The so-called Customer Lifetime Value is a metric that describes how much turnover a customer will generate for a company in the course of his 'customer life'. This metric plays a particularly important role in the acquisition of new customers. Every company would like to acquire customers likely to have a high CLV. This is because acquiring new customers is always a very cost-intensive venture, thus new customers often do not 'carry' their acquisition costs until their third or fourth order.

From a business management point of view, it makes absolute sense to steer your marketing toward high-value customers on a long-term perspective.

The calculation of the CLV is done on the incoming orders of a customer, or with a predictive modeling approach, which includes various data points of the customer, hence you already get a prediction of how much turnover the customer will generate in its lifetime right at the moment his order is placed.

A common Customer Journey at Adtriba starts with the first marketing touchpoint of a user and ends with the successful execution of your conversion goal. If the user does not convert within a 60-day look-back window, the customer journey will be cut automatically. The multi-touch attribution allocates weights for the channels based on individual conversions and their shopping cart values. In the CLV attribution, however, all conversions that a user completes within a specific defined look-back window are included in the weighting and value distribution. This means that the initial acquisition channels are remunerated sustainably over the entire CLV and not just once with the initial order.

Evaluation of channels according to regular attribution (focus on a customer journey)

The diagram above shows the conversion value attributed to each channel that participated in a successful customer journey and naturally in their conversion events. For the first customer journey, only SEA non-brand and direct receive a value, as they were identified as the only effective touchpoints in the respective customer journey. In general, for all three customer journeys, only those channels that were also involved in the respective CJ are credited with value.

Turning now to the CLV attribution we can observe a different shift of value per channel:

Now all channels that were involved in the entire 60-day customer lifetime cycle have been assigned with a credit that changes and adapts constantly as long as the customer lifetime value increases. Especially SEA nonbrand shows a strong increase in its attributed value. Being most efficient in the first sequence though.

By default, Adtriba follows the continuous calculation of the CLV over time. The results of the CLV can be easily chosen in the Customer Journey dashboard via a little toggle above.

Furthermore we provide a comparison between regular and CLV attribution model in the performance report in a dedicated table:

In addition, the CLV attribution view can also be activated for Adtriba's Google Ads export to optimize Google Ads bid management based on the CLV MTA.

It may be noted that the "sum of revenues" is a suitable proxy for the CLV. For a complete CLV analysis, however, the costs and operating margins per customer must also be taken into account. This is possible by combining the Customer Journey Export, including the CLV Attribution weightings, with your backend/CRM data.

Without first focusing on the data and looking at CLV attribution from a purely theoretical perspective, one would assume that the channels in the lower funnel (e.g. SEA Brand, Retargeting, and Direct) would lose in terms of conversion rate compared to those in the upper funnel (e.g. Non-Brand Paid Search, Display and Social).

The following statistics are based on a selection of Adtriba users only:

Reduction of conversions that are attributed to

Direct (-17%)

and Paid Search - Brand (-19%)

Raise of conversions that are attributed to the following channels:

Paid Search - Brand (8%),

Display (10%)

and Social (3%)

Taking the statistics above into consideration, we can confirm the assumption that marketing campaigns in the upper funnel are very likely to increase their performance whereas on the other hand marketing campaigns in the lower funnel tend to lose conversions through CLV attribution.

We are very pleased that our clients are working with these enhanced analytics and gaining actionable insights through CLV Attribution. If the findings do not result in concrete marketing measures, even the most innovative CLV Attribution analysis is worthless.

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