Taking a Lesson from E-commerce
This post was authored by Prem Uppaluru. Prem is the President & Chief Executive Officer of Transera.
Contact centers should think about modeling successful e-commerce strategies, which gather very precise information about who’s visiting their website—including their spending habits—before deciding how to engage with them.
In the world of e-commerce, each unique online visitor is identified through their cookies and demographically and behaviorally profiled through consumer or customer databases. They are greeted by a landing page customized to their profile and guided through a workflow that balances their needs and the online merchant’s business goals in a way that maximize conversions and order values. Upon a successful transaction, customers are often encouraged to purchase additional matching products, accessories, or services to increase total transaction value.
A similar paradigm can be applied to customers interacting with a contact center. Customers can be identified and classified using a combination of their caller ID, the number they dialed, the menu options they selected, and the digits they entered into the IVR. Once identified, customers can similarly be profiled using consumer and customer databases. These profiles can be used to match them with the right agent profile and call script to deliver the best business outcomes. If the interaction is successful, customers can be offered relevant add-on products and services to increase transaction value.
This is a unique approach that puts a business focus on managing interactions. Contact centers can maximize the impact of this approach by leveraging the power of Big Data and predictive analytics to make recommendations for call routing, customer-agent matches, scripts, and cross-selling.
I’ll talk about how contact centers can take advantage of Big Data and predictive analytics in subsequent blogs.