No, we haven’t become psychic, but we are working on the best thing. So just when you thought Zailab’s solution couldn’t get more epic we went and changed the game.
Eyes were popping all over the place at Customer Contact Week (CCW) last week when the team demonstrated a new feature currently in development.
We decided to unveil our software’s new capabilities in the form of a stage play, because why the heck not? The stage was none other than our larger-than-life ZaiTruck, which we parked right inside The Mirage Hotel Las Vegas.
Let’s just say we’re not known for being subtle.
We might have already hinted what we were up to when we announced our partnership with voice-analytics trailblazer VoiceBase, which as you know specializes in AI-driven speech analytics and predictive insights.
Yep, that’s right. We’ve gone and incorporated speech analytics into our already powerful omnichannel contact center software, both post-call and in real-time.
Imagine you no longer had to guess how your customers were feeling. Imagine if your agent knew in real time whether the call was likely to end in a sale.
The addition of speech analytics allows companies to assess the quality of their calls as soon as they occur. By being able to monitor all calls this way, you’ll get a much better sense of what is going on inside your contact centers. (And save a lot of money on disguises and closed-circuit cameras.)
It works like this: as the customer and agent talk, their speech is monitored to see how your agent is coming across and how your customer is feeling. So positive, negative and neutral sentiments are highlighted by green, red and yellow on the dashboard.
See, it’s not clairvoyance. It’s science.
Additional capabilities include a real-time sales predictor that lets agents know after 30 seconds what the probability of sale will be. This will eventually be generalized to a positive-outcome indicator. But before you get too excited – our dev wizards are still preparing beta versions of the routing and real-time speech analytics algorithms, so it’ll be a little longer before customers can dig into those. But hang tight, folks. It’s going to be worth the wait.
A closed beta is currently available incorporating both real-time and post-call analytics. Please get in touch if you want to give it a bash.
Once we’ve ironed out all the details, the insight provided by sentiment analysis will feed into our routing algorithm, which uses machine learning to prioritize interactions and match them to the agents most likely to result in a first-call resolution. These sentiment scores will contribute to the routing algorithm’s decision around which customer and agent should be matched in the future.
In practice, agents who get the highest quality scores would be served the most important customers. Customers with a previously negative sentiment score could be pushed to the front of the queue to avoid further frustration.
See what the team has to say about our new speech analytics feature here.
Curious to see what our solution can bring to the table? Check out an online demo and see for yourself.