Using customer lifetime value (CLV) for ecommerce success
Learn the metrics that matter, and how to apply them to your company to increase conversions and revenue.
Learn the metrics that matter, and how to apply them to your company to increase conversions and revenue.
30-second summary:
Exponea is a customer data and experience platform with predictive analytics capabilities. They work with many notable online retailers including Sofology, FitFlop, and Benefit. Exponea’s recently published white paper, “The Formula for E-Commerce Success,” highlights the role of customer lifetime value (CLV) in keeping acquisition costs down and improving overall ecommerce success.
The 38-page report provides a simple formula that retailers can use to determine CLV, focuses on why this metric is important for growth and customer retention, and provides an ecommerce optimization guide which drills down into the specific ways that retailers can improve customer retention and conversions.
Content produced in collaboration with Exponea.
Customer lifetime value represents a customer’s value to a company over a period of time.
The formula for determining the lifetime value of a customer is simple: average annual customer profit multiplied by average duration of customer retention.
Simply put, focusing on CLV as a topline metric has a significant impact on a company’s bottom line. Despite this, one UK study found that only 34% of marketers surveyed were aware of the term “customer lifetime value” and its implications.
Here are four ways CLV can be useful for marketers.
A key challenge that many companies face when assessing CLV is siloed or fragmented data. This can be a symptom of rapid company growth, complex technology stacks, or even a reflection of internal company culture—if each department operates independently toward certain goals, data can become fractured.
Exponea writes, “without unified customer profile data, it’s nearly impossible to get the sort of actionable results you want. In order to make use of the wealth of data that’s been collected, you need a CLV model that utilizes machine learning methods to make predictions. And that’s just not possible with siloed data.”
Data fragmentation is exacerbated by the fact that today’s customer makes purchases on multiple devices. This makes it difficult to glean meaningful insights from the various data streams. The use of a main dashboard which synthesizes data from multiple sources (i.e. a customer data platform) is critical for retailers who don’t want to be left behind compared with industry leaders who are taking a forward-thinking approach to data unification and analysis.
Another issue that companies face regarding data management and unification is a lack of in-house expertise.
Per Exponea, “Many companies who have not yet begun tracking CLV are dealing with a lack of qualified personnel to follow the data and produce actionable plans based on it. This, coupled with the need for an in-house dashboard for qualified personnel to use, creates a strong barrier to entry.”
Once a company has addressed the above issues — namely, all customer data is in one place, you have a main dashboard with predictive analytics capabilities to synthesize and communicate this data, and experienced personnel to monitor everything — you can move on to leveraging CLV.
CLV can be used to:
The report concludes with some concrete steps that retailers can take to optimize conversions and increase a customer’s CLV. This section is extremely tactical, emphasizing customer retention over customer acquisition.
Exponea writes, “It’s not just about selling anymore; it’s about building a place for your customers to return to, again and again. Convert your first-time purchasers into repeat shoppers, and move them along the path to VIP.”
The ecommerce optimization guide provides details on four technological tactics that online retailers must focus on to improve customer retention. At the top of the list? Personalization.
The four tactics include:
Says Exponea, “As AI becomes more rooted in ecommerce, the gap between the capabilities of retailers utilizing AI vs those without it will grow too wide for a company without AI to stay competitive.”
There is much more information available in the e-book, including tactics focused on improving authenticity (and integrity) in communication between the retailer and the customer. Examples of authenticity include what to do—and what not to do. “Write openly and conversationally; address your customers like living, breathing people, and you’ll keep them coming back,” explains Exponea.
To learn more about how marketers can use CLV, check out the full white paper, The Formula for E-Commerce Success.