In the world of athletics, there’s a saying, “No Days Off.” Basically, these endorphin-filled athletes with their glowing skin and finely-tuned microchip-like bodies (insert Chris Traeger intensity here) advocate for consistency in their training, utilizing all the tools available to them to better themselves, whether that looks like a rest day, a recovery day, or a day of intense training. No days off doesn’t mean overworking, it means utilizing the tools to work and rest smarter. 

In October of 2021, I ran my very first marathon and more fully understood the spirit of “No Days Off.” While I did learn a lot about myself in training for my marathon (I’ll spare you the details of my more personal enlightenments), my most surprising realization was the treasure trove of personal data that accompanies marathon training. With the right set of tools, instead of just relying on intuition or responding when “something hurts,” I was able to more proactively manage and adjust my regimen by gathering data about what’s happening in real-time. In our modern data-driven era, runners have a plethora of highly-personalized data and analytics at their disposal. This allows them to not only measure and regulate exertion on runs but to analyze caloric intake, macros, the shape of their feet, their walking patterns; every little detail of their routine.

On one of my long runs in which I had ample time to think—no, really think—about weird connections, I realized that this abundance of data collection and use directly applies to retail subscription models. Subscription is a powerful channel. A channel that requires a lot of care, data, tools, and experts to sustainably grow.

Subscription models have grown significantly in recent years. No longer are businesses blindly grasping to MRR, merely hoping to produce predictable income. As many businesses who based their revenue solely on the subscription model found out, there’s more to recurring-oriented customers than simply how much they’re currently ordering, when they’re ordering it, and how many days there are in the month.

Businesses now have the tools and data—right at their fingertips—to strategically measure, analyze, and grow businesses. The question is, is your brand using the correct data at your disposal to grow strategically? Don’t just run on intuition, or wait until something hurts. Use your data to your benefit. In other words, embrace “No Days Off.”

Subscriptions are a Complex System

The subscription channel is a living body of systems. Just like the human body is made up of many parts with different needs and rhythms, subscription-based businesses are made up of many different kinds of subscribers with different needs, or cohorts. The real-life humans on the other side of your subscription product have dependencies in their lives with ever-evolving circumstances. These subscribers, often grouped in cohorts have different rhythms—different purchasing patterns of how often they purchase, how much of your product they include in each purchase, etc. These different cohorts with their different rhythms require the necessary systems to provide value alongside your product offerings.

Your brand needs ways of analyzing this system, both as a whole and as individual units. You need to know if changes are body-wide across your entire channel, or contained to specific systems, or cohorts. Brands need to build and improve these systems by engaging both the one-time and sporadic purchasers, which means understanding, grooming, and collaborating with your traditional retail channel is essential to provide real value to your customers. Improving these systems and units will lower your churn rate and maximize your monthly recurring revenue.

Track and Analyze for Health and Growth

Proper analysis begins with utilizing the right tools. You need to have the correct technology to accurately capture data points and keep track of metrics. Find your proverbial Garmin Fenix 7 or Whoop 4.0. In other words, find the tool that will allow you to automatically track the subscription analytics that your team wants to focus on by capturing that data directly from transactions. This will provide you with insights to attract, engage, and retain customers leading to more selling opportunities and a higher LTV.

Finding those tools almost certainly means looking beyond the native capabilities of your eCommerce platform, or even your fancy new subscriptions platform. Subscription capture and management platforms may give you some of the baseline data but they often need to be augmented to understand the full picture of your customer’s journey. Invest in an analytics platform (such as Peel) that will give you all the data points you need to thoroughly understand your customers and make smarter decisions about your subscription channel.

Just like marathoners should track heart rate, pulse ox, muscle mass, hydration, sleep, caloric consumption, etc, there are key indicators that will help us understand how to set strategies and tactics for how to improve our subscriptions businesses.

Some of this is elementary. You need to understand which specific products your subscribers are purchasing. You should be analyzing subscription activation metrics that reveal the relationship between one-time-purchasers and subscribers and help you discover ways to activate more subscribers for your brand. Your team should segment all subscription metrics by-product, variant, duration, day of the week, day of the month, cancellation reason, etc.

There are quite a few metrics to track to get a complete picture. We’ve included a chart at the end of this guide that you can use as a reference for your own metrics.

