This series of blogs will address post promotion event automation and analytics.
We’ll start with a brief industry overview, including today’s challenges in the Promotion and Trade spend area. Over the course of the next few blogs, we’ll also detail the importance of automating the historically manual process of managing promotional events. Lastly, we’ll address the most important aspect of promotions, that being, the return on investment pertaining to your trade spend.
Trade spend is typically 15 to 20 percent of a company’s gross revenue. This chart from A.C. Nielsen shows that trade spend is the number one priority for American corporations today, in the CPG industry. It’s the highest spend priority and in many cases, it’s the second highest corporate expense next to payroll. What is Post Event Automation and Analytics? It is trade optimization that isn’t purely an exercise in implementing advanced statistical models but also an enterprise-wide agreement on processes and metrics.
Statistical models are great but if you can only apply them to 5 to 10 percent of trade spend your missing 90 to 95 percent of everything else that is going on out there. That is the problem with looking at it from just a statistical model stand point. It’s very complex and it’s very difficult to mold the data into those models today.
We think it’s best to find a framework that applies advanced calculations to multiple downstream data sources. In this way we can shift the promotion planning process from an art to a science, such that supply and demand can more effectively be met. Rather than having to cobble together spreadsheets from all over the place, we believe the goal should be to automate the process. Shift the work involved from an art that only a few people in the organization have a good grasp on, to an actual science.
Those of you in the trade marketing area working with promotions will know exactly what we mean when talk about spreadsheet hell! If we can streamline and automate the spreadsheet creation process, then we can avoid the costly, manual, error prone, process of harmonizing disparate data.
We estimate that about 80 to 90 percent of analyst’s time is spent gathering, collecting and integrating all of this disparate data, only to put it into spreadsheets. Then you have to redo it all over again, every time you want to run those analytics. So you have “data silos.” Every spreadsheet is a unique creation that requires days and weeks of work. These are spreadsheets that companies rely on and use just to run their business. Little, if any time is actually left to spend on actually analyzing the data to learn more about the actual promotion effectiveness. Automating the spreadsheet process frees up analysts to learn more about your business and how to make profitable decisions.
You can follow this blog series which will take you through the issues and solutions in this space. Watch for my next blog that addresses issues related to promotions and the inability to optimize trade spend across all retail segments.