From Cost Centre to Competitive Edge: How Contact Centre Data Drives Strategy

Why is the department with the most direct customer contact so often the least leveraged for strategic insights? Contact centres have long worn the unflattering label of “cost centres” – departments that consume resources without directly generating revenue. But in reality, they’re gold mines of rich, unfiltered customer data flowing in through thousands of interactions daily.

Contact centre management has always been about operational efficiency. More so than most other business functions. The pressure to keep cutting costs while improving average handling times and first-call resolution rates forces leadership into bad habits. It creates a race to the bottom, where service quality always suffers.

Hiring undertrained staff to free up resources, implementing overly rigid processes to keep calls short, moving operations offshore for cheaper labour. Managers are pushed to do all this as pressures rise at the expense of business impact. However, employing under skilled people to represent your brand and imposing unrealistic time constraints on complex customer issues leads to poor customer experiences. Those experiences damage customer loyalty and brand perception. And when people stop buying from and advocating for your company, revenue drops fast.

Some ambitious organisations are bucking the trend, realising their contact centres have unique characteristics that make them invaluable business intelligence sources. In fact, contact centre data shares the same traits as what analysts call “big data” – valuable information not just because of its size but also the richness, variety, and speed at which it’s collected. These traits are often summed up as the ‘four Vs’ of big data’:

• Volume. Contact centres process thousands or even millions of customer interactions annually. It’s an unparalleled sample size dwarfing surveys, focus groups and reviews.
• Variety. They handle interactions across multiple channels (e.g., calls, social media and live chat), collecting feedback from diverse customer segments.
• Velocity. Their data flows continuously in real time, not annually from organised focus groups or intermittently via reviews. Businesses can spot emerging trends instantly.
• Veracity. Contact centre interactions capture authentic, unfiltered customer sentiment rather than carefully considered survey responses.

So, where traditional research methods often provide planned feedback, contact centre interactions capture customers in the moment (velocity), expressing their real frustrations and desires without the polish of considered responses (veracity).

The more customers they have, the more data they generate (volume). And the more channels available, the more diverse the feedback (variety). In other words, you get to learn what your audience really thinks about you, your product and your service. Good and bad. And those unfiltered truths are precisely what you need to make improvements.

AI Unlocks the Full Potential of Contact Centre Data

As businesses begin to unlock the untapped value of contact centre data, advancements in artificial intelligence (AI) are making it much easier and more cost-effective to harvest, analyse and act on all this information. That’s supported by the prediction that sales of conversational intelligence software will rise at a CAGR of 8.2% over the next 10 years.

For example, platforms like Tethr and TTEC offer AI-powered analytics that turn their clients’ customer service conversations into intelligence. This way, teams can spot pain points, monitor agent performance and uncover trends.

Meanwhile, candidate assessment tools apply AI in a different but equally powerful way. How? By analysing contact centre conversations to evaluate soft skills like empathy, active listening and problem-solving.

This helps users identify the right talent faster, reduce hiring bias and improve contact centre performance – all using insights gathered through natural language processing (NLP) and real-world customer service scenarios.

Beyond Customer Service: 5 Practical Applications of Contact Centre Data

Having contact centre data is one thing. You must also know how to apply it to improve brand awareness, perception, sales and retention. Here are five solid use cases to get you started.

1. Product research and development (R&D)

Your product team could spend months guessing about features to add or issues to fix, struggling to draw inspiration from forced survey responses and isolated feedback. Or they could tap into thousands of honest customer conversations that precisely call out pain points, bugs and improvement opportunities.

This data-driven approach removes uncertainty from development decisions. It equips teams to prioritise improvements based on consensus rather than speculation. Meaning they make products and services better for most users, not just a few. For example, excessive packaging was a common bugbear for Amazon customers, who often complained through support channels.

So, in true “you spoke, we listened” fashion, the company began public efforts to minimise packaging waste. One Amazon post reads

“We know customers care about the packaging used to ship their Amazon orders. Customers want orders delivered in right-sized, easily recyclable packaging that makes sure the product arrives in great condition, and minimizes its impact on the environment. At Amazon, we care deeply about our packaging achieving both of these goals, and we have teams of scientists and other experts who are constantly working to reinvent how products are shipped for the good of customers and the planet.”

The retailer ultimately turned a common complaint from its support channels into a better product, while showing off its customer-centricity (check out the bold phrases above).

2. Sales, marketing and support effectiveness

Contact centres capture the authentic voice of the customer: recording how people naturally describe their problems, needs and desires in their own words.

“I hate it when…,” “This feature doesn’t help me…,” “I need to be able to…,” “How do I…”

Forward-thinking organisations leverage these honest, unfiltered conversations. They uncover hidden pain points to address and hear objections that kill potential sales before they happen. That data gives customer-facing teams a powerful head start.

Salespeople can get in front of issues their competitors don’t know about. Marketers can make content more relevant and customer-centric. And support staff can tailor their approaches to specific needs without any delay.

Not so long ago, Wired reported on companies using AI to interpret tone in customer calls. More specifically, it explained how insurer Metlife used Cogito’s technology to analyse callers’ stress levels, frustration and satisfaction in real time. It meant teams could understand how customers feel much sooner, so they could quickly personalise support.

Frequently asked questions (FAQ) pages are another simple but effective way of using contact centre data to win over new customers. Record the most common topics from sales and support conversations, then use your content to address them head-on.

3. Operational excellence

Every process improvement opportunity gets voiced during contact centre interactions. Every single one. If customers struggle with your website, they’ll tell you why. If delivery times disappoint them, you’ll hear about it. If your returns policy isn’t crystal clear, they won’t hold back. These conversations unearth operational inefficiencies you might never spot internally. And once you start capturing them systematically, patterns emerge.

You’ll spot friction points throughout the buyer journey. Processes so confusing that they drive staff and customers mad. Workflows that create needless delays. The earlier you know about these problems, the sooner you can fix them to make your business leaner and more profitable.

4. Fully-informed training and hiring strategies

Contact centre employees’ skills and performance data can identify which characteristics correlate with positive customer outcomes, making it a valuable asset for workforce planning. By layering this data into global employee tracking systems, companies can quickly learn which communication styles or problem-solving approaches lead to the best customer satisfaction scores—and then hire and train their teams accordingly. For example, skills-based hiring assessments help teams spot which traits really matter on the job.

Perhaps empathy drives higher satisfaction scores, while active listening leads to faster resolutions. Or maybe agents with strong problem-solving skills handle complex issues better than those who just follow scripts. With this insight, hiring managers can move beyond resume scanning. They focus on finding people with the communication techniques and de-escalation abilities that actually predict customer success. LinkedIn says focusing on skills can increase talent pools tenfold.

5. Strategic planning and emerging opportunities

Your contact centre doesn’t just solve today’s problems. It signals tomorrow’s challenges and opportunities before they arrive, allowing you to prepare. These daily conversations with customers:

• Are early warning systems for shifting consumer expectations
• Hint at competitor movements before formal announcements (e.g., mentioning hidden deals that other providers have offered them)
• Highlight emerging market gaps begging to be filled

They also showcase consumer trends that are still invisible to traditional research methods. When customers start asking about features you don’t offer? That’s market intelligence money can’t buy.

T-Mobile’s “T-Action” program is a great example. In one year, the comms company gathered over 3,000 employee ideas based on frontline customer interactions, addressing 60 pain points and implementing 150 new ideas. Those contact centre insights drove more than 800 experience improvements, making T-Mobile’s offering more appealing and profitable. That’s how you turn customer feedback into tangible business value.