Win Back of Inactive Customers: when the Wheel stops

Win Back lost customers: can we intervene before it's too late?

In this article, we will see how to recognize inactive customers and how to implement effective Win Back strategies.

Recognizing Inactive Customers

The first step in the Win Back process is to recognize who the inactive customers are.

Monitoring the time elapsed since their last purchase helps identify customers who may have lost interest or turned elsewhere for their needs.

Studying Re-Purchase Cycles

Customers are in the Sand-Mill Model Re-Purchase Wheel, where each rotation represents a new purchase.

The period of time between one purchase and another defines a Re-Purchase Cycle.

The duration of these cycles, besides significantly varying among different companies, also varies within the same company.
By studying the data, we might notice that the time between the first and second purchase is different from that between the second and third.

This time-frame can:

• Shorten for products with periodic purchase: after a few purchases, the consumption habit is already consolidated.
  The replenishment automations do the rest and help keep the Rebuy Wheel active.
• Lengthen for businesses based on the Value Scale: consuming high-end products or services usually takes more time than consuming entry-level ones.

In any case, identifying the duration of rebuy cycles for our businesses is like setting a benchmark.

It allows us to compare at any time a single customer's situation with this benchmark and consequently understand if they are an active, at-risk, or lost customer.

Example of a Repurchase Cycle Analysis document.
You can create a copy of the template here.

Data-driven Win Back Automations

Analysis of customer behavior data in each Repurchase Cycle is essential to determine whether a user has been lost or not.

Generally, there are 3 errors in Win Back strategies.

In order of importance, they are:

• Not setting up any Reacquisition Automation (the issue here is lack of awareness)
• Not building data-driven Win Back automations (many companies set random dates instead of analyzing individual Repurchase Cycles)
• Basing data on the mean instead of the median

In my experience, the median is much more accurate than the mean.

The reason is simple: the average, in fact, is influenced by all those outliers that reappear long time after "contaminating" our analyses.

How to use these data?

Simple. Once the median value is identified, we can consider as "at risk of abandonment" the users who have exceeded this time frame since their last purchase.

Instead, those who have exceeded 2.5 times that date will become inactive or lost customers.

1. The simplest way to manage these dynamics is to adopt a dynamic RFM segmentation, defining different ranges for the 3 metrics Recency, Frequency, and Monetary.
   
   The data we have identified are the Recency parameters, while Frequency identifies the Repurchase Cycle in which we operate and Monetary the Level of Value reached.
   The 3 metrics can be combined in pairs to form segmentation matrices.
   
   
   
   
   

2. Another technique I use is to make a time stamp of each purchase by saving a custom date for First Purchase, Second Purchase, Third Purchase, and so on.
   
   
   
   

3. Finally, if this is your first time approaching this type of analysis, you can start simply by analyzing the metric Average Days Between Orders. The process is simple: you will need to export the data from a segment (e.g. exactly 2 purchases or more than 2 purchases) and identify the median value.

Example of data analysis

As an example, I report the actual data of average and median of the metric Average Days Between Orders for the customer segment that has made at least 2 purchases in an ecommerce I follow.

AVERAGE	78.78
MEDIAN	33.75

As it is evident, the average easily lies and is tainted by some users with "anomalous" behavior.

But how do we use this data?

Simple: we can consider users who have not made a purchase in the following 34 days after their last purchase as at risk of abandonment, while those who have not made a purchase for more than 85 days (=34*2.5) are seen as lost customers.

These latter become the target of our Win Back automations.

Win Back Strategies

Win Back strategies can vary depending on the business.

The golden rule is to remind users why they bought from us in the past.

This is especially true for those who have purchased only once and are stuck in the first Reacquisition cycle.

Generally, most inactive customers have made just one purchase.

The very first win back email for users stuck in the first Reacquisition Cycle can simply do this:

• Remind the customer why they purchased in the past
• Clearly show the benefits offered by the product
• Make the customer feel recognized and appreciated, part of a community

An email like this repositions the brand in the customer's mind.

This simple activity can already bear fruit.

