"Increasing customer retention rates by 5% increases profits by 25% to 95%."
- Reicheld & Schefter, Harvard Business School
Have you ever been shocked to see a client discontinue their services with your firm?
Client retention strategy is critical in any line of business. It doesn’t matter if you’re B2C, B2B, or B2G. Gartner research has found that companies that prioritize customer experience have 60% higher profits than their peers. Even more importantly, customer experience investments have a 25% higher return than pure sales and marketing to existing clientele. The importance of client retention strategy is heightened for agencies, SaaS organizations, professional services firms, and other companies who operate based on recurring revenue and lasting relationships.
For an in-depth analysis of why you need to gain fluency in customer lifetime value (LTV), cost of customer acquisition (CoCA) and the intersection of these two metrics, we recommend Why Customer Retention is Critical to Recurring Revenue Businesses.
The Basics of CHI: What is a Customer Happiness Index?
One incredibly simple way to predict your client retention efforts before you’re dealing with churn is a client happiness index (CHI). Inspired by the Chinese word for lifeforce, this is a measure of your client’s satisfaction with your organization on a broad and individual basis.
Jonah Lopin, the former VP of Client Success at HubSpot and current founder of design repository Crayon, reports that CHI was developed to predict customer success. HubSpot’s CHI model looks beyond simple customer satisfaction surveying and Net Promoter Score (NPS) to include implicit data on customer behavior, especially whether customers are engaging with software in a way that will lead to successful marketing. HubSpot’s model includes a large number of factors, each of which has been assigned a different weight.
While customer engagement is a critical component of CHI, your organization’s customer happiness index doesn’t need to be nearly as complex as HubSpot’s. Simply taking the steps to begin measuring, acting, and responding to customer happiness can move your organization from a place where you’re reacting to customer dissatisfaction to proactively responding to your customer’s needs.
Benefits of Measuring Chi
The average highly satisfied customer tells 9 of their friends about their brand experience. However, the average dissatisfied person spreads their opinion to 22 people. Bad experiences are louder than good ones. In a very immediate sense, measuring CHI is positive PR. It allows your organization to salvage damaged relationships before they turn into negative online reviews or a damaged reputation.
Additionally, CHI is a tool for mass-management of personalized outreach. Smart organizations will automate ways of inviting their most-satisfied customers to participate in co-branding opportunities or client referral programs, while performing immediate outreach to the least satisfied buyers. By having a single, quantitative measure throughout your organization, you’ll gain an ability to take a more balanced approach to customer relationships.
Finally, your organization could benefit immensely from increased insights into customer priorities. Lopin reports that he was shocked to find that HubSpot customers who blogged had much better success rates than individuals who focused on social media marketing. By learning which of your customers are the happiest, you can gain insights into behavior that can inform your customer acquisition strategy, lead management, and onboarding processes.
Measuring CHI: How to Build a Customer Happiness Index
There is no single, universal measure of CHI. In fact, approaching an optimal measure can vary significantly between brands. If your organization is entirely new to the topic of customer satisfaction surveying, it’s best to start simply with a basic measure and then work towards building more complex models.
B2B analyst Andrew Dalglish writes that a very basic measure of CHI would encompass the following factors:
Satisfaction (Likert Scale of 1-10)
Loyalty (Measured in length of client relationship)
Propensity to Recommend to a Friend or Colleague/NPS (Likert Scale of 1-10)
Calculating CHI: Example Client Happiness Equation
For the purpose of illustration, we’ll assume that your organization has sufficient sales technology and client relationship oversight to measure your length of relationships as a percentile. The first client you signed would measure 100, since they’re in the 100th percentile of relationship length.
When applied in a concrete setting, the equation for a very simple index built on these three components could resemble the following.
Satisfaction Score (1-10) + [Loyalty (Percentile within Organization)/10] + Propensity to Recommend/NPS = CHI
When concrete numbers are added to this equation, it could resemble the following:
9 + (90/10) + 10 = 28
If your organization has a strong history of engagement with your customer relationship management software (CRM), you can build a more complex model of CHI based on real data from your most satisfied customers. You may discover that your most satisfied customers are likely to request weekly calls with your account management team, subscribe to your blog, or any other number of factors that can assist in the development of a sophisticated CHI index.
Responding to CHI Scores: Building a Client Response Matrix
Given that the maximum CHI a client could achieve is 30, this proverbial client’s score of 28 is quite good. For simplification, you could divide the final metric by 3 to score the outcome on a 1-10 scale, which is familiar for individuals with a background in customer satisfaction surveying, for a final result of 9.33.
Develop a response matrix for your CHI outcome. A basic CHI response matrix, which is heavily influenced by the NPS methodology, is demonstrated below:
- 9.0-10: Loyal Customers. Reward and Encourage.
- 3.0-8.9: Low Churn Risk, Require Additional Engagement
- 0.0-2.9: High Church Risk, Require Immediate, Personalized Outreach and Resolution
Treat Your CHI Like a Hypothesis: Improving Measures of Client Happiness
Even if your organization chooses to develop a highly sophisticated model of client happiness out of the gate, remember, this is always a hypothesis. Even HubSpot’s model of CHI is a hypothesis. Hypotheses require extensive testing to be accepted, and the results of experimentation can lead to significant modification of hypotheses.
Use data from your most and least satisfied customers to continually improve your measure of client happiness. While clients who leave your organization are a significant loss, be sure to engage in lessons learned. If their CHI measure didn’t fit your profile for a high churn risk, dig deep into their behavioral data to discover which factors you aren’t currently measuring could have lead to their departure.
Additionally, continue to adjust the relative weights of factors in your index until you’ve gotten the mix optimized. Perhaps engagement matters more than length of time as a customer? The only way to tell is application in a real-world environment.
Why Quantifying Happiness Matters
Even the most perfect measure of CHI won’t prevent customers from leaving your organization. Economic factors, leadership, and other separate variables can sever relationships between highly satisfied customers and their vendors. CHI isn’t a perfect measure of your organization’s ability to retain your clients over the long term, but it’s a very good one.
There are almost no downsides to beginning a systemic culture of measuring customer happiness and responding immediately. While the benefits of this practice will increase significantly if you work tirelessly to improve your model, even simple surveying can provide rich and critical insights. A customer-centric culture should involve personal relationships, but it should also involve quantitative measures of client engagement.
Does your organization’s client retention strategy include regular, quantitative measures of CHI? Why or why not?
image credit: moyan brenn/flickr cc