Enhancing Promotion Effectiveness Through Collaboration
In a given year, a consumer packaged goods manufacturer will propose thousands of promotions across its portfolio of brands and categories to every retailer it partners with across the country. Meanwhile, retailers are working with multiple CPG manufacturers in each product category.
With both sides having their own strategic priorities, objectives and calendars, and with outdated systems and processes in place to manage their respective activity, it’s impossible to efficiently align strategic priorities with day-to-day promotion planning and execution.
With retailers and CPGs each having distinct strategic priorities across markets, categories and brands, what’s needed is an effective way for them to collaborate with one another. As it stands, 72% of promotions fail to break even, according to Nielsen. But now, with artificial intelligence-driven technology, retailers and CPGs can work together to ensure their promotional planning is optimized.
Adjusting tactics for maximized lift
When planning for promotions, retail account managers don’t have the luxury of running models for billions of possible combinations to find the best outcome. Yet even the smallest adjustments can create major changes in sales.
A single, consolidated promotion bank that holds retailer and CPG-initiated promotions can provide real-time insights, showing where adjustments should be made to drive the greatest impact. And once a retailer has built its promotion plan from all possible sources, AI can further optimize to understand the collective impact — including the effects of switching certain promotions.
For example, AI can suggest offering $1 off coffee creamer instead of a BOGO deal, and it can explain what the impact will be if the promotion is switched. AI enables retailers and CPGs to answer the question, “What’s the best promotions experience I can offer my customers?” and make strategic investments around their strategies, whether it’s increasing basket size or increasing traffic to stores.
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.