Operations
10 April
Meet Max, an AI chat assistant for data analysis, powered by GPT-4
AnswerRocket launched the conversational tool to help CPGs zero in on insights held within growing volumes of data.
Photo by Pietro Jeng on Unsplash
×
The Current, delivered daily.
Ecommerce news, right to your inbox.
Sign up for our email newsletter.
Subscribe.sticky-cta-wrapper {
width: 100%;
position: fixed;
bottom: 0;
left: 0;
background-color: var(--black);
}
Subscribe to The Current newsletter
For most businesses, any problems that arise with data are no longer tied to scarcity.
Enterprises have access to more data than ever, coming from a multitude of sources.
This can provide a path to enhancing understanding of consumers and how a business operates, all so that a business might improve.
But there’s now so much data that issues are stemming from abundance.
The question asked around CPGs and other enterprises is no longer, "Do we have data on this, and how can we get it?"
Instead, business leaders are asking, "What data do we have? And, how can we find it and put it to use in the most resource-efficient way?"
That’s an area where AnswerRocket is finding a role for the generative AI engine GPT-4, and a conversational approach.
The company recently released Max, an AI assistant that is designed to help businesses analyze their data through chat. On its recent launch, it was set to be used by CPGs such as Anheuser-Busch InBev and American Licorice Company.
The tool allows users to ask questions of the assistant that can be answered through their data. Then, they receive answers back in the form of insights and visualizations.
It arrives on the heels of the March release of GPT-4, which is the latest version of OpenAI’s large language model that powers tools such as the wildly popular ChatGPT.
AnswerRocket CEO Alon Goren has been working on technology that helps businesses find and analyze data since the company was founded in 2013, and before. Recent advances in large language models, particularly with the release of GPT-4, marked a step forward that enhanced both the technology’s ability to understand the question, and deliver answers to users that had the amount of detail necessary to solve a problem, Goren said.
These backend leaps have also improved the user experience. A tool like Max can now be approachable, even for those without data or tech skills.
“It's designed to be used as you would converse with an assistant,” Goren said.
Max aims to take high-level questions, and provide answers that go deep into a company’s data. Combining AnswerRocket’s augmented analytics platform with GPT-4, Max allows users to ask questions to the assistant in the same language they would use with another person when curious about a trend or outlier, and technical expertise isn’t required to dig into the data.
“It enables us to go from what the user said to a format where we can now query available content, search the data and then respond in a very natural narrative that a user can read,” Goren said.
While the questions can be basic and high-level, Max can provide statistical, diagnostic and predictive analytics that go deep into a company's data. In a large business, Goren said this can help advanced analytics spread across different departments. With an AI powered assistant, access to data analysis will be less tied to the decisionmaking that goes with expenditure and prioritization of human-powered resources.
“Suddenly, this long tail of products becomes much more manageable than it previously was with having to have a human in the loop to do every bit of analysis,” Goren said.
Along with availability, such a tool also holds the promise of making technology and data analysis more integrated into workflows than ever.
“A chat-based tool like Max can help more users feel comfortable interacting with data,” said Sabine Van den Bergh, director of brand strategy and insights for Europe at Anheuser-Busch InBev, in a statement. “Having an on-demand assistant that can quickly answer the questions that pop up throughout the day would enable our team to make data-driven decisions at scale.”
Nestle and General Mills joint venture Cereal Partners Worldwide, which is an existing AnswerRocket partner, sees the chat experience taking AnswerRocket "to the next level," said Chris Potter, global applied analytics at CPW.
"We need our teams to make informed, fact-based decisions," Potter said, in a statement. "Max will enable users across all levels of CPW to quickly access data and insights through intuitive questions and responses.”
AnswerRocket will be rolling out the technology to businesses throughout the second quarter.
Subscribe to The Current Newsletter
SubscribeTrending in Operations
Shopper Experience
08 June
AI, but make it fashion: Rent the Runway, Stitch Fix look generative
"Fashion ecommerce is one of the most cumbersome customer experiences that exists," said Rent the Runway CEO Jennifer Hyman.
Photo by Daniel G. Wells III, used under a Creative Commons license.
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: From search to concierge
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: Inventory buying and beyond
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.
Keep reading...Show less
Loading...
Subscribe to The Current Newsletter
SubscribeLatest from Operations
.sticky-cta-wrapper {
width: 100%;
position: fixed;
bottom: 0;
left: 0;
background-color: var(--black);
}
Subscribe to The Current newsletter