Transforming CPG Promotions Through the Power of AI
How AI and machine learning can help CPG companies execute promotions with greater precision and more impactful results. The vast majority of CPG promotions fail to break even, but artificial intelligence and machine learning can help companies execute promotions that hit the mark with customers.
April 2, 2019
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Seventy-two percent of CPG promotions fail to break even. This statistic is a bitter pill to swallow, considering companies invest 15%-20% of their total revenue in trade promotions each year. Most teams plan the same or slightly varied events year after year, adjusting based on anecdotal lessons or larger corporate objectives. But sustained incremental revenue growth is possible, and emerging technology can help.
When it comes to personal development, you see motivational quotes along the lines of, “If you want different results, try different approaches.” This common-sense mantra resonates with individuals wanting to make a change, and the same could be said of CPG efforts in trade promotions. The old way of doing things hasn’t proven to be optimal—so what needs to change?
The issue is, promotions have become more complex to manage, and 60% of companies are still using manual processes such as spreadsheets and basic rules-based technologies. This stunts revenue growth for a number of reasons, such as:
CPGs lack real-time, accurate insights to help them understand the big picture.
The integration of forecasting and planning isn’t harmonious.
Visibility into the usage of allocated funds and into competitor activity is poor.
Post-event analysis is inadequate for improving promotion performance.
AI as the Brainpower for Promotion Decisions
To shake up the way trade promotions are managed, CPGs are now leveraging artificial intelligence (AI) to make data-informed decisions about promotions. Consumer goods and retail are among the top five industries in which AI is being applied.
AI and machine learning can help CPGs run promotions with greater precision through more accurate data analysis, due to unmatched capabilities versus human outputs. The machine-learning component of AI informs every stage of promotions: forecasting, planning, execution and evaluation. Data can be analyzed in an instant, arming CPGs with prescriptive recommendations for spending trade dollars more wisely.
Consider the promotion of a new brand. Deep learning finds similarities and hidden patterns that go far beyond “look-alike” promotions, allowing CPG account managers to boldly plan promotions that don’t have their own historical data. It also lets them consider promotions in different markets, depending on whether the brand is a category leader or laggard. AI algorithms assign the right promotion tactics, and the learning comes in to adjust over time as needed. Teams of data scientists might be able to provide these insights, but certainly not as quickly as AI demonstrates.
Optimized Offer Specifics and Powerful Automation
Promotions are all about making the right decisions more frequently, working off predictions that more closely reflect actual outcomes. AI learns and understands, based on historical and contextual data, what will return maximum revenue growth. The right tool will predict and make a recommendation on whether a buy one, get one offer is the most impactful in a given situation, or if a percentage or dollar-amount discount would be a better investment.
AI can explore hundreds of thousands of alternative scenarios and consider trade-offs across variables (e.g., channels, retailers, etc.) before delivering the optimal recommendation for a promotion. Actionable insights such as these aren’t possible using legacy techniques.
Additionally, the massive automation power that AI brings to trade promotions management allows for efficient optimization of micro-segmentation strategies, leveraging the full scope of customer data to better understand, target and connect with CPG customers. This micro-segmentation automation increases the speed and scale at which a CPG company can make decisions for trade promotions, eliminating the data-crunching through manual spreadsheets that often make this granular level of targeting impossible.
AI gives CPGs the ability to interpret data and make more informed decisions for future promotions. Through continued learning, better promotion execution and AI-driven creative, CPGs can turn their data into a true competitive advantage and alleviate the margin erosion that threatens their growth.
Steven Hornyak is CEO of Symphony RetailAI CPG Solutions. He has spent the past 30 years in the software, SAAS and retail technology business sectors, and has experience managing fast-growing and startup companies; Photograph courtesy of Symphony RetailAI CPG Solutions.