The typical North American sports team has a CRM with hundreds of thousands of contact records. Teams looking to target their “best” prospects have been leveraging various lead scoring tools and methodologies for decades. They have made major cash investments into these systems which, in theory, should provide these sales teams with some real efficiencies.
However, most teams have begun to realize that many of these tools aren’t delivering the efficiencies that should be obvious impacts of their investments. Many teams are looking for new tools. Others are bringing their lead scoring efforts entirely in-house.
piLYTIX has identified 3 core characteristics of disappointing lead scoring approaches. Sales leaders who understand why these tools have historically failed to drive expected results will be prepared to source more reliable tools and will have confidence in the output.
#1 Pre-Defined Categories
A typical sports team’s CRM may have dozens of data points on each prospect relating to:
Demographic Attributes: Being something…rich, poor, old, young, nearby, far away.
Behavioral Attributes: Doing something…buying tickets, inbound inquiries, email opens, website visits.
Account Attributes: B2B vs. B2C, Business size, Business location
However, most lead scoring methodologies arbitrarily pre-select a small handful of these factors and jam all contacts through the same machinery that spits out a singular number which is supposed to help sales leaders decide which contacts are good leads and which contacts are not.
If this sounds like a reasonable approach, ask yourself the following questions:
Does your team track the exact same data as all other teams?
Does your prospect universe identically mirror the prospect universe of any other team?
Do you have the same sales resources and capabilities that any other team has?
Of course not! There may be high-level similarities, but an approach that pre-selects certain data fields to score prospects – without regard to your specific team’s data – is designed to ignore the nuances of your team, your market, and the purchase pattern of your prospects.
#2 Everything Changes….Except Lead Scores
People change. Situations change. Everything in life changes. Except, it seems, many teams’ lead scores.
Most teams update their lead scores very infrequently. Once a year or less, in many cases.
To illustrate the opportunity cost of static lead scores, consider the following example:
John Smith, a fictional sales prospect for the fictional Isotopes baseball club, has the following contact attributes:
· Previous Purchase History: Has never purchased from the team
· Credit Score: 335 (Very Low)
· Email: Has never opened an email from the team
· Website: Has never visited the team’s website
· Previous Sales Activity: Told a sales rep “no” last year
· Lives 75 miles away
Now let’s say that the team ran its annual lead scoring exercise and some combination of these factors resulted in a low lead score for John Smith. However, the day after the scores were processed, John bought four tickets for the next home game. The day after the game, John opened an email from the team and clicked on links that took him to a page on your website that discusses partial season ticket packages and their prices.
Its probably a safe bet that John is a better prospect on Day 3 than he was on the day that the lead scores were run. However, a static lead score won’t reflect John’s improved buying profile. An organization that puts significant value in these lead scores may overlook a sales prospect who is doing everything short of standing outside the stadium with a bullhorn and yelling “CALL ME!!” Further, John’s interests may be diverted by the time the scores are recalculated next year.
By ignoring the fan who was in the right place at the right time, the team likely missed a great first sales opportunity and any potential of developing a lifelong patron.
#3 One Size Fits All:
Broke college students tend not to purchase courtside season ticket packages. Multibillion-dollar corporations tend not to buy nosebleeds. However, most lead scoring models jam every contact into a single lead scoring model that boils every prospect down to a single number.
See a problem here?
Failing to consider meaningful differences in the buying populations of different products results in less reliable lead scores. This is a costly mistake; Instead of achieving sales targets with smaller prospect pools, team have to expand their prospect pools. The only way to effectively communicate with a larger-than-necessary prospect pool is with a larger-than-necessary sales and marketing team. piLYTIX Sports has written extensively about the excessive costs that result from having too many salespeople. “We’ve Hired Too Many Salespeople!”
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