I remember it vividly. I was a freshly minted consultant. It was one of my first engagements. The client’s business was growing quickly, but at the end of every month, he barely had any money left.
So, I did an individual profit and lost statement for every single customer. I did some quick math and calculated the percent of each revenue dollar (at his current volume) that went to cover fixed costs, then applied the remainder of that dollar to the variable costs associated with each individual customer. Not a perfect methodology, but it worked well for quickly flushing out the problem. Eureka – the lightbulb moment. For every revenue dollar from the client’s biggest customer, he was breaking even (the reasons why are interesting, but that’s another story for another day). The more this giant customer spent, the more my client “broke even”. We applied the same methodology to every other customer and even found a couple that he went backward on for every dollar the customer spent.
I’m a strong proponent for a P/L for every customer. I realize it only makes sense in certain industries, but if it works in yours, you should do it.
That’s not the topic for this week’s One Year, Thirty Minute Challenge, but that type of math is at the heart of this week’s exercise.
In many industries, a company is upside down financially when they first begin a relationship with a customer. The costs associated with marketing, advertising, selling, onboarding and servicing the customer the first time exceed the revenue from the customer’s initial purchase. Hopefully, just a few purchases in, the company is right side up and making money. In the course of calculating the acquisition and onboarding costs, the company should be projecting and making customer experience decisions based on the potential lifetime value of the customer. Loyal, happy customers, depending on the industry, could represent a lifetime revenue stream of 1000s, 10000s or even 100000s of dollars. Happy customers tell their friends. That can translate into even more lucrative customers.
This week’s One Year, Thirty Minute Challenge is to identify the factors that constitute the lifetime customer value calculation for your products and services.
Let’s jump into this week’s exercise.
- What are the costs associated with acquiring a new customer? Depending on your industry, it could include annual marketing and advertising expenses (divided by the number of new customers each year), direct selling costs (lead generation, sales technology, sales salaries, sales commission), onboarding costs (customer training, installations services).
- What does the customer pay for the product?
- How many times will the customer buy the product? What is the range from the most sporadic customer to the most loyal customer?
- What does it cost to produce each copy of the product? Depending on your product or service, it will include cost of goods sold, plus additional costs for packaging and delivery.
- What does it cost to service already acquired customers? There might be customer service calls, technical support calls or costs for billing and collecting.
The math should look something like this –
Number of times purchased * purchase price
– number of times purchased * cost of goods sold (and additional costs)
– initial acquisition costs
– ongoing support costs
= total lifetime value
You’ll probably want to do some math that’s similar to what I did in my initial illustration to reduce the top line purchase price number to reflect the impact of fixed costs.
So, what do you do with this information once you have it? Here are some ideas –
- What are the primary drivers of purchase frequency? How can we move less frequent purchasers to more frequent purchasers allowing us to spread the acquisition cost over more units and consequently increase lifetime customer value?
- Can we draw any correlation between purchase frequency and acquisition costs or support costs? Does a more expensive acquisition equal a more frequent purchaser? If so, maybe the extra acquisition cost is desirable? Maybe there’s an inverse relationship between frequency and support cost – the more they use the product or service, the less they need support.
- If a customer is ready to defect, what can we do to save them? Is there any correlation between defecting customers and their use of support? Based on their potential lifetime customer value, what can we afford to spend to keep them?
- How can we leverage the personal networks of high total lifetime value customers to find more like them? They should be our best brand ambassadors.
- Since high total lifetime value customers have demonstrated a willingness to spend money with our company, are there other products or services that might be of interest to them?
Once you’ve completed your exercise, begin educating your team on the importance of lifetime customer value. The first time that new customer walks through the door could be the beginning of a long and profitable relationship. Treat the opportunity that way.