Since Conversation Analytics is such a revolutionary product on the call tracking and marketing analytics landscape, we’re struggled to define exactly what it is best used for.
Or, said another way, we’ve struggled to define it’s purpose.
– Is Conversation Analytics a tool to improve marketing ROI? Yes.
– Is Conversation Analytics a tool that will improve sales performance? Yes.
– Is Conversation Analytics a tool that will give you never-before-seen customer intelligence? Yes.
– Is Conversation Analytics a tool that will, for the first time, provide phone call lead scoring? Yes.
Conversation Analytics does all these things and dozens more. But, ultimately, these are not core to it’s purpose.
The purpose of Conversation Analytics is to increase your conversions. Conversation Analytics is the tool that will help you convert more leads to customers.
The Use Case: Let’s assume that only 7 of the 100 callers to your business buy within 6 months. You have a lead-to-customer conversion rate of 7%.
We’ve identified over 50 ways Conversation Analytics increases this lead-to-customer conversion rate. In this blog we’ll list only 5. (We have other blogs to write after all).
Conversation Analytics calculates a lead score on every call. Whenever a lead score is high (say above 70) and the caller doesn’t end up purchasing, a Webhook could be sent to a CRM placing that lead into a ‘call back’ list of some sort. Two days later someone calls the leads back and sell two additional accounts. These are accounts that otherwise wouldn’t have received a phone call and likely wouldn’t have purchased within the next 6 months, or maybe ever.
Conversation Analytics can determine if the caller was agitated. If the agitation indicator is high (over 65, for example), a Webhook could immediately send a text message or an email to a manager alerting them that a customer was upset on a recent call. They can then call the customer/prospect back and salvage the situation. Several customers per month can be saved with this strategy, and several prospects could be converted to customers.
Conversation Analytics can determine when a prospect should have purchased but didn’t. In other words, a specific objection or poor phone sales performance, stopped them from buying. Whenever a missed opportunity indicator rises to 80 (for example), a Webhook can fire into the CRM and assign the lead to a different sales rep. The new sales rep calls, apologizes for the other sales rep’s stupidity, and several prospects turn to customers.
Sophisticated companies have various email ‘tracks’ dependent on the lead’s level of interest. For example, at Convirza we generally send ‘warm’ leads educational marketing material, but if the lead is deemed ‘hot’ we send more direct sales pitch emails about Convirza. Those emails result in purchases.
Well, if Conversation Analytics determines that a lead is sales ready–again, based on the words said on the call–it could send a Webhook to an email- marketing platform that changes the email ‘track’ for that lead. It could shoot them into the ‘hot’ lead email campaign. This will result in several conversions.
Conversation Analytics can determine if a lead is price sensitive. If price sensitivity scores reach a certain threshold, Conversation Analytics could fire a Webhook to a CRM that fills in a field indicating price sensitivity and putting the lead in a callback list. When the sales team follows up on this lead in a few days they will remember the price sensitivity of the lead and customize their pitch accordingly. This will result in additional conversions.
Even if each of these methods only resulted in one or two more of our 100 calls converting to customers in a 6 months period, that’s still a conversion increase of 80%+. Instead of only 7 calls out of each 100 purchasing, suddenly there are 12 or 13 purchasing.
In fact, our preliminary testing indicates that Conversation Analytics increases conversion rates by 70%+. This of course ignores other benefits that Conversation Analytics provides such as better marketing ROI calculations, phone lead scoring, customer intelligence, sales performance data, general awesomeness etc.