How Good Data Collection Can Help You Identify and Refine Admissions Practices
If anyone reading this is looking for a lullaby to put their kids to sleep, skip the Dr. Seuss (too interesting) and instead try talking to them about the importance of data collection for refining businesses processes. It’s a guaranteed formula to put young and old to sleep. But fight off those Zzzzs, my friends, because we’re about to show you why good data collection processes can give you important insight into process problems and help your admissions team increase the conversion rate of inquiries.
TRANSFER RATES, CONVERSION RATES, AND DATA COLLECTION
Let’s start with some basic definitions. When I say “transfer” I’m talking about the successful transfer of an inquiry from a school-managed call center to a school’s admissions team so they can work their magic. For example, a potential student fills out an inquiry form and that inquiry makes it to the admissions staff AND you have a record to show that it happened. A non-transfer is either an inquiry that was not transferred to a school’s admissions team OR an inquiry that was transferred but with no record of the transfer recorded. For schools using a call center, it is no secret that a successful transfer is the first step for a student to begin their quest for a diploma or degree. The data in the graph below shows just how much of a difference the workings of schools’ admissions teams have on enrollment and start figures.
However, take into account that not all transfers are classified as such. In other words, evaluating metrics like those included in the above graph have a lot to do with data collection and storage. Although the example above, which is for five schools from Q1 and Q2 of 2012, illustrates largely accurate data, it is clear that non-transfer data does result in converting inquiries most likely because data is not being classified correctly. Schools should be aware that evaluating inquiry sources and their performance is increasingly difficult when data is not classified and/or stored correctly and can result in failed objectives and marketing spend that is not being optimized. Good data is like good directions. It’s hard to figure out exactly where to go without it.
TRANSFER TIME OF DAY AND CONVERSION RATES
Phew! Okay, now that we got that out of the way, let’s move on to the fun stuff. Transfers and conversions clearly correlate with one another. But when we take a close look at how time of day relates to inquiry transfers and conversion rates, we can begin drawing some interesting conclusions about business practices that can be refined to improve conversion rates. The same five schools were once again analyzed for the first and second quarters of 2012, and the following chart illustrates how conversion percentages play out over the course of a day.
For all five schools, conversion rates vary considerably throughout the course of the day. But for the most part, the morning hours appear to be the most productive time of day when successful transfers result in a conversion. As the day progresses, conversion rates tend to decrease but the data clearly shows a lack of overall pattern across schools. Could this have to do with different admissions policies at schools? Do conversions slow after some of the admissions staff has gone home for the day? The chart below shows that the total number of transfers, however, does follow the same pattern. (Note: School A is not illustrated in the chart below due to volume differences from the other schools)
Although total transfers decreases as the day progresses, the decrease is gradual. Unlike the chart depicting transfer hour of day and conversion rates, this chart has a much more consistent pattern, which could point to a couple of things:
- Potential students may become harder to contact towards the end of the day
- There may be less admissions staff working toward the end of the day
- Potentially, some other admissions staff policy may be in play here
While there’s not a lot that can be done about the first potential problem, the second and third are things that can be affected by refining business practices to increase productivity. This data doesn’t conclusively tell us what the issue is, but it gives us a place to start investigating to increase efficiency. I know this was probably a lot to slog through, but I hope it gave you an idea about how good data collection can have a significant impact on improving internal business practices. In my next post, we’re going to take the same type of analysis that we did here, but look what transfer and conversion rates, and day of week, can tell us about improving business practices.
This entry was posted on Tuesday, October 2nd, 2012 at 4:11 pm and is filed under Marketing Analysis, Transparency & Compliance. You can follow any responses to this entry through the RSS 2.0 feed. You can leave a response, or trackback from your own site.