Trade promotion management has a lot of moving parts – and getting them all to work together is a real challenge. Learn how AI can help CPG companies and retailers get the most out of their trade promotion activities.

AI, Trade Promotion, Forecasting, Planning

For CPGs and retailers alike, managing promotional trade funds presents some significant challenges. Billions of dollars are invested each year, but approximately 70% of promotions don’t break even. Leadership knows about this, but changes have been slow to come. Why? Because of the inherent complexity of the retail-CPG relationship.

Why Are Profitable Promotions So Hard?

Although both retailers and CPG companies have the same goal – profitability – they have different methods of achieving it and different obstacles. There’s usually a many-to-many relationship going on, too; retailers work with more than one CPG company, and CPG companies work with many retailers. Thus, retailers may execute promotional plans in ways other than the CPG company intended, while CPGs may struggle to create tailored plans that work across disparate markets. Plus, CPG companies may not be aware of their competitors’ plans for the same market; price, competing offers, and available alternatives will all impinge on promotional profitability.

Additionally, there is a time element in play. Many CPG teams and retail managers don’t have access to real-time performance information; it often takes about a month for trade promotion data to filter to business users. And that’s no surprise when you consider that 60% of companies were very recently using manual or custom processes (instead of purpose-built software) to manage their trade promotions.

And let’s not forget the other factors complicating the picture:

  • Lack of deal economics transparency.
  • Inability to align local actions with global corporate priorities.
  • Absence of integrated planning and forecasting.
  • Poor visibility of allocated funds and their usage.
  • Inefficient retail execution and compliance.
  • Inadequate post-event analysis.

The wrong kinds of software and management processes are definitely to blame for some of this turbulence. Fortunately, the right kind of technology – AI and machine learning – can help CPGs and retailers optimize their trade promotion management.

5 Ways AI Can Make Trade Promotions More Productive

AI can radically improve the TPM process. Here are five key areas where it has real potential to drive change:

Enabling Precise Segmentation

CPG products are often sold in multiple categories, across several channels, and in widely diverse markets by widely diverse retailers. This adds up to a lot of strain on the promotion planning front as well as divergent priorities for retailers and CPGs – something that traditional TPM paradigms can’t easily conquer.

AI can analyze each promotional micro-segment, develop the appropriate messaging, goals, etc. and adjust its recommendations as new information comes in. Consider how many variables there are and how much they influence promotional strategy: consumer characteristics, the brand’s position in the category and market, the retailer’s location, region, etc. For humans working with manual processes, factoring in all the possible variants is daunting – if not impossible. For AI, it’s all simply data to be analyzed.

Finding Forecast Patterns

Very rarely does the present or near-future conform exactly to the past; that’s why we adjust our projections based on incoming information. For companies that use predictive analytics, this becomes much easier. If you’re dealing with the same products and stores, machine learning algorithms can enhance the historical data’s effectiveness with information on current category trends and thus provide more accurate results. If you’re working with new products, markets, etc. AI can run look-alike scenarios on similar promotions to provide an initial forecast. This provides a foundation for developing promotional strategy as well as an idea of which directions to take.

Creating Tailored Offers

As mentioned earlier, there’s often a lapse between when promotions are run and when the data is available. This is not ideal, as it makes it very hard to adjust course and work towards a more productive outcome while the promotion is in progress. By facilitating access to current data, AI allows business users a real-time look into how promotions are faring. It also provides what-if analysis, current forecasts, and data-backed action recommendations that allow teams to make continuous tweaks to ongoing promotions (down to determining whether dollars-off or percentage-off will be most effective). This can influence everything from advertisement placement in circulars to shaping future promotions.

Optimizing Promotions Within a Plan

To enable both retailers and CPGs to meet their goals, promotional planning is a must. This is especially true when both parties are running multiple promotions simultaneously. AI can help CPGs develop promotional tactics that drive the best outcomes, make sense of the myriad possible combinations, and outline the collective impact of different promotions – all while staying in the desired margins. CPGs can then share this information with their retail counterparts. Consider it as a way to create and implement mutually beneficial strategies. And, in combination with the above points, there’s also the possibility of real-time feedback on how promotions are going, which allows both CPGs and retailers to make adjustments accordingly.

Scaling and Managing Data-Backed Insights

Of course, for promotions to truly be maximized, all the above dots have to be connected. CPGs and retailers have to be able to scale up their forecasting, planning, and adjustments to match the amount of incoming data. And they have to see the interactions between many promotions operating at the same time. If that sounds like a nearly impossible task, it is – especially for larger companies. Once again, AI steps into the fray, managing overwhelming amounts of data, finding the connections and hidden patterns, and delivering understandable data-backed insights that can lead to better decisions.

AI’s Benefits for Trade Promotion Management Are Clear

We could go on (and on) about the possible applications of AI in trade promotion management. It’s clear that AI makes promotions more personalized, more effective, and more scalable. In a word, we could say that it makes the whole process easier – to understand, to manage, to plan, and to adjust. As more CPGs and retailers adopt AI, we can expect to see trade promotions reach new levels of optimization and profitability.

Authored by: Dr. Anil Kaul, Co-founder and CEO  of Absolutdata


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