Own Your Data To Improve Performance

Data collection only goes so far. In order for it to help, you have to analyze it correctly. How does the data help you convert more of those one-off transactional purchase customers and turn them into subscribers on auto-billing? Are your "one-time purchasers" becoming subscribers? 

Here are some questions to help you understand how acquisition is trending:

• How many people make a one-time purchase, and then does it turn into a subscription?

• What is the number of days between the first one-time purchase and the first subscription?
  Days to Activation Metric
• When should you send campaigns to one-time purchasers to promote subscription?
  Days to Activation & then Rate of One-time Subscriber Metric
• Are my subscribers subscribing and never purchasing things before, or are the majority of my customers one-time purchasers who then become subscribers?
  Rate of One-time Subscriber Metric‍
• What is my total number of active subscriptions on any given day?
  Active Subscriptions Metric‍
• What is the number of new subscribers? How many people are joining our subscription program?
  New Subscribers Metric‍
• What is the number of one-time purchase customers becoming subscribers?
  ‍New OTP Subscribers Metric
• What is the rate that my customers are becoming subscribers over time in their lifecycles?
  Subscribers Rate cohort analysis 
  

Other metrics that can inform tactics for acquisition are ROI, LTV, and LTV to CAC ratio.

Additionally, you can determine the actual ad budget you can afford by finding average LTV for customers segmented by-products, SKUs, discount codes, and attribution channels.

Beyond acquisition, you need to know how to improve the health of your existing business:

• What products are the leading indicators for LTV, retention & repurchase? Leaning into those products and driving campaigns through your marketing channels to push those high-performing products.
• How are the cohorts developing over time? Using that data to find where you can improve the customer journey and engage cohorts with the right content to improve their repurchase rates and time it takes to convert to subscribers
• Is your brand attracting higher-value customers? Is average order value (AOV) increasing for new customers and increasing over time for returning customers?
• What are the most profitable products in terms of Margins? Push those into subscription packages and find upsell opportunities for these products
• Can you take a loss on a popular product and upsell later in email marketing?

Final Note: Partner with Experts

Getting outside opinions that know how to properly interpret this data is one of the most valuable things for your brand. Be proactive—hire an agency or consultant to help you interpret your data or validate your own analysis. Hiring an agency is very much like hiring a doctor: you must both trust them and partner with them to keep your subscription business healthy. Even if you have in-house expertise, getting second opinions can be either mind-altering or validating. Doctors often consult other doctors for their own health.

Now, get out there and treat that subscription channel with the respect it deserves so that when you drop the hammer on mile 25 you don’t bonk.

Key Metrics:

The most important metrics - that indicate your performance, growth, and trajectory are: 

• Average order value “AOV” : Represents the average amount of money a customer spends in a single transaction. 
  

• Lifetime Value "LTV": Represents the average amount of money a single customer spends throughout their customer lifetime. 
  

• Monthly Recurring Revenue "MRR": Total revenue generated from subscription sales over a one-month period.
  

A set of actions for eCom business is to boost AOV, reduce churn to improve MRR to grow LTV. 

• Active Subscribers: Customers with an active subscription on record - that are not canceled or expired during any given time period. Helpful to know how many subscribers you have and how much you have grown in subscriber count over time.
  ‍‍
• Active Subscriptions: Amount of active subscriptions on record - that are not canceled or expired. Helpful to know how many subscriptions you have and how much you have grown in subscription count over time. It is common that for many businesses there are always more subscriptions than subscribers, as a subscriber can hold multiple subscriptions depending on your offering.
  

• Duration of Active Subscribers: Looking at currently active subscribers, tracks the number of days since each customer's earliest subscription started:
  = [sum subscription time ] / [number active customers] (on any date or date range)
  Helpful to know how long your active subscribers stick around and stay a customer. This is best used by fast-growing brands with more active than churned subscribers.‍
  ‍
• Duration of Active Subscriptions: Looking at currently active subscriptions, tracks the number of days since each subscription started:
  = [sum subscription time ] / [number active subscriptions] (on any date or date range)
  Helpful to know how long your subscriptions last.
  

