The biggest names in retail are seeking ways to lower prices. While that’s great news for consumers, certain retailers and especially CPGs are likely feeling uneasy.
Price changes and increased promotional activity can further thin profit margins, something many retailers are already seeing in their quarterly reports. However, by working with internal teams and by leveraging predictive analytics and AI, CPGs don’t need to settle for thinner margins and volume tradeoffs. Brands of any size can confidently test various pricing and promotion scenarios within AI-powered predictive tools to identify the most effective pricing strategies.
In this blog, brands will learn how AI-supported pricing analysis uncovers the price changes that matter most for their consumers, ensuring volume and profitability become healthier.
Retailers rally around slashing prices
Across channels, retail leaders publicly promised to lower prices on thousands of products through this summer. Notable examples include:
- Walgreens said it will cut prices on 1,300 items, particularly snack foods and personal care products.
- Target said it will drop prices on more than 5,000 frequently purchased items across its assortment.
- Aldi aims to double the savings on 250-plus summer items, claiming to save shoppers $60 million.
The push to appease price-sensitive shoppers also includes a new private brand food line from Walmart called bettergoods, which includes items priced at less than $5. It’s Walmart’s first private-label food launch in 20 years, and the company said it’s the fastest brand that it has ever brought to market, emphasizing the urgency of price-conscious products.
Retailers aren’t just shaving off a few pennies, too. Walgreens listed price reductions on many of its personal care items, and consumers will save one or two dollars per item. Target similarly is trimming prices by around a dollar across both national and private brand foods.
With the U.S. Consumer Price Index showing a hold on price increases, inflation seems to be cooling off, also opening a door for retailers to entertain price cuts. But brands and retailers need to be smart about how they adjust prices; for what gain, and where. Predictive AI applications can deliver data-driven recommendations on the products with the most pricing adjustment opportunity, including how much to adjust price, at which stores, and what corresponding changes to expect.
AI helps brands defend prices strategically
Insite AI’s pricing applications contain price elasticity models. These run inside a brand’s IT environment, leaning on limited sales data and macroeconomic feeds to deliver precise readouts on how prices are performing and an outlook of how they will perform. Models are customized to a CPG’s data set and other business logic is formatted to fit how brands like to work.
This process is important to how brands target and control pricing with AI. The Insite AI models give CPGs predictions and strategic actions on their business that brand teams can experiment with in very easy to use planning software.
Here are a few examples of what brands can do with AI-supported pricing applications:
- Score and rank the true price-sensitivity of products within seconds. To assess prices, brands need to learn which products within a category would benefit most from a price decrease, hold, or increase. Good models don’t just look at historical data but also can incorporate messy data such as retailer sales, competitors, shopper group reactions, macroeconomic trends, and attributes – like ingredients, pack sizes, rate of sale, assortment architecture, and more – to holistically identify prices expected to underperform. The modeling also spots items that consumers will buy anyway — whether prices go up or down — allowing retailers to keep prices at a profitable number. Looking at the total behavior in the category, brands can help illustrate their strategy to retailers on the most effective assortment, price architecture, and pricing within minutes, as opposed to teams having to crunch through hours, weeks, or months in tightly controlled meetings.
- Get a granular, data-backed story to defend prices. Insite AI models deliver highly granular metrics from pricing changes down to the SKU and store level. By being able to quantitatively attribute the factors which drive and drag on a pricing decision or price elasticities, brands can decide their strategy. A CPG may find in a certain region, channel, and set of products that pricing can remain strong without effect to volume – because of a lack of competitor options, shopper resilience, and infrequency of promotion. That same CPG will inevitably find in a different set of products and retailers’ other factors – such as disposable income, product costs, and non-performing innovation – an opening for price tradeoffs that lend to better volume gains.
- Better allocate trade promotion budgets. Similarly, brands can run several scenarios to see how certain trade budget allocations will impact sales volume, incrementality, and profits. CPGs can detail budget allocation more wisely by brand, products, shopper segments, stores, or regions to truly hyper-optimize results on “last year’s promotion calendar.” Retailers that are looking to lower prices will favor brands that bring data-driven insights on how well trade dollars work on top of optimized pricing across the category. Furthermore, being able to demonstrate incrementality of promotion tactics and types across days, weeks, and months are highly enabling to sales teams.
Brands brace for savings beyond the summer
While much of recent news highlights a summer of savings for consumers, CPGs that tap into predictive analytics and machine learning projects to refine pricing can leverage strategic pricing for many seasons to come. Running AI models to review ongoing pricing and promotions down to a store level, by item, by day, week, and month, helps brands maintain and subsequently plan effective pricing on an aggregated basis, all year long.
Reviewing pricing strategies aren’t just a one-off play, and the tendency to let events play out – such as elections, interest rates, or consumer confidence reports – are becoming archaic due to their reactionary nature. Brands need to use data, regardless of its state, to pinpoint accurate and precise pricing and promotions for all their goods – and at their retailer partners – to maintain margins.
Contact Insite AI to see how our custom applications help you stay on top of pricing strategy.
