Personalization and Innovation
In last year’s Power of Private Brands survey from FMI, eight in 10 food retailers and private
label manufacturers named innovation as the top priority for trying to increase share of private
Innovation can be broad, encompassing exclusive flavor launches or packaging sizes, or it can be more specific. However, just coming up with innovative store brand products isn’t enough — retailers need to ensure they have the right strategies and tactics in place to drive sales and innovation. When it comes to unit sales and share, predictive technology can enable retailers to
optimize pricing, assortment, cross-merchandising opportunities and ways that put store brands
in the strongest position on-shelf. Those ways could include:
Automated, personalized content that understands store brand buyers- The ability to know a shopper and to recommend meaningful products to a shopper starts with identifying and understanding their buying patterns.
Retailers own a wealth of data and they can leverage AI to sift through data and find competing products a shopper enjoys, what private brands they buy in what categories, and which categories where they haven’t tried a store brand product. At the same time, machine learning can be used to perfect targeted marketing messaging, learning from content that received the best results and personalizing a message that best fits a specific shopper.
Insights that monitor store brand performance in near real time- Retailers can also lean into the speed and accuracy of machine learning to track how well store brand items are performing. AI delivers an unbiased look at how a retailer’s private brands are doing based on price, promotions and where they’re sitting on the shelf. Retailers can also identify what trends are growing across categories to inspire new flavors or private brand item introductions and elevate overall portfolios.
Omnichannel private brand strategies that improve online stickiness- Omnichannel shopping is becoming the norm, and private brands need to be in sync with both online and in-store behaviors. Technology such as AI that has a view into how private brands are performing online and in stores can help retailers develop a well-coordinated omnichannel private brand strategy that improves online stickiness, loyalty and overall basket success.
AI can identify the digital promotions that work best and perhaps more importantly stop the online or in-store promotions that are not working, needlessly bleeding margins. AI produces automated knowledge faster than older, legacy platforms and the predictive insights can accurately drive a more efficient promotional strategy for a retailer’s private brands.
AI and Momentum- Like private label, AI is having a moment. The popular conversation is fueled by products like ChatGPT and Bard, but retailers have been getting real-world results with retail-focused AI for some time — not only for customer insights and category planning, but also to keep the supply chain in sync and maintaining inventory and planogram compliance on shelves.
The technology can also be the innovation they need to take their private label lines to a new level of success. Retailers have the data, and now it’s time for them to use automated insights to help make faster and more accurate decisions to keep profitable private label offerings on a fast-moving