• Duration of Churned Subscribers: Looking at subscribers who churned on a given day, tracks the number of days since each of these churned customers' earliest subscriptions started.
  = [sum subscription time] / [number churned customers] (on any date or date range)
  Amount of time in days between the day a customer subscribed and their last subscription canceled. Helpful to know how long the customers that churn have subscribed to your company - knowing this information, and knowing what products they purchased can be helpful in providing experiences and outreach at specific intervals to decrease churn.
  

• Duration of Churned Subscriptions: Looking at subscriptions who churned on a given day, tracks the number of days since each of these churned subscriptions started.
  Amount of time in days between the day a customer started a subscription and their subscription canceled. Helpful to know how long the subscriptions that have churn last and knowing what products the subscriptions were on can help provide experiences and outreach at specific intervals to decrease churn.
  

• Churned Subscribers: The number of churned subscribers on any given day. Subscriptions have a churn date due to cancellation or failed payments, so they're churned on that date. Helpful to keep track of the number of subscribers that leave your brand, so you can find ways to reverse it.
  

• Churned Subscriptions: The number of churned subscriptions during any given time period. Helpful to keep track of the number of subscriptions that churn over time. Note that in many deployments, subscribers have multiple subscriptions, one for each SKU/product, and it is common to churn subscriptions to replace them by a new one upon a customer's request to switch products.
  

• Churn Rate: = # of subscribers canceling during a time period divided by # of subscribers at the beginning of the time period. You want this to always be decreasing.
  
  
• Growth Rate: = # of subscribers at the end of the time period divided by # of subscribers at the beginning of the time period. You want this to always be increasing. 
  

• MRR: MRR on any given day is the sum of revenue expected per month for all active subscribers on that day.
  
  If a subscription renews every 6 weeks, we’ll count 6 (weeks) * 7 (days) / 30.5 (days) of the revenue towards the MRR, and put simply, if a $100 subscription renews every other month, we count $50 towards MRR.
  

• Net Sales - New Subscribers: Net Sales = gross sales - discounts - returns
  This is only counting only Net Sales from New Subscribers. It is the Net Sales from first recurring orders.
  

• Net Sales - Subscribers: Net Sales = gross sales - discounts - returns
  This is counting only Net Sales from Subscribers
  

• New Subscribers: How many people started a subscription for the first time during a specific time period.
  This is counting customers' first subscriptions. This metric tells us the number of subscribers. Including One-Time Purchasers and people who are starting their subscription for the first time - they are both considered new subscribers. Anyone who is starting a subscription.
  This metric is counting customers. If you go to the metric New Subscriptions - you will see the number of subscriptions. The New Subscription number could be higher because in some businesses a customer can have multiple subscriptions.
  

• New Subscriptions: The number of new subscriptions on any given day.
  The number of new unique subscriptions. This is counting customers' subscriptions. Some customers could have multiple subscriptions.
  

• Total Sales Subscribers: A revenue metric that only looks at Total Sales from Subscribers. Equates to gross sales - discounts - returns + taxes + shipping charges
  

• Subscription Revenue Rate: Percentage of revenue that is Subscription Revenue. When segmented (e.g. by product type), the percentage is for each segment = [Subscription Revenue] / [Total Revenue]
  This allows you to answer the question - What percent of overall revenue is subscription revenue.
  You can segment these metrics like all the metrics in this list to see the segmented percentage of subscription revenue compared to overall revenue.
  

• Subscribers Churn Rate: Rate of churned subscribers during a given time period
  The churn rate is looking at each subscriber and counting how many of the active subscribers 30 days ago are still active today.
  Our definition of churn is any customer who's canceling all their subscriptions or failing to pay and the absence of a future charge scheduled. When a customer is recovered, the churn rate is revised.
  As a formula: it is taking the number (A) of subscribers (All) at the beginning of a time period, count the number (C) of these (All) subscribers who churned during that time period. The churn rate is = C / A as a percentage.
  

• Subscriptions Churn Rate: Rate of churned subscriptions during a given time period
  The churn rate is looking at each subscription and counting how many of the active subscriptions 30 days ago are still active today.
  Our definition of churn is any subscription canceled or failing to pay and the absence of a future charge scheduled. When a customer is recovered, the churn rate is revised.
  As a formula: it is taking the number (A) of subscriptions (All) at the beginning of a time period, count the number (C) of these (All) subscriptions who churned during that time period. The churn rate is = C / A as a percentage.
  

