Why Last-Click Doesn’t Tell the Whole Story
Paul Pellman is CEO of Adometry, which utilizes advertising attribution technology.
The fallacy of the current, and increasingly antiquated, last-click standard is that it assumes that if any media touch point is in the path of a conversion, it deserves a share of credit. There is a fundamental difference between causality and correlation, and only an advanced attribution approach can adequately uncover that difference.
Simple attribution uses predetermined weights to assign credit to every touch point. Marketers assign 100 percent of the conversion credit to the last click or last ad event seen, whether or not it played a part in the conversion. As marketers have come to recognize the inaccuracies inherent in last-click attribution, the scope of simple attribution models has proliferated. Some examples include linear attribution, which evenly allocates credit to all touch points in the conversion path, or time decay attribution, which allocates credit to touch points based on their proximity to the conversion. Also, ad hoc attribution heavily allocates credit to the first and last touch points, with the remainder evenly spread across all other touch points. Ultimately, none of these approaches are truly reliable because credits are arbitrarily assigned.
Meanwhile, advanced attribution’s approach determines attribution weights by analyzing 100 percent of the data, instead of subjectively assigning how much weighted credit is attached to a channel, campaign, creative or placement. It looks at all of the media touch points in the consumer’s path to conversion and calculates the appropriate credit based on the touch point’s true contribution to the conversion. This shows marketers which parts of their marketing campaigns are actually driving conversions.
Look at the concept of the introducer — the first media element in the conversion path to receive credit. With simple attribution, the introducer is defined as the first element served. There are several problems with this approach. First, advertisers deliver a constant stream of media, so there is no simple way to identify the true introducer. Predetermined look-back rules can be used to credit the first ad seen within a pre-established time frame as the introducer. For instance, if it is decided that the first ad seen within 30 days of a conversion earns the credit, marketers risk excluding an ad served before that window, which may have been the actual introducer. It’s irresponsible to assume all consumers make decisions on the same schedule. The first touch point that matters is the one that definitively moved the consumer toward conversion.
Additionally, not every media element performs the same. Simple attribution can merely estimate introducers, promoters and closers in the funnel, mechanically giving the same credit to all funnel stage creative and campaigns, which means marketers are unable to test creatives that target top- or bottom-of-funnel users. That’s like driving a stick-shift car stuck in one gear. Only an advanced attribution approach can discern and accurately measure the relative performance of different creatives at different points of the conversion funnel.
While optimizing in-flight campaigns, advanced attribution trumps simple attribution. Because simple attribution uses predetermined weights to assign credit to campaign elements, marketers cannot see which sites, channels, creative or placements are performing best — and therefore can’t move their ad spend to optimize for these sites. With advanced attribution, marketers can make incremental, adaptive changes to existing placements or manage budget reallocations across channels mid-campaign. A data-driven model, like the one used by advanced attribution, allows advertisers to optimize many different KPIs – conversions, revenue, ROI, reach, lifetime user value and more.
Advanced attribution provides a more accurate way to analyze marketing campaigns, so marketers may make changes to drive improvements for future buying and investment decisions. Will you take off the blinders of simple attribution before your competitors do?
With Canva and Adobe’s new updates, the generative AI race enters the brand design space
Canva and Adobe are just two of several major design and visual platforms that are rapidly introducing new generative AI capabilities in the service of brands.
Terry Kawaja explains why he invested in Possible, the Dmexco founder’s new conference
Kawaja believes Possible will super-serve the intersection of marketing, media and tech like no other tentpole can. And he's invested his own money into it.
Execs are ignoring the dangers of ‘confidently incorrect’ AI and why it’s a massive problem
That means significant risks are emerging as companies rapidly race to re-orient themselves around ChatGPT without being aware of – or ignoring – the numerous pitfalls.
SponsoredHow ironSource’s hybrid mediation solution is enhancing mobile ad monetization
Produced in partnership with Marketecture The following article highlights an interview between Nimrod Zuta, ironSource’s senior vice president of product, and Eric Seufert, general partner at Heracles Capital. Register to watch more of the discussion and learn how advertisers are leveraging hybrid mediation solutions to fuel more effective ad monetization. Advertisers are facing a particular […]
Why Chips Ahoy’s linear TV budget is crumbling in the face of new digital options
To keep up with Gen Z shoppers, Mondelēz-owned brand Chips Ahoy! is all but waving bon voyage to its linear television advertising budget in favor of digital advertising.
Why the esports community’s toxicity is becoming the industry’s most enduring problem with brands
As fan blowback becomes a regular occurrence in esports, the industry is turning into a potential minefield for the brands looking to use it as a vehicle to reach gamers.