Colgate-Palmolive is tapping into generative AI to help manage its hundreds of product detail pages.
The consumer package goods giant best known for its toothpaste has close to 1,000 online product detail pages when factoring in its dozens of SKUs across the 10-plus retailers where it sells its products, including Amazon.com, Walmart.com, Thrivemarket.com, Instacart.com, Albertsons’ brands and more, says Todd Hassenfelt, global digital commerce director, strategy and execution at Colgate-Palmolive.
Ensuring those product detail pages are up to date, and resonating with the target audience on each of those brands’ sites, takes a team of people. That’s why Colgate is piloting a new generative artificial intelligence tool to help optimize those pages.
Colgate already uses digital analytics vendor Profitero Inc.’s digital shelf technology to manage these pages. Starting in July and through September, Profitero is piloting a generative AI tool called “Ask Profitero” with eight of its existing clients, including Colgate.
How Colgate plans to use the generative AI bot
The tool allows brands to ask the generative AI bot questions about specific details on any product detail page on a merchant’s site. For example, Colgate could want to improve the conversion rate of its mouthwash on the Walmart.com site. It could ask the bot, “What is the optimal title length to drive sales in this category?” The bot could then answer with the ideal length of characters for the specific category on that merchant’s website.
The bot could even recommend new titles for products and explain why it tweaked the language.
![Todd Hassenfelt, global digital commerce director, strategy and execution at Colgate-Palmolive](https://www.digitalcommerce360.com/wp-content/uploads/2023/08/Todd-colgate-150x150.jpg)
Todd Hassenfelt, global digital commerce director, strategy and execution at Colgate-Palmolive
Profitero derives these insights based on how highly products rank in search results on a retailer’s website when a shopper inputs certain keywords, says Bryan Wiener, CEO at Profitero.
This data is publicly available but takes time to analyze. The vendor also has 4,000 brands globally that use its software (one account can have multiple brands, Profitero says) that also helps improve its data models.
Retrieving insights faster
The AI tool can also just be a quicker way to retrieve insights from Profitero’s software. For example, a Colgate employee could log in and find these insights, or it could just ask the chatbot, “How are my sales on total whitening toothpaste in mint across all brands?” Or retrieve out-of-stock data and find out how often a product is out of stock at a certain retailer and for how many days over the course of 30 days, Hassenfelt says.
Another example of how Colgate plans to use the tool is to easily summarize the sentiment of ratings and reviews. Instead of finding the information and doing a manual analysis, Colgate could ask “what is the sentiment of reviews for this product?” If many of the highest-ranking reviews highlight a certain attribute, such as good flavor, Colgate can then update the product detail page with this information.
Effective product detail pages are not only important for online sales. They’re important for in-store sales as well, Hassenfelt says. Shoppers frequently check their phones while shopping in stores, and they might look up additional details on product detail pages. Plus, retailers may pull information from a product detail page for any in-store signage or product promotions. Ensuring this information is up to date with the information a retailer’s audience cares most about could help influence even more sales, Hassenfelt says.
Goals for the Ask Profitero AI tool
Hassenfelt expects this tool to save its teams weeks or months of time in manual analysis. There is a huge time component to creating content and content variations for one SKU in multiple places, he says. Then, if Colgate wants to change something and then see how that improves the conversion rate, it could take months of waiting to implement and analyze something, he says.
Despite the time savings, Colgate doesn’t anticipate changing any headcount.
“It will allow our teams to make faster decisions,” Hassenfelt says.
Another goal for using the tool is an increase in conversion rate, Hassenfelt says. A one percentage point increase in conversion (for example going to a 3% conversion from a 2% conversion) could equate to $1,000 to $10,000 in dollars for each product, Hassenfelt says. An increase like this would be possible if it received actionable insights out of the tool, he says.
In the short-term, overall the goal is to, “make it simpler and faster for our teams to take the analysis from our products to then actionability, going to act on those insights, specifically for conversion rate and improving sales,” Hassenfelt says.
“Long term, does this give our teams a source really to take information in a more timely way, in a way to consolidate data and find the trends and find the information,” he adds.
Colgate has about 10-20 employees from its U.S. team working on the pilot. Plus, the brand added another seven to 10 employees from various teams across its global digital organization including marketing, branding, customer service and logistics to make a cross-functional team.
Profitero builds AI tool
Profitero built this tool in house based on artificial intelligence consortium Open AI’s language model, Wiener says. After OpenAI became available to companies, Profitero developed its tool in about 60 days, he says.
![Bryan Wiener, CEO, Profitero](https://www.digitalcommerce360.com/wp-content/uploads/2023/08/Bryan_Wiener-profitero-150x150.jpg)
Bryan Wiener, CEO, Profitero
“We immediately saw the opportunity to make our clients’ lives easier by providing faster and better insights. The question was how to implement it,” Weiner says.
Profitero debuted the tool at a user conference in June and began working with clients on the private beta then. It was looking for the right clients to work with Profitero to train and tweak the tool to ensure it delivers valuable insights, such as, “Yes, I agree with these insights,” or “These answers are not working,” Wiener says.
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