Text Information Analysis

 

Using text analytics to get a 360° view of customer

Organizations often have multiple touch points with the customer that occurs across the organization, through sales, support, warranty and accounting interactions. The “Voice of Customer” is spread across call centre Logs, web-chats, complaints, feedback, survey among others.

A true 360 degree view of customers requires combining the customer’s feedback, experiences with the hard data. According to a survey by E&Y – “Poor Customer Experience” cost US companies USD 40 billion a year. Another survey by genesys telecom in 2013 suggested that poor customer service cost the United Kingdom’s businesses a total of £15.3 billion every year. Customer complaints or feedback about service are the most important places to start with.

Text captures deep and broad business value in ways that numbers and record-based computing systems designed to process transactions cannot. Text contains factual, qualitative, and subjective information not present in conventional data systems and analytical data warehouses. This data is difficult to analyze as it is voluminous and unstructured in nature. Though the effort is challenging it can be truly rewarding.

 

Leveraging complaint-data to strengthen customer- experience

Customers leave their footprints in the form of calls, written complaints on public websites, blogs or in guest books. Given that they cannot be quantified or made actionable till they are analyzed, categorized and cleansed – the complaints department may see little traction. This results in customer dissatisfaction and likely customer defect. The operations risk management department needs to look beyond traditional low frequency/high impact risk. Getting early and better risk signals can offer insights into customer behavior and process modification.

With the emergence of the Consumer Financial Protection Bureau (CFPB) in the united states and the FSA’s market -conduct successor –the Financial Conduct Authority (FCA) in the united kingdom, policymakers and regulators have made clear their intention to more proactively ensure “fair” treatment of consumers and other bank customers. It is therefore becoming even more important to track “Customer Speak “– especially regulatory specific complaints

Understanding customer-reviews

In the hospitality industry – there are specific ways in which customer expresses his/her experience. It is a known fact that – Hotel reviews drive the occupancy or price by a few percentage points and affect profitability. Though the percentage of reviews to those who are customers may be less – the impact is far reaching. An organization cannot afford to ignore this.

 

According to research from the international marketing firm of PhoCusWright – 80 % of respondents reported that reading reviews on TripAdvisor made them "feel more confident in their travel decisions," and "it helped them experience a better trip." A Model can be established to predict customer- loyalty or provide advance warning for corrective action.

How Can Ixsight help in providing this combined view?

Ixsight uses text analytics to turn your unstructured data into structured data. The process includes the following:

  • Compiling, analyzing and summarizing data
  • Semantic processing – in context of target domain
  • Mapping semantics to a known ontology for target domains – banking, food, travel etc.
  • Qualitative modelling & sentiment analysis
  • Report findings by exploring emerging issues, top themes, customer sentiment and more
  • Identify the top 5 themes or big picture