginning of the project, are available at the “SELECT” and “EDIT” stages of the TagCommander product, in the tags library.

The “MIX - Click and Site Tracking” tag retrieves all the visitor’s browsing details (number of pages viewed, bounce rate, visits, etc.), and its traffic source.

This must be called on all your site’s pages except for the confirmation page, where you should call the “MIX – Site Tracking Only” tag and the “Measure –Conversion 3.5” tags. The “Measure–Site Tracking Only” tag is used to collect the visitor’s browsing information on the confirmation page without capturing the visit’s origins, in order to avoid seeing touchpoints from online payment platforms in the customer journey (e.g.: Ogone, PayPal, etc.).

Configuring the "MIX - Click & Site Tracking V3.5" tag

Step 1 – “EDIT”

You first add the “MIX - Click and Site Tracking V3.5” tag in the “SELECT” or “EDIT” step. Then add all the data it needs to generate full reports on the MixCommander interface. To do so, go to the “EDIT” tab of the TagCommander product.

Add the following variables to your “MixCommander Click and Site Tracking 3.5” tag:

The type of pages visited

• Variable #PAGENAME# is the page name (generally external variable tc_vars[“page_name”] or URL of the current page)

• Variable #PAGETYPE# must be mapped to the page’s template (generally external variable tc_vars[“env_template”])

Brand name details

These are optional and should only be completed if you wish to distinguish between brand SEO and non-brand SEO (NB: As Google no longer transmits the user’s search keywords, the brand/non-brand SEO data collected by the Commanders Act MixCommander product will not be exhaustive):

• Variables #BRAND_NAME…# must be completed with the name(s) of your brand required to identify brand SEO.

User ID

This information is optional, it allows Commanders Act to match a given user’s journeys and conversions occurring on different devices (Note: for optimal performance, it is recommended that the user ID is made available during all of the user’s browsing).

• The #USER_ID# variable has to be populated with your visitors’ User ID.

Sites to exclude from the “Referrer” channel

When a user clicks an untracked link and lands on your site, the touchpoint is attributed to “referrer”. If you wish to exclude sites from the “referrer” channel (ex: payment platforms), you need to specify their domain names.

• The #EXCLUDED_REFERRER# variable has to be populated with the domain names or sub-domain names to exclude, separated by a coma. (It is not necessary to type “www”).

Additional search engines to consider for the “SEO” channel

Commanders Act has an up to date, comprehensive list of search engines, but you have the possibility to add more.

• The #SEARCH ENGINES# variable has to be populated with the names of search engines that will be taken into consideration for SEO, as well as the value of the URL parameter containing the keyword that is searched for by the user. (ex: parameter “q” in the following URL : https://www.google.fr/webhp?sourceid=chrome-instant&ion=1&espv=2&ie=UTF-8#q=keyword . The name of the search engine and the parameter’s name have to be separated with “|”. The names of search engines that are considered need to be separated with a comma.

Additional Social networks

Commanders Act has an up to date, comprehensive list of social networks, but you have the possibility to add more.

• The #SOCIAL NETWORKS# variable needs to be populated with the names of the social networks to be taken into consideration and separated with a comma.

SEO Brand

In case you wish to count SEO visits without keywords that land on your website’s homepage as “SEO brand”.

• The #BRAND_URSL# variable needs to be populated with the exact URLs of landing pages separated with a comma. (Remember to take the protocol into consideration and do not forget the “/” at the end of the URL if it is present). Ex: http://www.mysite.com/

Sites to consider as “internal” traffic

When a user clicks an untracked link and lands on your site, the touchpoint is attributed to “referrer”. If you do not want to consider internal traffic (ex: a brand’s satellite sites or other countries’ sites), you need to specify the websites.

• The #SUBDOMAINS# variable has to be populated with the URLs of the sites you want to exclude, without the protocol and the query string. Each URL needs to be separated with a comma. Pay attention not to mention your own site’s domain name (i.e. the site on which the Measure tag is placed).

Step 2 – “Rules”

The second step consists in adding the “MixCommander Click and Site Tracking 3.5” tag to all the pages on your site apart from the confirmation page.

You can create your rule on the “Rules” tab:

Configuring the "MIX - Site Tracking only V3.5" tag

Step 1 – “Edit”

You first add the “MIX - Site Tracking Only V3.5” tag in the “SELECT” or “EDIT” steps. AThen add all the data it needs to generate full reports on the MixCommander interface. To do so, go to the “EDIT” tab of the TagCommander product.

Your “MIX - Site Tracking Only V3.5” tag must be completed with:

The name of the viewed page

Variable #PAGENAME# must be completed with the name of the page (generally external variable tc_vars[“page_name”] or URL of the current page).

The type of page viewed

Variable #PAGETYPE# must be mapped to the page template (generally external variable tc_vars[“env_template”]).

Step 2 – “Rules”

The second step consists in adding the “MixCommander Site Tracking Only 3.5” tag to the confirmation page only.

You can create your rule on the “Rules” tab:

Configuring the "MIX - Conversion V3.5" tag

Conversion data is collected via a TagCommander tag called “MIX - Conversion V3.5“. This tag, set up by your consultant at the beginning of the project, is available in the “SELECT” or “EDIT” steps in the TagCommander product:

It retrieves all the conversion details: order ID, order amount at the very least. But also other details concerning conversions, such as segments (repeat/new customers, device, country, etc.).

It must be included on your site’s confirmation page.

Step 1 – “EDIT”

The first step consists in adding the “MIX - Conversion V3.5” tag in the “SELECT” or “EDIT” sections in the TagCommander product. Then, adding all the data it needs to provide conversion information in the reports.

Your “MIX - Conversion V3.5” tag must be completed with:

Details of the conversion ID

• variable #TCIDORDER# must be completed with the conversion ID (generally external variable tc_vars[“order_id”]).

Conversion amount details

• variable #TCAMOUNT# must be completed with the conversion amount (generally external variable tc_vars[“order_amount”]). If you do not have the conversion amount (e.g.: when conversions on your site consist in form-filling or registration), the value of this variable is “1”.

Details of the conversion currency

• variable #TCCURRENCY# must be completed with the currency of your site (EUR by default).

You can also add other parameters to your conversion tag. Just fill in the line labelled “tC.msr.additional_params“.

In the example below, we have added 3 conversion segments to the tag “MixCommander Conversion 3.5“: a “device” segment to retrieve the device on which the conversion took place, a “customer_type” segment to determine user status (repeat or new customer), and a “country” segment to determine the country of conversion:

To retrieve more information, just add parameters like this:

Step 2 – “RULES”

The second step consists in adding the “MIX - Conversion V3.5” tag to the site’s conversion page.

You can create your rule on the “RULES” step (1) in the TagCommander module:

When the “MIX - Click and Site Tracking V3.5“, “MIX - Site Tracking Only V3.5” and “MIX - Conversion V3.5” tags are in place, Commanders Act is ready to collect all the needed information to generate Attribution reports.

The “Channel affinity” report can be accessed by clicking the “Attribution” > “Channel affinity” tab:

This report shows you the affinities between customer journey channels: it highlights the pairs of channels that generate the most sales when they are in the same customer journey.

