5 Mistakes Every Marketer Should Avoid
Flaws in Attribution Are Costing the Industry Billions in Profits
Flawed multi-touch attribution models are costing companies billions in sales and profits.
An informal consortium of companies came together to look into the matter. The consortium included a few marketers, including a prominent insurance company, a leading advertising software company, a couple ad agencies, and a few academics. Each had independently found fatal flaws in the recommendations coming out of popular attribution solutions. These budget re-allocations were so contrary to effective spending that, when applied, they actually reduce the amount of sales per dollar of marketing spend. One retailer reported faithfully applying the findings of the MTA for two-years, yet, business growth didn’t materialize.
Some questioned if the attribution vendors owned by media companies were self-serving in their inaccuracy. They suggested either fraud or system gaming. Others were more deferential, noting that applying math to a problem can create an illusion of good science, but may blur obvious logic. They pointed to over-reporting the value of impressions delivered to people that would have bought anyway. Whatever the reason for the flaws in attribution recommendations, the consortium members all believe in the value of analytics and want to ensure the industry gets the analytics right. As one member explained, “The consortium’s desire is to shine a bright light into these dark, black boxes of attribution. This will help the industry make better decisions to create more value.”
In this brief whitepaper, we outline the consortium’s findings and open a dialogue in the industry, ensuring that we get the science of multi-touch attribution models right. With billions at stake, we have an obligation to the professionalism of the industry to identify problems and promote best practices.
We’ve organized this whitepaper into two sections. First, a review of three independent validation studies that identify problems with multi-touch attribution models, and second, a discussion of the biases we’ve identified and advice on how to avoid them.
Download your free whitepaper and learn about flaws in attribution that could be seriously hurting your bottom line.