Q/A with Ryan Stout at Summit Professional Education
Our overall goal was to obtain day-of product performance in a high-volume setting. In producing thousands of live events each year, all driven by a direct mail/direct response model, Summit has a predictable response pattern. This pattern is a non-linear response curve that is difficult to calculate for team members on-the-fly, especially in our high-volume setting. Knowing how well a product is performing right now, based on known averages, vastly improves on-the-fly go/no-go, marketing, and development decisions (the quicker a decision is made the better!).
How were you getting the necessary information prior to using Informer?
Prior to Informer, this analysis was always performed post-event or at the end of a product cycle and only meaningful on a large sample size. Breaking down on to a product level was simply too tedious a task to do on a regular basis. Microsoft Excel provided the necessary calculation support but instantly registration data became stale and out-of-date.
How did Informer help you to address these challenges?
Using Informer, we’re able to pull in marketing data and apply our target performance rate(s) for all upcoming products in one, very quick report. In the same report, by using Informer’s JS handling, calculated columns figure where each product is in relation to our known response curve — by calculating the percentage of registrations that should have occurred as of “today.” With this information, Informer is able to show us how far ahead or behind a product is compared to where our averages place it; and do so dynamically whenever running the report. We’ve also added in calculations for “last week” and a increase/decrease column to help spot the movers and shakers. Hiding the complex calculations in the background of Informer allows for a simple 6-8 column report that shows the important above metrics. They’re easy to read and understand for all team members during review settings.
What features of Informer were particularly useful?
What organizational benefit did you realize by using this approach?
Watching product performance rise and fall daily produces much quicker decisions and product analysis. Due to our production and direct mail timeline, decisions must be made before we have final registration data available. In the past this has been a best-guess situation. Now, we’re able to adjust marketing or products mid-stream, rather than waste valuable time waiting on final data. Essentially we now have more confidence in on-the-fly adjustments as they are backed by live data.
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