Customer Intelligence

What is customer intelligence?

By
Steve Hazelton
September 27, 2022
5 min read

In today's increasingly competitive business landscape, you and your team need every possible advantage to help you stand out.

From analyzing customer data to perfecting the customer journey for your users, there's no shortage of things to do to give yourself an edge. Today's most successful businesses continue to turn to customer intelligence to help them improve their products and services and to implement an effective business strategy.

In this article, we'll answer the question: What is customer intelligence? As well as show how customer intelligence can be instrumental in improving customer loyalty, customer experience, and more.

What is Customer intelligence?

Customer intelligence is the process of collecting and analyzing customer data from internal and external sources. It plays a critical role in unlocking customer insights. 

Customer intelligence (CI) covers everything from interviewing your customers and asking for direct feedback to looking at your data to know where there's room to optimize your funnel. 

The customer intelligence process is not something you can check off your to-do list and call it a day. Instead, it's a never-ending process that will keep you competitive. 

How to turn customer data into actionable insights

When a customer emails you, "Hey, can you add this feature?" they want you to use that data. In a perfect world, you could implement any feature a customer requests. Still, as you likely know all too well, resources are limited.

To make matters worse, ensuring the data gets to the right team can take time and effort. Collecting data is easy, but turning that data into insights is the challenge. Unstructured data is one of the biggest challenges teams face today.

It's not like your email messages have a data field that tells your engineering team, "Hey, build this." 

At smaller companies, you can get by manually recording this information with rules like "Hey, if something important happens, log it in Salesforce." 

At larger companies, this doesn't work. 

The conversion of unstructured data to useful data is the most challenging part and where you can reap the most significant benefits. Turning unstructured data into helpful info is one of the most critical parts of a successful customer intelligence strategy.

Today, many organizations are getting hundreds, if not thousands, of messages daily. And virtually none of that data is converted to easy-to-use insights automatically. 

Cracking the customer intelligence code: "turn noise into music."

Imagine if all of the customer data across your company was working together (including your black holes, like email). Imagine the efficiency your organization can achieve when you're not only collecting relevant data but you know exactly what steps you and your team need to take. 

This is customer intelligence at its finest.

If your best customer posts a bug, it might not be a big deal. If your best customer complains about a bug in chat, email, and ticket system, well, someone better take a look.

Before the emergence of customer intelligence platforms, this type of identification and triage was almost impossible, which is one of the biggest reasons we created Sturdy.

Analyzing customer data to win big with your business

We should continue doing everything possible to mine our customer communications and develop strategic customer signals. Yet, many companies know more about their anonymous website visitors than their paying customers. 

Truly understanding the customer journey of your customers from start to finish can pay massive dividends down the line. Understanding customer behavior and customer signals and being proactive in finding your users' pain points can dramatically improve the health of your business.

Virtually every company has a way to track and monitor its website visitors—something we like to call table stakes. Yet, almost zero have any way to monitor and monetize the happiness of their actual customers.

Here's a challenge...

Answer this: If your company was about to lose a customer, who would be the best person to save that customer? What metrics would you use to support your answer?

Most companies need customer intelligence data to answer this question.

Let's take it one step further.

How many times did a customer say, "You guys are great!" last month? How many times were those happy customers converted to references and case studies? And how many of those references are delivered to your sales team to help them close new business?

Again, it's the 21st century.

We realize the challenges of customer intelligence are great.

But in this area, failure is unacceptable. To have a truly operationalized customer-focused company, you need to mine these communications without bias and without manual data entry.

You need something that never gets tired, doesn't need training, and gets better as you throw more data at it. And most importantly, you can't wait until the quarterly business review is complete with triaging a churning customer.

Customer intelligence solutions are the answer to staying relevant in today's business world. And here at Sturdy, we are on a mission to help businesses deliver better products, services, and experiences through actionable data.  

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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.

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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?)

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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.

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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:

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  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.
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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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