Engaging potential leads through the calls has always been easy, with many possible pathways a caller could take. But with AI, you can pave an optimal journey for every lead while also collecting marketable insights on both the caller and the call.
Matthew Black, the Founder and CEO of Mav – an industry leader in automated two-way texting – and Evan Smith, Mav’s head of sales, joined Phonexa’s COO Jeff Schaffer to discuss the transformational potential of the AI as part of Phonexa’s Amplify series.
So let’s dive into the key takeaways and insights that came out of this conversation.
Watch the recording of this webinar here.
The Common Struggles of Call Centre Operators
The session started with an emphasis on the importance of using conversational AI to contact a consumer before your competitors do.
Schaffer presented the following hypothetical scenario: a consumer fills out a form, goes back to their busy day-to-day life, and the corresponding call centre wants to reach out to them via conversational AI.
| “The trend used to be email – people used to open and reply to every single email they got, and then email became something people couldn’t stand anymore,” says Smith. “With the advent of power diallers, lead generation, and comparison shopping sites, it became overwhelming to watch your phone blow up with call after call after call.” |
Black corroborated that by sharing his experience with taking out a mortgage loan, when he started receiving calls from unknown sources, which also accelerated the launch of Mav. Today, Mav uses conversational AI to provide “speed-to-experience” for SMS.
Addressing Call Centre Bottlenecks with Conversational AI
Smith demonstrated that text messages are more likely to be read than a phone call to be answered and elaborated on how this can be used to get more value out of call centres:
| “Now, with AI, when you tack on those open rates that no other channel gets and tack on automation, you’re able to do call centre-like work without actually having a call centre,” said Smith. “That’s where Mav has come in to be that minimum viable call centre that can operate entirely over text message – it can reply, qualify, do lead outreach, lead intake, and can live-transfer calls.” |
High labour costs and attrition are common call centre challenges, but conversational AI over SMS effectively solves these problems.
Top Practises for Lead Nurturing & Re-engagement for Calls
Black explained that the value of conversational AI over SMS, from the lead perspective, comes when they look at it as a utility.
| “[Consumers] can use this experience to get from point A to point B,” said Black. “Point A may be, ‘Hey, this is X insurance agency following up on a quote.’ Point B could be getting that quote or getting in touch with an insurance rep.” |
To really drive it home, he shared one of his client experiences:
| “We have a customer that’s a larger life insurance company, and when we were building their experience that delivers a life insurance quote online over SMS, a lot of the leads were asking, ‘What term policy do I need – 10, 20, or 30?’” said Black. |
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He soon realised that every time the leads called into the customer service centre, the reps would literally be always saying the same thing: ‘Do you have a child that’s going to graduate college? Do you have a mortgage? And if so, pick a term length that matches that policy.”
To make those questions a little more conversational, Mav customer service reps prefaced them with, “Pick a term length that lasts until your child is out of college” or “Consider picking a term length that lasts until your mortgage matures.”
| “[Prospective customers] then feel educated, gain some value, and know how to appropriately answer those questions along the journey of getting a quote,” said Black. “And that’s the kind of speed-to-experience that makes it a curated journey and sets you apart from everyone else.” |
Operational Efficiency
Smith related his experience of running a call centre to highlight that conversational AI makes processes more efficient as it entails less manpower.
| “If I had Mav back then, that call centre that was 100 people could’ve been 15 because the conversational AI could sit in front and be a call centre for the call centre,” said Smith. |
Smith praises conversational AI for scrubbing out low-intent, irrelevant, and unqualified consumers as well as those who don’t answer.
Next, he emphasizes the expenses of replacing a call centre representative, which may cost a year’s salary. For example, if a call centre representative was making $30,000, it would cost just as much to onboard a new one and train them to the same level.
| “Even if you have 10 reps and lose four, that’s $120,000 a year that you’re burning on attrition,” said Smith. “If you could run a four-person call centre instead and you only have to replace one person, conversational AI just saved you $90,000.” |
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Sales Script Customisation and Customer Journey
Smith commented that conversational AI adjusts the customer journey based on where the lead came in – much better than a human could. Ultimately, though, it’s a question of whether you want to initiate an over-the-phone conversation for every TOFU lead or qualify them first.
| “For a third-party aggregator in the home services field, you may want to scrub out anybody that’s looking for repairs – if you’re a remodelling company, you don’t want to talk to somebody about repairing a couple of shingles on their roof,” said Smith. “Those leads are likely to come from a third-party aggregator and be of slightly lower quality. Mav scrubs those out and does not offer the talk-to-human option until after they’ve qualified.” |
Such scrubbing certainly eases the process both for the call centre and the consumer.
| “Especially with third-party leads, you have to put yourself in the consumer’s shoes. It’s important that you make reference to the originating source,” said Black. “Bridging that gap is so important and will set you apart from all the [competitors] fighting for that consumer’s time and attention.” |
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