As sports teams work towards expanding their fan bases, the increased scope of sales and marketing efforts can make it challenging to predict the ‘best’ leads (which could be a function of social engagement, lifetime value, or other performance indicators important to the organization).
Using Facebook’s lead gen tool, one NFL team started leveraging dynamic targeting to generate leads for both individual and season tickets prior to the 2018 season. Relative to total spend, the 2018 campaign was a huge success – the marketing team was able to generate 3,600 leads and ultimately generated an impressive ROAS of 600% on their Facebook campaign.
Going into the 2019 season, however, the team chose to pursue a more aggressive ad spending strategy and achieved ~3x the number of leads (~11k) but less than half of the ROAS compared to 2018 (~250%), which is still positive ROI, but something about the original 2018 strategy resulted in thinner margins throughout 2019 once the advertising budget was scaled up.
Since the team widened its lead funnel by over 300%, identifying the leads with the highest propensity to purchase a season ticket package became more challenging without reliable tools to make sense of the larger database of new leads.
Your organization can use AI to help its membership service organization use the historic sales pipeline and metadata tied to the sale to predict the potential value and conversion likelihood of a given prospect. In the case of the situation above, an independent AI solution could dampen the effects of scale by more efficiently narrowing a larger funnel by scoring leads based on the attributes that are most relevant in predicting the outcome of the sale given any individual lead. AI will help you explore what kinds of promotions, marketing engagement, and other content is most engaging depending on the lead, by simply taking your historical sales pipeline and letting the model learn my example. Bring a new level of precision and care to the season ticket sales by using machine intelligence to build a smarter process.