Adaptive experiences are a crucial element of digital experience optimization and personalization for ecommerce sites and marketing.
What is an adaptive experience?
Ecommerce brands use adaptive experiences by capturing and analyzing customer data and leveraging integration and composition tools to then deploy personalized content (messages, offers, product, recommendations, etc.) in response to a customer's specific behaviours (or data).
In other words, adaptive experiences are a key weapon in the battle fordigital experience optimization and against a static, one-size-fits-all customer journey or digital experience.
With the right tools, ecommerce brands can use valuable customer insight to create and host adaptive experiences on their site that drive customer engagement, sales, repeat purchases, and brand loyalty.
5 examples of adaptive experiences (and the data that fuels them):
Product recommendations based on demographics: An ecommerce site selling apparel might highlight certain products based on a visitor's location. For example, an ecommerce site selling apparel might highlight thanksgiving dinner-appropriate outfits in September for a Canadian customer, but not until November for an American customer.
Complementary products based on real-time product browsing: For example, a product carousel on a queen sized mattress PDP offering complementary products like queen sized sheets, queen sized duvets, etc.
Special offer based on browsing history: If, for example, a site visitor added three pairs of jeans to their shopping cart, but ended up abandoning the cart before making a purchase, you might follow up with an email including a limited-time discount code to be used on any denim products.
Product recommendations based on first-party data: Surveys or quizzes are a great way to get information directly from your customer (what they're looking for, what they might be interested in). For example, an ecommerce site selling jewelry and accessories might have a pop-up quiz inquiring about who the visitor is shopping for, their budget, their style or color preferences. From there, the customer journey can be personalized and streamlined by suggesting exactly the kinds of products they want to see.
Marketing messages based on purchase history: If, for example, a customer previously purchased a skin care product, you might send a marketing message out a month later asking them to share their feedback in a review and suggesting it's time to re-stock (repurchase the same item).
...And these are just a few examples. The customer data collected by an ecommerce brand combined with right integration, automation, and composition tools allow for endless possibilities when it comes to creating and deploying adaptive experiences that optimize your ecommerce site experience for your customers.
