course in the organization’s e-newsletters.
In very little time, the association
had successfully created a targeted
list of potential attendees using
information it already had in its
database. The result: After approximately four weeks of targeted marketing, 17 of the course’s 25 slots
were filled with paid registrants.
algorithm, it looked at several different reports over the previous five-year period, including banquet event
orders; actual food and beverage
invoices; hotel pickup reports that
broke data down between singles
and doubles; registration reports featuring information about all attendees, including spouses and guests;
and optional event purchases showing the number of banquet tickets
that had been purchased.
The association discovered a relationship it thought would help it predict actual attendance, then took a
chance by guaranteeing meals for
that year’s banquet based on that
predictor. The result exceeded
expectations, as the predictor metric
came within one person of the actual
attendance and saved the association more than $10,000 that it
would have otherwise spent on gratuitous food and beverage costs.
3. Use Data to Reduce Your
Annual Meeting Costs
Because many hotels require that
guarantees be provided 72 hours
in advance — often before most
attendees have even arrived — accurately predicting food and beverage
costs for one’s annual meeting is a
challenge many organizations face.
At one such organization, guarantees for the final banquet were off
by more than 10 percent every year.
Because the event drew nearly 500
people and the hotel charged $200
per person, this translated into
$10,000 that could have otherwise
To avoid the unnecessary
expense, the association decided to
develop an algorithm that could be
used to predict actual attendance
based on existing data. To create the
Sara Cameron May, Ph.D., is principal with the
Cameron May Group and may be reached at (847)
837-9256 or email@example.com. Max G.
Moses is principal with Member Media and may be
reached at (312) 296-7864 or