Let’s face it, if pricing were easy, you wouldn’t be reading this blog. Pricing is a critical part of being a successful CPG. Promotional cycles, variables, deadlines, and the opinion factor— your marketing team, sales team, and even your customers might have opposing plans— can affect your ability to determine the best prices and promotions for your products.
That’s where artificial intelligence and machine learning come in. They rapidly change how CPGs strategize pricing, and they take companies of all sizes on a deep dive into key strategic areas (elasticity, cannibalization, leading price, competition performance, brand strategy, total sales, and more) with the aim of maximizing profits.
So, how can AI and machine learning help your company’s pricing challenges?
1. Discover the granularity of your data
Excel just doesn’t mine deep enough anymore. To effectively strategize prices and promotions, you need serious data and the ability to adapt to every individual area, region, and retailer where your products are found. Innovative, predictive, and analytical tools like AI can account for even the smallest market shifts and make it possible to pivot. This is a critical tool whether you have a single product or thousands of SKUs spread out across multiple regions and retailers.
Understanding price elasticity is a key advantage of our platform. Studies at Wise Athena have shown how common it is for companies to over-or underpredict elasticity by using traditional or advanced mathematical models that exclude machine learning. AI brings elasticity predictions closer to reality, often revealing previously unidentifiable peaks and valleys.
2. Make your dollars work for you
Many CPGs waste valuable resources on ineffective trade promotions, missing opportunities for truly impressive lifts in sales. Using Trial & Error methods—like studying old trends and previous sales seasons—to set prices or plan promotions is no longer an adequate solution. We’ve seen how the world can change in a heartbeat—consumer trends especially.
Every new placement is an investment, making machine learning the difference maker between leading highly targeted, successful launches in new regions or scaling beyond brand visibility and risking everything just to be on a big box shelf. There’s no shame in first approaching highly specified retailers, where products can thrive and ultimately become “big box ready.” Then again, the data may show your product is already equipped for major, national retailers. What’s essential here is having the data to understand where your most valuable placements are.
3. All your resources in one place + Continuous learning
Wise Athena’s platform offers every solution you need within just a few clicks: Pricing, demand prediction, strategic planning, analysis, and more. It’s all there for users to analyze, breaking data down faster while simplifying and organizing strategizing sessions. It does all the analyses for you and provides a reliable predictive solution with over 85% accuracy.
The best part is that AI never stops learning or adapting. Results continue to improve over time and strategy recommendations will identify, adapt and pivot to shifting markets, as opposed to responding to them after the damage has been done.
4. Sales and marketing can now work in tandem
Remember that earlier note about navigating differences of opinion between your marketing and sales teams and even your customer? No longer a problem. With the amount of actionable data that AI platforms provide, those teams will have more time to focus on highlighting the premium features of your products and what your retailer’s customers are shopping for then worrying over the best way to keep the company profitable.
Wise Athena helps CPG companies optimize Pricing & Trade Promotions strategies with A.I., giving clients insight into seasonal trends, fluctuating product demands, and daily changes resulting from market discrepancies. We’ve proven that we can increase sales and margins in less time, and with less effort, with data harmonization capabilities, high definition elasticity, and prediction certainty between 85-95%.
