How ThirdLove used AI for better personalisation

Using artificial intelligence (AI) to get a better bra fit and for personalising the marketing journey

For most women, a bra is a very personal and rarely spoken about thing. So to use artificial intelligence (AI) for not only determining a better bra fit for women, but for personalising the marketing journey, could easily have flipped over the line from helpful to creepy.

And yet, US underwear brand, ThirdLove, has struck that careful balance, growing revenue in the process.

Since 2013, ThirdLove has been on a quest to connect women with comfortable bras that actually fit. After taking the measurements of millions of women, the company introduced the industry’s first half-cup sizing, and developed an algorithm using the data to match each woman with the right size for them.

While the innovation was astonishing, ThirdLove needed to convince shoppers to take a chance on a new and relatively unknown brand with one of their most intimate requirements.

While it had been doing the usual marketing, including personalisation and split, A/B testing, it knew it needed to do better. After a research phase, ThirdLove engaged Dynamic Yield for its AI-enabled personalisation platform so it could take a far more tailored approach to its customer journey from the top of the funnel.

Personalising to build trust

ThirdLove required a solution that would help them to tailor messaging and creative to different audience groups, continuously optimise landing pages for each visitor, and surface the best product recommendations for each visitor. Its director of product growth, Desirae Oppong, said while ThirdLove’s products speak volumes about the company’s understanding of customers’ needs, for many women who have been disappointed buying bras in the past, a higher degree of personalisation was needed to gain their trust.

Since implementation, ThirdLove has offered initial landing page experience for different audiences, adjusted homepage messaging and creative based on browsing history, and has been collating data from users via a quiz to better improve its offerings.

Initial results are encouraging, including a 23 per cent increase in average revenue per user, a 3 per cent uplift in homepage hero banner click through rate, and a 75 per cent improvement in completion rate for its Fit Finder Quiz for first time visitors.

Oppong told CMO this is the tip of the iceberg in terms of what the business is hoping to achieve as it navigates through the new AI platform.

“We inherently knew there was a lot of opportunity around personalisation for us,” she told CMO. “And looking at examples of personalisation across other brands, it has been proven to drive considerable value by really honing in on what a certain user needs. So that was one of our big reasons for looking at Dynamic Yield.

“We also needed an updated way of doing A/B testing, as the prior tool we had was not nearly as robust.

“The change has allowed us to really hone in on what is the right experience for different users on our site, and how we customise and tailor that in a way that's truly effective."

Oppong cited growing diversity of the user base over time. "When you start off as a very young startup, almost all of your site visitors are brand new. And it's a little bit easier to think about them as one collective group," she commented. "But as you get larger, that diversity increases quite a bit, and suddenly you find yourself with a healthier balance of new visitors versus repeat customers.

“The content each of those groups is looking for is completely different. And so we've found it's incredibly important to personalise and make that journey a little bit tailored to each of those types of users. And you're missing the opportunity to really showcase something that they're likely to be interested in if you don't.”

To this end, instead of dropping first-time visitors on collection pages with entire product catalogues, ThirdLove directs a portion of traffic to specific pages more tailored to the segment. Additionally, visitors who land on the Fit Finder Quiz landing page from Facebook campaigns but have already completed the quiz in the past are automatically redirected to a landing page highlighting more relevant content. Simply doing this resulted in a dramatic increase in purchases and improvement in overall campaign performance.

ThirdLove also leveraged its hero banner on the homepage to drive engagement by tailoring it according to the individual’s browsing history, and for new versus returning visitors across desktop, tablet, and mobile.

Those who had not previously browsed the site received more evergreen content and messaging around core products. Returning visitors were shown newly launched products. By optimising the homepage experience, ThirdLove saw a 6 per cent increase in hero banner CTR and a 3 per cent lift in conversion.

“What we do is, first of all, is we look to understand what challenge the customer is coming to us with. So in that way we're able to tailor our recommendations on what might be the right products to recommend," Oppong explained.

“Then we do filtering based on the size that we recommended or sizes that you've bought in the past because one of the interesting things about this space is they might not have a size that fits them properly, and so being able to showcase the products that we have that truly fit you is one of the important experiences for our brand and for our site.

“If you're doing personalisation in a way where you're using information people are readily sharing with you, then it ends up being helpful instead of something else.”

Up next: How ThirdLove is convincing women through data

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