Customer Retention

Stop doing these 3 things now to improve your customer retention strategy

By
Joel Passen
January 16, 2023
5 min read

Customer retention is the ultimate force multiplier in any B2B SaaS business. It involves building strong relationships with existing customers, ensuring they stay loyal to your brand, helping them use more of your product or service, and becoming advocates who bring in more customers through word of mouth. By investing in customer retention and ultimately increasing your customers' lifetime value (LTV), SaaS businesses unlock tremendous potential for growth and profitability.

Sometimes the SaaS world seems like alphabet soup. Lots of acronyms. As a reminder, Lifetime Value (LTV) is an essential metric for SaaS businesses. It measures the profitability of a customer over their entire lifetime of their contract or subscription. LTV provides an indication of how much revenue can be expected from a customer within any given point in time. 

Calculate LTV

Here’s how I suggest calculating LTV. First, determine the average revenue per user (ARPU). This is calculated by dividing total revenues by the number of users over a specific timeframe. Then, divide this result by the customer churn rate for that same period — this will estimate how long each customer’s subscription lasts on average. Multiply the ARPU and estimated lifecycle together to get your lifetime value. Doing so will allow you to accurately measure customer loyalty and help you devise meaningful customer retention strategies. 

Over the course of my career, I’ve learned that sometimes the best strategy is to stop doing something rather than create a new process. Making changes and implementing new processes and workflows can be time-consuming, lead to more complications, and cause confusion for your teams and customers. Simply put, here are a few things you can do to stop pissing off your customers because we can all agree that pissing off customers is a bad strategy.  

Stop ignoring customer feedback

Ignoring customer feedback is more than a mistake; it’s negligence. Customer feedback is the single most valuable thing a customer can provide — arguably more than their contract value. Insights about your products or services allow you to make improvements and create better experiences for every customer and every prospective customer. 

I’ve written about the perils of relying on surveys to capture customer feedback. So as a modern business leader, it’s high time you establish the channels to capture it and share it with the teams that can benefit the most. Have a system for everyone in your organization to access and analyze customer feedback — make feedback a collective reality. Democratize it. 

At one company where I served as the chief revenue officer, we provided hiring software to medium-sized employers, which helped them attract job applicants and manage the interview and hiring processes. We monitored customer feedback carefully. In fact, we monitored feedback so closely that it became a part of our culture and was more or less the genesis of my current company, Sturdy. 

In addition to fielding and responding to occasional issues and concerns about how our service worked, we identified patterns within the feedback: features that were missing, UI that was confusing, bugs that caused frustrations, coaching opportunities for associates, and more. These patterns in the customer feedback informed the creation of very focused rules of engagement and playbooks that ultimately increased our LTV. This lift in LTV helped us successfully sell that business to one of the largest payroll providers in the world. 

Stop overpromising

Whether the account manager said “yes” when they should have said “no,” or what they said was accurate until someone else messed it up, overpromising often comes back to haunt post-sales teams. Poorly aligned expectations leave everyone involved feeling disappointed and let down. This fracture in the customer-to-business relationship is one of the leading causes of cancellations. It’s also one that often goes undocumented or improperly categorized. 

Just as important as capturing the reasons why customers cancel, customer success teams should identify and document common trends and topics that indicate overpromises. By understanding the areas where false promises are made, you can enable customer-facing teams to consistently provide accurate information about the capabilities of your product and services. 

Shameless plug for Sturdy — Our AI looks for Signals of overpromises in communications with your customers. This Signal detects when a customer indicates a discrepancy between the product or service they expected and the one they received.

Here are some overpromise signals that were detected in customer-business emails. Sound familiar? 

"This is something that was promised in the implementation stage."

"… even excited about the features that were promised. But do feel ... underdelivered on the capabilities."

"Below is a list of things that were promised and hasn’t happened:"

"That was promised, but I still have not received anything."

"We can't use these services that were promised/promoted."

Stop doing Silly QBRs 

Ok. This may seem trivial and maybe even a little silly itself, but I can’t let this one go. For those unfamiliar with the term, a Quarterly Business Review (QBR) is a look into the performance and value of your service over the past quarter. The objective of a QBR is to identify areas of improvement and offer strategies for moving the relationship with your customer forward. As the name suggests, QBRs are typically conducted at least once per quarter and most often with a typical, boring format — a presentation on some slides.  The TLDR — 95% of the time, QBRs are awful. Personally, I loathe being on either end of them.

