Data is everything in the world of SaaS, but how can you be sure that you’re analyzing the right data and drawing conclusions that will help you refine your offerings and grow your overall sales? With the massive amounts of data headed your way, analyzing each customer individually is not only an exercise in futility, but would require staff time that you simply cannot spare for the benefit that you’ll reap. However, breaking your customers into cohorts—or groups with similar characteristics—for analysis can help you get your data into bite-sized and actionable chunks that will let you move the needle on your marketing efforts.
Going on Gut
For many marketers, gut instinct is something that drives a great deal of their decisions—we think that customers will like a certain offering, or behave in a certain way, so that’s how we tailor our goods and services. However, when this approach is no longer delivering the results that we need, breaking down the data becomes increasingly important. Numbers such as churn, customer acquisition cost and monthly recurring revenue can help you make more informed decisions on hard evidence; which can ultimately lead to higher revenue.
Making Sense of the Madness
With a SaaS business, the fire hose of data coming at you on a daily business can be overwhelming and cause paralysis. That’s why cohort analysis is so important. Defining your cohorts is the first step towards success, and most cohorts are defined as either time-based or segment-based; depending on your particular business and needs.
Time-based cohorts are simple: they are the customers who have signed up for a specific product or service (like a trial) during a specific period of time. This period of time could be a month, a block of several months depending on your sales cycle. What is important is that they’re all essentially having the same experience; starting out in a process, mid-way through with lots of questions, or getting ready to make a final decision at the end of the process. The same can be true of current customers—are customers who signed up in 2015 churning out faster than those who signed up in 2016? Maybe your product offerings aren’t keeping up with promises, or a new competitor hit the market and is targeting your customer base. These are all data points that you can react to, and create a plan to retain your customers.
Segment-based cohorts are those who may have signed up at any point in the past to test your product line, but maybe you have various service levels. Those who are interested in an enterprise-level system have very different needs than those who are with a small business. Understanding the needs of your different cohorts can help you tailor messaging directly to their needs, and keep you from sending push notifications that are not relevant and will eventually be ignored.
There is no one right answer for which type of cohort analysis to use for your business. Instead, you should look at how meshing the two together can provide you with deep insights into how your customers are interacting with your software and your sales team. By looking at time-based cohorts, you may notice a trend—that 85% of potential customers who are working through a free trial search your help documentation for a specific question two days into their trial. This gives you an opportunity to proactively provide them with the information that they need either on screen or via a phone call or email follow-up—making you the hero for anticipating their needs before they even knew they needed you!
Customer lifetime value is an important metric for SaaS companies—arguably the most important metric—especially with the soaring acquisition costs for each new customer. In order to get to profitability, many SaaS companies need to retain paying customers for at least 12 months and churn before that time is actually costing them money. However, with new and shiny software offerings coming on the market all the time, this core metric is increasingly difficult to achieve and maintain. Cohort analysis is one way to more effectively target companies before they give up on you—during a critical renewal period or when new competitors come on the market.
Best Practices for Customer Acquisition
Cohort analysis is a way of taking your buyer personas to the next level—creating a grouping of like customers and targeting your messaging to them in that way. For instance, if you’re offering a web design service you will have a different offering for businesses that already have a website versus those who are building their first site. If you’re able to successfully target your messaging to the larger cohort group, then you can meet people where they are in the sales cycle and provide them with the most effective messaging possible to close the sale.
Cohort Analysis Example
One of the most important things to understand about cohort analysis is that churn can overlap and lead you to some erroneous conclusions. For instance, in an SaaS business, churn is most likely higher in the first few months of a particular cohort’s lifecycle, and then it begins to average out as customers who stay for over a certain period of time tend to stay for at least a year or more. You have to look at each month’s new customers (a cohort) together, because in any one month you could have customers who are in Month 1, Month 3, Month 9 and Month 12 of their lifecycle. Averaging these together to get one churn rate is not appropriate; but if you’re looking at the customers by cohort, you can get a better idea about whether your overall churn rate is increasing or decreasing. When you look across the graph below, you’ll see retention over a user lifetime, while looking down the graph provides you with the change in retention over the product lifetime.
% of retained customers in lifetime month
Monthly Spending and Churn
Once you’ve acquired customers, it can become easier to slot them into segment-based cohorts based on how you see them use the software. It’s likely that you’ll have some customers who will come in gangbusters and start using the software every day, while you’ll have others who seem to log in once or twice the first week and then lose interest. The engaged customer is the one who is going to continue being a customer, so you have to find a way to re-engage a customer whose interest in your offering is flagging. By using segment analysis, you can create a series of triggered emails aimed at reeling your customers back in with content aimed at individuals in their portion of the sales cycle.
While cohort analysis is a great way to keep people engaged and involved, in order to be successful you have to have incredibly clean data or you risk alienating people by offering them messages that are not relevant. Imagine how frustrated you would be if your SaaS software service sent you a ‘Welcome’ message after you had been a customer for at least six months. That’s the type of customer experience you want to avoid at all costs. Start with the largest cohort groups and work your way up, testing and adding points as you go at a higher level instead of diving deep on your first try. Just like most digital marketing, trial and error and tweaking are what will deliver the most value to your organization over time.