But every Win Back strategy needs to be tailored.

Here are some possibilities to include.

The irresistible offer

A classic automation strategy to win back inactive customers is to propose an irresistible offer, something so enticing as to stimulate a renewed interest in the company.

This can include significant discounts, access to exclusive products, or unique benefits that are hard to refuse.

The good old discount that always works. But don't overdo it.

Relaunch of new products

An alternative solution to discounts could be to automate the highlighting of new products that have been launched since their last purchase.

We leverage the novelty principle to rekindle interest.

We show how these new products help achieve the goal that the customer has shown us to have with his first purchase.

Understanding motivations through surveys

Once inactive customers are identified, it is interesting to try to understand their motivations.

These customers have not reacted to the re-purchase automations we have built.

Why? Let's try to find out.

Customers are not all the same and feedback collection questionnaires are valuable tools in this phase: they offer direct insights into the reasons for their inactivity.

This information is crucial for adapting Win Back strategies.

The answers to the questionnaires allow us to segment customers based on the reason for their lack of re-purchase.

Assignment to a segment can trigger specific automatic flows to manage each of these reasons.

But beware: we cannot expect a high completion rate from a segment of inactive customers.

Therefore, in parallel, we must implement solid reactivation strategies that do not necessarily depend on these responses.

Gift Card on promotion

Ok, these (ex) customers are no longer buying for themselves. But maybe our product can be a great gift idea. Let's try to reactivate lost customers with a promotion on Gift Cards.

The result could be surprising.

The founder's email

An effective idea is to have the Win Back email sent directly in the name of the company's Founder.

This tactic works well and can be integrated with those seen earlier.

First of all, change the sender's name, moving from a corporate Sender Name (e.g., Visologiq) to a personal one (Valentina from Visologiq).

This is an opportunity to reaffirm the brand values, what led to the founding of the company, and especially the famous "why buy from us".

Finally, we can insert a tempting offer, such as a limited-time discount, to encourage a quick decision.

Here is an example of an effective founder email that embodies all these elements:

Win-back Through Multichannel Messaging

Another effective tactic for reactivating inactive customers involves using multichannel messages to create engaging and personalized dialogue.

As we have seen with the Sunset Workflow, if the main channel (email) seems not to be working, let's try another one: WhatsApp.

Varying communication channels and adapting them based on customer actions increases the chances of capturing their attention and inspiring a new purchase.

For example, if an inactive customer visits the website but does not make a purchase, we can replace the classic browse abandonment email with a targeted and personal WhatsApp message.

KPIs for Win Back strategies

Among the key metrics to evaluate the effectiveness of Win Back strategies stands out the reactivation rate, which is the percentage of inactive customers who make a purchase after receiving Win Back communications.

It is also important to monitor the interaction rate (open, click, conversion, and unsubscribe) on different channels (email, SMS, WhatsApp), in order to continuously optimize the reactivation strategy.

Finally, it is crucial to monitor the impact of these campaigns on the long-term customer value (LTV) and on the number of churns. Wheel of Rebuy.

Conclusion

Although rebuying is at the core of the logics of the Sand-Mill Model, there will always be customers who do not repurchase within the timescales set by basic automations.

These customers need to be identified and managed with specific automations: Win Back automations.

The goal is clear: reactivate the Wheel of Rebuy.

Remember: you can identify inactive contacts, such as those who have exceeded 2.5 times the median time in each Rebuy Cycle.

Once identified, you will need to implement an automatic strategy to reactivate them.

But remember that prevention is better than cure. Winback flows have modest results for a very simple reason: they intervene when it's already too late.

Do not abandon post-purchase customers, only to try to reactivate them when you have already lost them.

It is much better to invest energies beforehand in creating real Repurchase Cycles and prevent churn.

To help you map out each timed communication in each Repurchase Cycle, I have decided to share the template that I use.

It's a Google Sheet file that you can duplicate and that allows you to:

• View the sending frequency in each Repurchase Cycle
• Avoid overlaps that confuse your customers.
• Schedule timing for each email
• Segment the audience with precision

You can access it for free here.