Introduction
Increased customer retention represents an imperative as much as an opportunity for the business success of every organization, especially since acquiring a new customer can cost as much as 10 times as keeping an existing one. Many organizations will make operational changes, create retention-marketing programs and introduce new products in their effort to be proactive in ensuring customer retention. But how can they be sure that the changes, programs and new products are offering their customers what they need and want?
This kind of information is most reliable when it comes directly from the customer. And while surveys and focus groups may help, the best way to understand customer intent is through the intelligence that can be extracted from direct interaction. Every interaction you have with your customer provides an opportunity to improve.
This is where the contact center comes in, serving as a strategic focal point and hub for gathering customer inputs. Every day your customer service representatives are talking with customers about the issues that matter most: product or service feedback, spending patterns and competitive offerings. With up to millions of calls coming into a contact center every year, contact centers have the potential to listen to millions of customers and gain insight into what action is required to increase customer retention and drive business performance.
The Challenge
If an organization could identify those customers who showed a high risk of choosing the competition and treat them immediately, the risk of losing that customer would be mitigated. But gaining insight from customer interactions and turning that into meaningful business action is very difficult. With so many calls coming into a call center every year, the call center is faced with mounds and mounds of information. It becomes nearly impossible to glean that down to meaningful business information and understand the real issues.
The Solution
Several speech technologies (integrated with capture platforms) that aim to provide insight on customer and dynamics are available today, including: phonetic search, transcription and word spotting. While the first two have seen some success, only word spotting scores high in all three of the critical performance categories (e.g. processing speed, search speed and accuracy).
But word spotting alone will not get the job done. Without context, content can not be accurately and reliably ascertained. This is where stereo capture comes in. By capturing separately the customer and agent and performing independent audio processing for each, context is provided and the benefits of word spotting can truly be gained. This kind of advanced analysis capabilities helps the supervisor understand whether “buy again” signifies an up-sell opportunity (“with so many great features I will want to buy again”), or a customer at risk (“with such bad service I will never buy again”).
Another element of context is the tone with which the key words are spoken. The word spotting functionality may have caught “yes, you have great service”, but only with emotion detection capabilities can it be identified that what was really said was an angry “YES, you have GREAT service!!!!”.
Emotion detection is critical to identifying true customer intent and pre-empting defection. If a customer expresses dissatisfaction, this needs to be flagged in real time. And once this call is flagged, it should be queued and routed to a member of the management staff. The issue can then be reviewed, and the caller may get a call back, almost instantaneously. This would result in unprecedented responsiveness and customer loyalty.
And finally, to take full advantage of advanced speech analytics, the solution needs to be integrated with as many data sources as possible, e.g. CTI, business data, call-flow analysis, screen activity, customer feedback. Full integration translates into unprecedented speed and accuracy (as well as cost-efficiency).
With an interactions capture and analysis solution that has fully integrated speech analysis, through which advanced analytics are performed not only on key words, but are derived from a variety of additional sources (such as emotion detection and talk analysis) you can ensure the effectiveness and accuracy of analysis and extract the insight from interactions that helps increase customer retention.