How hospitality operators can use data to reveal loyal customers

Your loyal customers are already in the data. Here's how to find them and what to do next.

Your loyal customer base shouldn't be a gut feeling. You can and should put a real number on it, and you don't need new tools to do it: the data is already sitting in your systems.

Here's how to go from vague suspicion to a concrete count.

Where loyalty data comes from

Plenty of in-venue and online sources tell you who keeps coming back:

• Wi-Fi logins from your guest Wi-Fi

• Interactions with your loyalty scheme

• Bookings made through your booking system

• Transactions from your POS

• Purchases from your ecommerce store

What you want from all of them is the same thing: how many interactions each customer had over a given period.

Segment to spot your regulars

Segmenting the data reveals the behaviours behind loyalty. You're looking for patterns:

• How much do they spend on average, in the venue or online

• How often do they visit or book over a period

• How engaged are they with your loyalty scheme, for example stamps collected or points frequency

• How often do they book special events

Patterns turn into trends, and trends turn into action. Say you notice bookings per month drop off after a guest's third visit. Set up an automated email for exactly those people: feature a few venue highlights and invite them back before the habit fades.

The retention cohort report

For a hard percentage of customers who returned over a period, build a retention cohort report. Before you fire up a spreadsheet, check your analytics first: a lot of hospitality and ecommerce software generates one automatically as part of its reporting.

These reports look complicated and read simply. The example below shows monthly cohorts.

The left column is the monthly time interval. The top row is the number of subsequent visits. The chart starts with the first visit: the total number of customers in that month, which is your reference number from then on. Reading left to right, you see how many of those customers reached each level of return visit.

Each column is a separate cohort, a group of customers who share one trait: their number of return visits. A customer sits in exactly one cohort at a time, so there's no overlap and no double counting.

What to do with it

Build segments from your cohorts and write to each one properly. Someone who has visited ten times expects a different message from someone who has visited twice, and now you can tell them apart.

Stop guessing and start measuring. Your next campaign should start from a cohort, not a hunch.