Optimize Digital Touchpoints: Attribution or Path to Purchase?

Digital Touchpoints

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Attribution modeling vs. path to purchase analysis: What’s the difference between the two? Which model is better?

The purpose of both models is to establish optimal touchpoints for consumer interaction with the brand and to achieve the best cost savings and customer experience. Attribution is ad-centric; path to purchase is consumer-centric. Attribution modeling is prompt; path to purchase modeling is deep.

In attribution modeling, marketers use the data generated from tagging ad placements to understand the degree of influence each ad has on the consumer. Attribution analysis apportions “credit” for each conversion among the ads, essentially prioritizing which ads are more effective than others.  Marketers can then use that information to change strategies by re-allocating media spend to the ads that had the greatest impact.

The path to purchase analysis concentrates on the sequence and intensity of each relevant behavior that may eventually impact a consumer’s decision. Exposure to an ad or a click on a paid search ad are all accounted for (attribution model), but so are the visits to a competitor’s site, a review site, the use of a search engine on an aggregator site, seeing a product placement in a YouTube video, etc. The approach is exploratory – no prior assumptions are made about consumers’ behaviors.

So which is better: attribution modeling or path to purchase analysis?

Attribution management, at its basic level, is almost real-time. The results of users’ exposure/interactions with ads are immediately processed, weighted, translated into algorithms and fed into media optimization engines. But in today’s diverse and fragmented media ecosystem, paid ads are hardly the main factor steering consumers to purchase. Other purchase factors include: earned media, word-of-mouth, competitive activity, seasonality and much, much more. Ad credits can only be allocated between the entities that can be tagged, and this external, relevant data (not immediately available) has to be collected, cleaned and matched to campaign data. This turns the entire process into another media mix modeling exercise – and slows the process to a halt.

An alternative approach is to identify where and when consumers are most open to marketing messages during the purchase process – and then strategically optimize advertising at the stages of consumer decision making when ads matter the most.

The path to purchase approach serves such a purpose. By looking at the entire industry rather than at an individual advertiser’s campaign, the path to purchase analysis discovers previously neglected touch points that result in a loss of prospective customers to the competition. With this, digital marketers can re-allocate resources and spend to remedy the situation.

So, which model do you like now?

About Yaakov Kimelfeld:
Yaakov Kimelfeld, Ph.D., is Chief Research Officer at Compete. He is an industry expert in media research and analytics and is responsible for the establishment of best-in-class processes for refining and expanding Compete's data, analytic, and research products. Connect with him on Twitter @YaakovKimelfeld.