How to Scale Lead Generation Across Calls by Automating & Enhancing Outreach with Conversational AI

Engaging potential leads across calls can often feel like navigating a labyrinth, but leveraging the power of conversational AI emerges as a beacon of efficiency and efficacy.

Matthew Black, the Founder and CEO of Mav – an industry leader in automated two-way texting – and Evan Smith, the Head of Sales for Mav, joined forces with Phonexa COO Jeff Schaffer to illuminate the transformative potential of the technology as part of Phonexa’s Amplify series.

Delving into the economic impact and efficiency gains, the trio discussed how pioneering AI-driven text-first strategy is reshaping outbound call outreach and crafting an inbound-style experience that resonates with leads and propels conversion rates to new heights.

Let’s dive into the key takeaways and insights from the enlightening conversation.

Watch the webinar here.

High-level Pain Points Call Center Operators Encounter

The informative session kicked off by taking a hard look at call center operations, challenges, and where conversational AI belongs in the world of lead generation.

Speed-to-lead is outdated, and in its place, the importance of speed-to-experience – leveraging conversational AI to get in touch with a consumer and take them off the market before a competitor reaches them – cannot be overstated.

To illustrate this point, Schaffer presented the following hypothetical scenario: a consumer submits a form, returns to their busy day-to-day life, and the respective call center wants to contact them without 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,” said Smith. “With the advent of power dialers, lead generation, and comparison shopping sites, it became [overwhelming] to watch your phone blow up with call after call after call.”

Black echoed these sentiments by sharing his experience shopping for a mortgage loan and being bombarded with calls from unknown sources, eventually becoming the specific use case for launching Mav.

Today, Mav uses conversational AI to offer “speed-to-experience” for SMS.

Solving Pain Points with Conversational AI Across Calls

Smith demonstrated how text messages helped fill the void from dwindling contact rates since consumers are more likely to read every text message they receive rather than answer each call that comes in.

“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 center-like work without actually having a call center,” said Smith. “That’s where Mav has come in to be that minimum viable call center that can operate entirely over text message – it can reply, qualify, do lead outreach, lead intake, and can live-transfer calls.”

High labor costs and attrition are common challenges of operating a call center and also make it hard to run campaigns.

Conversational AI over SMS can solve these issues, saving call centers tens or hundreds of thousands of dollars in the process.

Best Practices for Lead Nurturing & Re-engagement for Calls

Black explained how the benefit of using conversational AI over SMS from the lead’s perspective unlocks 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.”

Black views the transition from Point A to Point B as an opportunity to educate consumers and further differentiate your brand from the competition by providing value – for example, by answering any pressing questions a prospective customer may have regarding your product or service. He shared one of his client experiences to drive the point home.

“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.

He soon realized that whenever the leads called into the customer service center, the reps always said the same thing: ‘Do you have a mortgage? Do you have a child that’s going to graduate college? And if so, pick a term length that matches that policy.’”

To improve the conversational flow, Mav customer service reps prefixed those questions with, “Consider picking a term length that lasts until your mortgage matures” or “Pick a term length that lasts until your child is out of college.”

“[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 shared his experience running a call center to highlight how conversational AI makes processes more efficient by requiring less manpower.

“If I had Mav back then, that call center that was 100 people could’ve been 15 because the conversational AI could sit in front and be a call center for the call center,” said Smith.

Smith lauds conversational AI for essentially performing lead triage by scrubbing out uninterested consumers, getting rid of those unqualified leads, and trimming down the list of phone numbers to call by removing those who don’t respond. This also helps to reduce overhead costs by addressing issues related to attrition, which can price call centers out of growth.

Smith explains that the general rule of thumb when replacing a call center rep is that it’s going to cost one year’s salary. For instance, if a former call center rep was making $30,000, it’s going to cost that much in lost revenue, onboarding training, HR, and more just to get a new rep back to the level of the person that churned out.

“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 center instead and you only have to replace one person, conversational AI just saved you $90,000.”

Operational efficiency ultimately sets the stage for a call center to achieve long-term growth.

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Customizing Sales Scripts and the Customer Journey

Smith touched on how conversational AI improves efficiency as it pertains to changing the customer journey based on where a lead originated from, especially when compared to a human who may take a script down several paths when working on a lead.

In the end, it comes down to whether you want to offer a talk-to-human option for all leads at the top of the funnel or wait until you qualify them.

“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 remodeling 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.”

It’s these types of procedures that improve the experience for both the call center and the consumer, particularly for the latter, since they won’t have their time wasted if they don’t qualify.

“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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