This report is divided into three parts:

1) – Four key metrics in the report header

• “Best affinity: turnover“: pair of channels generating the highest turnover.

• “Worst affinity: turnover“: pair of channels generating the lowest turnover.

2) – A Table presenting in detail the Top 5 pairs of channels

... that generate the highest turnover (1), and the 5 pairs of channels that generate the lowest turnover (2). The “click” and “impression” icons tell you what type of touchpoint is included in the analysis.

You can click the “Metrics” (3) dropdown menu to display three other metrics:

• “Turnover share“: share of turnover generated by a pair of channels.

• “Conversions“: number of conversions generated by a pair of channels.

• “Conversion share“: share of conversions generated by a pair of channels.

3) – A Matrix

... showing the details of the pairs of channels having strong affinities (in green) and those having few or no affinities at all (in red). By default the matrix displays the “Turnover” metric and focuses on the synergies between paid levers.

You can click the “Turnover” (1) dropdown menu to display three other metrics:

• “Turnover share“: share of turnover generated by a pair of channels

• “Conversions“: number of conversions generated by a pair of channels

• “Conversion share“: share of conversions generated by a pair of channels

Click the “paid channels” dropdown menu (2) to display other categories of channels in the matrix:

• “All channels“: affinities between natural and paid channels

How to interpret the “Channel affinity” report?

The “Channel affinity” report helps you understand synergies between the channels of your customer journeys. This report can help you optimize the messages of your campaigns and optimize your media investments.

In the example below, we see that the paid channels having the strongest affinity are SEM and affiliation, as they generate 4.55% of the turnover. By cutting or reducing budgets on one of the two channels, you may therefore adversely affect the performance of the other channel and your total turnover.

If there are budget restrictions, you therefore tend to concentrate your budget on channels having strong affinities and implement consistent communication between the channels that jointly generate a higher number of conversions.

The Sunburst Reports give an easy to understand visual representation of the channels preceding a conversion along the customer journey. These reports will give you the insight you need to better allocate your digital marketing spend.

This type of visualization shows hierarchy through a series of rings that are sliced for each channel node. Each ring corresponds to a level in the hierarchy, with the central circle representing the root node and the hierarchy moving outwards from it. Rings are sliced up and divided based on their hierarchical relationship to the parent slice.

In the above graph, the size of each slice is made proportional to the value of its immediate parent ring.

Hover over a ring or a portion of a ring in the Sunburst Report's diagram to reveal the percentage of conversions that traversed the path from the selected vein.

The “Attribution model comparison” report lets you compare two attribution models of your choice and see how they affect the sales attributed to each channel. You access it by clicking the “Attribution” > “Attribution model comparison” tab:

This report is divided into two parts:

1) – A Graph part presenting in a succinct form the differential between two attribution models. The figures for the first model (benchmark model) are shown in green, those for the model being compared are shown in blue. By default the graph displays the “Revenue” (turnover) metric.

You can click the “Revenue” (1) dropdown menu to display three other metrics:

• “Conversions”: number of conversions generated by a pair of channels.

• “Conversion share”: share of conversions generated by a pair of channels.

• “Turnover share”: share of turnover generated by a pair of channels.

2) – A Table part comparing in greater detail the impact of two different attribution models on conversions.

To compare two attribution models of your choice, in the left-hand dropdown menu (1) select a model among those at your disposal, and do likewise in the second column (2). In the “Comparison” column (3) you can see the impact on existing conversions of one attribution model compared with another: the positive impacts are shown in green, the negative ones in red.

For instance, if you select the “Pure PV 48h” model in the first column and the “First touch point” model in the second column, in the “comparison” column you will see the gain or loss of revenue generated for each one of the channels. The table can be read in this manner: “if we were using the ‘Pure PV 48h” attribution model instead of “First Touch Point”, the SEO channel would generate €1,130,605.99 more revenue in the period under review.

By default the table displays the “Revenue” (turnover) metric.

You can click the “Revenue” (4) dropdown menu to display three other metrics:

• “Conversions”: number of conversions generated by a pair of channels.

• “Conversion share“: share of conversions generated by a pair of channels.

• “Turnover share“: share of turnover generated by a pair of channels.

How to interpret the “Attribution comparison” report?

The “Attribution comparison” report lets you analyze in a succinct form the impacts of a change of attribution model on the conversions of a given period.

We advise you to start by choosing the attribution model your company currently considers official in the left-hand column, and compare it with one or more attribution models that interest you. You can than directly simulate the number of conversions and the revenue that each of your channels would win or lose.

In the example below, by switching from the “Last Touch point” model to the “First Touch Point” model, the affiliation would lose €118,761.87 of revenue, which means that it would make fewer sales than at present and that you would thus pay your partner much less commission:

Acquisition metrics

A selection window pops up, listing all the acquisition metrics in the “Acquisition” column (1). Select the metric(s) you want and click “Apply” (2):

The following “Traffic acquisition” metrics are available:

Impressions: Number of banner impressions (i.e. the raw measurement of displays of a banner on a site, regardless of whether or not the user has actually seen the banner). The impressions count is measured with the MixCommander impression pixel placed in your banners.

Visible Impressions: This is the number of visible impressions, as per the IAB definition: “50% of pixels must be in view for a minimum of one second, and for desktop video 50% for two seconds”. Visibility measurement is not possible in all environments (e.g.: JavaScript blocked). Optional activation is not included in the basic setup. Contact the Sales Department for more information.

Visibility Rate: Ratio between the number of visible impressions and the number of delivered impressions.

Unique Clicks (by Channel): Number of unique clicks (made by the same visitor) in a day, by channel.

Clicks: Number of clicks on links or banners (or number of site accesses for levers not tracked by Commanders Act redirects). The clicks count is measured with the Commanders Act redirect URL placed on your campaigns via the captured tracking parameters of your analytics tool.

CTR: Click-through rate (number of clicks/number of views x 100)

How should these acquisition metrics be interpreted?

Acquisition metrics are a way of analyzing whether your campaigns are adequately rolled out (“impressions” metric) and bring enough traffic to your site (“clicks” metric).

A small number of impressions or clicks may reveal a problem regarding the relaying of your campaign or a message that is not optimized enough as to convince people to visit your site.

Conversely, a campaign generating a lot of impressions and clicks but few conversions (see metrics concerning conversion) may be symptomatic of the fact that your campaigns are aimed at the wrong target, or of a bad user experience on your site (in which case the “site visitor behavior” metrics will help you determine the root cause of the problem).

Acquisition metrics are therefore extremely important for measuring the visibility and effectiveness of your campaigns, and for analyzing the performance of your partners who relay them.

Behavioral metrics

A selection window pops up, listing all the acquisition metrics in the “Behavior” column (1). Select the metric(s) you want and click “Apply” (2):

The following “Behavioral” metrics are available:

Visitors: Number of unique visitors (cookies) in the day by Channel/source/campaign.

Visits: Number of visits. The visit ends after 30 minutes’ inactivity.

1 page visits: Visits consisting in only viewing the landing page.

