Why you need clean data for your retention strategy
We've been fortunate enough to be involved in national retention reports for north America, for the UK, Australia and New Zealand and we've done some of those multiple times.
What always disappoints me is if we do a study of a million customers or we do a report based on a million customers or members that usually means we've had to throw away another million records because of the poor quality of data.
Club management systems are getting better but there's still always human error.
It's really really important if you want to make accurate decisions about your business using data, then you need to make sure that data is clean.
But what you need to do within your business is make sure any data you are collecting is clean and by clean what I mean is that numbers are actual numbers when they go into the system and they're not letters.
If you look on a keyboard on a traditional QWERTY keyboard, in the top right hand corner there is the letter 'O'.
Diagonally next to it is the figure zero.
The number of times people put an 'O' instead of a zero in a number sequence is ridiculous.
In fact, when I quote my cell phone number to people, it starts 'O' 7, 9, 5, 6. It doesn't because there is no 'O' number but people put the wrong numbers in. They don't put dates of birth in.
There are software systems where you can skip inputting the date of birth.
They are getting better but check because if you don't, the computer puts in 0 1, 0 1, 1900. Which when you work out the average age of your members, anyone who's not in there is that 116 years old.
So it skews your membership data.
You want clean accurate data all the time so you can run stuff.
Computers and machines can't read inaccurate data.
Get a really good membership system that allows you to accurately track your member behaviour by visit frequency, by age, by gender, secondary purchases, membership types. Check if you have a multi-site business or even a single site business that your membership types can only be coded one way.
By that I mean you can't have a membership that is 12 months single off peak and another one that's off peak single 12 months because it's the same thing but it's just been coded the opposite way round. When I go to look at that type of data, now I'm looking at two different types of membership, not one.
It's one in the way you sell it but you want to get it to be readable the same way.
