A Step-by-Step Guide to Grow Your Customer's Lifetime Value (LTV)

Introduction

We’ve seen this before. Every once in a while, some major catalyst drives customer acquisition cost (CAC) up. During the late 2010s, it was the influx of VC capital into brands like Casper and Allbirds that drove CPMs higher and higher. In the summer of 2021, it was iOS 14.5. And now, into 2023, it’s the macroeconomic environment driven by reduced consumer confidence and rising interest rates. When this happens, most brand founders and marketing leaders come up with two action items: 1) diversify channel mix and 2) improve customer lifetime value (LTV). It’s the basic e-commerce playbook that most operators know all too well.

Rather than a one-time focus when in dire need, focusing on increasing LTV continuously can drive step-function improvements in businesses that impact both the top and bottom lines. When I first joined Winc, a digitally-native winery, I was tasked with improving the LTV of the online wine club’s customers to help drive incremental profit from the 100K+ new subscribers that had joined through the pandemic. There, I developed a data-driven approach to continuously evaluate and improve LTV.

Before jumping into the approach and tactics, it’s important to note the two primary drivers determining the nature of LTV for any e-commerce business: product and business model. On the product side, consumable products (such as beverages and personal care products) will  typically have much higher repeat purchase rates than non-consumables (such as jewelry). In terms of business model, some businesses run on a subscription basis, some on a one-time purchase, and others on a combination of both. Focusing on LTV can be fruitful for all businesses, but will have the most impact on companies with consumable products that are meant to be purchased over and over again. Also, depending on your company’s business model, you’ll want to focus on certain tactics over others. Keep your business model and product profile in mind as you determine your LTV strategy and roadmap.

Breakdown of LTV

LTV can be broken down into actionable components that make it easier to develop initiatives against. LTV is:

‍

• # of Orders: The total number of purchases made by a customer throughout his lifecycle with a company. 
• Average Order Value (AOV): AOV refers to the average amount of money a customer spends each time they purchase from your e-commerce store. 
• Gross Margin: Refers to the profit % a company makes on each sale after subtracting the cost of goods sold

It’s also crucial to measure LTV in a time-bound way. LTV earlier in a customer’s journey is significantly more valuable than future LTV because it helps improve cash conversion cycles. Most brands should measure 3-month, 6-month, and 12-month LTV on an ongoing basis, focusing primarily on early LTV metrics.

Components of LTV

Average Order Value & Gross Margin

Let’s talk about AOV and Gross Margin together— AOV is the primary lever a marketing leader can pull to drive gross margin improvements. By increasing AOV, you automatically increase gross margin. The other component of Gross Margin — COGS — is typically influenced by product & operations teams through supplier & sourcing agreements, so we’ll save that for another post in the future.

You can increase average order value by:

1. Increasing the average price of your products
2. Increasing the number of products a customer purchases on a per-order basis

Increasing the Average Price of Your Products

From a pricing perspective, A/B testing price elasticity of demand is important. This can be a great lever when executed correctly, but can also hurt your business significantly if not. There are a few ways you can execute against an A/B test in e-commerce:

1. True A/B Test: this refers to randomly segmenting your traffic into a test and control group. This means that one visitor could see one price and another could see a different price, even if they access your site at the same date and time. You can implement this through custom development or an app, such as Intelligems.
2. Pre-Post Test: You can also do a pre/post-test (test a $X price point for 2 weeks and a $Y price point for the following 2-week period) instead of an A/B test, but you have to choose your times and traffic wisely so outside factors (such as a promotion or change in season) don’t influence the results of your experiment. 
3. Email or Ad Split Test: Instead of testing different prices on your website, you can run an A/B test with different price points across your email list or ad creative. This is likely the least accurate way to A/B test price points as the metric you’ll look at is click-through rate, which is much further up in the funnel than an actual purchase itself, which introduces more room for error.

Tip: When running pricing experiments, you’ll also need to prepare your CX team in case a customer asks or complains about it— it’s easy to upset customers if they realize they’re being charged more than someone else for the same product. Typically the best way to handle this is to honor the lower price for everyone who inquires.

To evaluate the results of a pricing experiment, you’ll want to evaluate the aggregate financial outcome, which can involve the following KPIs:

• CAC (or CVR)
• Gross Profit
• Returns
• Repeat Purchases

By looking at customer behavior from a pricing experiment holistically and over a period of time, you’ll get a better complete picture of the impact the test had. If a price increase shows positive results, you can always test another increase down the line.

Increasing the # of Products Purchased (per Order)

Outside of price increases, you can also increase AOV by increasing the number of products a customer adds to their cart. A few ways to do that are:

• Launching new products or variations
• Tiered discounts based on the total value of products offered
• In-cart upsells
• Post-purchase upsells
• Cart gamification (e.g., cart thermometer)
• Adjusting free shipping thresholds

Of these, the most impactful is launching new products or variations. By increasing your assortment with products your customers love, you can make step-function changes to your AOV. Great examples of this include:

• Magic Spoon launching cereal bars
• Alo Yoga adding new colors to their most loved projects
• Dr. Squatch breaking into non-soap categories

The other levers mentioned can drive great results too, but will ultimately have less of an overall impact.

