Fingerhut actions their rich CDP data by using Monetate Personalization to deliver hyper-personalized experiences
Overview
Fingerhut wanted to deliver hyper-personalized experiences to their customers using proprietary data from their customer data platform (CDP), Tealium. They turned to Monetate Personalization to address this issue.
With its market-leading personalization software and open platform infrastructure, Monetate enabled Fingerhut to easily connect and input data from Tealium Audience Stream to fingerhut.com, their flagship eCommerce website. Fingerhut makes merchandise affordable by offering credit accounts with low monthly payments, which means serving relevant promotions based on individual customer profiles is crucial.
By connecting their CDP, Tealium, to the Monetate Personalization engine, Fingerhut was able to act on customer insights like third-party credit data, past shopping behavior, and brand/category affinity, achieving exceptional results with personalization of content over random assignment of offers.
Before implementing a 1-to-1 personalization engine, Fingerhut had to manually create their audience segments and decide which experience (content or promotion) to show to each segment. Now they’re saving 50% of the marketing teams’ time by utilizing Monetate machine learning.
“Monetate has made it easy for us to use our proprietary data without having to pull in our business intelligence resources for assistance,” explains Aimee Pederson, Site Optimization & Tools Manager, Ecommerce at Fingerhut. “We’d typically need Business Intelligence to set up a feed, but they’re always in demand. Tealium Audience Stream allowed us to self-serve in a way that we couldn’t before. Being able to connect that to Monetate has saved us a lot of time and allowed us to fully utilize this data source. It’s allowed us to add hyper personalization to our specific value proposition and our brand.”
Background
Leveraging CDP Data for 1-to-1 Personalization
Fingerhut wanted to leverage the proprietary customer information housed within their CDP, Tealium, to deliver hyper-relevant promotions and content to each individual shopper on Fingerhut.
“We’re an eCommerce retailer, but what separates us is that we help customers build or rebuild their credit,” says Pederson. “We need to be able to segment based on the data that fits our customers.”
The openness of Monetate’s platform combined with the machine learning capabilities of Monetate, enabled Fingerhut to connect, input, and utilize data from Tealium.
Aimee Pederson
Site Optimization & Tools Manager, Ecommerce, Fingerhut
We’re an eCommerce retailer, but what separates us is that we help customers build or rebuild their credit. We need to be able to segment based on the data that fits our customers.
The Approach
Creating unique personalized experiences
By combining the customer data housed in Tealium Audience Stream with Monetate Personalization, Fingerhut created the following personalized shopping experiences:
Experience 1: Individualized Homepage Experiences
Fingerhut wanted to automate the process of delivering personalized homepage experiences for individual shoppers. They suspected that automating the process of serving individualized content on the homepage would increase total conversion. Automation would also reduce time invested cross-functionally from initial planning to execution.
Using Monetate’s automated 1-to-1 personalization engine, Fingerhut customized the Homepage asset located immediately beneath the Hero image, displaying one of ten possible highlight offers driven by Automated Personalization algorithms.
After implementing the automated individual fit experiences, Fingerhut saw a total conversion increase of 1.1% while spending half the time they’d spent manually curating segments and increasing customer engagement.
Experience 2: Personalized Homepage Category
Fingerhut wanted to see if serving customized offers on the Fingerhut.com Homepage based on each customer’s favorite category would increase conversions versus serving static Homepage Hero offers.
Using Monetate Automated Personalization experiences, Fingerhut served website visitors one of three category-focused promotional offers: Electronics-based, Home or Kitchen-based, or Apparel-based, matching the offer to the customer profile.
With engagement set as the goal metric, the personalized Homepage Hero offers increased product views by 4%.
After connecting Tealium to Monetate, Fingerhut was able to automatically update the master data set to include information such as a customer’s available credit, favorite sections, and more. This data is fed as a constant variable into the Monetate Personalization Decisioning Engine.
Aimee Pederson
Site Optimization & Tools Manager, Ecommerce, Fingerhut
What separates us from other retailers is that we help our customers build or rebuild credit. So, we need the ability to segment our audience based on the data that fits that market and have access to our customer information so that we can market to our customers in a way that is all about them and their needs. That means putting the customer first so that they can improve their credit scores. Having that data available to us is really what allows us to do that.
Results
The impact of achieving personalization at scale
Fingerhut has a unique value proposition as an eCommerce retailer that enables people to build or rebuild their credit. The ability to easily connect their CDP, Tealium, to Monetate’s personalization engine and scale experiences using Monetate’s 1-to-1 personalization and testing capabilities meant they could optimize and tailor each shopping experience to individual Fingerhut shoppers who have varying needs.
“What separates us from other retailers is that we help our customers build or rebuild credit,” explains Pederson. “So, we need the ability to segment our audience based on the data that fits that market and have access to our customer information so that we can market to our customers in a way that is all about them and their needs. That means putting the customer first so that they can improve their credit scores. Having that data available to us is really what allows us to do that.”