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Jul 28, 2020
The pandemic has altered many things including how sports organizations view and understand their data. Although there are limited situations where fans are back in venues, most teams are still focused on finding new ways to generate leads and nurture those leads appropriately until they can sell tickets.
New lead acquisition strategies have embraced creativity more than ever before. Teams are making data collection fun for fans, with gamified surveys or sweepstakes, to not only learn new things about fans but also update old data (think, single or married status a few years ago changing to a family with young children status now). Another way to update and collect new data on individual fans can come directly from the conversations your sales reps are having with customers and leads since the focus is more on developing relationships right now. CRM touchpoints are also gaining additional insights into how fans feel about games returning or comfort level of returning to venues.
As new data comes in, all the analytics teams we’ve spoken with are spending the vast amount of their time connecting more systems to their single customer view and cleansing data. From flagging and removing duplicate accounts to supporting ‘sorry to see you go’ campaigns, the goal for these departments is to improve data quality.
Historically, leads generated through ticketing systems from single-game tickets purchases were far and away the biggest acquisition channel for teams. So much so that across the industry, ticketing systems account for at least half the leads generated for major league teams and over 70% for minor leagues and as much as 90% in some cases (averages via StellarAlgo platform statistics). Due to the pandemic, the frequency of ticket sales has all but halted, which means teams are looking to other sources to fill the void.
Although digital is a relatively new, and somewhat complex, data source that organizations are just starting to bring into their single customer view, the pandemic has accelerated the importance of tracking and measuring this lead source. Digital data points include social ads, web pixels, e-commerce, online sweepstakes and contesting, and more. E-commerce in particular has been performing well these past few months, generating a host of new leads for sports teams. We’re seeing on average 11% new, in-market e-commerce leads acquired in the past three months alone. From a web pixel standpoint, many organizations are using this down period to re-evaluate how pixels are placed on their website in order to improve identity resolution. Web tracking becomes more important as teams try to stay on top of how fans are engaging with their brand and who’s most engaged so they can adequately nurture those engaged fans when ticket sales do return. The key to success in these nurturing efforts is the identity resolution so that engagement scores can be tied back to individual customers rather than blanket aggregate insights. These digital data sources are here to stay and will continue to be important touch points to connect back to fan profiles and to build into predictive models.
While new data points increase in importance to determine fan engagement, avidity, and likelihoods to purchase to renew, data models will also adjust. Using the term predictive has started to become a buzzword among technology vendors in the sports world but in this pandemic world, static models will not fare nearly as well at predicting future behavior since behaviors and actions of fans have all been so distorted. At StellarAlgo, our lead and retention scores are built from supervised learning, which means that models continue to learn and evolve not only in individual markets but across the baseline model that accounts for over 50-million fan records and 32 billion fan data points. On top of that, we are going back and tuning with new data points to ensure that scores are performant and trusted.
Mentioned above, avidity and engagement scores are another way to track how well your team is connecting with fans during this time. Both of these models take multiple different data sets into consideration and are good strategic metrics to think about right now. We’re seeing organizations using both of these scores to set growth targets from. For example, while pre-pandemic fan avidity scores were distributed on average like this: 54.2% Lite, 30.6% Casual, 15.2% Avid; Avid fans have dropped off the most since January 2020, but mostly down to casual (via StellarAlgo models). As seasons start again and teams build up to allow fans into venues at a limited capacity, some organizations are using avidity scores as a way to measure how well they are nurturing fans.
Whether your organization is mining 2 or 3 of your systems for customer data or a dozen, there’s an opportunity to use this period to capture more data, improve its quality, and use it to inform organizational strategy as sports open back up.