Call tracking has been around for about 15 years.
It tells marketers which ads, campaigns, and keywords generate calls and which don’t. It’s used by agencies, SMBs, and enterprise-level companies. It improves their ROI and gives them valuable insight into their marketing data.
Call tracking is good. But it stops gathering data when the phone rings.
Why is that a problem?
Because there is a lot of useful stuff that happens after the phone rings….like, pretty much everything of importance.
Gartner says that over 420 billion words are spoken on phone calls between businesses and customers/prospects everyday. Those words contain buyer sentiment, customer intelligence, sales performance data, close rate and conversion data, and a host of other information.
And right now NONE of these words are being analyzed.
We launched Conversation Analytics to analyze these 420 billion words.
In essence, call tracking analyzes what happens before the call; Conversation Analytics analyzes what happens ON the call.
Conversation Analytics uses sophisticated speech recognition technology and thousands of proprietary algorithms to analyze the content of the call. Conversation Analytics analyzes the call content in near real-time.
Conversation Analytics is the most substantial development in the call tracking space…ever.
Once Conversation Analytics analyzes the call it spits out a variety of ‘indicators’ for each call. There are over 50 indicators already built-in to Conversation Analytics, things like: agitation level, percent silence, cancellation, complaints, compliments, dissatisfaction, objection language, conversion, commitment to buy, payment language, reservation made, agent empathy, phone etiquette, lead score, etc.
Again, Conversation Analytics derives this data strictly from the words, phrases and other cues actually said on the call.
For each of these indicators Conversation Analytics provides a number between 0-100. This number is a strength indication, or a level of confidence that the event in question occurred on the call. For example, if the lead score was 85, that indicates that Conversation Analytics is very confident the caller was a good lead. On the other hand, if the complaint indicator is 15, that means Conversation Analytics is not confident that caller complained on the call.
In additon to simply extracting data from calls, Conversation Analytics actually allows you to do something with the data. This is done via Convirza Webhooks. Here are a couple of examples:
– Lead Score Automation: If a lead score indicator is 80 or above (or whatever) a Webhook could be sent to a CRM that places the caller in an immediate call back list.
– Email Automation: If a sales readiness indicator is 73 or above (or whatever) a Webhook could be sent to an email marketing platform that places the caller in a different email track that sends them more ‘salesy’ emails.
– Missed Opportunity Notification: If Conversation Analytics spits out a Missed Opportunity indicator of 75 (which would mean that Conversation Analytics is very confident the call was a Missed Opportunity), a Webhook could trigger a text message or an email sent to a manager or a salesperson immediately. They could then call the lead back and un-miss the Missed Opportunity.
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