I suggest taking a page out of Customer Success Keynote Speaker & Educator Aaron Thompson’s playbook and turning QBRs into something meaningful for your customers. Use them as an opportunity to strengthen your relationship. Don’t just go through the motions. Here are some other tips from Aaron’s blog post on LinkedIn titled “Stupid Is As Stupid Does...And QBRs Are In Fact Stupid

  1. Make them a conversation, not a presentation.
  2. Come with more questions than statements.
  3. Don't get into SLAs, IRTs, or anything tactical. The topic du jour is their business strategy, and you are there to learn, not to teach. 
  4. Make them 50% retrospective and 50% prospective. 100% strategic still. 
  5. Get Creative. Much like Spotify's #Wrapped2019 (and 2020 and 2021) campaign, they demonstrate value to their millions of subscribers at the end of each year at scale.

At several of the companies that I’ve started, advised, consulted for, and worked at, we’ve used the ‘stop, start, continue’ framework. If you aren’t familiar, the ‘stop, start, continue’ framework facilitates retrospectives. The outcome is improving future work performance through open communication and collaboration. In that vein, if you stop doing these things that damage customer relationships, you will open up the possibility of developing deeper relationships with your customers based on trust and value. Implementing even one of these changes can significantly impact your customer retention strategy. Which of these are you going to commit to first? 

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Improving Revenue Retention in 2025

Joel Passen
November 15, 2024
5 min read

If improving revenue retention is a key priority in FY25, here is some food for thought. If you believe data is the essential foundation for improving retention, imagine the possibilities with 50-100x more data about your customers. Here’s the thing: Every business has this customer data, but 99% of businesses are sleeping on a data set that could change their business. It’s the unstructured data that’s sitting in ticketing systems, CRMs, chat systems, surveys, and the biggest silo by volume - corporate email systems. Most of us still rely on structured data like usage, click rates, and engagement logs to gauge our customers' health. However, structured data provides only a partial view of customer behavior and revenue drivers. Unstructured data—like customer emails, chats, tickets, and calls —holds the most valuable insights that, when leveraged, will significantly improve revenue outcomes.

Why Unstructured Data is Essential for Revenue GrowthImproving Customer Retention: Unstructured data helps businesses identify early warning signs of dissatisfaction, allowing them to create proactive interventions before customers churn. Repeated mentions of poor experiences, response lags, product-related frustration, and more in call transcripts, cases, and emails indicate potential churn risks. By identifying these trends while they are trending, businesses will improve retention.

Fueling Product Innovation: Let’s face it: Our customers bought a product or service. Post-sales teams don’t develop products and are limited in what they can directly impact. Product teams need more unbiased, unfiltered contextual customer data, and they need it consistently. Unstructured data provides real-time feedback on how customers use products and services. Businesses can analyze customer feedback from multiple channels to identify recurring requests and pain points. This data fuels product innovation and informs customer-led roadmaps that lead to higher engagement rates and more profound value. Developing products that directly respond to customer feedback leads to faster adoption, better advocacy, and a competitive advantage.

Identifying Expansion Opportunities: Unstructured data reveals customer needs and preferences that structured data often overlooks. Businesses can uncover untapped expansion opportunities by analyzing email, chats, and case feedback. These insights help identify additional products or services that interest customers, leading to new upsell or cross-sell possibilities. To drive immediate improvements in revenue retention, the key isn't pouring resources into complex churn algorithms, chatbots, or traditional customer success platforms—it's being more creative with the data you're already collecting. Start listening more closely to your customers, identify the patterns in their pain points, and share this knowledge with your peers who can improve your offerings. This is the year to start thinking outside of the box.

Customer Retention

Burton's Broken Zippers

Steve Hazelton
November 15, 2024
5 min read

Last year, I bought a pair of ski pants and the zipper fell out on the first chair lift. I called Burton, and they offered an exchange. New pants, first chair, same problem. Support informed me that I was required to return the pants for repair. The repairs would be completed after ski season. For the inconvenience, Burton offered me a 20% discount on my next purchase of skiwear. The next time I am in the market for skiwear that I can't wear during ski season, I will use that coupon.