# of Purchases

The final component of LTV is the total number of purchases a customer makes with a company. This, like LTV overall, is a time-bound metric. The time in which you should measure this is defined by your product category & business model.

Increasing order frequency is one way to increase number of purchases; however, changing customer consumption habits, especially for consumable products, can be difficult. One company that increases order frequency well is Starbucks, through its individualized loyalty program. If a customer typically purchases coffee from Starbucks on weekdays, they’ll incentivize that person to start purchasing on the weekends through bonus stars (points) in the hopes they’ll create a habit out of it. Similarly, if a customer purchases Starbucks in the morning every day, they’ll incentivize that person to purchase in the afternoons as well. While this method is extremely effective for Starbucks, it’s difficult for everyday consumer brands to change habits the way Starbucks does— it requires ubiquity of product, strong segmentation, and the ability to send offers on a personalized basis. Offers without personalization or segmentation can be cannibalistic, as most customers who redeem them likely would have purchased anyway.

Increasing customer retention (or the length of time an average customer spends with your brand) is the primary driver that e-commerce brands can leverage to help drive the overall number of purchases up.

Some drivers of customer retention include:

• Product & packaging
• Shipping experience
• Brand
• Customer support
• Acquisition channel/offer

Most of these drivers impact customer satisfaction against promised value, which combined with customer need, drive retention and overall repeat purchase. The main questions brands should be asking themselves are: 

1. What are customer expectations of their experience with my brand/product?
2. How are we delivering against those expectations?

Ultimately, understanding the answers to those two questions can set an underlying foundation for a customer retention strategy. When I was running customer retention at Winc, I sought to answer them. On question 1, we analyzed our top-performing paid media creatives and subscriber surveys to understand why customers were signing up for a subscription with us.

We found that the top two reasons were:

1. Wine delivered directly to their door (this was in H2 2020, so the results of this value prop are skewed due to the pandemic)
2. Discovery of new wines from around the world

For the first reason, this was something we could confidently say that we delivered on. After all, the very nature of our business was delivering wine. That being said, we didn’t have a monopoly on the wine subscription market, so just fulfilling this value prop wasn’t enough to retain customers on a long-term basis.

Where we were lacking was in fulfillment of the “discovery” value proposition our customers were coming to us for. In performance creative and our landing page copy, we promised customers they would “discover a new world of wine”, indicating they could explore dozens (if not hundreds) of new wines. While this was typically true, the demand surge from the pandemic had depleted most of our supply and the number of products on the site was limited. While we couldn’t see the impact of this on top-line revenue and retention rates quite yet, I used this framework to push our team to quickly source, develop, and add new products to the site to prevent future retention woes.

When the new products were ready to launch a few months later, the impact of the pandemic on our business had already started to die down, and we could see retention rates decreasing. We launched with a 3-month A/B test to measure the impact of the new products on retention, and the results were astounding. In the test group, retention rates slowly began to rise to pandemic-era levels. Moving forward, focusing on product diversity and availability became a top priority for the company.

Looking at retention through the lens of these two questions can help uncover insights that lagging indicators may not be able to tell you. That being said, retention should be looked at holistically. I always leveraged data-driven retention analyses as a secondary lever to develop initiatives to improve retention and increase the number of purchases customers were making. 

Retention analyses can involve looking at customer survival curves to identify drop-off points in your customer journey to understand where you should focus your time and efforts. The survival curve shows what % of your customers still purchase over X time.

To break down this concept further, you can look at survival curves on a cohort-based approach. For example, you can break down your customer base by month of customer acquisition to understand how your survival curve is changing over time.

This example shows decreasing month-over-month retention rates from various cohorts, indicating that some drivers through late Q1 and early Q2 2022 led to customers churning faster. The next step in this analysis would be to find out the “why” and then develop initiatives to help address any uncovered issues. You can also look at cohort-based survival curves to evaluate differences in retention rates by other factors, such as first product purchased, acquisition channel, and introductory offer.

While cohort-based survival curves can uncover valuable insights, the lagging nature of the analysis makes it necessary to have other, more timely measures to analyze and address retention, such as the two-question approach shared earlier. 

Wrap Up

To wrap up, creating a playbook to continuously work on improving customer LTV can be one of the largest levers to drive top and bottom-line improvement for your e-commerce business. One of the most effective ways to start this work is to break down LTV into its core components (average order value, gross margin, and # of purchases) and create/prioritize initiatives to address them. There is no perfect answer to what initiatives or metrics to go after first— they’re dependent on the nuance of each product and business model. By investing in the right strategies and initiatives, e-commerce brands can cultivate a loyal customer base that will continue to engage with their products over time, driving revenue growth and increasing the odds of long-term success.

Want some help improving your customer’s LTV? Check out The Starters for retention leaders and experts who can work hand-in-hand with you to execute some of these strategies.

‍