Analyze Customer Retention in Just 2 Steps
As a subscription business owner, you will encounter a smattering of metrics that are considered vital for runway, profitability, beating your competitor, etc. Many inexperienced subscription businessesmake the mistake of relying on surface level metrics from their eCommerce store or data analytics apps that don’t provide granular customer retention data. Most subscription companies lose money on initial customer acquisition cost (CAC) understanding their profitability lies in recurring revenue, so why do many businesses go without truly understanding their customer retention metrics?
Defining customer retention as it relates to the true value driven for your business in the subscription industry can be tricky, due to agreeing upon what constitutes as the ‘active’ subscriber. Imagine this: John has an ‘active’ account for years but skips 80% of his shipments; while Sarah is only a customer for three months but has actually driven a higher value for your business. Do you want to consider John and Sarah the same within your customer retention data?
You Can Analyze Customer Retention By Answering These 2 Questions:
What defines an active subscriber?
When is my customer retention cliff and why?
We are going to take you from a basic level of understanding the proper customer retention definition and then help you gain insights into where your retention cliff resides and what to do about it.
Define an Active Subscriber
Many subscription brands will rely on dashboards or manual data exports from their ecommerce platforms to determine ‘Active’ customers. Here is the issue with that – the term ‘Active’ in leading subscription eCommerce platforms like Recharge, Bold or Cratejoy, simply means that an individual customer has a subscription and has not actively cancelled. This does not mean they are actively driving revenue for your business, because they could be taking advantage of skips or adjusting next charge dates.
Some platforms even consider prepaid ‘subscriptions’ with outstanding shipments active; however you have already collected all of the revenue from the customer up-front; therefore including them in this count that skew customer retention data.
Determine Your Retention Cliff and Churn Reason(s)
In the following examples we are going to look at the Overall Retention Rate to investigate the real ‘churn cliff’ and what to do about it. Overall Retention Rate is defined by the percentage of active subscriptions that successfully processed a charge, divided by the total subscriptions acquired for your desired cohort (Successful Subscription Charges / Total Eligible Subscription Charges).
The Report Details: Sublytics provides widgets and dashboards to help automatically normalize and visualize your data. Without a subscription focused analytics platform, you may need to manually extract and manipulate data from your eCommerce store and billing payments provider.
Retention Rate limited to a single subscription offer plan (example 30 Day Charge Frequency Renewal Cycle)
The X axis reflects Renewal Cycle on a 30 Day charge frequency, so each Renewal Cycle in this example the timeframe is month over month looking back at 13 months.
Note: The last day of the time frame is set to at least 30 days prior to allow for new subscribers to reach renewal maturity.
How to Analyze
Review the cycle to cycle retention rates to determine where you are seeing the greatest dips overall. In this example, the “cliff”occurs between Cycles 1 and 3 due to the 40% drop in Overall Retention Rate. Note that the Overall Retention Rate starts to stabilize between cycles 3 and 4 with only a 10% drop in Overall Retention Rate, so the likelihood of someone remaining a loyal, long-term subscriber increases once they have successfully received at least three boxes.
Now that we have isolated the cycle(s) responsible for most of our churn, we want to first understand if it is due to active or passive churn. Sublytics defines active churn as a customer actively cancelling their subscription, while passive churn occurs when a customer’s credit card is declined a max number of times. If there is a large percentage of passive churn, you can leverage dunning strategies to reattempt and auto-update expired cards to recover lost revenue.
Next, you will want to drill down into active churn to understand how factors like Product, Discount Code or Acquisition Source impact retention.
Finding Themes in Your Highest Churn Cycle:
For this example we will try to find common themes in retention rates across a variety of metrics in Cycle 2 – starting with Discount. Our experience with hundreds of subscription brands, has driven insights into retention issues rooting back to offering too steep of an initial discount which typically attracts the wrong kind of subscribers – one and done opportunists rather than those who are truly aligned with your service.
In looking at the data above, you can see that higher discounts in the 40 to 50% range drive a higher volume of acquisition; however the quality of customer is lower. As you move from left to right, the discount rates decline in regard to the amount of promotional value offered. You can clearly see that the retention increases when customers are willing to pay closer to full price.
For a sustainable acquisition program you will want to find a sweet spot for your promotional strategythat drives significant volume with a profitable retention rate. Here we see the company enjoys a 40 to 50% retention rate on discounts between 15% and 25% off while maintaining new customer volume.
For future promotions they should continue to leverage Rewards & Referral loyalty programs to maximize their reach across existing brand ambassadors, while testing discounts between 20 to 25% off for new customer acquisition promotions across paid media channels.
Now that we have identified retention trends for discount strategies, let’s take a look at Acquisition Source. Tying retention data to acquisition sources based on first-click or last-click attribution will be key for your growth and acquisition teams to optimize marketing efforts.
