In our quest to providing an effective tech support environment to provide a superlative customer experience, it is vital to understand the opinions that our actual and potential customers express in new channels that are much more spontaneous and less structured than the traditional surveys. The reach, the immediacy and the “emotional” aspect (Yeah, it’s all about emotional intelligence, right?) of these channels make them an impressive source of raw materials for obtaining valuable insights that can then be correlated with the traditional data collected at the tech support centre.
For this very reason, businesses are expanding their VoC initiatives towards that new territory, with active analytics on unsolicited and unstructured comments that is derived out of contact centre interactions (voice, email and chat), Social Media conversations, Blogs and News, Comments from forums and third party sites. Gartner defines customer experience (CX) as the customer's perceptions and related feelings caused by the one-off and cumulative effect of interactions with a supplier's employees, channels, systems or products1. Customer experience is increasingly the single most important factor determining competitive advantage and differentiation for many organizations2. According to Gartner, while 95% of such companies surveyed collect customer feedback, only 5% close the loop by letting participants know what was done based on their feedback3.
By incorporating analytics around VoC program to provide active insights, businesses can not only improve their customer experience but their bottom line as well. A sound analytics framework around tech support (capable to handle big data & analytics) can ensure businesses benefit from the massive and quick treatment of unstructured information provided by text mining and sentiment analysis technologies. The end goal is to extract the meaning from all the customer interactions correlating to their products/services/markets.
With VoC, our core focus should be on aggregating such data collected on three main dimensions:
- Customer – eg: Detect support request patterns, identify the stage of “customer journey”, detect churn and other potential risks, identify influencers, promoters and detractors, engage customers and proactively manage conversation
- Product/Service – eg: Generate insights around problem/customer, solution/product or service dimensions. Generate ideas for new offerings, identify existing issues and missing features in their product/service offerings, assess customer satisfaction and compare against competition
- Business – eg: Aggregate public opinion and media coverage around predefined variables that have an impact on business reputation (one eg: CSS Corp Analytics during one such exercise for one of our clients, identified negative sentiments around product usability correlating to customer attrition around the same timeline). This help business to act upon such leading indicators and rebuild its brand with its existing customers and general public.
A trusted tech support partner can play a big role in bringing about this awareness and then, using analytics to provide active insights on the goldmine of data you are sitting on. Such a tech support partner will help businesses build a defensible advantage in delivering superlative customer experience. These encounters lead your business to top line growth, profitability and improved customer loyalty.
1 Lessons From 10 Consumer Brands Cited for Outstanding' Customer Experience in U.S., Gartner, 2014
2 Alcatel-Lucent customer experience survey, 2012
3 Customer Experience Management: Raising Customer Satisfaction, Loyalty and Advocacy – Gartner
