During the 2021 Dataiku Product Days, Mark Sucrese, VP of Marketing Sciences at Epsilon, shared some insights on a very common challenge that businesses are facing today: moving from brick and mortar to online stores.
Maintaining a Personalized Customer Experience
One particular customer Mark presented in this session was a large automotive retailer facing this challenge. The brand already had thousands of storefronts across the U.S., but wanted to create one-to-one experiences online. How could they ensure that these experiences remain similar online and in-store to maintain customer loyalty and satisfaction?
Bringing content together to execute on personalization was the goal, but this automotive retailer was faced with a couple challenges, including:
- A low number of resources to handle the workload
- Thousands of products that were available to everybody every given day
- Trying to cater content and messaging on a one-on-one level
Your brand only has seconds to make sure that the message and content information that they're providing a customer is relevant. If you don't get it right, customers will move on to another brand to help them solve their problems.”
Two solutions to these problems were either throwing a lot of bodies at them and hoping that a very large marketing team could solve them, or looking to technology. Epsilon and their client decided to tackle the latter with Dataiku.
Creating a Hub-and-Spoke Environment
The critical piece of the project was creating a hub-and-spoke environment for a technology solution that sits at the center of these various experiences. Whether through email, website, mobile application, or storefront, this hub-and-spoke environment allows data to come in from all sources and be processed through models created to predict relevant personalized products, messaging, and content. The predicted information is then distributed out to those channels in a relevant way. So when the consumer hits the brand, whether they browse some product on-site or drive to the store, the hub-and-spoke model allows this retailer to have a connected experience with each customer.
To be able to do this, however, you have to be able to process information, train and retrain machine learning models, and then to serve that out wherever the consumer is, in a relevant way. This is where Dataiku comes in.
Creating Value From Data With Dataiku
This automotive retailer was now faced with a new challenge around how to consolidate all the new data coming in from online transactions. By moving online, the amount of data this omni-channel retailer had now massively increased. So let’s see how Dataiku helped make sense of and extract value from this data.
There were two main considerations to tackle with Dataiku:
- Ensuring data consolidation and profiles were mapped properly
- Ensuring content was readily available
Dataiku helped the team reach these two goals as they used the platform to:
- Create structured data schemas to connect all the data sources
- Build feature creation and feature engineering that focused on ways to construct data as it came into the models
- Build a library of models to solve various problems like product recommendation models and content optimization
- Use automation and API nodes to serve out batching and real-time processes
Dataiku acted as a sort of intelligence centre making all these decisions.”
Epsilon and their client turned Dataiku into a decision engine that did more than just generate insights and information — it was used as a real-time action engine that produced personalized experiences continuously researched by marketers.