The ultimate goal of promotions planning is to make the right decisions more frequently to positively impact sales. That requires advanced predictions that more closely reflect actual outcomes. Retailers walk a fine line of either over- or under-predicting — spending more on promotions than is needed, or not investing enough to get the desired sales. However, the value of a promotion is difficult to predict before it’s actually implemented; it takes an average of four weeks after a promotion is run to determine if it was successful.
What’s more, promotional planning and product allocations are extremely important to customer satisfaction and experience. If a customer is successfully driven to a store by a promotion only to find that the products are out of stock, or if the store has not executed as advertised, that negative experience can have a long-term impact, potentially resulting in that shopper’s entire basket being switched to a competitive retailer or brand.
AI enables more effective forecasting, since it’s predictive and can analyze different mechanics to identify the optimal impact. By using last year’s promotion data and plans as a starting point, AI forecasts the best events for the year based on results of last year’s ratings in addition to new deals from suppliers. With AI-driven recommendations and “what if” analysis, retailers and CPGs can view forecasts and tweak promotions in real time. AI can even highlight the different types of offers that will impact sales the most.
For CPGs, the appropriate promotional posture needs to be radically different between markets where they are a category leader, a close follower or a laggard. For example, continuous promotions may be required to build awareness for a secondary product, while the category leader may only need promotions around specific events.
Promotional strategies will also vary depending on whether the promoted brand is established or a launch. The depth of discount, type of offer, frequency of promotion and “first to market” commitments made to individual retailers will impact how CPGs allocate their spend. AI-enabled solutions enable CPGs to plan for these nuances across geographies, retailers, and their brand portfolios.
It’s also important for CPGs and retailers to establish their own goals, priorities and guard rails on aggressiveness — but these priorities can often clash. With AI, models can be orchestrated autonomously by algorithms so the ideal promotional postures are assigned for each micro-segment. With automation, local tactics for any given retailer, category, region and/or brand can be effortlessly executed, allowing retailers and CPGs to remain continuously aligned with global strategies.
With a central, AI-driven hub for creating and deploying mutually beneficial promotions, CPGs can easily keep margins within their desired thresholds and propose promotions to a category manager for inclusion in the retailer’s plans. By providing each party visibility into the economics of a deal, both sides can enforce rules that reflect their own priorities.
In addition, providing retailers and CPGs with the ability to quickly interpret data and make informed decisions for future promotions is a significant competitive advantage that will lead to more profitable promotions and increased sales lift.
About the Author
Steve Towarnicki, vice president of CPG engagement for Symphony RetailAI, works with retailers and CPGs from the C-suite to the store level to develop strategic, customer-centric, data-driven insights that lead to actionable recommendations.