Julia is joined by Spencer Price. co-founder and CEO of Halla, a US-based tech startup working to bring greater personalisation to online grocery shopping. Spencer talks about Halla’s plans for international expansion and the opportunities he sees in the UK grocery market, the challenges of product discovery in online grocery and how retailers can get much smarter about substitutions.

Plus, they chat about the “Amazonification of Whole Foods”, balancing personalisation with privacy concerns – and jellied eels.

CB Insights today named Halla, the Taste Intelligence company and creator of the only human preference engine designed for grocery, to its Retail Tech 100 ranking, which showcases the 100 most promising B2B retail tech companies in the world.

The 2022 Retail Tech 100 cohort highlights startups reimagining the retail experience across 13 categories. This year’s winning companies are working on hyper-personalized shopping, blockchain-powered commerce, autonomous delivery, virtual shopping, and more. 19 countries are represented this year, including India, China, Mexico, Singapore, and the Netherlands, among others.

“By almost any measure, this has been a breakout year for retail tech. We’ve seen skyrocketing funding across the industry, powering companies involved in every aspect of retail from instant grocery delivery to supply chain technology,” said Brian Lee, SVP of CB Insights’ Intelligence Unit. “In 2021 alone, these 100 companies raised $13.1B in funding, an incredibly impressive feat. As the retail landscape evolves, we’re excited to see how the companies on the Retail Tech 100 continue to revolutionize how consumers shop.”

“We’re honored to have Halla’s Taste Intelligence engine recognized as an important contribution to the future of grocery,” said Spencer Price, co-founder and CEO of Halla. “To provide an exceptional customer experience today, retailers must be able to recognize customer intent, and then present options that meet customers’ individual needs across all touchpoints in real-time. This is not only a nod to Halla for solving this imperative in one engine, but also to our grocery partners who have recognized these new consumer expectations and achieved double-digit basket size growth by meeting them.”

Through an evidence-based approach, the CB Insights research team selected the Retail Tech 100 from a pool of over 7,000 companies, including applicants and nominees. Selection was based on factors including patent activity, business relations, investor profiles, news sentiment analysis, proprietary Mosaic Scores, market potential, competitive landscape, team strength, and tech novelty. The Mosaic Score, based on CB Insights’ algorithm, measures the overall health and growth potential of private companies to help predict a company’s momentum. To find out more about the selection process and this year’s winners, join the CB Insights team for a webinar today at 2 p.m. ET.

Halla’s Taste Intelligence engine has redefined personalization in grocery by introducing a solution that predicts what individual customers will want to buy next. Its API-first technology can easily plug into any digital touchpoint within the grocers’ existing platform. The engine leverages over 100 billion shopper and product data points to predict, with remarkable accuracy, what grocery shoppers are actually looking for, and delivers real-time personalized search results, substitutions and recommendations. Halla has been deployed in over 1,100 ecommerce storefronts for multiple top-50 U.S. grocers, driving best-in-class digital ad media performance and improvement in ecommerce profitability.

Henry Michaelson and Dr. Alexander Tuzhilin continue their conversation about recommender systems through the lens of machine learning and deep learning within the food domain. They also discuss how and why Halla is approaching the challenge with purpose!

Interview Originally Published in Progressive Grocer in December, 2021

Retail personalization makes shoppers 110% more likely to buy unplanned items and 40% more likely to exceed their planned budget, according to Boston Consulting Group. But how does this translate to grocery? How is “grocery personalization” different from general retail? And what does great grocery personalization look like?

QUESTION: How do you think most retailers and providers promote “personalization”?

ANSWER: “Personalization” is often sold as a feature that you load up with personally identifying information in order to segment shoppers into large persona groups. Recommending Axe body wash to men, for instance, is a type of personalization that uses correlation averaging, and frequently shows up as “people like you bought” type of algorithms. This is not true 1:1 personalization and it will never deliver the results that grocers need.

Q: How do you define personalization?

