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Blog
Dec 17, 2018
StellarAlgo
Read time: 4 mins
If you’ve been activating sales and marketing efforts around scored customers (as outlined in a previous blog series) you are on the right track toward creating a data-driven sales and marketing organization.
Prospect scoring will continue to act as your northern star throughout the year as you hone in on which customers to prioritize for nurturing efforts. Direction is important but as we all know the realities of a busy season fraught with unforeseen circumstances and having less time to react than expected will force us to act swiftly in order to reach our goals. This is why we work in sports right?!
This post is about using data to rise to meet those unforeseen challenges that can sink you before you reach your destination. It’s about understanding the fans in your database and using segmentation techniques to maximize conversion. We recommend breaking the the individual event sales cycle into two distinct parts.
Pre-Season Package and Group Selling These really set your base. The higher the coverage from packages and pre-season groups the less pressure on the organization to make those individual event sales with sand running through the perishable inventory hourglass. We spent time on this in previous blog posts already, so we aren’t going to dig into it here.
Scheduled Major Sales Opportunities We know these natural calendar or curated dates that can act as catalysts for major sales. The major ones are season on-sales, season pre-sales, Black Fridays, Cyber Mondays, no fees days, etc.
Segmentation does come in here and having the ability to understand your database well enough to know who might be a potential buyer at these events will drive results. Positioning these events in front of the right customers will go a long way toward driving conversions and nurturing customers toward being lifelong fans. This means making sure customers don’t fall through the cracks but also using data to create targeted and tailored content.
An example would be pulling a targeted sub-list for an on-sale campaign on the following two personas:
Persona A
Tagged as on-sale buyer (has purchased at on-sale the past 3 years)
Tagged as non-package (has never purchased a package)
Tagged as prime sight-line (purchases seats at premium price points)
Tagged as weekend buyer (buys for Friday or Saturday events)
Tagged as early buyer (purchases more than 30 days before event occurs)
Tagged as multi-purchase buyer (generally buys more than one event per season)
Persona B
Tagged as last minute buyer (generally purchases within 48hrs of an event)
Tagged as value driven buyer (typically buys seats at lowest price points available)
Tagged as weekday buyer (typically buys weekday events)
As you can see these customers are very different. Tailoring messaging and nurturing them accordingly will drive meaningful revenues and result in major improvements to your retention of individual event buyers in your database. (Did you know that with the StellarAlgo data platform you have this capability?)
Targeting Specific Event Sales
This can be the most stressful part of the year and can really derail an organization during an already busy season. The manual work often required to segment a database often forces organizations to launch broad email campaigns that hurt the engagement of fans as much or more than they actually help with event sales. This lack of visibility only heightens stress levels as the season progresses and events draw nearer.
With access to automated data and segmentation tools, you have the ability to quickly pull segments of fans that align with your events and sleep easy knowing that you are taking the right steps to market events to relevant fans. Here is an example to help you on your way.
Example – “I have a Friday night event, it’s two weeks away but I thought it would be selling better at this point. I still have some really great inventory in prime locations that would have a material impact on my revenues”
Sample Fan Attributes/ Tags to Pull: Event Tag: Weekend event buyer Season Cycle Tag: Early-Season buyer (or blank) Price Level Tag: Premium Distance Tag: 0 – 20 miles from stadium Product Type Buyer: Individual
Sample List Summary Metrics: Sample Cohort Size: 3,750 Expected Total Conversion: 7.0% Expected Conversion for Target Event: 4.0% Ticket Sold Estimate: 338 tickets
Saving and tracking the cohort allow you to unearth which customer attributes were common around those that bought and how closely the estimates matched reality. The converting attributes may be different than the ones you expected and this can help inform future list pulls! Try…learn…and improve your targeting over time.
Knowing the above makes it pretty easy to tailor a message to this particular group of fans. You change the attributes around in order to get a cohort size you know will lead to the needed number of conversions.
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