fuboTV is a live TV streaming platform (also called a virtual MVPD) with the world’s most popular sports, news and entertainment content. Founded in 2015, fuboTV originally focused on streaming live soccer events; it has since grown to offer over 100 premium channels from network partners including, FOX, ViacomCBS, A+E Networks, AMC Networks, beIN Sports, Crown Media, Discovery Communications, NBA TV, NFL Network, NFL Redzone, Turner, SHOWTIME, Univision and more. fuboTV is the only virtual MVPD that streams live and VOD content in 4K.
fuboTV users have the option of choosing which devices they want to stream content on – mobile, web or connected and smart TV devices. Many of their most loyal users will utilize several of these options based on personal preference and for convenience (e.g. streaming on mobile during a commute, on a laptop while working and on their smart TV while at home).
The team realized, however, that the multiplicity of devices was not only designed to offer convenience to the users; it also opened opportunities for multiple user acquisition strategies.
As a subscription-based service, the team’s goal is to drive loyal, engaged, paying users. To drive higher ROI and minimize user acquisition costs on mobile, the team decided to double down on driving subscriptions to the service from the fuboTV website instead of supporting in-app purchases.
While effectively reducing UA costs, this strategy created a gap in the user journey and challenges in attributing the source of the acquisition. With users typically going from mobile to web and back again, it was difficult to paint the full picture.
As AppsFlyer veterans, fuboTV was excited to learn of the People-Based Attribution (PBA) product. As daily users of AppsFlyer’s mobile attribution dashboards and reports, the prospect of connecting their web and connected devices as well was an easy decision.
After a short onboarding process, fuboTV was able to gain access to the new raw data and begin streaming it into their BI systems for analysis and visualization.
With PBA data at hand, the marketing team was able to complete the puzzle, crossing extensive raw data from mobile attribution with new raw data from website activity as well as their own CRM. By joining forces cross-functionally across the marketing teams, the PBA data became the tool they used to connect all the pieces of the disjointed web and app funnel.
While the initial goal for the team was to gain visibility into the entire user journey, the whole turned out to be greater than the sum of its parts.
Reallocating marketing budgets
AppsFlyer’s People-Based Attribution aggregated all of their marketing initiatives data in a single place: affiliate, search, display and social. This provided the team with a clearer understanding of the journeys that lead up to a subscription event, across channels and devices, while also exposing some cases in which spend was needlessly overlapping between teams for the same users.
As a result, each team was able to reallocate its budget to ensure the right balance of exposure along the journey to acquisition. Occasionally, the team saw fit to even increase the mobile ad spend as they were now able to attribute user subscriptions that occurred on the company website to mobile acquisition efforts. Following the adjustment to the budget allocation, the team was able to drive more loyal, highly-engaged users with the existing budget.
Focusing acquisition efforts toward loyal users
fuboTV’s marketing team already knew that customer loyalty is directly correlated with the number of devices used; a user who consumes content regularly on three different devices is more likely to become a loyal user than a user enjoying content on a single device. By tying in the cross-device data from People-Based Attribution, the team was able to better recognize the channels that were driving the most loyal users, and stream more of their budget towards the channels delivering high retention rates.
Bringing a siloed team together
Perhaps most importantly, the new visibility helped fuboTV bring together the entire marketing team. The new data exposed how each team’s efforts played into the bigger picture, how channels were interacting, and which ones were driving which parts of the user journey.