Trade promotion ineffectiveness can be paralyzing until you see the big picture.
Much has been made about the stagnant returns that many CPG companies are showing at the start of 2016 (See Gearing Up for Growth from Food Business News). The consequences of these observations for trade promotion and revenue management professionals are twofold:
- The pressure is greater than ever for CPG companies to quantify that their trade spend is not just successful, but optimized for maximum returns.
- Real-time visibility and analysis capabilities of all consumption, shipping and spending data are expectations for incremental reporting and revisions to trade promotion planning
However, it is accepted that timely calculation of the trade promotion ROI is unrealistic; so much so that many CPG companies simply accept the significant trade promotion spend as a loss. In fact, Nielsen implies that up to “59% of trade promotions don’t even break even.”
In an increasingly competitive marketplace with trade spending averaging 23% of gross revenue, can we just accept that trade promotion spend is a necessary and costly act?
True trade promotion optimization is not only about changing practices. It is about gaining increased visibility and control of trade promotions data to make more informed decisions. In doing so, we uncover several problems with the way trade promotion effectiveness is measured today.
Problem: Inaccurate or inflated baselines
Baselines that are utilized directly from syndicated data or direct POS data from the retailer can be misleading. They can be inaccurate due data anomaly or by going higher by trying to project the impact of loyal purchases during a promotion Accurate baselines for true TPM/TPO financial analysis should be representative of what would be sold in the absence of a promotion.
Result: The likelihood that the baseline volume is overstated leading to understated incremental volume and profit. As a result, trade promotions appear to have negative RO, when in reality their effectiveness is being assessed on an inaccurate baseline.
Solution: We find that a high percentage of trade promotions are effective when all factors are taken into consideration and recommend a comprehensive approach to baseline maintenance/monitoring. Analysts and trade promotion managers will not be accurate in their post event analysis utilizing a baseline that does not model out data anomaly and loyal purchase projections It is imperative to have a system that can accurately model and monitor the accuracy of your baseline trends with every 4-week data refresh.
Problem: Incomplete or isolated view of activity
We know that shopper behavior is influenced by an infinite number of factors, but in most cases when we determineour trade promotion effectiveness, we do so with the isolated view that our promotion is the single factor in determining whether a shopper purchases a product.
Result: Apathy. If it works, we do it again next year. If not, we just accept the failure. Even worse than not knowing, is the fact the delayed access to data paralyzes trade promotion planning in its ability to improve future promotions.
Solution: You need access to the big picture. When you can collectively have a view of consumer/shopper marketing initiatives, competitive promotion activity and planned vs. actual event performance, you can more accurately perform post-event analysis. This results in real-time KPI analysis enabling you to shift from tactics that are underperforming.
Problem: Data Anomalies
If data told the entire story, the average data scientist would not be paid $160,000 annually. There is a narrative behind the numbers. There is human error, weather conditions, shipment delays, etc. Even your competitors’ reactions to these events affect the data.
Result: A failure or inability to account for these data anomalies when performing post-event analysis results in inaccurate lifts to the baseline which skew both the reporting of ROI and future planning.
Solution: Empower the people who can see the circumstances surrounding data inconsistencies with the ability to watch and account for these anomalies. You should be able to be alerted when there is an inconsistency in baselines, modify baselines to account for this as an exception and not a trend, and align promotions reflecting planned vs. actual execution.
If we accept that trade promotions will continue to miss their objective 59% of the time, then the doom’s day prophecies of stagnant growth and declining market share will continue to drive revenue reports. Instead, CPG companies today have the option to adopt the solutions and practices that can move them from the perils of analyzing inaccurate data, to empowering themselves to act more effectively as a result of their data. The future will continue to draw a stark line between those companies who continue to use the insanity approach to data analysis (doing the same thing over and over again and expecting a different result) and those that take advantage of the affordable TPM/TPO solutions that result in a quantified return on the significant trade spend.
Which company are you today and more importantly which company do you want to be tomorrow?
What to read next: Why is optimization a game changer for CPGs?