Understanding the User’s Path to Conversion

June 3, 2014 — by MediaMath    

Traditionally, marketers have relied on the last click/last view attribution model, which assigns full credit to the last click or touchpoint in a customer’s path to purchase.  Marketers know that using this model just doesn’t cut it anymore, as it doesn’t accurately or fairly represent all of the preceding touchpoints that might have had impact on generating brand awareness, engagement, and ultimately conversion. Different messages serve different purposes down the consumers’ path to purchase, and marketers have traditionally had little visibility into all of the driving directions leading to the last stop, settling instead for simply knowing the last turn before arriving at the destination. However, with the development and proliferation of powerful advertising technology, that’s all changed.

In online advertising, a path is a sequential list of media touchpoints a user was exposed to prior to converting.  These touchpoints could be focused on one media partner to establish the relationship between different media strategies (e.g. Prospecting vs. Remarketing) or could be focused on the work being done with multiple media partners (e.g. Yahoo homepage vs. remnant RTB vs. YouTube video).  Understanding which strategies/partners served impressions to the same user will reveal that there is conversion influence coming from impressions other than the last touchpoint.  Additionally, you can see which strategies/partners are able to find incrementally unique convertors, rather than those simply fighting for the same users.  Understanding this could pay dividends when deciding how to allocate future budgets appropriately.

MediaMath’s Pathway Analysis reporting helps marketers understand the steps along the path — particularly if the media buys are disparate, as they often are. For example, let’s look at a typical acquisition strategy:

1.    Brand A runs audience-targeted display ads across a network as a prospecting strategy.
2.    A consumer clicks through one of those to Brand A’s site and shops briefly, but does not complete a purchase.
3.    Brand A (which has a super-savvy CMO) remarkets to that consumer, purchasing media via RTB across an ad network. The consumer sees the ad several times over the course of the next three days.
4.    During the remarketing campaign, the consumer coincidentally interacts with a premium rich media ad Brand A has purchased directly on
5.    Finally, ready to buy, perhaps days later, the consumer searches for Brand A’s product on Google, clicks an AdWords listing, and completes her purchase.


Frequently, there are many interaction points between awareness and acquisition. But in the last click/last view scenario, only Google will receive credit for the purchase in spite of the activities higher up the funnel that clearly contributed to the conversion.

While a Pathway Analysis report can be a very powerful tool, for sophisticated advertisers who already understand the pathing concept, the true north star should be leaning harder on advanced models that are able to quantify the fractional credit that each touchpoint deserves. MediaMath’s attribution partners capable of such analyses include Adometry, Convertro, and Visual IQ.  Even more powerful is the ability to ingest this 3rd-party data and automatically leverage it in real-time when decisioning on the right bid price for an impression opportunity, as provided by MediaMath’s Closed Loop Attribution product.

With real data to guide them, marketing organizations can become more effective in their messaging and more efficient in their media buying, investing in the right creative formats and the right media at each phase of the buyer’s journey. While Pathway Analysis doesn’t completely solve the attribution problem, it paves the way, providing the insight marketers need to find the gaps and opportunities in their campaigns.