With digital marketing reaching new levels of maturity, the pressure is on to demonstrate the role each channel and activity plays in driving business value and optimizing investments across digital channels.
Therefore, how are retailers planning to identify potentially wasteful affiliate spend, reduce pay-per-click (PPC) and search engine optimization costs without impacting results, or identify which activities most contribute to different online transaction types? And when?
These essential measures are certainly not going to be achieved using traditional aggregate-level data or 'last click' analysis. This article outlines the importance of individual-level data in developing the insight needed to build robust, accurate digital marketing attribution models which take into account a customer's whole route to conversion, not just the first or last click.
Marketing optimism may be on the up according to the latest Bellwether report, but unless companies can evaluate marketing effectiveness and demonstrate return on investment, that optimism may be short-lived.
With budgets increasing for the first time in years, marketers can begin to exploit omnichannel marketing opportunities and attain new levels of customer insight. However, there's no return to the blank checks of the past. Digital is still highly compelling, but justifying spend and demonstrating value for money is now, quite rightly, top of the agenda. It's essential therefore that retailers move beyond current, somewhat blunt, models for measuring attribution and achieve accurate and credible insight into performance.
Critically, it's time to admit that attributing the full value of the marketing investment to the last or "converting" click is fundamentally flawed. By ignoring all previous activities which have contributed to the eventual sale, this approach is inaccurate, untrustworthy and often results in investment in key activities being reduced or cut.
"Last click" misses essential elements of the consumer journey. With even the fastest-moving products, there are usually at least a few stages in the buying cycle from initial awareness through to eventual purchase. Showrooming is a prime example, with consumers increasingly comparing prices and reviews on a mobile device while in-store. According to the latest figures from the Pew Research Center, 25 percent of mobile users look up prices online and 24 percent look up product reviews while in-store.