Qualified visits: Visits with at least two pages viewed on the site.

New visitors: Visitors coming to the site for the first time (calculation based on the TCID).

Bounce rate: Bounce rate. The bounce rate is the percentage of visits during which the web user has only viewed one page on your site.

Avg. visit duration: Average length of visits.

Page views per visit: Number of pages viewed per visit.

Page views: Number of pages viewed on the site.

How should these behavioral metrics be interpreted ?

Behavioral metrics are a way of analyzing the behavior of your visitors on your site.

The “bounce rate” for instance may be high if site browsing is hard or the landing page is inappropriate.

In such cases, certain visitors will quit the site after viewing the first page. However, a high bounce rate does not always point to a problem on your site. It may also mean that your site is extremely optimized and that web users only need to view one page to find the information they are looking for. This figure can therefore be interpreted positively or negatively, depending on the context.

Another example, the “number of pages viewed per visit” and “Average visit duration” metrics are indicators of time spent and pages viewed by your visitors: a high number of pages viewed and a long time spent may mean that your users like to browse and spend time on your site, but it may also mean that they can’t find their way around the site and are forced to spend a long time there before finding what they are looking for. There again, these figures should be analyzed alongside the conversion figures to check whether or the viewed pages lead the user to convert.

Behavioral metrics therefore help you better understand the behavior of visitors on your site, and help you improve certain aspects of the site: campaign home page, internal searches, site organization, etc.

Conversion & attribution metrics

A selection window pops up, listing all the acquisition metrics in the “Attribution” column (1). Select the metric(s) you want and click “Apply” (2):

The following “Conversion” metrics are available:

• Conversions: Number of conversions.

• Revenue: Revenue generated by the conversions.

• Avg. basket: Average basket of the conversions (“Revenue” divided by “Conversions”).

• Conversion rate: Visit conversion rate of the channel or source (“Conversions” of the channel or source divided by the number of channel or source visits). The higher the “Conversion rate”, the better the visits/conversions ratio is for your channel or source.

• Conversion rate (qualified visits): Qualified visit conversion rate of the channel or source (“Conversions” of the channel or source divided by the number of qualified channel or source visits).

• % all conversions: Sales of the channel or source as a share of the total number of sales (“Conversions” of the channel or source divided by the total number of conversions). If “% all conversion” is high for one of your channels/sources, this means that it is a large proportion of the total conversions on your site.

• Turnover per visit: Revenue generated per visit (“Revenue” divided by the number of visits).

• Turnover per qualified visit: Revenue generated per qualified visit (“Revenue” divided by the number of qualified visits).

• New customers: Orders from new customers, calculated with a variable to provide in the TagCommander conversion tag implemented when the Attribution product is set up.

• Revenue (new customers): The amount for orders placed by new customers.

• Avg. basket (new customers): Average basket of new customers (“Avg. basket” divided by “New Customers”).

• Repeat customers: Orders from repeat customers, calculated with a variable to provide in the TagCommander conversion tag implemented when the Attribution product is set up.

• Revenue (repeat customers): The amount for orders placed by customers who have already ordered from the site.

• Avg. basket (repeat customers): Average basket of existing customers (“Avg. basket (repeat customer)” divided by “Repeat Customers”).

• New customer conversion share: New customer conversion share (“Conversions” divided by “New Customers”).

• Repeat customer conversion share: Repeat customer conversion share (“Conversions” divided by “Repeat Customers”).

• Return on Investment (ROI):Return on Investment (“Revenue” divided by “Costs”).

• Assisted channel conversion (not last): The number of conversions in which a channel played a part. This metric includes clicks in the last 90 days. The last touchpoint is ignored. In the example below, the “Assisted Channel conversion (not last)” metric counts 1 conversion for “SEM” (we only count one instance in customer journey 1 and nothing in customer journey 2 as SEM comes last). No conversions will be attributed to Display because impressions are not considered by this metric:

• Exclusive channel conversion: The number of conversions generated with a single channel. Only clicks are taken into account. In the example below, the “Assisted Channel conversion” metric counts 3 conversions for “SEM”:

• Assisted channel conversion: The number of conversions in which a channel or source played a part. This metric includes clicks only, counted in the last 90 days. Unlike “Assisted Channel conversion (not last)”, the last touchpoint is taken into account. In the example below, the “Assisted Channel conversion” metric counts 2 conversions for “SEM” (we count one instance in customer journey 1 and 2). 2 conversions for Retargeting (in customer journeys one and two) and no conversions for display as impressions are not considered.

Conversion metrics are closely related to the attribution concept. One of the main aims of the Commanders Act MixCommander module is to see whether each of your channels is attributed more or fewer conversions by changing your attribution model. To access your attribution models and see their impact on your conversions, click the “Attribution model” dropdown menu above the table (1) or the dropdown menu on the right of the graph (2):

A selection window pops up, listing all your attribution models (those included by default in the tool and those you have created). Select the metric(s) you want and click “Apply” (2):

Campaign cost metrics

Certain metrics in the “All Channels” report let you analyze the costs of your campaigns. Cost metrics only appear in the interface if you configure your campaign costs in the cost configuration interface accessible through “Options”>”Cost configuration”.

A selection window pops up, listing all the cost metrics in the “Costs” column (1). Select the metric(s) you want and click “Apply”:

Here are the “Cost” metrics offered by default:

• Cost: Total cost of campaigns

• Cost per click (CPC): “Cost” divided by the number of ‘Clicks”

• Cost per thousand impressions (CPM): “Cost” divided by the number of “Impressions”

• Cost per visit: “Cost” divided by the number of “Visits”

• Cost per qualified visit: “Cost” divided by the number of “Qualified visits”

• Cost of conversions: “Cost” divided by “Revenue”

• Cost per conversion: “Cost” divided by the number of “Conversions”

• Cost per conversion (new customer): “Cost” divided by the number of new customer conversions (“Conversions”)

• Cost per conversion (repeat customer): “Cost” divided by the number of repeated customer conversions (“Conversions”)

How to interpret cost metrics?

Cost metrics are a way of tracking your campaign budgets.

Certain cost metrics relate to customer acquisition: “CPC” lets you analyze the cost of your campaigns per click, “CPM” your banner display campaigns, provided you track impressions with Commanders Act. “Cost per visit” and “Cost per qualified visit” tell you the cost of acquiring a visitor to your site.

Other cost metrics focus on conversion: “Cost of conversion” tells you how much you need to spend on average to generate conversions on your site. “Cost per conversion (new customer)” and “Cost per conversion (repeat customer)” highlight the cost of acquiring a new customer compared with the cost of retaining a repeated customer.

The lower your costs, the more profitable your channels and partners can be.

How to interpret conversion and attribution metrics?

Conversion metrics are a way of analyzing the user conversion on your website.

The “Conversion Rate” and “% global conversions” metrics focus on the performance of a channel or source, combined with a “ROI” metrics that measures budget investment, enabling you to answer an important question: are your partners profitable enough? You can thus maintain or increase budgets for your most efficient partners, and reduce or cut them for underperforming partners.

