Operations
17 May 2022
Veryfi's camera tech is turning store receipts into valuable brand data
The company's AI-powered receipt capture tech is helping to power DTC loyalty programs.
The company's AI-powered receipt capture tech is helping to power DTC loyalty programs.
What’s the value of a receipt?
Usually, it’s the slip of paper that shoppers slide into a bag, only to be checked in the rare case of a discrepancy.
The data on that slip, however, should not be overlooked.
With loyalty programs, however, CPG brands are tapping what's in the receipts. By taking a picture of a receipt and submitting it through a website or app, shoppers receive a coupon or cash back.
As brands run more of these types of programs directly with consumers through standalone marketing or loyalty apps, these receipts can also offer insights about consumers. With that piece of paper, brands are not just getting the info that a product was purchased. They can also see specifics about the item, and other items that were purchased in the basket along with that item, some of which may have been from a competitor. They can also cross-check whether other items around it were on sale. The data can go a long way toward helping brands understand their business.
It’s data that Veryfi is providing access to with mobile capture technology that can be used within a retailer or CPG brand’s loyalty app.
“They need to be able to extract the data, they need to be able to generate insights from the data and then reimburse the end user,” said Veryfi CEO Ernest Semerda. “We provide technology to capture, the technology to extract and then they can generate insights. We give them data that is standardized that they can rely on, and it’s clean.”
Veryfi recently debuted enhanced capabilities for receipt capture through it software called Veryfi Lens. Comprised of a software development kit and OCR API, the tool contains a custom camera application that takes a picture of a receipt. Is it able to stitch together a long receipt into a single picture by running a phone over the length of a slip.
This powers the capture of data at the SKU level. Using AI, Veryfi can extract the info from the receipt and turn it into structured data in seconds. This is the real-time information that brands can then use to draw insights.
Addressing an issue that’s of top concern to brands running loyalty programs, Veryfi has fraud detection that uses image analysis to identify whether a receipt was doctored or duplicated.
Veryfi, which is based in Silicon Valley, was founded in 2016 by Semerda and Dmitry Birulia, who both previously worked at Coupons Inc. They’re engineers who built technology to transform unstructured data, and they are now applying it to receipt capture, among other markets. The company raised $12 million in Series A funding in 2021.
To Semerda, this time recalls the 2008 recession. At that point, brands and manufacturers were infusing funds into the market in an effort to boost business.
With the current macroeconomic challenges brought by a pandemic and inflation, he sees similar activity happening now.
“History doesn’t repeat itself, but it rhymes,” he said.
Especially as shoppers return to in-store settings, loyalty programs are one way brands are incentivizing purchases with cash rewards. Where brands may have previously worked with third parties, the ability to go direct-to-consumer opens up opportunities to run loyalty program themselves. Companies like Veryfi provide the tech tools to help them perform functions quickly, accurately and securely, where they might have previously turned to bookkeepers.
Veryfi’s tools also collects the first-party data that brands prize. It’s also data that they wouldn’t otherwise receive from retailers.
“Data is the new oil,” said cofounder Birulia. “If brands want to make decisions about how to improve and how to be relevant to Gen-Z, they have to know their customer. To know their customer, the receipt is the perfect example of where they can get a wealth of data.”
With receipts from different retailers, brands can compare results across multiple point of sale locations, or even different retail businesses. The data can also help brands to adjust their approach based on what the data shows. With real-time data offered by Veryfi, they can adjust quickly. Rather than getting info once a month as many brands often do, Semerda likens what Veryfi enables to the driver of a car, who is always adjusting the steering wheel as they go.
“That’s much more powerful because you can see the business much more clearly than your competitor," he said. "That's the beauty of working directly with the brands and having technology that’s available in real time, giving that information so they can steer it.”
"Fashion ecommerce is one of the most cumbersome customer experiences that exists," said Rent the Runway CEO Jennifer Hyman.
The rise of generative AI is bringing with it a groundswell of interest and concern about how the capability to automatically synthesize information and create something new will change how we work.
Given that AI will sit within the architecture of our digital lives, it’s also worth considering how the technology will introduce new tools for other aspects of life, as well.
For two ecommerce innovators in the apparel space, it’s a time to explore how it will transform shopping. Rent the Runway is set to roll out new AI-powered search capabilities, while Stitch Fix is drawing on a long history with data science and machine learning to personalize the inventory buying process.
Here’s a look at the initiatives underway at each company, and their visions for the future:
Rent the Runway is putting a focus on the customer experience this year as it seeks to retain more subscribers and continue a yearslong push toward profitability.
This is resulting in the introduction of a variety of new initiatives, from the addition of an extra item to all orders to speeding up page load times. Yet as CEO Jennifer Hyman zooms out, she sees change being necessary on an industry-wide level in fashion. Beyond adding new features, AI can play a transformational role.
