This video/transcript describes a transformation of a traditional fuel retailer into a digitally driven consumer-goods retailer and integrated mobility service provider. The project leverages Salesforce (including Data Cloud, Loyalty Cloud, Marketing/Experience Cloud), Databricks, and IBM WatsonX to harmonize customer data, create micro-segmented personas via feature engineering, and power generative-AI-enabled marketing with the goals of increasing visit frequency and basket size.
Questions this video answers
Over 5 million loyalty shopping transactions every month
IBM WatsonX
Salesforce Loyalty Cloud, CRM Experience Cloud, Marketing Cloud, Data Cloud
Increasing frequency and basket size
Chapters
Our vision for Moore Group is to evolve our service station from a place where you just fuel up your car to a place where you want to go on your journey. Currently we are in a transformation from a traditional analog fuel retailer to a digitally driven consumer goods retailer and an integrated complex mobility service provider. Based on in depth research. Our consumers want first of all quality fuel at affordable prices. Secondly, a friendly staff and a great service station experience. And thirdly, a great loyalty program where they get personalized benefits.
With over 5 million loyalty shopping transactions every month, MALD has collected a lot of data around their customers. So over the years we connected and harmonized different processes and data leveraging Salesforce platform. But the big next step was to move them to data cloud as a new foundational capability. To start moving them on the journey on generative AI, we had to turn the customer data from data cloud and databricks into micro segment Persona. With feature engineering we built a new Salesforce marketer workbench to enable interaction with creative capabilities of generative AI. We and we used IBM WatsonX platform to manage larger language models supporting Eastern European languages.
So to run our loyalty program we use Salesforce Loyalty Cloud, CRM Experience Cloud Marketing Cloud Data Cloud and MU software integration. We built strategic segmentation on Data Cloud with two main goals, increasing frequency and basket size.
We have 34 segments based on customers transaction frequency and purchase our HERO products. We wanted to take that to the next level with predictive AI and generative AI and de average further our strategic segments into micro segments and then tailor the communications through Genai to a specific micro segment. For example, we take one strategic segment which is customers who are not yet buying our coffee. With Predictv and Genai, we broke that segment into 15 micro segments, 15 different Personas and we defined 15 different communications. Our personalized campaigns deliver three times the return of our general campaigns. Teaming up with IBM was essential because they acted as a strategic partner providing us with the necessary engineering capabilities to develop our Salesforce platform and roll it out across many countries. What excites me about our pilot with IBM and Salesforce is that it sets the foundation for future scalability. With Salesforce's flexibility and capabilities, there is no business need we can't address. Setting the stage for our next advancements in generative AI.
