Numbers That Count - Part Four
Financial models designed in excel are lies.
Polite lies, ones that feel clean and comfortable.
We can base our models on economics; on ideas like “Perfect Competition” and “Rational Customers”.
Unfortunately, these don’t exist in the real world.
To build models that are grounded in truth, we need to thoroughly understand our real world customers, even if their behaviour seems illogical and frustrating.
Here are some good ways of thinking about customer behaviour:
Churn Rate = How quickly our customers leave.
It’s easy to measure sales, but that doesn’t tell us if we’re selling to new customers or to our regulars. If we had 2,000 subscribers last year, and 2,000 this year, how many people in total have used our service in the last 12 months?
What does it tell you if customers leave quickly?
“We get about 1,500 likes per post, but these aren’t the same group each time. We have quite a high churn rate, which influences the style of post we create in a typical month”
“Our growth is low but so is our churn. Once they sign up, they’re with us for a while”
Basket Size = How much our customers buy at a time.
When I worked at IGA, I noticed that almost no customers used a trolley. Shoppers basket size was literally a basket-size; enough to fit in Doritos, milk and beer. If you wanted to do a larger shop, you’d go to Coles. Similarly, very few people go to a Mazda dealership to buy two cars at once.
“Our customers tend to prefer a monthly payment rather than a cheaper annual payment”
“People tend to order more than one book at a time from our website, that’s why we use algorithms to create automated recommendations”
“The typical customer orders one drink and one donut”
“Readers tend to stay on the site for between 2 and 5 minutes, that’s how much time they’ve allocated to their research before they move on”
Order Velocity = How quickly someone comes back. Instead of categorising customers as “repeat”, we can gauge whether they come back twice or ten times in a year. This is an important distinction, and it influences how we prompt a repeat order.
“Most people who buy a new car don’t want to think about cars again for at least three years – that’s when we re-establish contact”
“If a user has a good experience, they tend to return to the app within 7 days. If their account is inactive for more than two months, they’ll probably never return”
Size of Wallet = How much money a customer has available to solve a particular problem. We can experiment with premium value propositions, but if customers can’t afford them then it means nothing.
“We know our customers can afford a $20,000 car, but not a $30,000 one. That’s shaped our pricing strategy, we’ll try to push them from 21 to 24, or 25 to 28, but 32 is off the table”
“Our customers have to go to tender for anything over $5,000. That’s why we set our services at $4,999”
“Melbournians just aren’t ready to pay more than $5 for a latte”
These metrics, when put together, give us a clear picture about how each customer segment makes purchase decisions.
This should influence our marketing – targeting customers who are contemplating a repeat purchase.
It influences our pricing – designing price points that will give us some margin, whilst also being realistic for our customers.
It influences our sales projections – estimating how many times in a year each customer comes back, and how much they buy each time.
It also tells us about the difference between customers who like us and those who love us, by comparing Net Promoter Score with the frequency and size of purchase.
Whatever your industry, it’s worth measuring your sales in detail: it keeps you in touch with the market, and will help boost your income.
More money, more impact, fewer headaches.
This is a four-part series on useful financial metrics.
You can jump straight to:
Part One Introduction, Margins and Breakevens
Part Two Market Sizing and Forecasting Sales
Part Three Customer Value, Acquisition and Retention