Conversion analysis is inseparable from the attribution concept. To find out how many conversions a partner generates, you first need to define the attribution rule:

• Is a conversion attributed to the last partner involved in the customer journey (“Last Touch Point”) or on the contrary, to the first (“First Touch Point”)? In either case, the conversion is attributed to only one partner, who wins 100% of the conversion (this is the type of attribution proposed in the 6 default attribution models in the interface).

• Do you prefer to attribute the conversion to all partners of the customer journey who contributed to the conversion? The “Assisted Channel conversion” metric lets you view the participation of each of the channels/sources in the site conversions. To reward partners playing a part in the conversion, you can set a conversion percentage per channel/source (this is the type of attribution proposed in the customer models you can construct in the interface: the “Linear” model, “U model”, etc.). You will note that by comparing two different attribution models you will achieve very different results in the conversion metrics.

The “First touch point” and “Last touch point” attribution models let you see whether your partners’ contribution to the conversion occurs more towards the beginning or more towards the end of the customer journey.

The “Last click” vision, which is now the most widely used on the market, highlights partners who precede conversion, so at first sight the most efficient and effective partners.

However, confining oneself to this analysis is too restrictive: the fact is that certain partner often found in Last Touch (e.g.: cashback solutions, money-off coupons or retargeting) can only have played a very minor role in the conversion on your site because they intervene only when the site is known and the web user’s intention to buy or sign up is obvious.

Conversely, a partner who generates few “Last” conversions may prove to be extremely effective as a “First” touch in attracting traffic to your site.

If you confine yourself to a “Last” analysis in this particular instance, you may underestimate a solution because it generates few “Last touch point” conversions whereas the “First touch point” vision highlights the fact that it plays an important part in driving the performance of your site.

In the example below, we compare the number and amounts of conversions according to two different attribution models: “Last Touch Point” and “First Touch Point”. If we look at the “Affiliation” channel figures, we see that it generates 804 Last Touch Point conversions, nearly 9% of total conversions. The same channel only wins 259 conversions, under 3% of sales, with the First Touch Point attribution model. We can thus conclude that affiliation plays a more important role at the end of the journey (leading the user to convert) than at the beginning of the journey to attract traffic to the site:

Conversion metrics combined with attribution analysis helps you to better understand what lever is operative – and where – in the customer journey, and focus on partners who perform best.

The “Touchpoint number” report can be accessed by clicking the “Attribution” > “Touchpoint number” tab:

This report shows you the extension of customer journeys (i.e. the number of touchpoints in the customer journey) that generate the most conversions on your site. You can see the performance of customer journeys from “1” touchpoint to “10 and more”.

This report is divided into three parts:

1) – Four key metrics in the report header:

• “Best touchpoint number: conversion“: length of the customer journey generating the most conversions on the site.

• “Best touchpoint number: average basket“: length of the customer journey generating the best average spend.

• “Best touchpoint number: turnover“: length of the customer journey generating the highest turnover on the site.

• “Worst touchpoint number: turnover“: length of the customer journey generating the fewest conversions on the site.

2) – A Graph part showing the performance of different lengths of customer journeys.

By default the graphs show the following metrics:

• “Conversions“: number of conversions according to customer journey length

• “Average basket“: average basket according to customer journey length

• “Turnover“: turnover according to customer journey length

You can click the “Metrics” (1) dropdown menu to display two other metrics:

• “Conversion share“: conversion share according to customer journey length

• “Turnover share“: turnover share according to customer journey length

Click the “All Channels” (2) dropdown menu to see the same analysis but focusing on the performance of a particular channel. If for instance you select the “Affiliation” channel, you can see whether your customer journeys containing an “affiliation” touchpoint convert swiftly (with only 1 touchpoint) or slowly.

3) – A Table part presenting the detailed figures for each extension of customer journey.

By default the tables show the following metrics:

• “Touchpoint number“: length of customer journey (= number of touchpoints on the customer journey).

• “Conversions“: number of conversions according to customer journey length.

• “Average basket“: average basket according to customer journey length.

• “Turnover“: turnover according to customer journey length.

You can click the “Metrics” (1) dropdown menu to display two other metrics:

• “Conversion share“: conversion share according to customer journey length.

• “Turnover share“: turnover share according to customer journey length.

How to interpret the “Touchpoint number” report?

The “Touchpoint number” report can help you understand whether your users convert on your site with customer journeys containing a large or small amount of touchpoints.

In the following example, we see that most conversions are made with customer journeys containing only one touchpoint (1).

This means that your customers convert very quickly on your site. These figures are fairly positive, and when compared with an analysis of the “Customer journey type” report, they help you understand whether it is your campaigns (paid levers) that work well or rather your natural levers.

On the other hand, if the majority of your conversions contained more than 10 touchpoints, this would mean that your customers do not immediately convert on your site.

If your company markets products or services that impose restrictions (travel services for instance), this type of customer journey is fairly common because your users generally need time to think before converting.

But, if your products do not require much time to think before purchase (for instance clothes, shoes), a customer journey like this one may be indicative of campaigns that are not effective enough or a there is a poor presentation of your products on your site.

The 'contributive analysis' reports allows you to benefit from a new angle of analysis of your customers journeys and to highlight the stage at which your partners and your campaigns are helping you score points in the generation of a conversion. This analysis is carried out from the data that we calculate for you, in a trusted third party position. It is carried out without sampling and without prioritization rules. It naturally benefits from our reconciliation algorithm which brings together conversion journeys started on different devices.

This part of the reports highlights the top of contributors.

INITIATOR : The beginner, the first click

SCORER : Is the finisher the last click

PASSER : is only a contributor. Not first and not last click. He is between them.

AUTONOMOUS : only the one on the customer journey (to come)

How to read ?

Unsurprisingly, the customer journeys are very rich, the channels and media partners are more and more numerous. So how do you gain height and identify the information that will allow you to understand and make the right decisions? We suggest you zoom in on the key contact points. The 'Contributive Analysis' report is a playground where the different channels and partners work as a team. Like a competition, each element plays a well-defined role. We tend to favor the 'last touch' but in order for it to be able to finalize, it needs others to prepare the ground for it upstream. What leverage makes it possible to initiate new journeys, the one that attracts new customers? Between the start and the end of the journey, which channel/ partner ensures that the user comes back and does not forget the message? You might expect this to be retargeting, but you might just be surprised!

Prediction

The prediction line represents your future performance over the next 9 days, notably by framing it with a minimum and a maximum confidence curve (light orange band). Our Data Scientist team has refined a predictive model that learns your own seasonality based on a mix on last weeks activity and last year at the same period. So, to have a better accuracy you must have at least 12 month of data.

The analysis can then be extended to other metrics. Our team is ready to discover your expectations. The forecast provided to you today has been built in silos based on historical data from your account. Prediction performance was appreciated for its ability to predict your account history. The algorithm developed has been particularly developed to offer a good prediction of exceptional sequences such as the main moments of market activity (Black Monday, Sales,...). These major market upsurge movements are one of the characteristics of the web. Once you have access this analysis, you will notice that it is retroactive, so that you can see how good would have been over past periods.

