Home Business & Management Customer Lifetime Value(CLV): A prediction of the Net Profit

# Customer Lifetime Value(CLV): A prediction of the Net Profit

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Simply put, Customer Lifetime Value is the estimated spending that a customer does in your business over time. For the CLV metrics, they consider a customer’s total revenue value and compare it with the customer’s predicted lifespan.

Based on the current stage of a customer, you will be able to calculate a customer’s monetary value for your organization, and there you can accordingly plan how much can you spend in acquiring a new customer.

For example, say you googled a certain book. Now the e-commerce companies started showing you ads of the same book on various platforms. But the fact is that by selling that book they would have a small profit only. Still, they are spending heavily on showing you ads (Cost of ads > profit on that book).

Why do you think are they doing this? The simple logic is that they have calculated your CLV. They suppose that after buying ones from them, you are more likely to come back on their website again and again to buy more stuff. And thus they will have an overall profit from you in the long run.

What’s in it for me?

## How important is CLV?

By determining the CLV of your customer, you can take a calculated decision in your business. They say that 80% of your business comes from nearly 20% of your customers. So it is a big deal to acquire long term customers.

• How much to spend on acquiring new customers?
• How much to spend on retaining old customers?
• Which marketing channels can you use based on the amount you can spend on different customers.
• The segment of customers who are worth pursuing and at what cost?
• How to maintain a good relationship with high CLV customers? Maybe send them offers, early access, special discounts, etc.
• How to increase the up-sell of a current customer? So that the average value spent by them on a transaction increases.
• How to reduce churn rate(rate at which customer stops doing business with you)?

Let’s talk some maths!

CLV = Average purchase value * Total items customer will buy every year * Average customer relationship length(in years)

Suppose you own a T-Shirt store. And a customer buys 5 T-Shirts from you every year. And the average cost of the T-Shirt is Rs. 500. And he is your customer for the next 7 years.

So for your T-Shirt store, this customer is worth:

500*5*7 = Rs. 17500.

And, there is another customer, who buys 5 T-shirts for their child every year, for the next 2 years. The average cost of each T-Shirt is Rs. 200.

This parent would be worth:

200 * 5 * 2 = Rs. 2000.

Now you have a better picture of which customer is worth more attention. Surely in first guy in this case.

After calculating CLV, the most important step even before starting the marketing operations is to plan a business strategy, It helps in keeping the whole team focused towards the same goal.

## How to boost CLV?

According to past data by eConsultancy, current customers of your business are 60% – 70% more likely to buy from you rather than a new customer whose probability of buying is just 5% – 20%. Also, a study by Bain & Company suggests that just by increasing the customer retention rate by 5%, profit can be increased anywhere between 25% to 95%.

Thus it is a good idea to spend more resources on selling to an old customer than a new one. And to help you in this regard, these are some methods:

• Give rewards to your customer for doing repeat purchases that align with your customer needs. Ex: Cash backs, holiday trips, or whatever suits your type of business.
• Occasionally offer freebies, to build brand loyalty.
• Surprise them sometimes by giving unexpected gifts on certain purchases.
• If you are a business that delivers them a certain product. Keep them updated about the route the parcel is going through.
Also the delivery date they can expect their product on. Delivering their product before the promised date always adds an element of surprise to it, which gives them a positive signal about your company. So make use of such instances.
• Make the return process easy for the customer. This is a big let down for a customer if they don’t get the right support from your side at such times.
• Use upsell techniques. It increases the average money spent on a transaction. A good example which you must have experienced yourself would be when the billing staff at KFC asked if you want french fries with your order.
• Stay in touch with the customer may be via emails or messages so that they recall your brand. Also, make it easy and quick for them to access you. For example, a one-click link to your product page.

According to HubSpot, 55% of growing businesses invest in customer service programs. Whereas in the stagnant or declining companies only 29% said it is important to do something like that.

Any company that is actively working towards customer’s success automatically projects more revenue, and the reason being increased customer satisfaction. A satisfied customer is both, a long-term customer and a brand advocate.

Thus we can say that all the above points basically boils down to keeping the customer happy and satisfied with your service.

I would like to conclude by saying that CLV is based on past data. We can’t really predict if and when will the customer buy again. A business that is working for 5 months will obviously have a poor idea of there CLV compared to a company doing business since say 5 years.

Thus a new company should focus even more on customer retention to get this data quickly. Meanwhile, if you can get hold of some other old company’s’ data who are working for many years in the same niche as you.

## FAQs

Can Customer Lifetime Value(CLV) be negative?

Yes, there are situations when your overall expenditure on a customer is more then how much profit you make from them. In such cases either you should decrease the expenditure or totally stop selling to them.

Formula to calculate Customer Lifetime Value?

CLV = Average purchase value * Total items customer will buy every year * Average customer relationship length(in years)
I have explained it in the blog with examples.