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The more, the merrier- a saying that doesn't apply to your holiday party but also to SaaS companies. Everyone is always looking to attract more customers, but how do you actually keep them?
Today, we're looking at customer retention - why it's essential and how you can improve it.
Customer retention (or just 'retention') refers to the ability of a company to maintain its existing customers and avoid having them "churn."
Customer Retention Rate - or simply Retention Rate - is the percentage of customers over a period of time that did not churn.
Customer retention strategy is the collection of activities that a company engages in to increase the number of repeat customers and ensure that existing customers remain loyal.
The goal of this strategy is for new customers to have a positive relationship with your company, with high customer satisfaction and greater customer loyalty.
You want these new customers to continue to renew their subscriptions and maximize their lifetime value throughout their customer journey.
Paying attention to customer retention allows you to track your customers' loyalty, identify any potential red flags that pop up along the customer journey, and turn customers into product evangelists.
Focusing on retention is also a great way to maximize profitability and increase the ROI of customers.
It's 5-25% more expensive to acquire a new customer than retain existing customers. Furthermore, increasing your customer retention rate by even 5% can increase your company's overall revenue between 25-95%.
Those retained customers are also more likely to remain loyal to your company, meaning they buy more and at a higher frequency than new customers just learning your product's value.
Plus, customers who have formed a long-term relationship with your company and understand your product's inherent value will be better advocates singing your praise and referring new customers to your product.
So how do you determine your company's retention rate to start reaping all these benefits? More below!
Customer retention rate is the percentage of customers retained over a specific period.
The basic formula for retention rate:
(Number of Customers at End of Period — Number of Customers Acquired During Period) / Customers at Start of Period] x 100
First, you must determine the period you're interested in understanding. It could be a month, quarter, or for the entire year.
Let's start with an easy example. Say you're interested in finding out your retention rate for the last year.
In January, you started with 50 customers; over the year, you added another 15 customers, and by the end of December, you had 60 customers.
Your customer retention rate for that year would be 90%- [(60-15)/50]x100. This means that 90% of the customers you acquired over the year remained with your company.
You can also compare retention rates across different time frames to help determine the success of new retention strategies.
For instance, say your retention rate for the first quarter of the year was 75%, and then your team decided to implement a new onboarding strategy for Q2.
All other things being equal, in the company, if your retention rate for Q2 was 83%, you could say the onboarding strategy positively impacted customer retention.
Although pinning down the exact impact different company efforts have on these metrics isn't always straightforward, it's still important to try so that you can track your retention and validate the success of different strategies.
This depends on many factors, including your industry, company maturity, and sales cycles.
Obviously, the best case scenario is that you retain 100% of the customers that sign your contract. That won't always be the case, though.
It's important to understand industry guidelines and benchmarks to ensure your company remains competitive.
Average customer retention rates by industry:
Industry benchmarks give you a starting place to understand where you fall in the market. From there, tracking and comparing your metrics to your past performance is good. This way, you can see where your company is falling short and where you have clear indications of success.
A data-driven retention strategy can have a massive impact if used properly.
However, due to the complexity of the analysis required, many companies don't always take full advantage of their customer data.
The challenge involved in tracking this data is that it involves combining information from multiple siloed tools across different organizations.
For many companies, contact and account information lives in the CRM.
Tickets, bug reports, and communications with the success team are logged in a customer success tool, and events and actions within the product are found in the data warehouse or database.
Combining this information, syncing product data with the CRM, and being able to identify behavioral signals in all that data is extremely difficult, especially without a dedicated data science and operations team to help.
In fact, McKinsey found that executive teams that extensively use customer data analytics across all business decisions see a 126% profit improvement over companies that don't.
Let's look at five common customer retention analytics companies use to track and understand how their customers move through the customer journey.
This is the most commonly used analytical tool.
Predictive analytics helps you predict how your customers will behave in the future. The behavior in question could include churn reduction or renewal risk.
Although the model is never 100% accurate, using data from past customer behavior and market trends allows the predictive model to be helpful for understanding likely outcomes that your team can proactively prepare for.
Prescriptive analytics is one step past predictive analytics. Where the predictive model only outlines potential behavioral outcomes, the prescriptive model prescribes - or recommends - a course of action based on that predicted customer behavior.