• Subscriptions Growth Rate:  Rate of new subscriptions during a given time period
  # of subscriptions at the end of the time period divided # of subscriptions at the beginning of the time period. You want this to always be increasing.
  

Particular “system” metrics for cohort analysis include:

• Active Subscribers per Cohort - Retention analysis: This metric shows your retention of your subscribers over time. You are able to see if a particular cohort month has a different retention pattern or if there are patterns with acquisition and churn.
  
  
• Active Subscriptions per Cohort - Retention analysis: This metric shows the retention of your subscriptions over time. You are able to see if a particular cohort month has a different retention pattern or if there are patterns with acquisition and churn.
  
  
• Cumulative MRR per Subscriber: Monthly Recurring Revenue divided by active subscriber, normalized into a monthly amount. It is cumulative, so it looks at the amount of Monthly Recurring Revenue since the beginning of the Subscriber's first subscription. For example, in Month 1, the MRR is $20 per Subscriber and then in Month 2, the Cumulative MRR is $40, which is cumulative and the MRR earned is $20 per Subscriber. You can look at the MRR per Active Subscriber if you want to see the non-cumulative analysis. It’s important to notice that MRR is an indication of the monthly-equivalent revenue (think of subscriptions shipping every 6 weeks for example) and not an actual amount charged.
  You can use this analysis to see what your MRR is at different periods of time and with specific monthly cohorts and purchasing patterns.
  

• Cumulative MRR per Subscription: Monthly Recurring Revenue divided by active subscription, normalized into a monthly amount.
  It is cumulative, so it looks at the amount of Monthly Recurring Revenue since the beginning of the Subscriber's first subscription. Cumulative means it shows you the current Monthly Recurring Revenue, not each month's monthly recurring revenue - there is the non-cumulative metric available for that analysis. 
  It’s important to notice that MRR is an indication of the monthly-equivalent revenue (think of subscriptions shipping every 6 weeks for example) and not an actual amount charged.
  You can use this analysis to see what your MRR is at different periods of time and with specific monthly cohorts and purchasing patterns.
  

• Earned Profit per Subscriber: Cumulative earned profit per subscriber across all of their subscriptions = MRR equivalent minus COGS revenue attributed to each month, per subscription. ie. If a customer pays for a 3-month subscription upfront, 1/3rd of the amount is added each month, unlike LTV would display all profit on the month the charges occur on. 
  This is divided by the number of Subscribers in the Cohort.
  This is a helpful metric to analyze prepaid revenue.
  ‍
• Earned Profit per Subscriber Cohort: Cumulative earned profit per subscriber cohort across all of their subscriptions = MRR equivalent minus COGS revenue attributed to each month, per subscription. ie. If a customer pays for a 3-month subscription upfront, 1/3rd of the amount is added each month, unlike LTV that would display all profit on the month the charges occur on.
  ‍This is the amount for the entire cohort. It takes into consideration product costs.
  This is a helpful metric to analyze prepaid revenue.
  

• Earned Profit per Subscription: Cumulative earned profit per subscription = MRR equivalent minus COGS revenue attributed to each month, per subscription. ie. If a customer pays for a 3-month subscription upfront, 1/3rd of the amount is added each month, unlike LTV that would display all profit on the month the charges occur on
  This is the amount for the entire cohort.
  This is a helpful metric to analyze prepaid revenue.
  ‍
• Earned Profit per Subscription Cohort: Cumulative earned profit per subscription = MRR equivalent minus COGS revenue attributed to each month, per subscription. ie. If a customer pays for a 3-month subscription upfront, 1/3rd of the amount is added each month, unlike LTV that would display all profit on the month the charges occur on
  This is divided by the number of Subscribers in the Cohort.
  This is a helpful metric to analyze prepaid revenue.
  

• LTV per Subscriber: LTV is the lifetime profit from the subscribers. 
  LTV total revenue from subscribers, and subtracts, costs, refunds, discounts and divides that by the total number of subscribers in the cohort.
  It is a cumulative metric
  

• LTV Per Subscriber Cohort: LTV is the lifetime profit from the subscribers in a cohort.
  LTV total revenue from subscribers, and subtracts, costs, refunds, discounts. It is the cumulative amount for the entire cohort of subscribers. 
  It increases when customers come back and repurchase.
  This is the amount for the entire cohort.
  

