Imagine you’re on the hunt for a new shirt. You know you want something colorful, possibly with a fun pattern, but you haven’t liked the options at your local department store or what’s available online.
But what if you could design the perfect item yourself with the help of AI — or vote for your favorite from a list of hundreds (or thousands) of options that will later be produced?
These new ways of getting products into the hands of customers are expanding, and generative AI is reshaping the product development process.
There are many ways to use generative artificial intelligence (AI) in commerce — and these tactics span every stage of the go-to-market (GTM) process. Product development is no exception, offering many unique opportunities for brands.
Explore how AI is being used in product development and get real-world examples of how some leading brands are leveraging its capabilities to drive digital shelf success.
From enhancing go-to-market efficiency and powering data-driven market, consumer, and trend insights to facilitating product design and enabling product personalization and customization, the list of beneficial uses for the product development process is continually growing.
Here are some of the most common ways AI is being used in the product development process.
AI can gather and analyze customer feedback to identify pain points, feedback, and new product requests. Brands often gather feedback from several channels, including product ratings and reviews, focus groups, social listening campaigns, and more.
Using an AI algorithm, brands can leverage AI to process and analyze these data points, turning them into insights on emerging trends, new product ideas, product optimization ideas, competitive insights, and other information that support current market demands.
Similar to the process for turning customer feedback into product ideas and updates, AI could also be used to gather and digest market research and trend analysis, which help support the product development process.
Brands can get the latest insights into the continually evolving market and shifting buying behaviors to help them stay up-to-speed strategically.
Brands are increasingly using AI to power the product design and prototyping process, leveraging AI algorithms to develop new product ideas and support the ideation and brainstorming process.
Many brands are taking this a step further by also implementing first-party customer data, customer reviews, and market trends and insights into their prompts to anticipate future product creation wants and needs.
Personalization in ecommerce has been a growing trend, as 2022 Salsify consumer research found that 70% of U.S. shoppers are more likely to buy an item if there are “personally relevant” images, text, and reviews on a product page.
Generative AI could be leveraged to deliver products that cater to the individual tastes and needs of consumers, helping them curate and design products within their unique parameters.
Several legacy brands are already leveraging (or planning to leverage) AI within their product development process. As with all new technologies, this test-and-learn approach allows brands to capture consumers' attention with innovative ideas and move quickly to understand what drives engagement — and, ultimately, sales.
Here are some examples of brands using AI within their product development process.
The Coca-Cola Company launched a limited edition flavor, Coca-Cola Y3000, co-created with human and artificial intelligence to understand “how fans envision the future through emotions, aspirations, colors, flavors, and more.”
The brand collected data from its customers worldwide, combined them with AI insights, and developed a new flavor that predicts what the palates of the future will enjoy — offering customers a “chance to taste the year 3000 today.”
Video Source: The Coca-Cola Company Instagram
Clothing brand FINESSE dubs itself the first “AI-driven fashion house,” combining its proprietary AI algorithms for clothing design with a shopper voting process that determines which items will get manufactured and how much will be created — all based on demand.
This combination of AI with shopper data allows the brand to avoid overproduction and prioritize products with pre-established popularity, all while avoiding the traditional testing stage for new product launches.
Image Source: FINESSE
Estée Lauder continues its expansion of generative AI to improve the customer experience across its brand sites, leveraging AI-powered solutions to “better understand consumer sentiment, inform R&D [research and development] efforts, and translate the magic of prestige beauty brands into best-in-class, high-touch digital experiences.”
The company, noticing that trends — such as viral products on TikTok — are increasingly driving customer tastes in beauty and cosmetics, is extending its investment in generative AI.
For Estée Lauder, product development is about to get a lot faster.
Brands that harness the power of AI within the product development process have an enormous opportunity.
From gaining up-to-speed market insights and strategic product feedback to delivering product personalization options and launching AI-driven product brainstorming, generative AI can supercharge the product development process.
Stay ahead of the competition by keeping up with the continually shifting demands of shoppers and deliver engaging shopping experiences — full of products consumers want now and in the future — to drive digital shelf success.