Putting a Price on CLV

CLV helps marketers estimate how much to invest to retain a customer. But how do you calculate it? 

American companies have been overlooking the value of customer retention rates. Every year, they lose $83 billion on average because of bad customer retention strategies. The lack of customer retention naturally hampers their lifetime value to the company. 

Customer lifetime value (CLV) helps a firm predict revenue and measure long-term business success. It can also measure the amount of profit your company can expect from a typical consumer till the time s/he is availing of your services. 

CLV also helps you estimate how much you should invest in retaining a customer. After all, the chance of selling services to an existing customer is greater (60%-70%) than selling them to an entirely new consumer (5%-20%). 

Since CLV is a financial projection, businesses are expected to make informed calculations about the average sale value, average number of transactions, and the duration of the business relationship with a given customer. Companies with historical data on customers can calculate their customer lifetime value more accurately.

Historical customer lifetime value

This model uses historical data to forecast CLV without considering if the consumer will have a relationship with the company. In this model, the average order value is used to determine the value of your customers. This model is useful if your customers restrict interaction with you for a limited time. 

For instance, the average CLV for Starbucks is $25,272. It was calculated by estimating how much a customer spends on the average per visit ($5) and the number of visits made by customers every week. Then, the customer’s average lifetime at the cafe chain was pegged at 20 years through data collected. These values are calculated together to determine the average CLV. 

However, this model has disadvantages since not all customer journeys are identical. If active customers stop interacting with your business, it can skew your data. And you might overlook inactive customers who have started buying again due to their dormant status.

Predictive customer lifetime value

The model predicts buying behavior of new and existing customers using machine learning. The predictive model can help a business identify its most valuable customers, the product or service that brings in the most sales, and how you can improve customer retention. 

Netflix is a good example of how CLV can be calculated through a predictive model. In 2007, the streaming giant found out that a subscriber availed their services for a little above two years and that their CLV was 

$291.25. This helped them predict that their consumers were impatient for new content. After analyzing data, Netflix implemented online streaming. This kept its members engaged and improved the retention rate by 4%. 

Factors that increase the customer lifetime value

Optimized onboarding process

You can familiarize them with your brand through customer onboarding — what you do, why it matters, and why they should stick around. Onboarding takes place as soon as consumers make their first purchase. When they return to your website to look for more products or inquire through some channel, they learn about your company. This customer data can be used to offer curated items. This can be followed up to check if customer expectations have been met. The tailored onboarding system works because it fosters long-term customer relationships that help increase CLV.

Increasing average order value

Even a slight increase in the average order value leads to increased CLV and a rise in revenue. The average order value can be increased by offering complementary products to a consumer at checkout. McDonald’s is a great instance of cross-selling – that suggests tempting add-ons to meals while billing. While adding a $0.5 or $1 may not seem a lot, multiple such transactions – depending on the largesse of your company – can add to the revenue and help increase CLV.

Listening to customers

To improve CLV, it is imperative to listen to what the customers say. This could be done by creating polls about new products or service ideas to see what the customers think. However, ensure that you do not restrict their choices. Give them ample space so that they can add their ideas. Also, it is essential to credit a customer for their idea by sending them a token of appreciation. This technique works because they will associate with the business longer when customers feel heard.

Easy connections are the way to go

Customers do not like waiting around for a business to respond to their queries. Thus, it is prudent for companies to shorten their response times. This could be achieved through active social media; a team could monitor and respond to customer comments or concerns. This way, brands can kickstart the connections with customers.

Ameliorated customer service

Around 90% of consumers worldwide say that issue resolution is their most crucial customer service concern. To cater to these needs, a business must offer personalized services to consumers, omnichannel customer support, and a proper return or refund policy. The better the customer service, the more customers feel valued by your brand for more than their purchases. If you back your products with return and refund policies, it communicates to customers that you prioritize quality and satisfaction. It results in increased CLV.

Conclusion

CLV can help a business find a balance between how much to invest in retaining their existing customers and acquiring new ones. It has been found that when you increase your customer retention rate by only 5% –by employing several techniques to increase their lifetime value – it could lead to an increase in profits between 25% to 95%. 

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