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.
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)
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.
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.
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.
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):
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”)
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.
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.