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The Secret Sauce of CX

Customer intent is a treasure trove of actionable data hiding in plain sight

Two employees studying a wall of charts and graphs

Every time customers interact with a customer service representative, do a keyword search, click through a brand’s website, or engage other touchpoints, they’re giving hints about their interests and intentions. The companies that understand customer intent—the purpose or reason behind a customer’s behavior—are better positioned to give customers want they want and outperform competitors.

Insights into what customers want and need are more important than ever as the economy and market conditions change. Businesses are eager to unlock insights that can help them adapt to change and reengage customers.
According to IDC analysts, businesses were estimated to have spent $215 billion in 2021 on big data and business analytics solutions, a 10% increase over 2020. By 2025, smart workflows and seamless interactions among humans and machines will be as standard as the corporate balance sheet, and most employees will use data to optimize nearly every aspect of their work, predicts McKinsey & Company. At the same time, data models for understanding customer intent and other insights are not infallible; even data-driven companies are a constant work in progress.
What is customer intent?
Customer intent is defined as the reason or purpose behind a customer’s actions or behavior towards a brand. It looks beyond the superficial factors such as what customers are requesting or where they are requesting it and focuses on the customers’ true goals for the interaction. Detecting and understanding customer intent can give brands clarity into what a customer is trying to do beyond what they are saying or clicking on, whether it’s an upsell opportunity, a chance to deepen the customer relationship, increase customer retention, enhance a product or service, or something else.
“Oftentimes, the user experience developed by a company for its customers overlooks critical components of the underlying intents the customer wants resolved through their customer experience (CX),” says Ravi Bharadwaj, executive director of corporate strategy at TTEC. “By looking at the CX lifecycle though granular intents, companies can 1) benchmark where they are strong/blemished, 2) identify where a human touch in a contact center helps/over-indexes the needs of a customer, and 3) solve for customers’ CX needs with surgical precision.”
For example, based on millions of customer interactions (contact center inquiries over calls, chats, bots, searches, etc.), TTEC identified the top reasons (intents) customers contact companies across different industries for customer support.
What the company found was that refund and replacement inquiries were most common among industries such as retail, public sector, automotive, and manufacturing. And inquiries about loyalty rewards were common across nearly all industries — retail, public sector, automotive and manufacturing, travel and tourism, insurance, finance. .
These insights can help companies better train their customer support teams and ensure they’re equipped with the right information to meet customer needs. Having the right information on hand also reduces wait times, costs to serve, and increases customer satisfaction.

Better insights = happy customers
Luke Lee, CEO of PalaLeather, a fashion company and retailer, agrees that customer insights are essential. “Businesses will be able to foster customer-centric innovations once they truly understand their audience' wants and needs,” he says. “In doing so, companies must work backward to solve their customers' pain points, then move forward with technological innovations that are in tune with the changing times.”
One of the ways that his company is improving its customer experience, particularly in the digital space, is by providing greater personalization through automation and marketing analytics, according to Lee. The company is “utilizing software that documents the customer or audience journey on our website and we continuously work on tweaking our processes with the help of our customers in shortening the marketing funnel and maximizing conversions,” he says. The company is also using digital marketing strategies such as search engine optimization (SEO), link building, and pay-per-click (PPC) marketing to strengthen its brand. “Businesses can capture a wider range of audiences if they work on putting a more personal touch side by side with automation and predictive analytics today,” Lee says.

The value of transparency
Numerous industries benefit from insights into customer intent and preferences. Apparel companies Stitch Fix and ThirdLove are two examples of companies that tout their use of data analytics and artificial intelligence in their services.
“Our business model enables unprecedented data science, not only in recommendation systems, but also in human computation, resource management, inventory management, algorithmic fashion design, and many other areas. Experimentation and algorithm development is deeply engrained in everything that Stitch Fix does,” according to the company’s website.  

ThirdLove, an intimate apparel company, makes a similar claim about using data to “inform any decisions we make, from the images we use in marketing campaigns to the colors we offer in new product lines.”
But even companies that develop a system for collecting, parsing, analyzing, and visualizing data, may find that the data is not enough. Before customers receive clothing from Stitch Fix, the company sends an email with a preview of the box’s contents that customers can curate. RetailDive reports that the preview email is generated by an algorithm, although customers are under the impression that the clothing was selected by human stylists. If customers complain about the selection, the stylists are directed to take the blame for the errors, according to RetailDive (Stitch Fix did not immediately respond to a request for comment).  

Even data-driven approaches have flaws and it would behoove companies to be transparent about potential shortcomings. “Data leaders appreciate that the data journey is a transformation effort that unfolds over time,” writes Randy Bean, author of “Fail Fast, Learn Faster: Lessons in Data-Driven Leadership in an Age of Disruption, Big Data, and AI” in Harvard Business Review. “Data-driven companies recognize that success is achieved iteratively…successful organizations expect to be at this for a while.”
While companies face pressure from investors, customers, and other stakeholders to deliver the right product or service every time, transparency and managing expectations are important for the success of any long-term initiative.
A work in progress
Customers have long told businesses what they need in their actions (or inactions). Companies have an opportunity to truly listen to their customers and better engage. Understanding and leveraging customer intent is part of a data-driven culture that can foster continuous improvements to create differentiated customer and employee experiences—if companies are ready to let their customers lead.