This is the tale of two shopper marketing teams. One team measures event outcomes and sees continuous improvement in returns, and so for them, this is the best of times, the age of wisdom, the season of light.
Not knowing how, what, or why to measure, the other team stagnates in a season of darkness and posts no improvements.
Tyson Foods is a top-tier shopper marketing team that just keeps getting better through an ongoing measure-learn-improve process, which, over a five-year-period, has enabled the CPG superstar to double its shopper marketing ROI.
Continuous improvement in business has been around for a long time but is relatively new to marketing and newer still to shopper marketing in particular. The Marketing Accountability Standards Board aims to establish marketing measurement standards as a baseline for continuous improvement in financial performance. The MASB defines marketing accountability as linking marketing actions to financial performance and business growth, and the way to do that is through the measure-learn-improve process.
Measuring is the Means to Improvement
Measuring fuels improvement by establishing an objective and common understanding of the results with all stakeholders. Decision makers are informed and aligned to make better decisions. For measuring to beget better decision making and, ultimately, better results, shopper marketers need business intelligence tools to capture the measurements in one place and deliver insights and decision-support data to stakeholders. Predictive analytics technology is the preferred tool for Foresight ROI clients, including Tyson. The technology looks backward as well as forward, analyzing historical data to forecast the financial performance and overall effectiveness of shopper marketing events in the planning stages. The forecast becomes the performance benchmark.
When an event ends, data collected from retail partners and other sources is analyzed and the results measured. Then, the actual results are compared to the expected results. Where results are better or worse than expected, there’s room for learning and improvement. The goal is to repeat what is working, remove what is failing, and revise where there are opportunities to improve.
Key learnings are which strategies and tactics work best; which integrated marketing efforts are synergistic; which brands to promote and when; and which creative is most effective. It’s especially important to break down return rates by customer to learn who the best ones are, because they typically generate returns three times greater than the poorest-performing customers.
The Right Questions Lead to the Right Answers
Predictive analytics technology doesn’t provide all the answers or eliminate the need for judgment calls. Sometimes, measuring raises questions that shopper marketers would not otherwise know to ask. To give a real-life example, one brand’s microsite received some 5 million impressions yet fewer than 100 shoppers printed the digital coupon. Obviously, redemptions were wildly off target, and it wasn’t for lack of traffic. It turned out the microsite, though beautifully designed, did not have a “click here” call to action so it wasn’t clear how to get the coupon, or even that there was one. Tracing the failure to creative led to improvement and agency accountability. This qualitative analysis of the creative came about only because measurements were taken, which revealed the need for further investigation and guided the discovery process.
Situational variables often throw off expectations, creating discrepancies that require some sleuthing. For example, brands sometimes provide retailers with a durable merchandise display only to discover down the line that stores are stocking them with competitors’ products.
A critical component of continuous improvement is collaboration across functions in the organization, as well as with retailers, for all-win results. Having a single, measurable, attainable goal shared across this cross-functional team helps with planning, smart goalsetting, and accountability. Foresight ROI’s predictive software has a dashboard that allows every stakeholder to help plan, track, and evaluate events, and even monitor an event in progress in order to react and adjust quickly if something is amiss.
Start Small, Stay Consistent, Win Big
Dating back to its earliest days, the continuous improvement model is intended to produce small, incremental changes from one cycle to the next, but over time, they amount to big gains, as with Tyson. In our tale of two shopper marketing teams, both could come out on top if the team that’s not measuring understood how manageable it is to get started. Foresight ROI recommends companies that are first starting out limit their data analysis to perhaps two customers and two brands, which together, usually account for at least 10 to 20 percent of the shopper marketing budget. By starting small, and in the process of learning to use measurements to make better decisions, the team can be assured of the value of measuring before investing more time and money.
One final data point to nudge reluctant shopper marketers from the epoch of incredulity to the epoch of belief: Continuous use of a predictive analytics tool as part of a measure-learn-improve process typically results in a 10 percent or more increase in marketing ROI each year. That’s like getting an extra million dollars for every 10 million dollars invest in marketing. The tool also helps build best practice knowledge that begets greater wins and windfalls over time.
This is the second of a three-part blog series on the journey to becoming a top-tier shopper marketing organization. Part 1 outlined the five-part journey. Part 3 is Foresight ROI CEO Rick Abens’ highlight reel of the 2018 P2P Summit, March 12-14. Abens—an MASB director since 2008—co-presents with Tyson Foods VP Christopher Witte “Journey to Top-Tier Shopper Marketing Organization: A Case Study” at the Summit on March 14, 10:15-11:00 a.m.