“I think that fashion ecommerce is one of the most cumbersome customer experiences that exists. You are searching through pages and pages and pages of content to find the items that you like and no one likes doing this,” Hyman told analysts on the company’s earnings call this week. “As an industry that still is selling physical products, AI is going to be -- fashion is going to be a major beneficiary as an industry.”
As a rental service, Rent the Runway has a distinct niche in fashion that lends itself to AI’s advantages, Hyman said. As opposed to a retailer that a consumer may visit a couple of times a year, RTR is used frequently by customers. So Hyman said there are opportunities to turn Rent the Runway into a “utility” by creating a more seamless experience.
This frequent use also provides a “highly unique” dataset, Hyman said. They know what a customer is planning to do based on what they rented. They know whether she liked or disliked an item, and many customers are reviewing 10 items per month. They know her size and how an item fits. This can be put to work in tools that allow customers to ask questions, and find answers.
The first application that combines AI and these advantages will appear in the coming weeks, when Rent the Runway plans to launch a beta of AI-driven search. The tool will allow customers to search for common terms or use cases for an item. So a person will be able to write “Miami vibe,” “‘clambake in Nantucket,” or “tropical motifs,” and receive results about what to wear for such an occasion.
The goal is to help customers sift through the endless aisle, and instantly finds what's right for them.
“I think that across all fashion sites, all over the world, the way that people are searching for product is fairly vanilla, it's fairly functional, right?" Hyman said. "You can go to a site and search for a T-shirt, you can go to a site and search for a black-tie gown. The fact that we're going to be able to enable our customers to search how they actually want to use this closet in the cloud, to search for items to wear to my beach bonfire this weekend, that is a completely different way to search, and I think that it really brings out the value proposition of what a closet in the cloud is all about."
Hyman sees this as a first step in the company using AI models to improve the product experience, and expects more tools to appear in the coming months. RTR is also introducing an SMS concierge experience for onboarding that allows customers to text with a member of the customer service team. The company is already exploring ways that AI can be incorporated into that tool, as well.
In the longer term, Hyman said the company has a vision that will leverage AI to allow customers to communicate with Rent the Runway asynchronously across different modalities, and have a stylist that is constantly available to recommend items, pick out new inventory and answer questions.
“If we are utilizing AI appropriately over the next few years, I see no reason why someone even has to come to our website,” Hyman said.
Stitch Fix has long married AI with human curation to provide outfits on a subscription basis.
“For years, we have utilized capabilities in generative AI, injecting scores and language into our personalization engines and, more recently, automatically generated product descriptions,” CEO Katrina Lake told analysts. “We have also developed and implemented more advanced proprietary tools such as outfit generation and personalized style recommendations that create a unique and exciting experience we believe is unmatched in the market.”
A new area where the company is applying AI is inventory buying.
“We have historically utilized a number of tools to make data-informed decisions with our inventory purchases,” Lake said. “Now, directly leveraging our personalization algorithms, we have developed a new tool that creates an exciting paradigm shift, which will utilize math scores at the client level to drive company-level buying actions. We expect the clarity of demand signals at the individual client level to drive more proactive and efficient inventory decisions as a company. And because of this, we expect to see higher success rates on fixes and drive increases in keep rates and [average order value] over time.”
Early results are promising. When compared with existing buying tools, testing showed a 10% lift in keep rate and AOV. By the end of this quarter, Stitch Fix expects 20% of all purchase orders to be algorithmically informed.
With experience using AI and a team in place to build, Stitch Fix is investing in the technology. Like Rent the Runway, it also has a unique dataset that offers an immediate advantage.
Here are Lake’s thoughts about how Stitch Fix’s AI strategy:
One of the things that I love about our experience is that we have generative AI that's really in more of a visual format. And so, the outfits that we have in our app, those are actually taking into account your preferences, what we know about you, and then in combination with what we know that you own in your closet. And to be able to kind of continue to push that technology and to be able to continue to give people more value in their experience with Stitch Fix, that's a really good example of, I think, a capability that is, firstly, really aligned with our capabilities around data and personalization and really unique to us.
And then I think it's also really compelling because I really think that pushes us as we think about what that addressable market is. I think if we can push outfits to be something that can be an asset to everybody, I think that is a universal thing that people would love to be able to have, is to have access to advice on a daily basis around what to wear and how to wear it.
While these are distinct companies, their plans lead us to a common conclusion: While the talk around generative AI might be new, many technology-forward companies already have assets sitting inside them that can be leveraged to build new tools. Uncover what’s already there, learn about the AI’s capabilities and develop a solution that's right for your organization. Then, talk to customers to determine how to improve it. It might mean commerce looks different, but that’s okay. The point is to create a better experience.