Where prescriptive analysis looks to the future of customer behavior, descriptive analytics focuses on understanding customers' past trends and behavior patterns.
Historical data are compared and contrasted to understand what behaviors are most common for a segment of your customers. This type of analysis is often used when comparing customer behavior month-to-month or year-to-year to uncover long-term trends.
The type of analysis is focused on understanding how your customers consume, or use, your product and what affect this has on your company outcomes.
The outcomes you are trying to optimize include sales efforts, marketing expenses, or improving customer engagement and satisfaction.
The general idea is that you narrow your focus to a behavior that may be unusual, like a particular industry purchasing software outside of standard renewal patterns, and then dig in to learn that the industry has new laws.
So you can take the learnings from that specific industry information to adapt sales and marketing tactics to increase buying potential for that group of customers.
Diagnostic analyses revolve around the why of customer behavior.
This could include looking into the why behind usage trends, churn analysis or even customer health analysis.
For instance, why do customers purchase one product over another, or did one segment churn?
Once you run a diagnostic analysis to help determine causal relationships for past behaviors and outcomes, you can better address future behavior.
For the most part, maintaining and improving customer retention falls under the jurisdiction of Customer Success Managers (CSMs).
Their main goal is to support customers transitioning from the sales pipeline (prospects) to the support pipeline (active users).
They're typically responsible for maintaining customer loyalty, upselling existing customers to new features within the product, fostering long-term relationships with their customers, and ensuring that their customers are achieving the goals they were looking to accomplish when purchasing your product.
Tall order, right?
And it all feeds directly into customers being happy enough with your product to be retained.
So what are some strategies CSMs can do to help improve customer retention?
The purpose of a customer loyalty program is to take a new or existing customer and turn them into a brand ambassador; someone who sings the praises of your company, generates referral business, and is willing to go to bat for you as a reference.
It is the apex of a customer relationship with your company.
There are three basic types of loyalty programs for SaaS companies:
And, remember: loyal customers are not always a good fit for a loyalty program, but members of loyalty program are almost always loyal customers.
Regarding retention rates, customer success teams are your company's main loyalty drivers.
They're on the front lines, solving fundamental problems and empathizing with customers to ensure they feel valued and happy with your product rather than frustrated and more likely to churn.
It's important for CSMs to be proactive with their communications to customers to set and manage expectations so they have a positive experience and are more likely to keep using your product over a long period.
Sales teams are motivated by their quota and can often be singularly focused on getting a new sale through the door.
However, when an acquisition strategy is not targeted and you don't narrow your market down based on ICP fit, you risk a much greater risk of churn when it comes time for renewal.
A customer journey map is a visual representation of the customer experience with your product.
It covers all the different touchpoints customers have with your product to outline customer motivations, key interactions along their journey, and areas of existing and potential product friction.
By understanding these events, teams can better address current issues and make product improvements for a smoother customer experience.
The happier customers are with your product experience, the more loyal and likely they are to be advocates for your company.
Collecting customer feedback in an explicit manner, like via Net Promoter Score (NPS) or Customer Satisfaction Score (CSAT), is useful. However, it doesn't tell the whole story.
In order to interdict a potential churn event, account owners need to have their finger on the pulse of a customer's product usage. Customer behavior within the product is a powerful indicator for this.
However, leveraging product usage data, combined with customer data from other sources in your tech stack, is a hard nut to crack for many companies.
Having the necessary tools and system in place to identify, track, and take action on behavioral signals will positively impact customer retention, decrease churn, and increase Net Revenue Retention
With the market for SaaS products more competitive than ever, your prospects and customers have many alternatives to using your software.
One of the most effective strategies is constantly improving your customer's experience by making the most of the user feedback they provide.
After all, they're the ones using your product every day.
In addition to improving your product, responding to your users' feedback will keep those users more engaged.
By showing them that you listen to their input and that your product is a living, constantly improving thing, they'll feel like a valued collaborator and want to stick with you to help your company grow.
While your customer retention rate isn't likely to drastically improve over night, you can put clear strategies in place to elevate your product over time.
Understanding the experience customers have with your product, setting expectations, and removing friction points are all ways to improve the relationship your customers have with your product.
By keeping customers happy and engaged with your product, you're increasing the likelihood that they will remain loyal and become a champion for your company. The dedication and hard work you put in for your customers will pay off in the long run.
