A quick scroll through my targeted ads on social media makes me seem kind of crazy. Right now, there’s an ad for an off-the-shoulder lace bridesmaid dress that looks like it came out of an 80s prom movie, a 1920s art deco dress, and a set of dinosaur print pajamas.
I am not set to be a bridesmaid in any weddings, nor am I a flapper or a child in need of a new set of jammies. All I can figure is that I got on some list of millennial women and from there, advertisers just threw everything they had at me to see if anything would stick.
In a world where 74% of consumers (including me) are now willing to give up personal data for a more personalized ad experience, why am I being chased around the internet with T-rex pjs? It’s no wonder 69% of marketers rate their AI vendor’s performance as poor. There’s got to be some sort of problem in the pipeline between user data and AI targeting.
Here are a few examples of innovative companies who use AI to create messaging that matters.
Beyond standard segmentation
Traditional methods of segmentation are pretty rudimentary. Knowing that a user is a woman between the ages of 30 and 40 can only get messaging so far, since that group contains a diverse population from many different walks of life. Better AI is revolutionizing the ways we break down our audiences, using information based on browsing behavior, past purchases, comments, and likes in order to create better experiences for users.
For example, athletic wear brand Under Armour recently partnered with IBM’s Watson to create personalized training plans for its app users. The brand understood that a 32-year-old woman training for a marathon would probably need a different training regimen and meal plan than a 20-year-old man interested in weight lifting. The app is a great example of the ways AI can break down audiences beyond standard segmentation and offer personalized options for individual users.
Personalized product recommendations
And speaking of product recommendations, the woman training for a marathon is probably looking for a different kind of workout clothes than a woman of the same age who religiously attends barre classes. So it doesn’t make a lot of sense to target them with the same ads just because, in the most basic segments, they look the same.
Fashion retailers are leading the charge of AI-based product recommendations. For example, Syte.ai allows users to upload a picture of an outfit they like and then the AI-powered recommendation tool searches a retailer’s inventory for similar styles. UK-based clothing retailer Boohoo recently claimed that integrating Syte doubled revenue and increased conversions 100% among users who opted in.
And those numbers aren’t unusual among businesses who become early adopters of AI technology for better audience segmentation and product recommendation. Audiences are tired of being chased around the internet with images of products they don’t want and need just because they fall into some broad demographic.
Now can someone please recommend some better-looking pajamas? I really do need new ones.
Ready to learn more about integrating AI into your marketing strategy?
Check out our webinar from Nov 7 focusing on how you can use AI to bring better consumer personalization to your marketing strategy. The webinar covers:
- Segmenting audiences beyond age and gender
- Finding the right customer on the right channel at the right time
- Customized product recommendations based on individual preferences
AI isn’t going away anytime soon — and it’s early adopters who will see the most benefits. Are you ready to start incorporating it into your marketing strategy?