TL; DR: Revuze is on a mission to turn opinion into insight with its data analytics platform, which eliminates manual processes. The service, conveniently hosted in the cloud, immediately provides users with valuable information on their products and services, pinpointing problems for quick remediation. With existing strategies for boosting your star rankings and upcoming tools for keyword prediction, Revuze is working to help companies better grasp their clients’ preferences.
By now, you’ve undoubtedly heard a tech expert or two speculate that we’re in the midst of a big data gold rush. And sure, the phrase sounds like something a marketing department would churn out — but the business opportunity behind the buzzword is very real.
Like panning for gold, prospectors can freely collect data from streams all over the internet, but it’s not always easy to extract. Still, it’s so valuable in driving continuous, revenue-boosting improvement that hopeful businesses willingly partake in manual data wrangling.
Now, thanks to Revuze, there’s a better way to extract and analyze the publicly available data that modern businesses treasure. The Software-as-a-Service (SaaS) platform, conveniently hosted in the cloud, scans and derives insights from online customer reviews using text analytics, contextual analysis, and machine learning. This eliminates the daunting task of harnessing a vast data landscape.
“We take all the publicly available data and create somewhat of an ongoing survey,” said Alon Ghelber, CMO of Revuze. “Every time you have new reviews, launches, posts to social media, et cetera, the platform optimizes the insights it delivers to product managers or marketing managers.”
These specific analytic insights can then be used as a strategic asset to enhance products and services according to real customer feedback and concerns — leading to happier customers and more five-star ratings. With Revuze, outcomes that would otherwise require the lengthy involvement of IT and marketing experts are available in the blink of an eye.
An AI-Powered Analytics Engine Backed by Nielson and SAP
Revuze was originally launched in late 2015 as part of Nielsen Innovate (NIF), an investment fund and incubator focused on innovation in the retail, research, marketing, and media spaces. Partam Hi-Tech, one of Israel’s top early-stage venture capital funds, also contributed to the launch.
“We were one of the first rounds of this incubator,” Alon told us. “Our founders were looking at ways to utilize online reviews from a business-to-consumer (B2C) perspective to get better insights on what products to buy, which restaurants to visit, and so on.”
The founders quickly realized that the business-to-business (B2B) market had more promise. There were two obstacles with the B2C market. First, when analyzing online reviews, even the best artificial intelligence (AI) can’t properly assess minor attributes that vary by industry.
“For example, if we’re analyzing mentions of ketchup, people could be referring to the flavor of a condiment, but when you’re talking laundry care, ketchup is a stain,” Alon said. “So it changes the whole perspective: The review can go from positive to negative depending on the context.”
The second problem was the sheer cost of training complex AI systems in the wide-ranging B2C market.
“It was so expensive that the founders pivoted towards the B2B field and hired mathematicians to create a self-learning algorithm that would replace the need for training,” Alon said. “Basically, they built the machinery to train itself.”
In 2014, R&R ventures, Fred H. Langhammer, and Itzhak Fisher joined as shareholders. Later, in 2019, Revuze received funding from SAP.iO Fund, a strategic business unit within SAP designed to accelerate innovation and spawn new business models through investments in early-stage startups. In addition to revenue. Revuze’s wide range of partners bring the company vast experience in customer analytics, customer experience, machine learning, and natural language processing.
Tap Into Qualitative Opinion Insights for Ecommerce
Alon, who joined the team in 2019, told us he’s witnessed Revuze broaden its approach to customer insight with multiple additional attributes and categories — making the data analytics platform all the more powerful.
“Today, we’re actually helping product and marketing teams create new products and launch modifications to existing ones based on consumer experience, which is similar to what Amazon is doing with their private brands,” he said.
The idea is to emulate Amazon’s tight grasp on the user’s personal preferences and overall ecommerce journey — allowing smaller businesses and enterprises to leverage a similar data strategy without the crushing overhead that only industry giants can bear.
“We help brands tap into data and be like Amazon,” Alon said. “Revuze affords everyone in the organization the ability to make data-driven decisions and utilize an agile approach. It used to take millions of dollars to achieve such a digital transformation, and we did it with a simple SaaS product.”
The platform is about as plug-and-play as a user can get, even when compared with other cloud-hosted solutions.
“They don’t even need to supply data because it’s already public,” Alon said. “There are no installations, no setup costs, no maintenance costs, no advisers or IT experts you need to hire. The data is there — you just need to tap into it.”
If that’s not enough to convince a customer of Revuze’s value proposition, Alon encourages businesses to sign up for a product demo.
“I can say, “Tell me who your competitor is, tell me your best selling brands or product,’” he said. “ And with one click, I can show you how you compare against your biggest competitor. And that sells itself.”
Discover How to Improve Your Star Rating
Revuze drastically simplifies the process of gathering competitive intelligence with a novel concept: Actually listening to what your customers are saying.
The platform uses AI to automatically collect data from ecommerce reviews, surveys, and user-generated content (UGC), among other sources. Revuze then cleans the data, machine learning algorithms discover topics across multiple product categories, and the platform builds a classification system. The process effectively transforms raw data into easy-to-understand, actionable insights on a brand’s products, features, and competitors.
Best yet, Revuze’s self-learning analytics engine, easily accessible via the power of cloud hosting, accurately tackles these tasks without human interaction. This means marketers no longer have to waste time defining keywords and phrases or hiring pricey analysts.
“Your customers know best,” Alon said. “Our goal is to give all brands accessibility into what they are saying, to tap into the customer voice and understand exactly what they need. We’re democratizing this field.”
Revuze works with one of the most prominent vacuum cleaner suppliers in the U.S. In one situation, the platform’s AI identified a common problem with a single model where hair was getting stuck in the brushes.
“The day after I surfaced the problem with an email to the product manager, the company immediately released a quick fix to the product and sent out small gadgets to clean up the hair,” Alon said. “The process improved their star rating by 20% to 30% of a star — which is a whole lot in the marketing world, especially when it’s coming from AI.”
Up Next: A Look into the Keyword Crystal Ball
Next on the agenda for Revuze is a focus on improving the platform’s cloud-hosted recommendation engine and helping clients access even more actionable insights.
“We already have an analytics and monitoring engine, but we are striving to get better with actionable insights for our users,” Alon said. “For example, we want product managers to have their own dashboard with their own KPIs, and they’ll get insights and hints on potential product improvements or gaps in the market based on that KPI.”
Revuze also helps to get more involved with ecommerce SEO.
“We know what customers are looking for, how they talk about the product, so we are able to identify search terms way before they become keywords. In that way, we help companies to actually invent keywords. If you got one keyword ahead of everyone else in a month, or even a year, the outcome is incredible.”