Baseline

The Baseline shows how it would have evolved without the intervention of external factors, based on last 4 weeks activity. (Hidden bydefault, click on the legend to activate it)

Trend

The trend illustrates global tendency on the (non-predicted) period. (Hidden bydefault, click on the legend to activate it)

Minimum expected revenue today

This metric help you to see what will be your expected minimum income for the day in the worst case scenario.

Average basket today

This metric show you what will be your average basket at the end of the day.

Insights

On the lower part of the report, you will find insights that help you contextualize the prediction, including a series of metrics on the current period (excluding predicted days) that help you compare the difference in performance between the observed period and last year : Average daily conversions/revenue, average basket by week, revenue vs last year.

Here are the attribution models offered by default:

Last Touch Point: The conversion is attributed to the last paid or natural touchpoint in the 30 days before conversion. In the example below, the conversion is attributed to “SEO Google” with the Last Touch Point model, provided the “SEO Google” touchpoint was in a 30-hour attribution window:

First Touch Point: The conversion is attributed to the first paid or natural touchpoint in the 30 days before conversion. In the example below, the conversion is attributed to “SEM Google” with the First Paid Click model, provided the “SEM Google” touchpoint was in a 30-day attribution window:

Last Touch (Paid over Natural): The conversion is attributed to the last paid touchpoint in the 30 days before conversion. If the customer journey contains no paid clicks or impressions, the conversion is attributed to the last natural touchpoint in the 30 days before conversion. In the example below, the conversion is attributed to “Affiliation Tradedoubler” with the Last Touch (Paid over Natural) model, provided the “Affiliation Tradedoubler” touchpoint was in a 30-day attribution window:

In the second example, the conversion is attributed to “SEO Google” with the Last Touch (Paid over Natural) model, provided the ” SEO Google ” touchpoint was in a 30-day attribution window:

Linear flat: The conversion is attributed to all the touchpoints in the customer journey.

Each touchpoint receives an equitable percentage of the conversion.

First and Last 50/50 : the first touchpoint and the last one share1 sale (or the amount of the sale).

U model : • Mathematical U model based on mathematical formulas (parabolic, elliptic …).100% of the conversion needs to be allocated

U model personnalized : The conversion is attributed to all the touchpoints in the customer journey.

This model purpose is to encourage simultaneously to increase sales and to increase traffic. We define how much will earn the first and last touch (it can be different) with a scoring in percent and all touchpoints in the middles earn a proportional part of the rest. Same example with 35% for the first touch and 45% for the last one. Note: if there is only 2 touch, the percent in the middle are equally divided between each touch. If there is only one touch, it gets 100% of the sale

Linear increasing/decreasing : user defines a static value increasing the importance of touchpoint accordingly to its position into the conversion path. For example: we define that each touchpoint will earn 1.2 points of the sale according to its position and there are 6 touchpoints. • That model uses the following function: y=ax, where y = value, x = touchpoint and a = the growing coefficient. The absolute value determines the importance of close touchpoints or remote touchpoints. • Then the scoring is applicated regarding the share of each touchpoint against the value total.

Exponential increasing (or logarithmic decreasing) exactly the same as previously but instead of defining a static growth coefficient, we use an exponential formula (exp(x) =ex). The same example as before:

Custom : Possible to define the number of touch point to take into account and the weight to assign to each.

/ams/reports/{id}/data

GET https://api.commander1.com/v2/{siteId}/ams/reports/{id}/data

Returns data for each metric of the report. Metrics and attribution models are listed in the response in a columns array. Values are listed in a rows array. Each row has a type and a list of values for each metric. The type defines if the row describes the total of all values or a single value of the level.

Path Parameters

Query Parameters

{
  "data": {
    "columns": [
      "name",
      "metric-1",
      "metric-3",
      "attribution-model-1_metric-5",
      "attribution-model-1_metric-12",
      "attribution-model-2_metric-5",
      "attribution-model-2_metric-12"
    ],
    "rows": [
      {
        "name": {
          "type": "string",
          "value": "Criteo"
        },
        "metric-1": {
          "type": "number",
          "value": "4719671"
        },
        "metric-3": {
          "type": "number",
          "value": "1657901"
        },
        "attribution-model-1_metric-5": {
          "type": "number",
          "value": "21739964"
        },
        "attribution-model-1_metric-12": {
          "type": "ratio",
          "value": "29.47"
        },
        "attribution-model-2_metric-5": {
          "type": "number",
          "value": "25549890"
        },
        "attribution-model-2_metric-12": {
          "type": "ratio",
          "value": "47.45"
        }
      },
      {
        "name": {
          "type": "string",
          "value": "zanox"
        },
        "metric-1": {
          "type": "number",
          "value": "80592"
        },
        "metric-3": {
          "type": "number",
          "value": "19668"
        },
        "attribution-model-1_metric-5": {
          "type": "number",
          "value": "7122"
        },
        "attribution-model-1_metric-12": {
          "type": "ratio",
          "value": "70.53"
        },
        "attribution-model-2_metric-5": {
          "type": "number",
          "value": "39127"
        },
        "attribution-model-2_metric-12": {
          "type": "ratio",
          "value": "58.89"
        }
      }
    ],
    "total": {
      "name": {
        "type": "string",
        "value": "Criteo"
      },
      "metric-1": {
        "type": "number",
        "value": "4800263"
      },
      "metric-3": {
        "type": "number",
        "value": "1677569"
      },
      "attribution-model-1_metric-5": {
        "type": "number",
        "value": "21747086"
      },
      "attribution-model-1_metric-12": {
        "type": "ratio",
        "value": "100.00"
      },
      "attribution-model-2_metric-5": {
        "type": "number",
        "value": "25589017"
      },
      "attribution-model-2_metric-12": {
        "type": "ratio",
        "value": "100.00"
      }
    }
  },
  "meta": {
    "pagination": {
      "total": 72,
      "count": 50,
      "per_page": 50,
      "current_page": 1,
      "total_pages": 2
    }
  },
  "links": {
    "self": "https://api.commander1.com/v2/ams/reports?page=1",
    "first": "https://api.commander1.com/v2/ams/reports?page=1",
    "next": "https://api.commander1.com/v2/ams/reports?page=2",
    "last": "https://api.commander1.com/v2/ams/reports?page=2"
  }
}

This API uses JSON API to fetch, create and modify the resources, and to format responses. Authentication and information exchange are ensured with JSON WEB TOKEN.

How to get the token

For each API, you'll have to ask a token to your account manager or support team.

GET Conversion Details

Returns the list of conversion details

Resource URL: GET /{version}/measure/conversiondetails/?site=XXXX&token=YYYY&date_start=YYYY-MM-DD&date_end=YYYY-MM-DD&format=ZZZZ

Parameters:

Return codes:

Response Format The response is in a JSON or XML format.

