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.

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.

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.

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.

• 1. 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.

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

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.

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.

On the interface, you have

En arrivant sur l’interface, vous êtes directement placé sur la liste générale des rapports actifs, mais en cliquant sur l’onglet « Archive » vous avez accès à l’ensemble de vos rapports archivés.

• 1. Vue du rapport

L’écran de consultation des rapports vous permet de parcourir le tableau de donnée et les différents niveaux de dimensions prévus. Vous pouvez également utiliser les filtres définis lors de l’édition.

• • 1. Calendrier

Le calendrier est situé en haut à droite de l’interface. Vous pouvez définir la période dont vous avez besoin de trois façons différentes :

• Directement dans le champ d’input

• Par la liste de présélection

• Par les calendriers de début et de fin de période

Dans le champ d’input, le format à respecter est : aaaa-mm-jj – aaaa-mm-jj

Nota Bene :

Dans la liste de présélection, les propositions « Last X days » ne prennent pas en compte le jour courant.

Dans la liste de présélection, les propositions « X to date » prennent en compte le jour courant.

• • 1. Export

Le bouton d’export est situé en haut à droite de l’interface.

Attention : Pour le moment, seuls les 3 premiers niveaux de dimension du tableau sont disponibles à l’exportation.

Vous avec deux types d’exports disponibles :

• One shot : Le rapport qui s’affiche à l’écran est envoyé avec tous ses filtres actifs et la période de temps sélectionné. Il est envoyé via mail, une seul fois, à l’adresse enregistrée dans le profil de l’utilisateur.

• Scheduled : L’utilisateur peut prévoir une période, une fréquence d’envoi et un moyen d’envoi (soit mail, soit par serveur FTP)

Dans les possibilités de prévision, vous pouvez définir trois fréquences différentes :

• Quotidienne : l’export sera envoyé chaque jour avant 10h du matin.

• Hebdomadaire : l’export sera envoyé chaque semaine et vous pourrez choisir le jour de l’envoie.

• Mensuelle : l’export sera envoyé le premier lundi de chaque mois.

Les périodes sont légèrement moins variés que dans le calendrier pour correspondre aux possibilités de fréquences d’envoie.

En envoie via mail, vous pouvez ajouter autant d’adresse que désiré dans le champ prévu à cet effet, mais seules les adresses des collaborateurs inscrits sur la plateforme sont autorisées.

En envoie via serveur FTP, vous pouvez uniquement choisir un serveur FTP déjà configuré dans les options et ajouté un chemin pour entreposer l’export dans le dossier de votre choix

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:

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.

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.