Sturdy Signals

What is a customer Signal?

By
Joel Passen
July 7, 2021
5 min read

Customer Signal
(noun) a gesture, action, or transmission delivered intentionally or unintentionally by a customer that conveys information, instructions, or insights. 

Customers send Signals that help us predict churn, capture references, get in front of renewals, prioritize features, and just run our businesses better. Our customers are giving us this information in Slack, Email, Salesforce, Webinars, training sessions, quarterly business reviews, Zoom calls, etc. 

For B2B SaaS businesses, these Signals are immensely valuable. For example, reducing churn from 10% to 9% in a $10 million ARR business means that every customer is worth $17k more in lifetime value (500 customers, $20k annual contract value). And reducing churn in this example is saving just five customers a year. 

Examples of customer Signals

Identifying, classifying, and escalating customer Signals to the right people at the right time empowers companies with information and insights to preempt issues before they spiral and seize revenue opportunities to improve the bottom line. 

For example, when a customer asks, “Can I have a copy of our contract?” in a support ticket, a Signal is sent. In a SaaS environment, the customer is likely signaling risk. Maybe they are evaluating a competitor. Maybe there has been an executive change or a shift in priorities. Regardless, every SaaS leader will agree that this signal needs to be escalated so action can be taken. 

Below are a few other examples of customer Signals. This is not an exhaustive list; every company will vary on what is important. An interesting exercise is to sit down and list out the Signals that your teams should be watching for. The output of this exercise can be used to improve operations, user experience, training workflows, and more.  


Examples of customer Signals

Where to find Customer Signals

Most of us have given our customers the ability to communicate with us using a variety of channels. After all, we want to hear from them. This allows us to gauge their health, status, and likelihood of buying more of our products and services. 

Given the prevalence of multi-channel communications workflows, critical Signals are often trapped in layers of technology across multiple teams, gathering digital dust. The most common scenario for most businesses is that important customer Signals are hiding in plain sight. They’re trapped in email accounts, ticketing systems, call transcriptions, chat logs, and CRMs. And for most of us, the only way we utilize this information is if someone manually identifies, records, and escalates it.

How to use customer Signals 

In today’s competitive SaaS environment, the most successful companies are learning to “listen” and interpret the Signals that their customers are giving them about their products and services. The category-leading companies are doing this at scale - automatically. 

With SturdyAI, teams can easily sign up for alerts on specific Signals, accounts, and even competitor mentions. For example, the most appropriate team member in any group can get an alert whenever:

  • One of your customers requests a copy of their contract or asks about their renewal date
  • An account has a new executive, point of contact, or executive sponsor
  • A user asks for information about adding more users or adding a new product or service
  • One of your customers mentions one or more of your competitors
  • A user reports an outage or bug
  • A customer is signaling satisfaction and, ultimately, referenceability

What’s exciting about customer Signals

Customer Signals undoubtedly help us understand our customers better. Specifically, by defining and leveraging Signals at scale, we can have a clear understanding if our products are delivering the value promised at the time of the sale. We can also better understand if our customers are willing to grow with us or if they are growing away from us. 

Rapid advancements in technology, especially AI, are making it easier to help brands quickly and responsibly use data to understand customer behaviors and predict customer needs. When we have the ability to discover new patterns and insights in our data, we are better able to anticipate future decisions. In the end, harnessing customer Signals presents opportunities—and incentives—to deliver better service and find new ways to grow.

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Our data scientists have combed through mountains of unstructured customer usage data to crack the code on proactively identifying accounts that are a churn risk. After analyzing thousands of signal combinations, we found that four key indicators—Budget Issues, Unhappiness, Value Issues, and Urgency—are the ultimate predictors of revenue risk.

Nearly every B2B tech and services company sees the same pattern: when these signals align, it’s time for action.

Hold on, what is unstructured usage data? It’s the raw, untamed data that tells you what customers are *really* doing and saying—not just what they’re willing to admit in a survey or conveyed by numbers of daily average logins (also critical but lacking context). Here are the harbingers of risk; when combined, they are what the team needs to act on right now. 🧯

1️⃣ Budget Issue: This signals a customer struggling to justify the cost, possibly due to tighter budgets or a perceived lack of value.

2️⃣ Unhappy: Customer dissatisfaction can stem from unmet expectations, unresolved issues, or lack of engagement.

3️⃣ Value Issue: If a customer doesn’t see the ROI, they’ll start questioning the worth of your service.

4️⃣ Urgent: An urgent flag indicates an immediate problem that requires rapid action. They are expressing a need to engage with a teammate now.

Customer Retention

Improving Revenue Retention in 2025

Joel Passen
November 15, 2024
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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.

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

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