Customer Intelligence

Sturdy raises $3.1 million to strengthen its AI-led customer intelligence and automation platform

By
Joel Passen
June 28, 2022
5 min read
SturdyAI raises $3.1m to broaden awareness of Sturdy, the AI-powered customer intelligence and automation solution.


We are excited to announce that we’ve raised $3.1M in a financing round led by Lawson DeVries at Grotech Ventures. We'd also like to welcome Lawson to the board of directors. He brings over 20 years of software-focused venture investing and management experience with him.

Read the full press release here.

The idea for SturdyAI came from running SaaS businesses for the past 15+ years.

Our “Aha!” moment was when we realized that our customers were actually telling us what they want and need, every day.

The idea for SturdyAI came from building, bootstrapping, and scaling successful SaaS businesses. While running companies we realized that there is an ever-growing body of valuable data being created by our users. This feedback is just sitting in email accounts, in video conferencing systems, in chat logs, and buried in ticketing systems. We founded SturdyAI to empower businesses to solve problems that we faced as entrepreneurs and executives. At the end of the day, running a SaaS company is about keeping customers and taking advantage of the long tail of subscription revenue.

With the subscription business model reaching near ubiquity in many industries, particularly in cloud-based software, driving dollar retention (NDR) has evolved as the most important business metric. Companies with higher dollar retention are simply healthier and more valuable. So how does a subscription-based business drive dollar retention? Our earliest decks talked about, “getting your data in one spot”. But that wasn’t the problem we were trying to solve (wanting to see all the data in one spot is a symptom, not a solution). The problem wasn’t really a communication problem, it was a mining and refining problem. The problem we solve is separating the signals form the noise.

When a customer requests a copy of her contract, that message must get forwarded to the "Saves Team" - immediately. Save a customer — improve NDR.

Customers give us information to run our businesses better, to predict churn, to capture references, to get in front of renewals, to prioritize features, yet these critical signals are trapped and decaying in dozens, if not hundreds of data silos. Our customers are giving us the "answer to the test" in Slack, Email, Zendesk, Salesforce, Gong, Zoom, etc. Today, the only way we utilize this information is if someone manually identifies, records and escalates it.

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. And reducing churn in this example is just saving 5 customers.

Today's CX stack is missing a systems of intelligence. Sturdy fills the void.

Greylock's Jerry Chan may have coined the term system of intelligence. He wrote about the category in 2017 saying that "What makes a system of intelligence valuable is that it typically crosses multiple data sets, multiple systems of record." He actually predicted that SturdyAI would exist — "The next generation of enterprise products will use different artificial intelligence (AI) techniques to build systems of intelligence."

SturdyAI is a system of intelligence that bridges the gap between systems of record and systems of engagement.

SturdyAI’s customer intelligence and automation solution empowers B2B SaaS companies and other subscription-based businesses to: 

  • Unify all sources of customer feedback like email, tickets, chats, call transcripts, surveys, and more, into a unified channel.
  • Analyze all customer feedback for important business insights like churn triggers, contract requests, buyer changes, feature requests, quality of service issues, and more that help lift dollar retention (and more).
  • Create just-in-time automations to drive insights to the people, teams, and systems that need them most to enable immediate actions.

Here's how it works. SturdyAI reads every email, ticket, call transcript, chat, and more to discover signals that impact relationships and revenue. Critical signals are then automatically delivered to the people, teams, and systems to take the next best action.

We're just getting started.

We aren’t here to reinvent and change the way teams or companies work — necessarily. And that is what is so exciting about what we do. SturdyAI is the force multiplier for your business. If you already have a cutting edge BI tool, we just give it better data. If you have a good CX app, we make it more insightful. If you have spent years perfecting your customer health score, we have a new data source to make it more accurate. If you have a great Customer Success, Account Management, Operations, Marketing, and Product teams, we make them more efficient and provide them with better data.

SturdyAI's customer intelligence and automation solution empowers teams to run a data driven customer operations strategy. This is a screenshot of the Sturdy Home Page.

“SaaS companies collect a ton of information from their customers every day, but much of it fails to convert to useful and actionable data. Now using AI and automations businesses can proactively understand whether their customers are likely to churn, which features will entice them to renew, are they experiencing bugs, are they happy or not, and much more.,” said Lawson DeVries, Managing General Partner, Grotech Ventures. “Customer retention and expansion are critical for SaaS businesses to maintain consistent growth trajectories, especially as we head into a more challenging environment for acquiring net new customers. Actionable customer intelligence is no longer a nice-to-have aspect for companies of all sizes – it is mission critical for businesses to thrive in today’s market. Grotech has a long history in this segment of the software market, and we are proud to be a catalyst to help fuel Sturdy’s continued strong growth and bring AI to companies that will need to do more with less now and in the future,” continued Mr. DeVries.

“Churn doesn't happen in a vacuum. It's a culmination of bug reports, feature requests, executive changes, response lags, unhappy sentiment, and more. Sturdy discovers the preemptive signals that help teams create more enduring relationships to lift dollar retention.,” said Steve Hazelton, CEO and co-founder of SturdyAI.

“Every SaaS company has a customer database of record, some have systems of action like customer success platforms but the critical component that most companies lack is a scalable system of intelligence — a system that listens to all of your customer feedback and routes the important things to the right people in the systems that they use every day. That is why we built Sturdy.”

Interested in learning more about SturdyAI? Get in touch.

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Improving Revenue Retention in 2025

Joel Passen
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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
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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
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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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