Dynamic Yield Launches Affinity-Based Personalisation
The new capability automatically scores important interactions, profiling individual preference for use in targeting and experience delivery. Dynamic Yield, the AI-Powered Personalization Anywhere™ platform, announced the release of Affinity-Based Personalization – a new capability allowing brands to leverage automatically generated user affinity profiles to easily build a new class of user segments and deliver highly-targeted experiences across channels. […]
The new capability automatically scores important interactions, profiling individual preference for use in targeting and experience delivery.
Dynamic Yield, the AI-Powered Personalization Anywhere™ platform, announced the release of Affinity-Based Personalization – a new capability allowing brands to leverage automatically generated user affinity profiles to easily build a new class of user segments and deliver highly-targeted experiences across channels.
While retailers track purchases, they’ve missed out on a trove of highly valuable information in the form of product and category browsing activity over the years. This structured data can be used for the creation of more relevant and individualised marketing campaigns, but instead, it often goes completely unsaved.
Dynamic Yield can now match a visitor’s browsing activities with the attributes of the products they interact with, leveraging the data to build a unique affinity profile for each individual in real-time. In turn, this allows for the automated creation of new and sophisticated user segments that can be utilised across all channels, including web, mobile, app, email, as well as sent to external third-party platforms like DMPs, BI tools, DSPs, and more.
Also Read: Brands Must Look For Growth Opportunities Outside of Walled Gardens
Each user’s affinity profile is continuously refreshed with every interaction, providing unique insights into their preferences to specific colours, brands, sizes, categories, price ranges, or any such attribute present in the product or content feed.
A visual representation of a visitor’s individual affinities
Here are some actual, specific examples of how customers of Dynamic Yield have used Affinity-Based Personalization:
- A clothing retailer delivered highly individualised product recommendations based on user-affinity towards certain categories of products.
- A travel site built an audience of users only interested in a certain type of a vacation, and used all on-site banners & offers to promote that category of vacation.
- A multi-brand retailer identified users who were displaying affinities to select brands and aggressively promoted deals featuring the brand.
- Based on a user’s affinity to select categories and on-sale items, a retailer changed the layout of the top navigation to highlight on-sale products.
Also Read: Omnichannel Programmatic is The Way Ahead in 2019
“Product metadata is a huge asset to marketers which has largely been underutilised until now,” said Liad Agmon, CEO of Dynamic Yield. “With this new capability, it can be leveraged to uncover meaningful correlations between the product a user is interacting with and its many attributes for the creation of deeply segmented and tailored experiences across channels.”
“We love how Dynamic Yield has allowed us to learn more about our customer base,” said Greg Cormier, Global Director of Digital Marketing & Communications at G Adventures, the leading small group adventure travel company. “We’ve gained valuable insights into who the individuals are behind each of our trips, and utilising Affinity-Personalization, can more effectively connect with them based on their distinct buying habits.”
Also Read: How AI is Improving Predictive Analytics
Built on the back of direct customer feedback, Affinity-Based Personalization has been in beta since May 2019 and has already become the single fastest adopted capability within Dynamic Yield’s diverse feature set. This capability has been used to power both 1:1 experiences, as well as delivering highly targeted experiences to specific segments.
