Auto-Complete Me

Hollis Chin | May 19, 2014

“I want you to understand me. I want you to anticipate my needs. ”

No, I’m not talking about my relationship with my husband (though he certainly tries to understand me and does a great job of anticipating my needs). I’m talking about my relationship with your business. If I’m shopping on your e-commerce site or revising my flights on your airline, I want you to know why I’m calling or why I’m on your website. Furthermore, I want you to recommend what I need to do. Yes, to provide a truly amazing experience, know what I need before I even think of it.

In Opus Research’s new report, Predictive Analytics: Using Big Data to Improve Multi-channel Customer Care Senior Analyst Dan Miller discusses how Google has set the bar high for anticipating what we’re trying to accomplish such as when we type things into the search bar – Google autocompletes us. I’m sure you’ve experienced this. Google anticipates what we’re searching for and, because of predictive analytics, gets it right more often than not. Miller says that, to “delight” customers and prospects, businesses “must be like Google and apply the whole of their institutional knowledge to the purpose of helping each customer fulfill his or her personal objectives.”

Predictive analytics isn’t all that new. But what is new is predicting and orchestrating positive outcomes and supporting omnichannel conversations.

As a consumer, I expect you to not only follow my journey and maintain context as I traverse between channels and devices but I also expect you to anticipate where I’m going next and my objective. If my credit card was just rejected, you should know the “next best action” for me. You should call me and have me confirm my charges so that I can continue to make purchases with the card. You need to proactively resolve the situation. And you should interact with me in the way that is most convenient for me, whether that is with a phone call, text, or via the mobile web.

Today’s most admired companies and brands get this. They are utilizing Big Data and Predictive Analytics-based solutions to improve the customer experience by deploying intelligent IVRs and chat systems.

Of course, not all of the solutions are the same.

The Opus Research report provides in depth analysis of the predictive analytics offerings of nine leading platform vendors from the contact center market. It rates them in terms of range of products and capabilities, as well as in maturity of predictive analytics suite for multichannel customer care and how they apply predictive analytic models to:

- Manage the ongoing conversations across multiple channels

- Learn and adapt using machine learning

- Offer well-defined, engineered, action-oriented outcomes

According to Miller, the best solutions employ “knowledge management and deep analytic technologies into comprehendible and consumable enterprise solutions which have demonstrated the ability to achieve large scale and to support multiple vertical implementations. “

You can get a complimentary copy of the Opus Research Predictive Analytics report and read the comparison of the nine vendors here.