This level of deep dive provides you with the ability to dig into retention and LTV metrics beyond the all too surface-level Return On Ad Spend (ROAS) metrics, we often fall victim to relying upon. What can be tricky about allocating media spend based upon ROAS vs. Retention and LTV data, is that we can obviously allocate dollars to sources that look good on the front end with a low CAC and high volume.
In reviewing the data below, we see that channels like IG Shopping produce high volume but low retention for this company, while lower volume sources like Bing and Google Display Network, drive lower volume yet decent retention rates.
A campaign manager may be tempted to focus more on IG Shopping due to volume; however with these insights they can refocus energy to expand efforts on channels that drive customers that tend to stick around, such as search and podcast
Leveraging this data along with promotional insights will also help inform your strategy.
For example, the lowest retention rates were assigned to Youtube, where the brand was actively testing the 35% Off Black Friday discount. Understanding these trends will help you fine tune your media acquisition strategy.
Lastly, before we tie our major themes into cancellation reasons we need to look at Overall Retention Rate by Product. Regardless if you offer a curated box or replenishment model, retention ties heavily to the customer’s experience of the initial product that they try. Our example below is a replenishment model, so the same items are delivered each month, while a curated box would deliver a new array of products to try.
In this analysis, we are identifying any retention outliers to drive greater product promotion for the leaders and reassess the value prop or positioning for the losers. We can see the Anti-aging Monthly System is our sweet spot product for retention and volume, so we will want to continue to heavily promote this product with our target audience. Clear Skin is showing a slightly lower retention and significantly lower volume. This creates an opportunity to assess the marketing opportunity for increasing promotion of this system to an expanded, and likely younger audience.
The Beginner Skincare System is showing a low Overall Retention Rate in Cycle 2, which is likely tied to the nature of the product. Given that the product is marketed to those who may not be sold on skin care systems or are just trying out a skin care routine for the first time, a takeaway could be to offer this product with more flexible Charge Frequency options or leverage as a trial product that cross-sells into the Clear Skin Monthly System.
After looking at the themes we were able to draw in Overall Retention Rate for Cycle 2, we want to understand why customers are cancelling to help curb churn. Ideally we are able to draw connections between themes we saw analyzing Overall Retention Rate associated to Discounts, Acquisition Source, and Product.
The above chart is an example of Cancellation Revenue Lost for Renewal Cycle 2. To prioritize which Cancellation Reason to address first, we recommend looking at revenue loss associated with each Cancellation Reason rather than merely looking at the count of cancellations per reason.
In this scenario the number one reason for cancellation had to do with having too much product in the initial shipments. By the time Cycle 2 rolls around, the average customer realizes they haven’t run through their initial product and do not need more. A good strategy to counteract this consumption rate would be to adjust either the product quantity or adjust the charge frequency options.
The second highest cancellation reason had to do with pricing, meaning this company can either adjust their target audience to one more appropriately aligned with their price point or adjust their product / costs to meet the perceived value of their intended audience. The aggressive discount strategy may also impact this.
Another learning from this chart would be the broad definition of Customer Service Team Cancellation. Since this Cancellation Reason is so general there are not actionable takeaways, yet it is the third largest Cancellation Reason. We would recommend fine tuning all of the available cancellation reasons on your website and available to your Customer Service Team to ensure that they are insightful and actionable.
Lastly, a relatively low hanging fruit for reducing churn would be to target the “Passive Churn” in a campaign to update customers accounts with accurate credit card data.
Now that we have identified the 'active' subscriber, along with when and why customers are churning, here are key takeaways to consider as you dive into your own retention data.
Avoid Common Mistakes When Analyzing Retention:
Define an Active Subscriber.
Including prepaid, non-recurring orders and customers who are regularly skipping shipments can significantly impact your customer retention and LTV analysis.
Most brands only look at top-line customer retention data, but there are many factors that can impact retention and the power is in understanding how retention shifts based upon things like discount, product, or acquisition source.
Analyze Customer Retention by unique Charge Frequency
Renewal cycle length will impact your timeframe considerations and may skew the data when viewed in aggregate. For example, a bi-annual subscription will not be eligible for their first renewal until six month after their sign-up, while monthly subscriptions will be available for renewals every 30 days.
Review Active vs. Passive Churn.
Determine which customer are being lost due to credit card declines vs. customer cancellations to drive customer retention strategies separately.
Optimize your marketing and product development based upon the themes you learned in analyzing retention by discount, source, and product.
Optimize your marketing efforts and product development based upon your learnings. This may mean re-focusing efforts on marketing channels, adjusting promotional strategies and tweaking or sunsetting product lines.
Keep an eye on quick cancels (churn in the first 72 hours) and first renewal retention rates to help normalize early retention data. This is an early indicator of low quality traffic and can be used to proactively optimize.
Implement Customer Retention Strategies.
Explore innovative ideas like cycle level discounts and gifts to get more people through your high-churn cycles.
Implement Dunning Strategies.
Reduce passive churn through testing different strategies to reattempt and update credit cards.
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Up Next: The Essential Subscription Data Guide Chapter 2.2 – Lifetime Value in Acquisition