Sharpen your Customer Insights with Unstructured Data

Customer Insights with Unstructured Data

“The most important thing in communication is hearing the unsaid.”

When Peter Drucker said this, I am sure he must be thinking about customer experience and communicating with customers.

Customer insight is about understanding the activities of the customer. Still, it is more about understanding what a customer ‘feels,’ ‘perceives,’ and ‘thinks’ and about influencing the customer’s ‘thoughts’ and ‘perceptions.’

Traditional techniques of customer insights include collecting and aggregating data in CRM, billing, and various internal systems and sketching a picture of the customer journey. However, this picture is always complete with tracking communication happening with the customer.

Thus, analysis of unstructured data, spoken and written by and about customers, is imperative for gaining a competitive advantage.

So, how can businesses gain insights from what is being said by and about the customers?

Here are some interesting examples I have observed and implemented for some clients in the last couple of years.

Before a customer becomes a ‘customer.’

Find out who are good customers.

The quest for customer insights should begin before a customer becomes a ‘customer.’ One of our clients uses social media sentiment and feedback about small businesses to decide credit worthiness and grant loans to small businesses. Not just this, they also find out who are the competitors of a business applying for a loan and solicit these competitors! Data available on social media about various small businesses is used as input for all this.

Product recommendation

Today’s customers covet personalized experience. Product recommendation is one of the best ways to provide a personalized experience. Many studies have proven that ‘Product Recommendations’ based on customers’ behavior and preferences give a great conversion rate. Amazon’s product recommendation mechanism has proven it time and again. Analyzing the footprints of customers in the shape of unstructured data can give immense information about their behavior and preferences. In creating a customer persona, with the help of unstructured data, businesses can recommend products that customers would love to see.

During the journey of the customer

Make customer service more reliable

“It is no longer enough to satisfy your customers. It would help if you delighted them.”, said Marketing Guru Philip Kotler. Various parameters of customer service can be improved by knowing more about the customer’s journey since the product purchase. Customer Call centers generate large amounts of recorded voice call data. Many call centers have started to analyze this data to find areas to enhance. Impeccable and reliable customer service can be achieved by analyzing unstructured data like voice calls.

Best fit product for a customer

Customer service call logs can be a great input to achieve product cross-selling. One of our clients, an enterprise IT Product Company, uses pain areas expressed in the customer service calls as input to recommend the best product suitable for the customers. Many intense customer service calls have resulted in reshuffling the product portfolio of the customers for this company.

Analyze customer sentiment

The customer is not happy about some issue; she sends an email, but the mail needs to be taken note of properly, the problem aggravates, and there comes a day when it becomes a serious escalation. ‘Oh! How did we not notice this? Who could have avoided this? ‘Sounds familiar? Unstructured data has a solution for this challenge.

Some companies are tapping email exchanges between a customer and support/technology teams to summarize topics being discussed, probable escalation issues, and predict when and which issue can cause an escalation. Senior management of an organization can monitor a simple half-pager report and ensure no landmines are being ignored! Yes, text analytics can predict if your customer is getting unhappy with you by analyzing your email exchange with your customers. Contact me if you want to see a demo of this application. Check out our Gadfly, created on the same principle as well.

Is this process of gaining customer insights by leveraging unstructured data too complex? Does it involve complex technology implementations? How can small businesses leverage the power of unstructured and big data to gain a competitive advantage?

Stay tuned for answers to these questions in the next few blogs.