Difference between API and conversion details

API

List of fixed dimension in the API

• Fixed dimensions

• Traffic Dimensions on demand ( Jira ticket)

• Conversions Dimensions populated in the conversion hit ( Conversions tags or Server Side tags)

List of fixed dimension in the Api :

• tc_id

• id_order

• date

• amount_order

• score

• channel_winner

• source_winner

• click_number

• view_number

• touch_point

• time_convert

• user_agent

• ip

Export Conversion Details

List of fixed dimension in the Export

• Fixed dimensions

• Traffic Dimensions on demand ( ticket)

• "raw" dimensions (= option keep format checked )

• Conversion dimensions

List of fixed dimension in the Export:

• Identifier ID

• Order ID

• Date

• Amount

• Fraud score

• Winner Channel (one touch)

• Winner Source (one touch)

• Click

• Impression

• Touch points

• Time to convert

• Browser

• IP

3 remarks:

1. API send the dimensions only when the information is available in the hit

2. Export send all the dimensions, when it’s empty it send null as a value in the export

3. Some names of the properties are not the same for the exports and the API ( tc_id / Identifier ID ; view_number / Impression ; etc...)

Attributions metrics

Conversion metrics are closely related to the attribution concept. One of the main aims of MixCommander module is to see whether each of your channels is attributed more or fewer conversions by changing your attribution model. To access your attribution models and see their impact on your conversions, click the “Attribution model”, edit the report, click on the attribution model (1) choose one or severals models and validate (2):

The following “Conversion” metrics are available:

Ads

How should these ads metrics be interpreted?

Ads metrics are a way of analyzing whether your campaigns are adequately rolled out (“impressions” metric) and bring enough traffic to your site (“clicks” metric).

A small number of impressions or clicks may reveal a problem regarding the relaying of your campaign or a message that is not optimized enough as to convince people to visit your site.

Conversely, a campaign generating a lot of impressions and clicks but few conversions (see metrics concerning conversion) may be symptomatic of the fact that your campaigns are aimed at the wrong target, or of a bad user experience on your site (in which case the “attributed analytics” metrics will help you determine the root cause of the problem).

Ads metrics are therefore extremely important for measuring the visibility and effectiveness of your campaigns, and for analyzing the performance of your partners who relay them.

Attributed Analytics

How should these attributed analytics metrics be interpreted ?

Attributed Analytics metrics are a way of analyzing the behavior of your visitors on your site.The “bounce rate” for instance may be high if site browsing is hard or the landing page is inappropriate.In such cases, certain visitors will quit the site after viewing the first page.

However, a high bounce rate does not always point to a problem on your site. It may also mean that your site is extremely optimized and that web users only need to view one page to find the information they are looking for. This figure can therefore be interpreted positively or negatively, depending on the context.

Another example, the “number of pages viewed per visit” and “Average visit duration” metrics are indicators of time spent and pages viewed by your visitors: a high number of pages viewed and a long time spent may mean that your users like to browse and spend time on your site, but it may also mean that they can’t find their way around the site and are forced to spend a long time there before finding what they are looking for.

There again, these figures should be analyzed alongside the conversion figures to check whether or the viewed pages lead the user to convert.Attributed analytics attributed metrics therefore help you better understand the behavior of visitors on your site, and help you improve certain aspects of the site: campaign home page, internal searches, site organization, etc.

Costs Metrics

Is a session metric the same as a visit metric ?

Analytics tools on the market use the term "visit" or "session" and have each their own way of calculating more or less closely. Nevertheless, a visit is often associated to a metric which cannot spill over into the next day (i.e. a visit is cut at midnight), whereas a session is generally only link to the browser activity (eg: a session is generally not cut at midnight)

Here are the specification of our session metric :

1. The session ends after 30 minutes’ inactivity

2. The session ends when the user close its browser

3. A session can't last more than 4h.

4. After 30 min of inactivity, if the user start again the session the source will be Direct Access continuous session

5. No midnight cut-off : A 10mn session started at 23h59 will not be closed at 0h00. It will continue until 0h09 without generating 2 sessions (Some analytics tools cut will generates 2 visits in this cas, one from 23h59 to 0h00 and one from 0h00 to 0h09)

6. Each new entry point leads to a new session

Excluding IP addresses

In order to optimize the results submitted in your reports, Commanders Act allows you to exclude IP addresses in MixCommander’s Options Menu.

The goal is to allow you to retain only conversions generated by actual customers in your reports, excluding IP addresses used internally by your firm, by your partners for testing, or by robots.

To access the IP exclusion interface, click the “Options” tab > “IP Exclusion”:

You have two options:

• Excluding a single IP. To do so enter a name for the IP (e.g.: “Internal IP”) and its value, and then click the “Add” button on the upper right side of the interface:

• Excluding an IP range. To do so enter a name for the IP (e.g.: “Partner X IP”) and its value range, and then click the “Add” button on the upper right side of the interface:

Conversions from IP addresses you have excluded are not taken into account in your reports in order to not distort the results with conversions not made by your actual customers.

The exclusion rule is defined as follows: The IP + user agent combination must be associated to +1000 clicks, page views or conversions. The date on which an IP is excluded appears next to the “Auto:” label.

Channels creation & renaming

Commanders Act offers a list of default paid and natural channels. However, if the default names of the latter do no suit you, you may rename them to your liking.

The channel renaming interface is available on the “Options” tab > “Channel Identification”.

To rename your channel, click the “Edit” button to the right of the channel (pencil icon), and complete the “Alias” column with the name of your choice (2):

In your reports, you will see the channel name you selected instead of the channel’s original name.

You may also create new channels. To do so, click the “Options”>”Channel identification” tab, then the “Add Channel” button (1).

In the window that pops up: Enter the name of your Channel (1), the alias (i.e., the name that will be displayed in the reports available on the interface.)(2), the expected values for the “chn” parameter in the redirection URLs and impression pixels (3) and the channels category (4).

You can have your new channel added automatically to the existing attribution models by clicking “Yes“. Should you choose to not add it automatically, simply select the “Thanks. I’ll do it myself option (5)”. In case you choose “yes” in the step before, you will have the option to consider clicks only or clicks and impressions in the already created attribution models (6).

Channel categories creation

By default, two channel categories are proposed in the interface:

• “Paid” for paid channels (1)

• “Natural” for natural channels (2):

If you do not like these channel categories, you may rename them to your liking or create new ones.

The channel creation interface is available on the “Options” tab > “Channel Identification”. To create a new category, click the “TagCommander Categories” button (1):

A window pops up. Enter the category name (1) and click the “+” to add it (2):

To include channels in your new categories, click the “Edit” button to the right of the channel (1) and select the category of your choice from the dropdown menu (2):

Note: By creating channel categories you can prioritize certain channels over other in your attribution models.

Currency exchange rates

To include data in your reports according to your selected currency, Commanders Act provides the option of configuring currency exchange rates in the interface.

You may manage the currency exchange rate by clicking the “Options” tab > “Currency Exchange Rates”:

By default, the currency exchange rate is automatically updated in the tool every month: Commanders Act uses currency rates provided by http://www.xe.com.

The reference currency is the European Euro.

If you would like to personalize the currency exchange rates, you must be a site administrator.

Start by clicking the “Edit” icon (1):

A window pops up with 3 configuration options:

1) – Automatic: automatic configuration allows you to update currency exchange rates automatically at regular intervals. The exchange rates are taken from http://www.xe.com.

