Marketers are always looking for the next, best way to measure where sales are coming from. The leading system for figuring out what marketing tactics are influencing and driving purchases is multi-touch attribution (MTA), which is shaping up to be one of the most important digital marketing tactics of 2016. Why else would big names like Google, AOL, and Nielsen be investing in MTAs to help clients optimize ad spend? But, David Rekuc, Marketing Director for Ripen eCommerce writes in Marketing Land this month that looking for the perfect attribution model is a fool’s errand.
We happen to agree, but not necessarily for the same reasons outlined by Mr. Rekuc. Here’s the problem: Multi-touch attribution modeling uses a linear progression of events to assign value to each customer touch point in a marketing campaign. The whole idea behind attribution is to divide up credit for a conversion among the touchpoints preceding it, so a business can determine what marketing tactics are working and which are not.
While MTAs are getting more and more sophisticated, they still have major drawbacks like:
- The attributed ROI does not take into account offline media.
- They also do not take into account outside factors such as social perceptions, personal customer beliefs, pricing, promotions, seasonality, or the economy.
Perhaps the biggest flaw in MTA models is their inability to take the customer’s journey into account. Every customer grouping experiences a brand in different and unique ways. For a model to truly illuminate what marketing activities are influencing customers or groups of customers, it must ensure that a tailored customer experience is included in the unique profile of each customer grouping.
Instead of starting with an attribution model made up of ads, channels, and conversions, it is more effective to start with the customer in mind, and define the metrics that characterize a good customer. Most companies would likely agree that customer engagement, purchase history, sentiment, and brand advocacy would be good metrics for identifying a “good customer.” Once these attributes have been defined, a customer lifecycle attribution model can be created that drives these metrics.
The next step in implementing a customer lifecycle attribution model is to observe the behavior of these customers across all channels. Once achieved, customers can be clustered into groups according to similar behavior – or journey’s. By analyzing the lifecycle behavior across all channels for each customer group, companies can determine which groups drive the most revenue through which channel.
By undergoing this process, marketing spend can be derived for each group and channel combination. The important thing to remember is to test, predict, and compare the results – and continue to iteratively improve the approach of tracking and understanding the customer lifecycle – so a business can move closer to the holy grail: understanding the true impact of marketing efforts.
ENGAGE.cx provides businesses all the tools needed to implement a well-designed Lifecycle Attribution Model. ENGAGE.cx’s Relationship Cloud packages all of the necessary capabilities into one purpose-built solution that delivers personal customer relationships at scale. If you would like to learn more about the Customer LIfecycle Attribution Model, please download our newest white paper here.