I started my first business over 25 years ago. Since that day, I have lived in an almost constant state of fear that somehow, somewhere, things would get so broken that we'd treat a customer like this.

Let's be clear, no one who runs a business wants stuff like this to happen. Yet, it happens all the time.

If you run a software company, your engineering team will have usage tools and server logs to tell you when your product is "down" or running slowly. They can report which features are being used and which ones aren't. You'll learn that certain features in your product cost more to run than others, maybe because of a bad query, code, or something else. And you'll know what needs to be upgraded.

However, every time a customer contacts a business, they are "using" (or "testing") your product. If you sell ski pants, your product is ski pants, and your customer service team. If you sell software, your product is your tech and your customer service.

Yet, your customer-facing teams have very poor usage data, if any at all. Which feature of our service gets used the most (billing, success, support)? What are the common themes? Is one group working more effectively than the others? Does a team need an upgrade? 

(BTW, what costs more, your AWS bill or your payroll?)

The reason your customer-facing teams don't have usage data is because this data is "unstructured," and it is everywhere. Imagine if your engineering team needed to check 50 email inboxes, 1,000 phone recordings, a CRM, and a ticket system to get your product usage statistics. 

That's where your customer-facing teams are today. Until you can get answers from these systems as easily as an engineer can, you’ll continue to churn, annoy customers, and try to hire your way out of a retention problem. It won’t work.

AI & ML

Navigating AI Ethics

Joel Passen
October 14, 2024
5 min read

The question is no longer about whether you will use AI; it’s when. And no matter where you are on your journey, navigating the ethical implications of AI use is crucial. Ethical AI is not just a buzzword but a set of principles designed to ensure fairness, transparency, and accountability in how businesses use artificial intelligence. In the case of Sturdy, we’ve made ethical AI a core commitment. These principles guide our every move, ensuring AI benefits businesses without crossing the line into unmitigated risk.

What Is Ethical AI?

Ethical AI refers to developing and deploying AI systems that prioritize fairness, transparency, and respect for privacy. For businesses, this means using AI to make smarter decisions while ensuring that the data and technologies used do not cause harm or reinforce biases. The importance of this cannot be overstated—AI has the potential to either empower or exploit, and ethical guidelines ensure we remain on the right side of that divide.

Sturdy’s Commitment to Ethical AI

Sturdy's approach to AI revolves around several inviolable principles:

  1. Business-Only Data Use: Sturdy’s AI systems focus solely on improving how businesses make decisions. They don't delve into personal data or manipulate information for other purposes. The data processed by Sturdy comes from business sources like support tickets, corporate emails, or recorded calls—never from personal channels.
  2. No Ulterior Motives for Data: The data collected by Sturdy is knowingly provided by our customers, and the company doesn't use this data for any purpose beyond what's agreed upon. This ensures transparency and trust between the platform and its users.
  3. Privacy and Protection: One of the most critical aspects of Sturdy’s approach is its commitment to not allowing any entity—whether a business or government—to use its technology in ways that violate privacy. If a client were found to be doing so, Sturdy would terminate the relationship.
  4. No Deception: Our product is engineered to prevent deception. It never manipulates or deceives users, ensuring that the insights drawn from AI are used to enhance business practices rather than exploit loopholes.

Human Oversight and the Role of AI

At the core of Sturdy’s AI principles is the belief that AI should not replace human decision-making but augment it. Our Natural Language Classifiers (NLCs) are built to detect risks and opportunities based on the probability that a conversation indicates a particular issue. For example, when a customer complains about a "buggy" product, Sturdy’s AI might tag it as a "Bug" and label the customer as "Unhappy." However, humans remain in control—analyzing the situation and deciding the best action.

Final Thoughts

Sturdy's approach to AI exemplifies how businesses can responsibly use technology to drive growth and improve operations while safeguarding ethics. They demonstrate that AI doesn’t need to infringe on privacy or replace human decision-making. Instead, AI should be a tool that empowers teams, ensures transparency, and upholds ethical standards. Navigating the ethics of AI is not just a challenge—it’s an ongoing commitment, and Sturdy is setting a new standard for how it should be done.

How many customers will you have to lose before you try Sturdy?

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