Originally appeared in the July 2010 issue of Customer Inter@ction Solutions
Organizations may want to consider using predictive analytics on survey data collected by EFM solutions to figure out what customers will want to buy next. Predictive analytics informs and directs decision making by applying a combination of advanced analytics and decision optimization to both structured data, such as surveys and to unstructured data, like that gathered from social media. It can help companies gain “customer intimacy,” such as in-depth knowledge that can help develop deeper and more rewarding customer relationships, explains Heena Jethwa, predictive analytics strategist, SPSS (News - Alert), an IBM company.
Most organizations start their customer-focused activities with either a predictive analytics or an EFM approach, said Jethwa. In many cases, both may be undertaken to a certain degree, but each is deployed within different and siloed departments. For example, an organization’s CRM department might use predictive analytics based on existing CRM data, while the customer insight/market research department focuses on more attitudinal data gathered from surveys or focus groups.
“Both approaches are very valuable,” explains Jethwa, “however, the power of customer intimacy emerges through transforming the siloed philosophy to combine both practices, encompassing all the data across the entire enterprise, thus combining these valuable data elements to drive more actionable and accurate insight to determine what customers will want next.”
The Integrated EFM/Routing WFO Option
One EFM solution option is those that are pre-integrated into routing or WFO solutions. This choice has several key benefits that are worth weighing up against standalone and typically say some analysts, best-of-breed offerings. These include lower total costs of ownership by reducing the number of servers. They can directly capture operational data such as from the ACDs, and link into recordings, such as Verint’s (News - Alert) Impact 360 Customer Feedback integrated WFO solution that provides managers with review and analysis capabilities. They can also readily launch automated invitations to participate and can transfer callers to surveys automatically. These features within the same solution enable companies to easily drill down, uncover and if need be act quickly on the root cause behind customers’ comments and complaints.
The automated invitation feature is important as it avoids having agent bias creep in, points out Gina Clarkin, product manager for Interactive Intelligence (News - Alert), whose Interaction Feedback application is an add-on to its Customer Interaction Center all-in-one IP Communications software suite. When agents or employees control the survey decision process and must ask the customer if they would like to provide feedback, those agents or employees typically only extend the survey invitation on “good” interactions. In these cases, the organization will likely get a biased view of customer perceptions.
“Often, it is the unhappy customers that provide actionable information to improve service,” says Clarkin. “Removing the agent from the survey decision process increases the reliability and quality of survey results.”
Interactive Intelligence is developing new features to help gather customer feedback. One of these is agentless outbound surveys via SMS. Another, being created in partnership with Buzz International, an IT integration firm, is the ability to capture customers’ comments in Twitter tweets and send alerts to firms. The alerts would be sent to the right departments by CIC’s multichannel routing feature. CIC would also track the alerts.
“Sometimes a customer will tell you what they’re thinking in a survey and sometimes they won’t and then they’re going to go out and tweet to the world how annoyed they are,” explains Rachel Wentink (News - Alert), senior director of product management for Interactive Intelligence.
Brendan B. Read is TMCnet’s Senior Contributing Editor. To read more of Brendan’s articles, please visit his columnist page.
Edited by Stefania Viscusi