How to calculate customer lifetime value in Google Analytics for Shopify subscription stores

subscription selling

Many of Littledata’s subscription customers come to us with a similar problem: how to calculate return on advertising spend (ROAS), considering the varying customer lifetime value (LTV) of subscription signups.

Calculating marketing ROI for subscription ecommerce is a big problem with a number of potential solutions, but even the initial problem is often misunderstood.

In this post, I’ll break down what the problem is and walk through two proven solutions for getting consistent, reliable customer lifetime value reporting in Google Analytics.

Tip: Get accurate tracking for repeat orders with the ultimate Shopify ReCharge guide.

What is customer lifetime value?

I work with all kinds of subscription ecommerce businesses: beauty boxes, nutritional supplements, training courses and even sunglasses-by-the-month. All of them want to optimise customer acquisition costs. The common factor is they are all willing to pay way MORE than the value of the customers’ first subscription payment. Why? Because they expect the customer to subscribe for multiple months.

But for how many months exactly? That’s the big question.

Paying for a marketing campaign which bring trial customers who cancel after one payment – or worse, before the first payment – is very different from paying to attract sticky subscribers.

A marketing director of a subscription business should be willing to pay WAY more to attract customers that stay 12 months than customers who only stay one month.

12 times more, to be precise.

So how do we measure the different contribution of marketing campaigns to customer lifetime value?

In Google Analytics, you may be using ecommerce tracking to measure the first order value, but this misses the crucial detail of how long those shoppers will remain subscribers.

Try Littledata free for 30 days

As you can see below, with lifetime customer value segments, we can:

  • make more efficient use of media
  • tailor adverts to different segments
  • find new customers with lookalike audiences and
  • target loyalty campaigns
Efficient media, use data to tailor ads, find new customers

There are two ways for a marketing manager to see this data in Google Analytics: the first is a more difficult, manual solution. The other is an easier, automated solution that ties recurring payments back to their original campaigns.

Manual solution: segment orders and assign a lifetime value to each channel

It’s possible to see the required data in GA by manually segmenting orders and assigning a lifetime value to each channel.

For this solution you’ll need to join together:

  • (a) the source of a sample of first orders from more than a year ago, by customer number or transaction ID
  • and (b) the LTV of these customers

The accuracy of the data set for A is limited by how your Google Analytics is set up: if your ecommerce marketing attribution is not accurate (e.g. using Shopify’s out-the-box GA scripts) then any analysis is flawed.

You can get B from your subscription billing solution, exporting a list of customer payments (and anonymising the name or email before you share the file internally). To link B to A, you’ll need to either have the customer number or transaction ID of the first payment (if this is stored in Google Analytics).

Then you can join the two data sets in Excel (using VLOOKUP or similar function), and average out the lifetime value by channel. Even though it’s only a sample, if you have more than 100 customers in each major channel it should give you enough data to extrapolate from.

Now you’ve got that LTV by channel, and assuming that is steady over time, you could import that back into Google Analytics by sending a custom event when a new customer subscribes with the ‘event value’ set as the lifetime value.

The caveat is that LTV by channel will likely change over time, so you’ll need to repeat the analysis every month.

If you’re looking to get away from manual solutions and excessive spreadsheets, read on…

Calculating customer lifetime value

Subscription ecommerce is huge, and continuing to grow around the world. But Shopify Plus stores (in particular) selling products by subscription have a unique problem: how do I link the recurring customer payments back to the marketing campaign or channel that led to them subscribing?

Unlike standard ecommerce, it’s not enough to track the payment upon a first signup. It is the customer lifetime value (LTV) which counts in any marketing calculation.

“The great thing about a subscription businesses is that you don’t have to rely on one-time purchases.”
— Rob Hoxie, co-founder of Tiege Hanley (read the full interview).

I’ve already laid out the time-intensive manual solution for subscription tracking. But before we get into the automated solution, let’s discuss why you need to track customer lifetime value in the first place (and the various problems with tracking it in Google Analytics).

I’ll also get into Littledata’s solution, which will work for you whether you’re using Bold or ReCharge as your Shopify subscription app.

Note: Check out my ReCharge talk in full from the ChargeX conference in September 2019, where I discussed a similar topic.

