Now is the time for contact center leaders to embrace predictive modeling.
Speech analytics is not exactly a new technology at this point. These solutions have been around for a number of years, and companies are becoming more and more familiar with the value that they can bring to the contact center, and to the realm of customer service as a whole.
So the real question for 2016 is not whether speech analytics will continue to grow in popularity – they all but certainly will. No, the actual question is what comes next. Analytics as a field is always evolving, and businesses need to adapt to take advantage of the latest developments.
With that in mind, now is the time for contact center leaders to embrace predictive modeling. With predictive modeling, companies can leverage their analytics capabilities to accurately determine not just what happened on a call or calls, but also to look ahead to what is likely to happen next. Naturally, that presents a huge opportunity for businesses of all kinds.
Predictive is here
To appreciate why predictive modeling is poised to have such a big impact on the contact center in 2016, it’s first worth examining what the technology offers more broadly.
Predictive capabilities = huge value.
On the most basic level, predictive modeling is very straightforward: It represents an effort to use analytics data to forecast likely outcomes, both for individual customers and for the customer base as a whole. But what does that mean in practice?
There are a lot of possibilities here, all of which help demonstrate the value that the technology will deliver this year. Notably, Harvard Business Review contributor Tom Davenport ran down a few of the most significant benefits of predictive analytics on the company. These include:
- Determining a more accurate customer lifetime value assessment – how much a consumer is likely to spend for the entire customer relationship.
- Improved product recommendations, based on purchase history.
- Better ad placement and publisher selection.
These and other advantages have already had a very real, positive impact on companies’ bottom lines. For example, a recent survey of 150 B2B marketing executives conducted by Forrester found that predictive marketers were nearly three times more likely to experience revenue growth rates that beat out their industry averages than firms that did not use these solutions, Marketing Land reported. Similarly, companies using predictive analytics were 1.8 times more likely to consistently surpass their goals in terms of marketing contributing to the business.
Predictive in the contact center
That provides a sense of the value that predictive modeling can deliver in general. But what about in the contact center specifically?
Consider these sample use cases:
- Upsell opportunity: By analyzing customers’ past behaviors and speech, a firm can identify a high-value upsell opportunity in advance. Contact center agents can receive a notification at the ideal time to take advantage of this potential.
- Upcoming cancelation: By foreseeing a likely customer cancelation in advance, agents can address complaints early enough to turn problematic accounts around, improving customer retention rates.
- Likely complaints: Similarly, predictive modeling can determine if one or more customers are probably going to lodge a complaint in the near future – foresight which can enable the company to solve the problem early. This not only decreases the risk of cancelation, but, by impressing the customer, can provide a major boost to the customer satisfaction rate.
- Potential lawsuits: Analytics can gauge the possibility that a customer will reach the point of filing a lawsuit, giving the company time to prepare and reduce this risk. Considering the costs associated with lawsuits, that offers tremendous financial benefits.
Those are just a few of the most noteworthy examples of the value that predictive modeling can offer in the contact center. Given that, it’s easy to see why many firms have already hopped on this bandwagon and so many more are likely to follow suit in 2016.
Is predictive modeling in the contact center on your company’s 2016 agenda?