What Is Customer Profitability Analysis?
Customer profitability analysis allows you to segment your customers by their profit contribution to your brand and optimize your marketing, customer service, and operations costs around the customer segments who are the most profitable for your brand.
In this post, we'll dive into customer profitability and run through a customer profitability analysis example.
What Is Customer Profitability?
Customer profitability is far more than the gross or net margin generated on a transaction, or even customer lifetime value (LTV). Customer profitability is the profit (customer spend - customer cost) across every touch point that customer has with your brand, including customer service contacts, returns, custom fulfillment costs, and more.
Running a customer profitability analysis will allow you to see your customer profitability in detail.
Why Measuring Customer Profitability Is Important
Profitability is every business's goal. Many factors can influence how attainable and sustainable it is, and the key factor is your customer profitability. Measuring customer profitability is crucially important, and it can be an enlightening exercise.
Once you build the framework to run a customer profitability analysis, it should be easier to refresh annually or as often as makes sense for your business. The significant value you gain through running one is that you will determine if certain customers are actually costing you money rather than making you money.
In some instances, you may find that the customer group you thought was the most important (most profitable) is actually of lower value to your company than customer segments you haven’t identified yet, which suggests a need for a shift in overall strategy.
If you’re wondering how some customers could be costing you money, it usually comes down to servicing costs.
Do you have certain customers who call customer service frequently? Are there certain customers who have special requirements for fulfillment who require higher labor and fulfillment costs? Or, if you offer customers free shipping and free returns, are there customers who are using that service too much? You’ll start to uncover these segments after you run a customer profitability analysis.
The Steps in Customer Profitability Analysis
Step 1: Define your customer costs
The first step to measuring customer profitability is understanding your business expenses and all the places that a customer might interact with any area of your company. Beyond the actual product or service costs for what they purchase, other customer costs might include:
- Marketing costs (e.g., your Cost Per Acquisition)
- Customer service contact costs
- Social media contact costs
- Shipping costs (especially if you fund return shipping)
- Return costs, including restocking or refurbishing
Once you have a list of all the ways customers can interact with your company, you’re ready to move onto Step 2.
Step 2: Define your customer groups
Next, let's talk about customer profitability segmentation. Some businesses have well-defined customer segments that may be based on the size of the business or business unit they buy from. If you don’t have these customer groups easily defined, you can define them now.
For example, based on your business, what types of customers do you have, and why do they buy from you? Even if you don’t have empirical evidence or a big third-party study to define these segments, you know your business and product(s) and can define these segments: developing customer personas is one great customer segmentation approach. You can start creating these based on user data (demographic data), poll data, market research, and more.
You can also run an RFM Analysis to bucket your customers out into different segments. An RFM Analysis is a Recency, Frequency, Monetary Analysis, and it is a highly detailed way of segmenting customers for a customer profitability analysis. Through a RFM Analysis, you create customer cohorts around three variables: how recently they have purchased from your brand, how frequently they have purchased, and how much they have spent.
Another option is using RF Segmentation (Recency Frequency Segmentation). The visualization below shows how Daasity thinks about customer segments based on Recency and Frequency. We use 6 categories:
In this matrix:
R (recency) is broken into three categories:
- Active: last purchase <90 days ago
- Lapsed: last purchase >365 days ago
- Churning: last purchase >90 days ago
F (frequency) is broken into three more three categories:
- Single Buyers: 1 purchase
- Multi Buyers: 2 purchases
- High Value Customers: 3+ purchases
The result is a simple yet powerful matrix to understand key customer segments. This allows you to get strategic about which groups are more critical to engage.
Step 3: Find the data
Now onto Step 3, where you might have to put on your detective hat: it’s time to search for the details, and you’ll need help from colleagues in the business areas from Step 1.
The first question is, do you have data? You probably do have data, but is it tracked and easily accessible?
It’s unlikely you’ll find every piece of data tied to every single customer. Usually, expenses like customer service costs are lumped together as one expense as a line item in Selling, General & Administrative Expense (aka SG&A). But now, you can start putting more science behind it.
Here are some ideas to track down more detailed data:
Do you track customer service interactions with the customer? It’s possible you could take a sample of customer service inquiries and determine the customer groups who might over-index in contacting you. The next question is why? The reasons for these costs—whether they're customer service contacts, returns, or others—will come in handy later.
Marketing spend and cost per transaction are other important data points—there could be hidden pearls in this data when you break it down by marketing channel and tie it to specific customer groups.
Ultimately, what you’ll end up with, at a minimum, is a series of average costs per activity, such as:
- Marketing cost to generate an order (cost per order)
- Average customer service contact per order
- Average cost per customer service contact
- Average return rate
- Average shipping cost
Step 4: Putting it all together: a customer profitability analysis example
Let’s say you have two customer segments: Segment A and Segment B. A high-level glance at the revenue that each segment drives for your business (per transaction) makes Segment B look much more attractive:
Armed with this data alone, you may be tempted to shift your strategy, budgets, and even product development pipeline to cater more to Segment B. After all, they are 25% more valuable than Segment A. Based on these numbers, that would be a solid plan.
But, what if Segment B customers aren’t actually better customers? This is where a customer profitability analysis becomes truly valuable for your business.
Let’s say that customers from Segment B have special fulfillment requests that end up costing twice as much in labor and fulfillment fees. And after all of that, they actually return or cancel orders at a significantly higher rate than Segment A customers. Now, they’re not looking as good as they did at the start of this example, are they?
All those hidden costs might look something like this:
Those Segment B customers are actually costing you a lot of money, not including the cost of the actual product/service. Putting it all together, you would be better off shifting your focus, strategy, and budgets towards Segment A customers for the long-term health and growth of your business.
Without running a customer profitability analysis, you wouldn't have been able to gain actual insight into the profitability of Segment A vs. Segment B. In the context of your real business, there are tons of potential insights that you can unlock to optimize spending and understanding your customers better.
How to Improve Customer Profitability
Striving to improve customer profitability is an ongoing effort. The first and probably easiest action to take is to maximize your most profitable customer group. What proportion are they of your total business? Could they be bigger, and how? Evaluate the necessary resources, budget, and requirements to grow this customer segment. Consider implementing a VIP program or loyalty program to encourage more spending among your high value customers.
That doesn’t mean you should abandon all other customer segments. Just because Segment B in the example above costs more money than Segment A, it doesn’t mean you should never sell to Segment B again. There are likely areas that could improve these metrics.
This comes back to the why. What did you learn in your investigations into these areas that could point to a root cause?
Can you add details to the sales process that help guide customers to a product/service that better meets their expectations? Are there policies that could be implemented to prevent some of these costs? Can Customer Service macros or FAQs be created so that the CS team can more quickly and easily address time-consuming requests? Perhaps it’s time to implement automation or SaaS tools to ease the process of buying and selling.
Customer profitability is more than just the revenue that a customer brings in. Taking the time to evaluate each area of a customer’s journey with your company can reveal insights that have a meaningful impact on your business strategy and your bottom line. Once you determine the data you will use and build out a structure to run a customer profitability analysis, it should be easy to refresh this data in an ongoing fashion as your business grows.
Daasity is transforming the way companies access and use their data. It is the first and only eCommerce analytics company purpose-built for the direct-to-consumer industry that makes business-critical data accessible and usable for strategic decision-making. Daasity’s mission is to make business-critical data accessible for all DTC brands.