By selecting automatic mode, you may customize the update frequency:

• In the “Periodicity” section (1), indicate whether you want the updates to be daily, weekly, monthly, or annual.

• In the “Cycle” section (2), enter “1” if you would like the updates to be every day/week/month/year, “2” if you would like it to be every two days/months/weeks/years, etc.

2) – Manual: manual configuration allows you to update currency exchange rates manually.

Simply select the country of your choice from the list (1) and indicate the exchange rate to apply (2).

3) – FTP: FTP configuration allows you to upload your own exchange rate file in the interface so that your internal correspondences will be referenced in Commanders Act’s interface.

By selecting FTP mode, you may personalize various elements:

• In the “General Configuration” section (1), indicate whether you want the updates to be daily, weekly, monthly, or annual (“Periodicity”) and the update cycle (“Cycle”).

• In the “FTP Configuration” section (2), indicate all the elements (Host, Port, Password.) allowing us to access your FTP in order to download the currency equivalency file.

• In the “File Configuration” section (3), specify the format, name, and separator for the currency equivalency file TagCommander needs to download.

When you create a new report, only you (and administrators) can see it. You can share your report using the "Share" button when you are editing your report.

You can choose to share your report with some specific users and/or with a group of users (profiles), and define if these users will be availabe to modify it or only view it.

Ability to give access or not to the data set

There are 2 ways to manage this feature

1) Manage this option by configuring the profiles.

You can for example create un standard profile dedicated for your agencies and lock the possibility of accessing all of your data

2) Manage this option by configuring user rights

Your can now share a report with this new profil.

When the option "edit Dataset" is off the user will not be able to edit the data set in the report

Dont forget to publish the report ! otherwise the partner will not be able to display the report.

Dear Customer,

We have created (LRB) to bring you real-time functionality, a new higher-performance architecture, a simplified report creation process and an improved view to address the limitations with custom reports.

Therefore, custom reports will be deleted and replaced by LRB (refer to the schedule at the bottom of the page).

What about your data history?

The LRB module has been storing data since 18 March 2019, so that you can create reports retrospectively going back 15 months and analyse your campaign performance.

If you wish to archive the old data in your custom reports, we advise you to create backups using the export function or by contacting us (support or account manager) before 6 October 2020.

Refer to the schedule in the document below for details on the deactivation of custom reports.

GET Traffic Report Exports (deprecated, use live report builder API instead)

Returns data from the interface’s reports

Resource URL: GET /{version}/measure/reporttrafic/{id_type_rapport}?site=XXXX&token=YYYY&date_start=YYYY-MM-DD&date_end=YYYY-MM-DD&attrib=A,B,C&kpis=Q,S,D&segment=UUUU&breakdown=TTTT&format=ZZZZ

Parameters:

Return codes:

Response Format The response is in a JSON or XML format.

Response example in JSON and XML formats:

Funnel.io configuration

Welcome to the tutorial on how to configure costs with the Funnel.io API. The following steps explain how to:

• Configure a Funnel.io account with your platform partners

• Connect the Funnel.io API to MixCommander

• Check your costs import into the MixCommander interface

To set this up, make sure that you have all the required elements listed below:

• Your partner Ad platforms Login & Passwords (more information can be required depending on the partner e.g. For Criteo you will also need the Criteo API Key) to connect Funnel.io with the ad platform.

• Access to a Funnel.io account to set it up and obtain the API Key, Account ID and Project ID

• Access to the MixCommander platform to perform quality assessments.

A) Creating a Funnel.io Account

A Funnel account needs to be created by a Funnel.io staff member.

→ If you are a client of ours, please reach out to your Consultant or contact our support department (support@commandersact.com).

→If you are part of Commanders Act staff, please contact to create a new account and provide:

• The Commanders Act client’s name

• The name of the agency in charge of the client (if this is indeed the case)

Once the Account is created, you will have to go through a two-step configuration process:

• STEP 1: Connecting your advertising accounts to the Funnel.io Website

• STEP 2: Configuring the correct Source/campaign combination within the Funnel.io Website

B) Step 1: Connecting your Advertising Accounts to the Funnel.io Website

Select “Configuration” in the top navigation bar, and go to “Ad accounts” in the left navigation bar:

Hit “+ Advertising accounts” to open up the ad platform selection popup

Find the advertising platform you want to connect and follow the instructions. How to connect may vary depending on how Funnel integrates with each platform.

If you can’t find the advertising platform you’re looking for you can add it. Scroll down to the bottom of the popup and hit “Add it”:

Each advertising account you add will show up on the Ad accounts view. You can see their respective status, remove them as well as reconnect them if necessary.

C) Step 2: Configuring the Correct Source/Campaign Combination within the Funnel.io Website

Click on Websites > Your Website to configure.

Follow the setup wizard.

1- Skip Google Analytics link account

2- Import your advertising account (check the account that you have configured above)

3- Set up your currency

4 – Set up the Channel

How do I configure a Channel correctly so it matches data in MixCommander?

A correct channel configuration is necessary to ensure that data coming from a specific ad platform is associated to the corresponding traffic sources registered in MixCommander. When this is done you will notice how costs and channels/sources correlate properly.

A Channel in Funnel correspond to traffic source in MixCommander.

So how do you do this?

Editing a Channel:

To change the definition of a Channel, hit “Edit” next to it in the Website Settings view:

You will now be able to change what data this channel should capture and rename it with a unique label matching channels and sources present in MixCommander.

Select the campaign associated to the following rules:

Global report: Traffic & Conversions

CONGRATULATIONS! Your data has been configured!

Mapping Funnel.io and MixCommander

The FUNNEL API provides information on two levels (channel and campaign); they have to match Mix’s three levels (channel, source and campaign):

Channel/Source Level

A channel’s name, when configured in Funnel.io, has to be UNIQUE and be a match to only ONE CHN/SRC combination in Mix

Example 1: If in your Mix trafficking you have a unique source name per channel, you can name your Funnel.io channel the same as your source.

Example 2: If in your Mix trafficking several channels share the same source name, you have to name every Funnel.io channel differently.

NB: Please share the entire mapping table with your MixCommander consultant.

Campaign Level

Costs are displayed in MixComander on the campaign level in the Global Report All Channels – by campaign. To do so, you will need to populate the “cmp” parameter in your redirection tracking with the exact campaign name in your ad platform.

Example for a click on a Bing link:

http://client.commander1.com/v3/?tcs=123&chn=SEM&src=bing&cmp=IT%20Search_it%20Brand&…

The list of campaign names is available in Funnel.io

Connecting the Funnel.io API

API structure

With the Funnel API you can reunite all ad platform and Google Analytics data in your Funnel Account broken down by day, Channel and campaign. Calls to the API are issued through REST/JSON HTTP requests.

The URL’s format is:

https://api.funnel.io/<path>?param1=value&param2=value

The path can contain argument parts as detailed per endpoint below. Unless otherwise noted, you need to supply your apiToken or the Account ID as parameters.

