When it comes to managing trade investment, CPG companies can be paralyzed by the overwhelming task of managing incoming data. They rely on manual intervention and cumbersome spreadsheets to glean even the slightest bit of insight.
Combining Analytical with Artificial Intelligence
Industry leaders prioritize analytics initiatives within their organization to bridge the gap between data availability and actionable insight.
In doing so, these companies depend on advanced analytical solutions, like a trade promotion optimization (TPO) application, to improve the accuracy, efficiency and predictability of their trade promotion planning and analysis.
But, companies that can’t (or won’t) eliminate the manual intensiveness of data management, base and promotional analysis, and customer planning will 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 data, leading to actionable insights that boost the bottom line.
1) Smooth Baselines
To develop accurate post-event analysis and lift-coefficients for customer planning, your baseline has to be right. That said, manually compiling data to determine base volume and then managing these baselines is almost impossible.
Automate the harmonization of consumption, spending and shipment data to calculate the accurate baseline. Employ machine learning to smooth baselines to the correct curve as new data is added.
2) Generate Lift Coefficients
Calculating lift coefficients “is math not magic,” says Blacksmith TPO Chief Knowledge Officer, John Weller. With accurate lift coefficients, you can evaluate promotional lift during post-event analysis and inform precise forecasting during promotional planning.
However, the math behind the results frequently changes as new data enters the models. This means that traditionally there was a person, with a spreadsheet, that calculated the lift coefficients and then made 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, and then applies these real-time, data-driven predictive lift coefficients to your planning. In doing so, you eliminate manual mathematics. Now, use your time to focus on building the optimal plan by combining your industry experience with the auto-generated math.
3) Leverage Constraint-Based Modeling
It’s human nature to repeat something that works. Unfortunately, it is also human nature to repeat something that doesn’t work because we don’t know better. With artificial intelligence guided by constraint-based modeling, you can determine the “what else” when it comes to trade promotion event and customer planning. This functionality 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 Reward
AI technology has several applications within a consumer goods company. Applying AI to manage and quantify the impact of your trade investment is an area where need and capability collide for optimal opportunity.
Think about your investment in trade today, the time your company spends managing this spend and its return on this investment. Employing AI capabilities from a trade promotion optimization solution doesn’t mean taking on something new; it means investing in advanced practices, improved intelligence and profitable results. The real risk is to continue uninformed promotional spending and draining resources. Avoiding that risk means investing in a tool that enables you to work smarter, not harder.