Why you must track lifetime value

Let’s imagine a simple store selling a single subscription product for $50 per month. On average, it takes them $70 to acquire a new subscriber via Google Ads.

Now let’s think about 3 fictional customers of that store: Claire, Eric and Luke.

These 3 offer very different values to the business, and differentiating them (or the customer segment they represent) in Google Analytics is critical to business success.

In the graphic below, you’ll see that Claire is costing the business money, as her lifetime value is less than the cost of acquiring her as a customer.

Eric pays something, possibly buying twice from the business, but still has a short ‘lifetime’.

Only Luke continues for a reasonable time (and may continue subscribing).

Which of them brings the company profit?

The answer is only Luke.

Many subscription businesses only make money on customers who subscribe for over 3 months — but the loyal customers are immensely valuable, and may go on to pay for years. This also speaks to the immense value of customer retention among Shopify Plus stores.  

The problem with subscription analytics

Measuring and attributing this lifetime value is hard. The events happen in three different places, and need to be linked back to give a net value to be properly tracked:

Unfortunately, by default, the customer who chooses a subscription in Shopify may not be linked to the user that actually commits to a payment in ReCharge.

In other words, transactions are often left improperly tracked and attributed; in many cases, the refund or cancellation is not tracked at all.

Take this Google Analytics screenshot from one of our customers (before fixing):

Although 19% of the traffic comes from paid search, none of the ecommerce transactions are attributed to paid search. Instead, they are linked to a totally different group of users from ‘direct’ traffic.

Littledata’s solution 

Littledata’s Shopify app combines the three steps in the customer lifecycle to bring together a unified view of the customer in Google Analytics. 

Once that customer has gone through the checkout, we can also track each subsequent recurring payment back to that same pre-checkout user journey (including the marketing campaign from which they came), along with other custom dimensions in Google Analytics to help you analyse lifetime value.

How subscription stores can use data to optimise marketing campaigns 

Once you have recurring payments feeding into Google Analytics, you can begin segmenting your marketing channels by those that bring a higher quality customer — ones that nearly or exactly match your target personas.

By using Littledata’s smart PPC connections for Facebook Ads and Google Ads, you can also pull in advertising costs to calculate Return on Advertising Spend (ROAS).

So do you know which marketing channels bring you customers with the highest lifetime value? Maybe you have one stand-out channel that brings the majority of Lukes, and some that only bring you Claires.

A better, automated solution: tie recurring payments back to the original campaign(s)

What if you could import the recurring payments into Google Analytics directly, as they are paid, so the customer LTV is constantly updated and can be segmented by campaign, country, device or any other standard GA dimension?

This is what our Google Analytics connection for ReCharge does. Available for any store using Shopify or Shopify Plus as their ecommerce platform and ReCharge for recurring billing, the smart connection (integration) ties every recurring payment back to the campaigns in GA. 

Then, if you also import your campaign costs automatically, you can do the Return on Investment (ROI) calculations directly in Google Analytics, using GA’s new ROI Analysis report (under Conversions > Attribution), or in your favourite reporting tool.

Note: Now, with a revamped ReCharge connection — ReCharge v2 — you can track subscription lifecycle events with ease!

Do you have a unique way of tracking your marketing to maximize LTV? Are there other metrics you think are more important for subscription retailers?

Littledata’s connections are growing. We’ll be launching integrations for other payment solutions later this year, so let us know if there’s a particular one you’d like to see next.

Quick recap

  • Customer Lifetime Value (LTV) is the one metric that matters for a subscription business
  • To scale using metrics like Return on Advertising Spend (ROAS), you need to have accurate LTV calculations first 
  • Getting that data into Google Analytics allows you to segment by marketing channel or campaign
  • Littledata’s advanced Google Analytics integration for ReCharge stores provides an easy way to stitch the data together
3 Shopify apps every Shopify Plus store should use in 2020
shopify apps for shopify plus stores littledata

3 Shopify apps every Shopify Plus store should use in 2020

Finding the right tools for your ecommerce business can be a daunting task

How to optimize your Shopify conversion rate for fashion ecommerce
shopify fashion conversion rate optimization ecommerce

How to optimize your Shopify conversion rate for fashion ecommerce

Fashion consumers are buying more online than ever have before

You May Also Like