How can you segment e-commerce customers based on their lifetime value?

Clients segmentation is crucial on the scaling stage ($100K+/mo.) for any e-commerce business involving such stages as Ascend (repeat sales), Advocate (loyal customers) and Promote (referrals). For example, on the Ascend stage using segmentation of loyal customers (3+ orders during a quarter) and regulars (2-3 orders) in Loyalty programs and Campaign emails will give higher Engagement and ROIs. On the Advocate stage with regulars we can make product launch input survey, and with loyal ones even customer interviews. On the Promote stage both loyal segments will be happy share their reviews socially for friends & family promo codes which will give free awareness and more new customers.

E-commerce customer segmentation based on Lifetime Value (LTV) is a game-changer in optimizing marketing efforts. Personally, I believe LTV segmentation is like having a treasure map for your most valuable customers. It helps you navigate the vast customer landscape with precision. A practical tip: Start with the RFM model, which assesses Recency, Frequency, and Monetary Value. Assign scores to customers based on these factors and then categorize them into segments like high-value, loyal, at-risk, or lost. This provides actionable insights into each group's behavior and characteristics and empowers e-commerce businesses to make informed resource allocation decisions, making it a must-have strategy in today's competitive landscape.

By understanding what drives the variability in LTV by audience segment, you can assess how to capture more high value customers and where the oppportunity exists to migrate customers from low or mid LTV to high LTV. As the article suggests, a good starting point is RFM. From there digging deaper in the the source of the customers (paid media, SEM, social, affiliate/referral, etc.) along with purchase on promotional incentive vs full price will provide good direction for creating a test and learn matrix for meaningful, actionable segmentation. For a segment to be meaningful, there needs to be sufficient size and differentiation from the population while actionable depends on combination of response to stimulus and capability to execute.

Segment your customers into different tiers. Common segments are: High LTV Customers: These are your most valuable customers. They tend to buy often, spend more, and have a longer relationship with the brand- Focus on retention, personalized offers, loyalty programs, and upselling or cross-selling opportunities. Mid LTV Customers: These customers are valuable but may not have as frequent purchases or might spend less. Focus on increasing their purchase frequency or value. Personalized recommendations, incentives and continued delighters to move them to High LTV buckets. Low LTV Customers: These customers spend the least and may not have a long-term relationship with the brand.

It is easy to calculate a LTV when you have a subscription business, however most ecommerce websites are not subscription based and their definition of churn is an arbitrary line in the sand. In order to calculate LTV, you need to decide when the customer is considered churned and that is different for every website, niche, market, and business when you don't have a clear churn indicator (e.g. canceling subscription).

Don't forget to take into account the most frequently used channels, such as mobile, web, and in-store, when segmenting customers. This will allow for even more personalized targeting!

Remember data is the bedrock of customer segmentation. Using a unified customer data platform with which you can collect data in various formats ranging from - zero party - 1 party (behavioral data) - 3 party enrichment - order and purchase data gives you a better 360 view of your customers. These form the bedrock of how to make segments that are native and unique to your own business and category. Look at investing in your data science teams with collaborative notebook solutions that allow you to discover segments and surface insights across the entire organization. Modern notebook tools like Hex & Observable can really accelerate your data workflows.

One of the best tools for LTV is emails, so we use Klaviyo with welcome flow, abandoned card flow with promo-codes and sales. For SMS we use SMS Bump that works really good in America and Europe (same welcome and abandoned flows). Also, subscription tools work really good for products, which people buy every month (it can give up to 40-45% of all monthly revenue sometimes). And Family and Friends (F&F) promo codes also work really nice as referrals

In the modern commerce landscape, dozens of tools can help segment customer data. Large brands typically use a CRM or DXP in their tech stack to facilitate this. Instead of recommending specific tools, I recommend that someone looking to incorporate a CRM or DXP into their tech stack find a trusted partner agency interested in helping them grow. Find an agency that wants to look at your business and provide recommendations based on what is best for your use case; avoid agencies that appear more interested in recommending what works best for themselves.

What I can say from my side is that what we've noticed is that segmentation is not necessary if you are at the product-market fit or even growth stage (less than $100K+ mo. revenue). You can use just simple welcome and abandoned card flows to increase E-commerce CVR and AOV and grow with 1 or 2 traffic channels (like Facebook and Google). When you achieve at least $250K+ mo. revenue and have enough data for statistical significance you can start working with optimisation and conversations. Right actions at the right time give the best results.

Remember segmentation is only half the battle. A good segmentation strategy relies on good data collection infrastructure. Remember to keep your segments fresh by updating them based on fresh data. Utilize segments for building out personalized store experiences, product offerings, and marketing communications. Make your segments easily accessible with narratives and behaviors that are easily actionable for your team. Continuously measure the effectiveness of your segmentation strategy by looking at metrics like CVR, AOV and repeat purchase rates. Segmentation is not a goal in itself, it forms the building block for delivering exceptional consumer experience. This is what truly drives lifetime value up.