Archives for posts with tag: Customers

I’m sure I’ve written before about US strip malls and the fact that staff park their cars in the furthest away spots to allow their paying customers to take the most adjacent spots. It simple, thoughtful and common sense practice.

You don’t see so much of it in Europe in my experience. Staff seem to get priority. That cosy consultant’s parking space at the front of the hospital. How come they get that? Surely it should be for the nurses or the midwives who do most of the bloody work, no pun intended. Or perhaps, revolutionary thought, the patients, who have to pay to park in the next parish.

Anyway, I was waiting in the car park for my 9 o’clock doctor’s appointment the other day to rid myself of a pesky chesty cough that I didn’t want advancing to a chesty infection. I was 8 minutes early and so people watched from the comfort of my car. By 8:58, the car park was full, since staff had used up both the car park and the spaces behind the surgery which are supposed to be for staff only. There simply aren’t anywhere near enough spaces for both staff and paying patients.

Who has to to park on the curb? The paying patient of course, who in this country funds the vast majority of the salary of the attending staff.

Madness, I tell you. If I ruled the world, or at least administered some of it…

Advertisements

I was asked the other day what the average SaaS customer length is. I responded confidently that I thought it was about three-and-a-half years. My customer disagreed, though not without some uncertainty, and felt it was longer.

So I checked online, as you do, and I couldn’t find my three-and-a-half years statistic anywhere. Perhaps it was a customer I’d worked with previously that I was misremembering as an average. Anyway, I couldn’t find an average figure for customer churn anywhere. That’s because it depends.

It depends, of course, on the amount of customers you lose, otherwise known as your churn rate. Your average SaaS customer length is 1 divided by your churn rate. So if your churn rate is 5% per month, your average customer length is 20 months, which isn’t great. If it’s 10% per year, then your average SaaS customer length is 10 years, which is a whole lot healthier. Naturally, you can only make these calculations with a good body of data and some history behind you.

If you’re new to the game, then you need to do some research around average churn for the sector you sell into, or the size of company you sell into. To generalise grossly, churn rates tend to be lower the larger the customer you work with, since the deals tend to be bigger, more complex, more embedded, with a higher cost of sale, to generalise on the reasons as well.

If you want to read more on this, you might find this article, this one and this one useful.

 

I was waiting for a colleague of mine a few Saturdays ago, in the lobby of the local credit union – which is a bit like a local community bank. When I got there there was no-one in the queue, and I had been in earlier, when business was very slow. Five minutes later there were 6 in the queue. Just my luck I thought, and it reminded me of the old adage about waiting for a bus and then three come at once – although I suspect that has more to do with bus drivers moving in packs because they can complete their route more quickly by alternating which bus picks up the poor punters at which stop.

Queuing theory is fascinating. The whole science of it fascinates me both as an observer and a not very patient queuer. Back in the day we would all queue for a specific teller, and it was always a trick as to which line to pick. These days you see banks employing one queue which then distributes to the next available teller, and you see it also in some parts of supermarkets, airport passport controls and retail outlets. But, then again, you still see situations where you queue for your teller of choice, like in, well, other parts of supermarkets, airport passport controls and retail outlets.

I remember doing a bit of queuing theory at college when I was doing my MBA. It involves quite a bit of calculus – a subject which always sends me thinking about the unbelievably clever soul centuries ago who invented those formulas in the first place.

I mentioned this to my colleague when he turned up. As it turned out, he had an even more nerdy interest in queueing theory than I did, and we then proceeded to debate the strategies of some retailers to offer fewer servers so that the longer queues deter people from revisiting, pushing them online, though it’s highly risky.

But, the fact that you can use mathematics to account for and plan around the sheer randomness of something like people turning up somewhere and queuing is amazing to me.

People settle at their own level, or certainly tend to, I think. It’s a question of fit. Partners, spouses, friends. You can’t pick family 99% of the time, unless of course you marry into it.

Companies are the same. You get the type of customers you deserve. You also get the suppliers you deserve, the staff you deserve, and – I would argue – the boss you deserve.

These are your just deserts. If you don’t like the profile of your customers, suppliers, staff, or boss, then you need to work hard to change it. This is really hard to do as an individual.

It boils down to culture. The collective values, ethics, atmosphere and ambitions of the place where you work govern the stakeholders you interact with, and the individuals within those stakeholders.

To change your just deserts, you need to work harder, smarter, better and more honestly. If you can’t do it where you are, perhaps you could move to somewhere where you don’t need to?