Omer Kehat joined Revuze as the VP Product back in September and has already left an indelible mark with the release of the new Explorer UI. We sat down with Omer to talk about his experience, his vision for Revuze, and the direction of the online review industry.

Q: Even before joining the Revuze team, you were working in the online review space. What continues to draw you to it as a product professional? What gets you excited about them?

A: I have been in this industry for over a decade and it just keeps moving at a crazy pace. I love the fact that it really embraces technology and allows me to experience head on how to integrate cutting edge solutions into this fascinating world. I am really excited about the power of generative AI – not just the free text chat that we’ve all seen and used. I think we still haven’t seen real groundbreaking implementations of solutions that will revolutionize this space, but I feel we are very close and looking forward to being a part of it. 

At the end of the day, as a consumer myself, being able to make selections from the wide abundance of channels and options today is baffling. I really believe that it’s our mission to make it easier for everyone to trust brands, trust products and improve the overall purchase experience. 

Q: Why do you think brands are only beginning to understand that online review data is an important dimension for decision making?

A: Brands are evolving just like everything else, and it’s not an overnight process. If five years ago, social media was all the hype and understanding your brand awareness or equity was THE KPI to aim for, we’ve come a long way since. COVID propelled this industry and forced digital transformation down its throat. Brands invested so much in creating their digital presence, learning how to control hybrid supply chains to cater for brick and mortar and online retailers, developed business relationships with sellers and partners and mastered the world of online advertising

Brands are slowly realizing this change and asking challenging questions about the effectiveness of their campaigns, consumer feedback, how they are faring vs. the competition. They realize that they can’t find these answers in their own CRMs, social media or other traditional tools. This is when they start looking at other datasets and discover the world of online reviews, the importance of verified purchase opinion, the ability to understand SKU-level sentiment and the impact of negative reviews on performance.

Q: What are some of the data challenges (syndication, incentivized, organic, merging products, Big Data) with online reviews? What are some of the trends you foresee in this field?

A: I think that there is still a big challenge with generating good reviews – especially outside of the US. This makes analysis and generating insights difficult in certain categories based on low volume data. 

Other than that, I think retailers have to find a way to deliver the reviews in a much more meaningful way to consumers. Consumers don’t want to spend time scrolling through 10s or 100s of reviews to make an educated opinion on the product. I think this is where generative AI can play a big role in enhancing the consumer experience.

Q: How is sentiment calculated? 

A: Sentiment is calculated by analyzing the text and “understanding” if the user was satisfied or not with a certain product or feature of a product. Sentiment analysis has been commoditized over the past few years and there are reasonable “off-the-shelf” solutions today that perform well. However, when you’re making your next business decision about a new product launch, or investing your budget in the next cool feature, you want best-in-class solutions. The Revuze sentiment analysis model is unique in the fact that it’s tailored to specific categories and can understand that a 1-hour battery life would be considered negative for a laptop, but positive for your drone. 

Q: How does the AI break down the review by topic and sentiment?

A: We at Revuze understand that consumers have strong opinions about many things. Many of the reviews they post will have a mixture of statements about different features, and all those statements may be positive or negative depending on their experience with the product. Our technology will take the original review and break it down to its various statements. After that, our topic and sentiment models will be applied on all those statements and identify the specific topic and its associated sentiment. This makes our dataset unique since we can really drill down and understand at a product level, what consumers really love about that product, and what they hate.

Q: Amazon also launched its own AI product for online reviews in 2023. Why is it not enough for brands?

A: Amazon has great tools for its ecosystem. If you are a seller operating on Amazon only, the tools that were recently released might be enough for you to optimize your Amazon selling strategy. The reality is that most brands don’t sell on Amazon only and this is where you need tools that can give you a full 360-view of the market. Understanding what consumers are saying about your product and competitor products on different retailers, understanding that different demographics shop in different ways, and identifying new players that are not on Amazon yet, is key to helping your brand grow and win.

Q: Why are category insights so crucial for brands today?

A: Brands cannot succeed by using their own 1st-party data today. Focusing just on your sales data to predict future growth, or understand how to best optimize your marketing campaigns must be based on external signals that brands need to acquire. This external data needs to help brands paint a clear picture of industry and category landscape – without this level of data, brands will quickly go blind and find it hard to maneuver and find success in the overly complex digital world.

Q: Can you give us a taste of what you’re planning for this year?

A: We are busy finalizing our plans for 2024 and have some great features to be on the lookout for. We are investing in many areas:

1. We are going to streamline our applications making it easier and more intuitive for users to gain insights and take action
2. We are going to expand our coverage and enter social media, focusing on TikTok shop reviews to give our brands another point of view based on new audiences that don’t necessarily have enough presence in the “legacy” online retailers.
3. We are doubling down on our data offering, making it easier for consumers to acquire our data and plug it into their BI systems directly using DataBricks technology
4. And of course, we will experiment with in-app chat to allow faster time to insights and provide easier access to our data with our powerful “guiding star” chatbot solution.

Florence Broder