Methods:

• HEAD

• OPTIONS

• GET

Required arguments:

• project_id

• account_id

• group_by

• apiToken

API keys

1) $API_TOKEN

Get API Key into Funnel: Configuration>>Details

2) $ACCOUNT_ID

You can find this in the browser URL when logged in to Funnel. Go to one of your Websites and then to Channels under Analysis and look for the Account ID in the browser URL. The Account ID is located in the following part of the URL: …/account/{$ACCOUNT_ID}/project/…

3) $PROJECT_ID

Project is synonymous with “Website” in the Funnel user interface and you will have one Project ID per Website. You can find this in the browser URL when logged in to Funnel. Go to one of your Websites and then to Channels under Analysis and look for the account id in the browser URL. The Project ID is located in the following part of the URL: …/project/{$PROJECT_ID}/…

4) $GROUP_BY

Currently supports two different groupings, “day” or “campaign_day”.

Day: values will be grouped by Channel and day.

Campaign_day: values will be grouped by Channel, campaign and day. This is the option to use if you want the most granular data.

5) $START_DAY

The first date in the range of dates to include in the result, on the format “YYYY-MM-DD”, eg 2015-10-01

6) $END_DAY

The last date in the range of dates to include in the result, on the format “YYYY-MM-DD”, eg 2015-10-01

7) RESPONSE

The response from the API is a JSON that has some metadata and then an array with JSON objects per Channel, day and optionally campaign, where each object has name/value pairs for each metric field.

The Channel metadata in the “channels” array contains timestamps (in UTC).

• lastRead the last successful sync from the source to Funnel

• maxDate the latest date with metrics for this source

• minDate the earliest date with metrics for this source

The “sources” object that is not in the “channels” array reflects the state of the Google Analytics data.

Note that monetary values are encoded as 1000 * the base unit of currency. E.g 12.34 USD will be encoded as 12340.

The JSON’s format is:

{ “accountName”: “ACCOUNT NAME”, “channels”: [ { “name”: “CHANNEL A” “sources”: { “lastRead”: “2016-01-21T08:21:17”, “maxDate”: “2016-01-22T00:00:00”, “minDate”: “2013-01-01T00:00:00”, } }, { “name”: “CHANNEL B”, “sources”: { “lastRead”: “2016-01-21T08:21:17”, “maxDate”: “2016-01-22T00:00:00”, “minDate”: “2013-01-01T00:00:00”, } } ], “channelsReviewed”: true, “currency”: “USD”, “id”: “PROJECT_ID”, “name”: “PROJECT_NAME”, “per_day”: [ { “channel”: “CHANNEL A”, “campaign”: “Campaign x”, “common-cost”: 153430, “day”: “2015-10-01”, “ga-sessions”: 375 }, { “channel”: “CHANNEL B”, “campaign”: “Campaign y”, “common-cost”: 5078710, “day”: “2015-10-01”, “ga-sessions”: 5514 }, { “channel”: “CHANNEL A”, “campaign”: “Campaign x”, “common-cost”: 2051030, “day”: “2015-10-02”, “ga-sessions”: 2136 }, { “channel”: “CHANNEL B”, “campaign”: “Campaign y”, “common-cost”: null, “day”: “2015-10-02”, “ga-sessions”: 503 } ], “sources”: { “lastRead”: “2015-11-17T00:21:14”, “maxDate”: “2015-11-02T00:00:00”, “minDate”: “2015-12-01T00:00:00” } }

Note: you can download the JSONVIEW chrome plugin to format data

Quality Assessment

Note: The cost Funnel API is updated several times a day. In order to obtain the most recent costs, we verify the API every four hours. If you notice discrepancies, they may be due to synchronization delays. If the problem persists, please contact our support department.

→ Cost summaries are accessible by clicking the Websistes tab in funnel.io. Click Analysis/Channels and select the desired period. You can export files to excel.

→ Costs will be available in MixCommander’s global report, follow this path: Traffic & Conversions >> All channels and All channels – by Campaign

By implementing the MixCommander module, you enable Commanders Act to collect data about your campaigns.

Commanders Act stores the following data:

Data identifying visitors:

• The TCID: this identifier (stored in a cookie set on your domain name) enables Commanders Act to differentiate one visitor from another. Visitor identification is handled automatically by Commanders Act.

• The IP address and user-agent: the visitor’s IP address and user agent make up the user’s “fingerprint” and are always logged by Commanders Act. In particular, this information provides for monitoring conversions if the internet user’s browser does not accept cookies.

The user ID, as long as it is provided in the MixCommander tags

Touchpoints of customer journeys:

• The date of the touchpoint: among other things, logging the date of the touchpoint allows the cookie window concept to be managed in the models attribution.

• Type of action: for each touchpoint, TagCommander logs the user’s action, i.e. a click, an impression, or a visit to the site.

• Channel/Source and additional tracking parameters: for each touchpoint, TagCommander memorizes the channel and the source (in parameters “chn” and “src” in the TagCommander redirect URL, as well as additional tracking parameters (e.g.: the search keyword, the affiliate’s ID, the name of the campaign, etc.).

Conversion details:

• The date of the conversion.

• Segmentation data: if you want to retrieve additional details on the confirmation page (e.g.: repeat/new customers, country, device, etc.), they will also be stored on the Commanders Act servers.

The following diagram represents a typical customer journey for a visitor, followed by the conversion. The table below it gives you an idea of what data is stored by Commanders Act.

The data captured by MixCommander is stored on Commanders Act servers (hosted on French Equinix servers, SLA 99.98%).

Raw data is stored for 90 rolling days. This means that the window for recalculating the source customer journeys for reports is 90 days max. It is, therefore possible to correct report figures, but only during this period. Note: The data storage period on our servers can be extended. For that purpose, please contact the salesperson in charge of your account.

On the other hand, we should point out that all the data in MixCommander report is visible as soon as the project begins when Commanders Act starts collecting data on your site via the “MIX - Click and Site Tracking V3.5“, “MIX -Site Tracking Only V3.5” and “MIX - Conversion 3V.5” tags.

Raw data is stored in 4 universes (4 files): clicks, impressions, page view, orders.

This data can be exported from the user interface.

Export recent data via email

How to get access to the data via FTP

To speed up the process add the necessary FTP details under connection management and send them with your request.

Specification of the CSV exports

File Packaging:

Files are sent as a zip archive that has the same naming conventions as the files.

File naming:

Files are named with the following naming convention.

File specs:

CSV Columns

Visitor ID: (all files)

Field type: string

Session ID: (all files)

Field type: string

Timestamp: (all files)

The timestamp of the hit as ISO8601 with YYYY-MM-DD HH:mm:ss The timezone of Paris local time. CET or CEST

Field type: date

Order ID: (conversion file only)

Id of the conversion as submitted in the Mix Conversion Tag.

Field type: string

Amount: (conversion file only)

Conversion Amount

Field type: float

IP: (all files)

IPv4 address of the user. If IP anonymization is turned on the last octet of the IP address is replaced by a 0.

Field type: string

User-Agent: (all files)

Field type: string

Other Dimensions:

All other Dimensions as you configured them under dimensions.