• LTV per Subscription: LTV is the lifetime profit from the subscriptions in a cohort.
  LTV total revenue from subscribers, and subtracts, costs, refunds, discounts and divides that by the total number of subscriptions in the cohort.
  It is a cumulative metric.
  It increases when customers come back and repurchase and spend more money each time.
  This is the amount for the entire cohort divided by the number of subscriptions. 
  

• LTV per Subscription Cohort: LTV is the lifetime profit from the subscriptions in a cohort.
  LTV total revenue from subscribers, and subtracts, costs, refunds, discounts. It is the cumulative amount for the entire cohort of subscriptions.
  It increases when customers come back and repurchase and spend more money each time.
  This is the amount for the entire cohort. 
  

• MRR per Active Subscriber: Monthly Recurring Revenue divided by active subscriber, normalized into a monthly amount. MRR per cohort is a non-cumulative metric. It drops each month as the number of inactive customers drop too.
  MRR is an indication of the monthly-equivalent revenue (think of subscriptions shipping every 6 weeks for example) and not an actual amount charged. For that, we have recently updated the LTV per subscriber cohort metric and Lifetime revenue which is a cumulative sum of actual charges, grouped by cohorts.
  

• MRR per Active Subscription: Monthly recurring revenue (MRR) for each subscriptions in the cohort.
  MRR per cohort is a non-cumulative metric. It drops each month as the number of inactive customers drop too.
  ‍
• MRR per Subscribers Cohort: Cohort metric as a sum of MRR for subscribers in the cohort
  MRR per cohort is a non-cumulative metric. It drops each month as the number of inactive customers drop too.‍

Key “growth” metrics for understanding improvement:

• Activation Rate: Percentage of customers from the past 30 days who became subscribers today.
  

• Days to Activation: This is looking at the average number of days between when people subscribed and when they made their first non-subscription order. Depending on how many subscriptions you have, it is best to look at this monthly, but of course, can look at any timeframe. Start with monthly. 
  "For people that subscribed in May, it was an average of XX days since their first one-time purchase."
  "Satisfied customers will come back and subscribe within XX days."
  This is the time window to really push communications to encourage people to join your subscription program. 
  If you see zero, it's because you didn't have New OTP Subscribers in that time window. Read on to the next metric, `New OTP Subscribers` to learn more.
  ‍
• Subscriber Rate is looking at the number of customers that are and become subscribers over time in that cohort. It is the amount of subscribers compared to all customers.
  
  
• New OTP Subscribers: The number of new unique subscribers among customers who first had made a one-time purchase. This is counting customers instead of subscriptions.
  The month they appear is the month that they subscribed. This metric is counting subscribers who first made a one-time purchase. They became subscribers in the time period shown here. 
  When we segment by for example -- the product, this is the product that they subscribed to in their first subscription order.
  You can use this metric to track whether the experiments you are doing to activate one-time purchasers into subscribers. Are they improving?On average, these were people that were one-time purchases and subscribed. They had a one-time purchase and then they subscribed.
  

• Rate of One-time to Subscriber: Percentage of daily subscribers who had first made a one-time purchase earlier.
  This metric looks at all the subscribers today and sees how many had placed a one-time purchase before. It tells you the percentage of your subscribers that had a one-time purchase in their purchase history. It allows you to answer the question, “Are my subscribers subscribing and never purchasing things before or are the majority of my customers one-time purchasers who then become subscribers?”
  XX% of new subscribers were OTP before.
  When it is high, it means that one-time purchasers are a great driver for subscriptions.
  If you are wondering if you shouldn't have one-time purchases, then this is the metric to tell you if people try the product before they subscribe. If it is zero, then maybe rethink one-time purchase behavior, but if it is higher, you will see the opportunity.
  Sending campaigns to one-time purchasers to tell them to subscribe. We see in the Days to Activation metric the average amount of time when people activate to be a subscriber, so this metric tells you the success rate of that.
  If the Days to Activation metric is growing, but the Rate of One-Time to Subscriber metric is going up too, then it is a success because you are converting a larger % of those OTP customers.
  You want this metric to increase because ideally, you want all your One-Time Purchasers to Subscriber. Since subscribers commit to buying from you every month/week versus one-time purchasers only do one-off transactions & could easily never come back.