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If you’ve ever looked at a report in Google Analytics, you’ve used a customer journey analytics platform. Journey analytics tools allow merchants to track and analyze how customers interact with a website and/or other customer engagement channels.
Typical journey analytics reports include funnel reports, customer flow visualizations, and cohort retention charts.
To fully leverage a journey analytics tool (from commonplace tools like Google Analytics to more feature-rich platforms like MixPanel and Amplitude), merchants need to be able to collect and organize customer events, to provide a “stitched together” view of how each customer interacts with the brand’s website, email marketing, paid ads, and so forth.
Fueled provides a single approach to collecting, organizing, and cleaning this data for more complete analysis in customer journey analytics tools.
This sort of product analysis allows merchants to make better merchandizing decisions — both in-store and on their website storefronts.
The most talked about use case for CDPs and 1st-party attribution tools like Fueled is for personalization of website experiences, as well as other sales/marketing channel experiences like email and SMS.
Because Fueled captures all of a customer’s interactions with a brand, Fueled can power personalization tools placed on a storefront, or marketing automations that personalize email and SMS content experiences.
Similar to personalization strategies, CDPs and 1st-party attribution tools like Fueled provide merchants with a comprehensive view of customers’ interactions with a brand and its product catalog. This data allows merchants to create more precise segments, or lists of customers, which they can used for paid ad targeting, as well as the creation of “look-a-like” audiences in Facebook and Google.
While not commonly talked about (yet!), CDPs and 1st-party attribution tools like Fueled can push customer events into customer service platforms, such as Gorgias, Zendesk, and Kustomer.com. This provides a cost-effective way for merchants to provide customer service reps with the full history/context of a customer when addressing support issues.
More personalized, contextualized customer support experiences lead to happy customers with higher customer lifetime value.
Many eCommerce brands have started piping all of their customer behavioral events, most importantly purchase-related events, into a data warehouse. From there, they can use a BI tool (like Tableau or Power BI) to analyze what products are selling best and what discounting strategies might be better performing.