To avoid making costly errors, marketing professionals must answer two key questions: Am I gathering the right data, and is it being analyzed properly? After all, the point is to uncover a competitive advantage and get more out of every dollar spent.
Unfortunately, outdated tools like multi-touch attribution (MTA) and marketing-mix models (MMM) fail to deliver timely insights or contribute to impactful decision-making. These models cannot provide the holistic view of performance needed and their disconnected, one-dimensional views of of disparate channels are unable to provide a true understanding of what’s working and what may be hindering marketing efforts.
They fail for some simple reasons:
Last Touch Gets Too Much Credit: Measuring the complete consumer journey and contributions made by each message offer a better understanding of what drove the sale.
Cheap Inventory Is Over Represented: Chasing a low CPM may help achieve a reach and frequency goal, but this tactic may not move the sales needle as it’s likely not reaching the right audience at the right time in the right place.
Chasing the Digital: Relying solely on digital measures fails to account for longer lead brand building and customer loyalty efforts.
Backward Looking Optimization: Many attribution models report results after campaigns are over. While important, successful marketers need to look forward and optimize using leading indicators. Even more importantly, measurement tools must offer data to inform right-time optimizations to campaigns while they are live.
Chasing Ad Performance at the Expense of Brand Building: Attribution models focus too heavily on immediate response to advertising versus long-term effects of brand building.
Briggs, R. (2018, June 21). Measuring the Wrong Data Is Costing Marketers Billions. MediaPost.