A: True personalization requires predicting shopper intent based on everything you know about that individual customer and the products they love, or will love. That means giving the shopper an experience that is tailored to their personal preferences at the moment of decision. Great grocery personalization shows the shopper it knows why they are interested in a particular item and how they plan to use it. The next recommendation is then informed by what is highly relevant to that shopper, at that moment. To get to that level of personalization, grocers not only need a deep understanding of each shopper, but more importantly, a true understanding of every grocery product and their unique qualities. That knowledge is what we call “Taste Intelligence,” our human preference engine built specifically for grocery. That’s how we make recommendations, substitutions and search results that make sense on a human level.

Q: Why build a human preference engine just for grocery?

A: Grocery is radically different from any other industry. Standard retail personalization engines don’t understand the complexities of human food preferences. We wanted to build an engine that could make accurate, sales-generating, and split-second decisions at the moment that a shopper is filling up their cart.

Q: How does this play out for the customer?

A: Taste Intelligence is trained on billions of food items, recipes, flavor combinations, restaurant dishes, and grocery decisions. It understands what food items are, how they are used together, and how they relate to individual human preferences. With Halla, if a lactose-intolerant customer searches for butter, for example, the first search result will be a dairy-free butter, not butter that is popular with other shoppers. If that item has to be substituted, the replacement will also be customer-relevant, and if the shopper puts macaroni in their cart, they might be recommended dairy-free cheese and milk at checkout. That’s how smart Taste Intelligence is. This happens millions of times, down to the unique customer ID, in real time, in a grocery-specific and enterprise-ready context. Anything short of this doesn’t count as personalization.

Q: What advice do you have for grocers who are considering how to begin or improve their personalization?

A: Don’t wait! In the next year, the quality of the personalized grocery shopping experience will separate winners from losers. It will create a gap that will widen over time and make it very difficult for grocers to catch up.
Don’t look at personalization as a cost item, look at it as the center of your customer centric strategy to drive profitability across your digital channels. Set a very high bar. Be skeptical and ask technology vendors to explain what goes into the secret sauce.
Grocers should seek out personalization designed exclusively for grocery that functions on a 1:1 basis. Personalization technology must work in real-time. To Halla, “real-time” means “in-the-immediate moment,” meaning if the shopper adds an item to the cart, the recommendations instantly change based on this new information. No batch processing or overnight data science. It must happen in “real-time.” To some providers “real-time” might mean that they pre-cache recommendations and refresh them in the middle of the night. If you ask me, that is not real-time technology. Shoppers want you to predict what they need now, based on what they’re doing in their current session. In the future, that type of attention to customer experience will pay off in increased loyalty and profitability. Great grocery personalization makes customers feel like the store was built just for them. It improves customer experience, and therefore loyalty, and with Halla it also results in 5-15% uplift in basket size.

Henry Michaelson and Dr. Alexander Tuzhilin provide an overview of how recommender systems work and some of the challenges in bringing intuitive recommendations into the grocery ecosystem.

Henry Michaelson and Dr. Alexander Tuzhilin provide an overview of how recommender systems work and some of the challenges in bringing intuitive recommendations into the grocery ecosystem.

In this installment, Halla Advisor, Steve Yankovich and our Co-Founder and President, Henry Michaelson, move past substitutions to discuss the potential for AI to fully grasp the nuances of food preference.

We continue our discussion on the intricacies of teaching machines to think like humans in the latest episode of our ongoing HallaPod Series, where Halla shares ongoing perspectives at the intersection of how people make food choices, the grocery industry, and technology

Grocery Aisle 5 is the first of three installments, featuring Halla Co-Founder and President, Henry Michaelson in conversation with Steve Yankovich, CXO of HomeValet, discussing the complexities of effective substitutions in the digital grocery ecosystem.

Technology, technology technology. It’s all that the grocery industry is thinking about. How to increase efficiencies better than the shopper experience and create bigger basket size today. My guest is Spencer Price co-founder and CEO of Halla. Halla is the taste intelligence company and creator of the only human preference engine that’s designed for grocery. Its tastes intelligence uses AI to redefine personalization and to predict what individual shoppers will actually want to buy next in real time.