Almost 20% of businesses reported losing customers due to incomplete or inaccurate data. This underscores a pressing issue in today’s data-driven world: the need to look beyond mere numbers and truly understand the human stories they represent to avoid customer churn.

Enter thick data, a qualitative form of data that captures the emotions, stories, and cultural contexts behind numbers. This concept was championed by Tricia Wang, a renowned data ethnographer, tech anthropologist, and co-founder of the consulting firm Sudden Compass. Her firm has been instrumental in guiding Fortune 500 companies and tech startups to infuse customer centricity into their strategies, unlocking unprecedented growth opportunities and customer engagement.

In a session at this year’s SX Live, “The Human Side of Data: Leveraging Thick Data to Understand Customer Experiences,” Wang delved deep into the value of thick data. She emphasizes that while raw data and quantitative analysis are crucial, they only tell half the story. By integrating thick data into customer data analytics, businesses can craft experiences that resonate on a profoundly human level, bridging the gap between support, product development, marketing strategies, and sales.

Businesses must move beyond mere data-driven decisions to thrive in today’s competitive landscape. They must embrace a holistic approach that values their customers’ nuances, emotions, and stories. By doing so, they foster customer loyalty and pave the way for sustained growth and innovation.

Thick data: The key to better customer data analytics

In today’s data-driven world, businesses are inundated with vast amounts of information from CRM platforms and other analytics tools. But while big data offers quantitative insights, it often lacks a human touch.

“More data does not automatically lead to better decisions, higher profits, or more customers,” Wang says. That’s because over-relying on quantitative data can lead to a “quantification bias.” This may cause businesses to only value what’s measurable, often overlooking the immeasurable.

By integrating thick data into customer data analytics, businesses can delve deeper into customer interactions and experiences, leading to more informed decisions in product development and beyond.

A prime example of the power of thick data is Andy Mooney’s observations in his role as the head of Disney’s consumer products division. In 2000, he noticed many fans dressing up as Disney characters during “Disney on Ice” productions. Once he recognized this behavior, Disney created a new business unit to sell Disney Princess merchandise, resulting in a staggering $3 billion in revenue each year.

As Wang explains, “You need real-world context to really understand what your data means.” While big data gives you the numbers, thick data tells you the story behind those numbers to ensure your business is truly customer-centric.

3 ways to leverage thick data for customer data analytics

Delving deep into the human side of data is paramount for companies aiming to foster genuine connections and drive meaningful engagement. Let’s explore some strategies for leveraging thick data in customer analytics and making decisions that resonate with the heart of your customer base.

1. Integrate big data and thick data

More than half of businesses worldwide use big data, like advanced and predictive analytics. But your customer data analysis journey shouldn’t stop there. By integrating thick data with big data, you will paint a more comprehensive picture of customer behavior and understand the stories behind your data.

Why is this integration so crucial? Thick data provides the essential context that makes big data actionable. It enables better predictive insights that will make your business more responsive to customer needs.

This requires a two-pronged approach:

1. Use big data to spot patterns and analyze trends.
2. Harness thick data to delve into the reasons behind those patterns.

For example, while your purchase history data points might tell you that a particular product isn’t selling well, thick data gathered through in-depth interviews or ethnographic studies might reveal that customers find the product’s user interface confusing or its advertising misleading.

This qualitative approach provides rich, contextual insights that help your business not just react to trends but understand and empathize with your customer base.

2. Prioritize insight-driven decision-making

Insights dive deeper into why your data matters. “Data gives you the ‘what,’ but insights give you the ‘why,’” Wang explains.

While data-driven decisions are rooted in numbers and patterns, insight-driven decisions prioritize understanding the emotions, motivations, and contexts behind those numbers. This approach is crucial for businesses aiming to resonate with their customers on a deeper level.

Customer insights go beyond simple data collection and categorization. For instance, predictive analytics might tell you which product is trending, but thick data reveals why customers are drawn to it. By integrating both big data for pattern recognition and thick data for understanding the nuances, businesses can make decisions that are not only informed but also empathetic.

A classic example of the power of insight-driven decision-making is the online learning platform O’Reilly’s choice to reschedule an e-commerce conference. As Wang explains, O’Reilly noticed a significant drop in attendance, and they eventually connected with their support team to find out why. When going through their thick data, they quickly discovered that retailers reported being too busy preparing for Black Friday to attend an e-commerce conference in October. To increase attendance, they moved the conference to March, a slower time of year for retailers.

While data might have shown that a particular date was available and cost-effective, it was the insights about retailer preferences during Black Friday that led to the decision. This move ensured better attendance and engagement, proving that when businesses prioritize insights, they align more closely with their customers’ true preferences.

3. Invest in communication and collaboration

Rather than limiting data to technical teams only, businesses should promote a culture where insights derived from data are shared, discussed, and acted upon across all teams. In this cross-functional collaboration, be sure to focus on teams that interact directly with customers, like customer support.

The essence of this approach is to move beyond mere data-driven decisions and embrace insight-driven choices. Why is this shift so crucial? For starters, it ensures decisions are made holistically, valuing the insights of teams closest to the customers, like support and user research.

Wang points out that while various departments claim to understand the authentic voice of the customer, it’s often the support teams, those directly interacting with customers, who really grasp these nuances. Yet, ironically, they’re frequently sidelined in strategic decision-making.

“Oftentimes, it’s people with the least contact with consumers that often make the decisions to exclude the people with the most direct contact, which is the customer support team,” Wang says.

Fostering a culture of collaboration and open communication involves organizing cross-functional team meetings, encouraging discussions, and investing in what Wang calls “the 7 C’s”:

• Collecting
• Cleansing
• Classifying
• Culture
• Collaboration
• Communication
• Customers

Most companies focus only on collecting, cleansing, and classifying data. However, prioritizing the latter half of the list—culture, collaboration, communication, and of course, customers—helps you get more value out of your data.

That starts with leading by example. To create a culture where your teams incorporate thick data into their decision-making, you must first model that behavior and essentially permit people to do the same.

Jane Eggers, CEO of the AI-powered business intelligence platform Nara Logics, offers a compelling example of this approach in action: “Context is everything. It’s what makes our algorithms work. We believe the best way to get context is to get to talk to the subject-matter experts. We want to talk to the salesperson, the customer service team, and the researchers. We don’t start projects until we get to them.”

Unlock thick data to transform your organization

To truly thrive in today’s competitive landscape, companies must look beyond mere metrics and tap into the rich, contextual narratives that thick data offers, ensuring they meet customer expectations.

By investing in the support experience, companies can access this invaluable resource. Support teams are on the front lines, interacting with customers daily. They hear the concerns, joys, and frustrations firsthand. This direct interaction positions them uniquely to gather thick data, which can then be used to inform business decisions, refine products, and enhance overall customer satisfaction.

To learn more about the transformative power of thick data, watch Tricia’s keynote from SX Live.