When it comes to managing trade investment, CPG companies can be paralyzed by the overwhelming task of managing incoming data. They rely heavily on manual intervention and cumbersome spreadsheets to glean even the slightest bit of insight. Even those companies that have adopted Trade Promotion Management (TPM) tools to manage tactical execution of their promotional spending, only have automated accounting transactions and struggle with real-time, accurate post-event analysis and repeatable, informed planning decision making.
Combining Analytical with Artificial Intelligence
Industry leaders have prioritized analytics initiatives within their organization to bridge the gap between data availability and actionable insight. (See How Predictive Analytics is Defining the Future for CPG leaders) In doing so, these companies are depending on advanced analytical solutions, like a Trade Promotion Optimization (TPO) solution, to improve the accuracy, efficiency and predictability of their trade promotion planning and analysis. Even with these steps, a company that cannot eliminate the manual intensiveness of data management, base and promotional analysis, and customer planning will still be plagued with inaccuracies, redundancy and a lack of timely intelligence.
With this, companies must consider what, if any, artificial intelligence their TPO solution provides them to augment the manual limitations holding their company back from sustainable processes and results.
AI and Trade Marketing
These 3 AI capabilities, that should be part of any TPO solution you consider, can immediately improve your company’s actionable intelligence leading to direct impact on your bottom line.
1) Smoothing of baselines
An accurate baseline is paramount to accurate post-event analysis and to develop the accurate lift-coefficients
used in your customer planning. That said, manually compiling data to determine base volume and then managing these baselines is an almost impossible task. Automating the harmonization of consumption, spending and
shipment data to calculate an accurate baseline and employing machine learning to smooth baselines to the
correct curve as new data is added eliminates these concerns and immediately improves accuracy.
2) Generating lift coefficients
“It’s math not magic,” says T-Pro Chief Knowledge Officer, John Weller, about getting accurate lift coefficients to calculate promotional lift during post-event analysis and to inform accurate forecasting during promotional planning. However, the math behind the results frequently changes as new data enters the models. This means that traditionally there needed to be a person who used a spreadsheet to calculate the lift coefficients and then make them available for a sales planning team to forecast volume, revenue and profit for future events. AI-calculated lift coefficients autonomously update as the data refreshes in your TPO solution and then applies these real-time, data-driven predictive lift coefficients to your planning. In doing so, you eliminate the manual mathematics preserving time focus on combining your industry experience with the accurate mathematics to build the optimal plan.
3) Constraint-based modeling and optimization
Of course, it is human nature if something works to do it again. Unfortunately, it is also human nature to repeat something that doesn’t work because we don’t know any better. Using artificial intelligence guided by constraint-based modeling to determine the “what else” when it comes to trade promotion event and customer planning is critical to determine the optimal result. User defined budget, profit, retailer and other constraints set the parameters while the machine learning engine runs through the possible event scenarios or promotional mixes that prescriptively optimize results for revenue, volume or profit.
Risk vs RewardArtificial intelligence technology has several applications within a consumer goods company. Applying AI to not just manage, but also quantifiably impact your significant investment in trade is an area where need and capability collide for optimal opportunity. Thinking about your investment in trade today, the time your company spends managing this spending and the return on this investment, applying AI capabilities within a Trade Promotion Optimization solution is not taking on something new; it is investing in better practices, better intelligence and better results that should pay for itself. The real risk is to continue the uninformed spending and resource draining practices that threaten revenue generation. Industry leaders see that avoiding this risk means investing in and working smarter, not harder.