Today’s data-driven world has resulted in the emergence of data as an organization’s most valuable resource and cornerstone of corporate strategy. Marketers are using this information to drive smarter, more creative decisions. But all the data in the world is useless if marketers are measuring the wrong things, and may cost marketers billions of dollars in wasted resources.
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Unfortunately, outdated tools like multi-touch attribution (MTA) and marketing-mix models (MMM) fail to deliver timely insights or contribute to impactful decision-making.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: Older or siloed tools may give too much credit to the last piece of advertising a customer saw. For example, most marketers would agree that a billboard outside one’s store or the banner ad seen in advance of a purchase isn’t solely responsible for a sale. 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: Less expensive impressions show up more often in an ad buy. 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. These inexpensive placements drive activity but not business results.
Chasing the Digital: Digital efforts give marketers quick and easy performance data but it’s a one-dimensional look. Unfortunately, we may optimize based on “high performing” click-through rates (CTRs). Remember however, that a CTR of 2% is considered high performing, leaving a significant part of the market out of the equation. 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. This is particularly important for brands with specific selling seasons or short product life cycles.
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. A brand is the foundational element that buoys performance of the entire marketing effort. If you aren’t keeping a finger on the pulse of brand health, advertising performance may deteriorate.
McKinsey & Company research finds that organizations leveraging data analytics outperform peers by 85% in sales growth and more than 25% in gross margin. But at the end of the day, insights are only as good as the data collected and only then can marketers truly understand the health of their brands.