Most concert halls are currently struggling to engage with an increasingly demanding and fragmented audience. Such was the context of our client, a reputable venue with a loyal but narrow fanbase. One-time visitors were aplenty in the more attractive events, but retention rates were low.
Our short assessment aimed at improving the knowledge about the audience, taking advantage of vast transactional data from a decade of diversified events.
How could data-driven decisions help in expanding the audience beyond committed melomaniacs?
We started by segmenting the customer base according to frequency and preferences, from devoted concertgoers, passionate about classical music, to disengaged passers-by. This helped us grasp the customer journey, unveiling a big opportunity: launching a NBA (Next Best Action) engine, to target the right offer or suggestion to the right customer, at the right moment. For instance, the engine would realize that a second visit should be encouraged less than three months before the first one, as this stimulates retention.
Additionally, chances to cross-sell and prevent churn would be uncovered. But targeted campaigning was only a part of the solution.
We also prepared the ground for two other relevant opportunities: dynamic event pricing, responsive to the evolution of ticket sales, and analytical-driven support to the definition of the repertoire, by anticipating the attractiveness of a given potential event.
Our key deliverable was a thorough diagnosis of marketing practices, from an analytical standpoint. Besides uncovering key patterns of client behavior, we pinpointed several practical routes for improvement, consolidated in the three major opportunities mentioned above.
Furthermore, we prioritized such routes in an actionable roadmap aiming at expanding the client base, a massive prospect since only less than 10% of the venue’s annual visitors were regular attenders.
Besides the static report, we also deployed a dynamic dashboard with key marketing and customer-related metrics, allowing the concert hall’s internal team to autonomously explore the results of our analysis.