How to increase the Customer Lifetime Value of your customer base and avoid the most common pitfalls

Guest post written by Henrik Hoffman, co-founder of DEMA, a platform for prescriptive analytics in e-commerce.

What does "Value" stand for in Customer Lifetime Value?

You are probably already well acquainted with the importance of Customer Lifetime Value (CLV). But there is one important point that is easily missed with CLV/LTV/CLTV (however you want to shorten it). “Value” is too often in these predictive models the same as future revenue from these customers. But value should reasonably have something to do with the profit that these customers are expected to result in. This is often referred to by Swedes as Gross Profit 2 (all costs that the orders and returns result in, but not the marketing cost). Dema.ai’s CLV model is a prediction model that tries to forecast just that: the future actual value of the customer, not just the sales expected to come thanks to that customer. This is of course crucial for a business that wants/needs to grow its profitability.

CRM vs Analysis tools

As a former “CRM’er”, I also think it is important to distinguish between CRM as in a communication tool for e-retailers to reach their customers and a full-scale analytics tool. Today I am building a full-scale analytics tool so I may be biased, but what I have always expected from CRM tools is that they should be extremely effective around customer communicationHowever, I usually do the analysis outside, except on the basic CRM parts like Open Rate, Click Through Rate and more. To really optimize CLV you need to use pure analytics tools to understand the combination of customers, products, marketing, costs, etc. CRM is execution – the analysis shows what actually works and should help you understand what should work and what should be tested.

The basics:

Segmentation and analytics: Analyze CLV and other more advanced non-CRM

CLV starts with customer acquisition: Focus a lot on attracting the right customers with a high CLV.

Test – measure – test – measure: Regular evaluation of CLV, and how to successfully influence a previously lower CLV.

We all know that it’s easy to stare at numbers and almost become apathetic. Don’t fall into that trap, but force yourself to experiment at a high pace with a few KPIs that you follow. If analysis is not your strong point, ask a colleague for help or ask around others in the industry – people tend to be very helpful.

How a premium
e-commerce brand can use Rule + analytics via Dema

Many successful premium e-retailers combine analytics and execution to maximize customer lifetime value. A common approach is to use Rule to automate flows and ensure the right message reaches customers at the right time – and Dema to understand what content to push in newsletters in addition to brand campaigns and product launches.

By analyzing historical sales patterns, inventory levels, order profitability and projected sales velocity, products that need increased demand in specific markets are identified. These insights are then used to create relevant segments in Rule and reach the customers expected to be most interested.

Rule is used to manage and evaluate the ‘off-site’ performance of CRM efforts, such as open rate, click-through rate and audience segmentation. Dema is then used to analyze the on-site performance, including visits, orders and revenue – as well as which products attracted the most interest after being included in a specific newsletter.

5 concrete tips to increase the value of your customer base

Analyze first order profitability: Start by analyzing the correlation of CLV with a bunch of key factors on the first order; such as countries, product categories, sizes and discount level/vouchers etc. The insights here always need to be shared upwards in the organization, this often leads to a lot of changes in companies that have not done this analysis before. This can involve strategic changes to product range, market focus, etc.

Optimize customer acquisition based on CLV: Use the insights of the analysis above and create small hypotheses you can test directly. Both on the existing customer base to improve the outcome against expectation but also the marketing as mentioned earlier.

Evaluate the impact of CRM interventions: Find out which actions actually improve or worsen previously calculated CLV. What happens when you offer discounts to specific segments? Does it positively or negatively affect the long-term value of the customer? How does the customer base react to more personalized and relevant communication? Understanding the impact of your CRM efforts will help you optimize for long-term profitability.

Optimize for retention and repurchase: Create flows that are automatically triggered to bring customers back at the right time. For example, use loyalty programs or offers that match the customer’s previous purchases.

Engage inactive customers: Identify customers who are not reached by your CRM flows and create strategies to re-engage them, for example through retargeting or other channels such as SMS and push notifications.