[VIDEO] Mathlete Mondays- Enhanced Pickup Analysis

In today’s lesson I’m going to show you how to become a pickup expert.  No, not that type of pickup…

When I was a Director of Revenue, one of the most common questions asked of me by my GM or owners was “what did we pick up yesterday?”  This question was particularly popular in times of transition or immediately after we had deployed a new strategy.  At first I took this question literally- compiling an Excel report listing the daily variances for the room nights and revenue on the books that provided little context into what was driving booking behavior.

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First thing each morning I’d run the pickup report and fire it off to my executive team with a quick synopsis.  And after spending the first 45 minutes of my day creating the pickup report and typing up my summary, my analysis was met with radio silence from my team.

With so much data available for them to digest, they were opting to hit the delete button on my email and continue on with their day.  And yet, they would continue to ask me what we picked up yesterday when they passed me in the hallway.

Now it took while before I realized that the team didn’t actually care about the specific rooms and rates we had picked up the day prior.  Rather, they were interested in learning whether our booking levels would allow us to achieve our goals and whether we were doing an adequate job of protecting our high demand dates.

As a result I began to approach my daily pickup reporting in a different manner, starting with a high level overview of the days where pickup was leading or lagging expectations before drilling down by market segment and rate code in order to analyze why.

In order to build a more actionable pickup report, I’d recommend starting at a high level while allowing yourself to quickly and easily drill down.  By breaking recent pickup down day by day, you can easily sort and filter in order to identify the days that are experiencing the largest pickup volumes.

Beyond looking at pickup over the prior day, I also prefer to analyze pickup over the prior 7 days and prior 30 days, as extending the horizon can often help to smooth out the data in order to allow you to understand whether any major variances are the result of a short-term anomaly or longer-term trend.  You may also want to sort and filter the segments included in the report in order to isolate the impact of group block entries.

If you want to get really nerdy with it, you can also add in the ability to sort and filter your report by reservation status.  I like to do this as it allows me to determine the impact of cancellations and re-bookings.  Oftentimes, particularly in urban markets where the rates may at times soften as we approach the arrival date, we’ll see that bookings remain relatively flat when we look at it from a net basis, but our revenue is changing considerably.  By looking at the detailed data and isolating net bookings from new bookings from cancellations, we can more easily identify customer booking behavior.

In addition to reviewing the production values for the current analysis period, it can be really useful to bring in the same time last year pickup data to use as a basis for comparison.  In doing so, you’ll want to offset the data by day of week to ensure you’re aligning a Sunday to a Sunday, for example.  There may also be instances where you want to customize your comparison period as well.  For example, perhaps you began offering an advanced purchase rate midway through the year, and want to determine whether it’s had any impact in lengthening your booking window. Adjusting your comparison period allows you to quickly and easily jump in and identify whether that’s the case.

Once you’ve had the opportunity to review the daily data in order to determine your most in-demand booking dates, I would recommend drilling down into the data further in order to identify the primary factors behind the increase in production.

I prefer to start with a high level breakdown by STR segment, before drilling down into the individual market segments and underlying rate codes.  This allows me to determine whether the strategies that we put in place have had the desired impact.

Once I’ve completed my pickup review, I can now send a more actionable synopsis to my team.  Rather than just simply tallying the number of reservations made for a given period in time, I’m now able to understand that perhaps we need to increase or decrease our prices for a few key dates 60 days in advance, or that our advanced purchase rate plan hasn’t picked up the way we thought it would and we may need to reconsider our offering and course correct.

I hope this Mathlete Monday lesson was useful for you.  For additional videos, please check out our YouTube channel.

At Focal, we’re keyed into helping our hotel partners improve their revenue optimization efforts by obtaining actionable insights more quickly.  If you have any questions, or are interested in discussing this subject further, please feel free to reach out to me directly at mike@focalrevenue.com or via telephone at 970.471.6722.

Thank you for joining me, and until next time—good luck outrunning the competition!

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