Speech analytics? Its audio transcription with text searching, right ?
For the third time in as many weeks we had a conversation with a prospect that went along the lines of:
#1 “We looked at speech analytics a while ago, and we get it, “check 100% of calls, automate agent scoring, compliance checking, coaching effectiveness, discover new customer insights, improve the customer journey & the customer experience”.
#2 “Loved the idea in principle, but it turned out to be pricey and complicated”
#3 “Anyhow we think we can do this in-house, quicker and cheaper. We can we push the audio through Google and run a search on the transcript”.
Turning your customer conversations into meaningful insight.
The chances are you have heard of “speech analytics”, already use or considered what speech analytics could do for your business. its one of the “hot” technology topics, with many discussions surrounding the technology, future trends and best use cases.
As with any developing business tool there is debate about the best approach, potential benefits, return on investment, and whether the reality in delivery meets customers expectations and matches the hype.
So who are Vivo Analytics ?
Vivo was created to make speech analytics easy to use, cost effective and to overcome the issues that have arguably limited the success of some speech analytics solutions in the past.
We believe our approach makes speech analytics both viable and accessible for organisations of virtually any size, across a wide spectrum of sectors. So why do we think we are different?
Big data has been a hot topic for a few years, and predictive analytics is an aspect of data analytics that purports to forecast the outcome of future events. It does this by examining vast amounts of data, to identify patterns to inform the likely future outcomes of similar events. The power of artificial intelligence or machine learning, partnered with low cost cloud computing means processing huge amount of data has become cost efficient and accessible to many. Importantly AI can continually take the feedback of real world results to ensure the models accuracy is constantly improving. Essentially the more data the better!
A few calls are selected to assess agents, or to gather insights into your prospects and customers. The results are noted on a “score card”, typically a “tick list” or computer form. Outcome ? A report highlights suggestions for improvements, agents requiring support, important product or customer insights and so on.