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Why Your Marketing and Sales Outreach Sucks

• Evan Kirstel

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Ever wonder why nobody picks up your calls or reads your emails anymore? In this eye-opening conversation, Aaron Christopher "AC" Evans, founder of DRIPS, reveals why traditional outreach methods are increasingly ineffective in our distraction-filled world.

AC explains how our evolution into an "on-demand society" has fundamentally changed consumer psychology. When everyone is constantly engaged with content they actively choose – from social media to streaming services – traditional push messaging tactics that demand immediate attention are doomed to fail. The stark reality: about 80% of people simply won't answer calls from unknown numbers anymore.

DRIPS has pioneered a different approach through asynchronous, humanized AI conversations. Rather than forcing consumers to stop what they're doing, this technology allows meaningful interactions to unfold over days or even weeks, respecting people's time while still accomplishing business objectives. AC walks us through how their system differs from standard chatbots by interpreting natural language with sophisticated AI while maintaining tight compliance with complex regulatory requirements across healthcare and insurance industries.

The results speak for themselves. One national health insurance provider improved their star ratings from 3 to 4 across all contracts through DRIPS' technology. Another saw a tenfold increase in health risk assessment responses. For businesses struggling with diminishing returns from traditional outreach, AC offers practical advice on getting started – from simple text message "priming" before phone calls to implementing more sophisticated conversational AI. The key insight: when you give consumers a voice and meet them where they are, engagement dramatically improves.

Ready to stop annoying your customers and start having meaningful conversations that drive results? This episode reveals how the future of customer engagement is evolving beyond interruption marketing into thoughtful, AI-powered dialogue that respects consumers while delivering exceptional business outcomes.

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Speaker 1:

Hey everyone, Fascinating conversation today, as we talk about why your marketing and sales outreach suck and how AI-driven conversations can really be a game changer. With DRIPS AC, how are you? I'm good.

Speaker 2:

Evan, how are you doing?

Speaker 1:

I'm doing well. Thanks so much for joining. That's one of your taglines. Is your outreach sucks. Pretty controversial and bold statement. Before that, maybe introduce yourself and DRIPS what's the big idea these days?

Speaker 2:

Yeah, myself, aaron Christopher Evans. A lot of people call me AC. I'm a father, I'm a startup founder DRIPS my business now I've been in it for about 11 years started in 2014, really kind of pioneered the whole idea of conversational outreach. So you know, texting members and consumers. Essentially, what we're doing today is we're working with the biggest companies in the world to reach out to their members, to reach out to their prospects. All the big I shouldn't say all a lot of the big healthcare payer, health insurance companies and the majority of the PNC insurance companies as well are working with DRIPS for their outreach efforts.

Speaker 1:

Fantastic. And why do you think traditional outreach is broken? I think many of us have our own personal experiences, but what's the big picture?

Speaker 2:

Yeah, you know, thinking all the way back, right, I think it starts with, you know, we have now become an on-demand society, right? So, uh, I talked about this years and years ago. Uh, when, you know, shopify and Spotify and Amazon and Netflix kind of became the norm. Right, like we all of a sudden are getting used to being able to pause live norm. Right, like we all of a sudden are getting used to being able to pause live television right, get same day delivery stream anything we want. Right, have unlimited, you know, content in our fingertips. So, long story short, no one is bored anymore. Right Back when we were bored, right Back when you and I were growing up, you know the phone ringing was an exciting moment. Right, it's like, oh my God, who is? Who is calling me?

Speaker 1:

Right, because, when you got an email, we got an email it was like a big deal. Everyone opened their email back in the day, right.

Speaker 2:

but now we are in about the opposite of that right, where everybody is busy 100 of the time doing whatever it is that they want to do. Right doesn't necessarily mean they're productive. Busy just means they're busy, right? They'd be busy scrolling on instagram, and you bet they'd rather do that than to get a phone call about, you know, doing a policy review with their auto insurance carrier. So that's what kind of shifted.

Speaker 2:

You know psychology of people, right? Like? Commercials don't work, radio doesn't work, right, phone calls aren't being picked up, direct mail is not being read, email is not being read. So all these things have one thing in common, and is that they are trying to steal your attention. They're trying to stop you from doing what it is that you'd rather be doing and have you take some action, right? So if I call you, what are your options? Right, you have to stop what you're doing and deal with this phone call, or you ignore the phone call. And you know, long story short, people are ignoring that type of outreach, they're ignoring that type of push messaging that is trying to take their time.

Speaker 1:

Well said. So, Drips, you're talking a lot about humanized AI, because we're all AI, gen AI obsessed. So what does that mean in practice, and how is it different from just your average chatbot experience?

Speaker 2:

Sure, yeah, again, the difference between what we like to call conversations and push messaging is we are reaching out and holding an asynchronous conversation. Right. To hold a synchronous conversation, to get somebody on the phone, they have to stop what they're doing. Right, we can ask a question. We can say hey, evan, we're following up about your annual wellness visit. Have you had time to schedule that yet? Question mark you can respond. Then. You can respond later. You can respond the next day. If you don't respond within a certain amount of time, we can bump you and push you and say hey, evan, just making sure you got my message right. Should we jump on a call? Can I help you? You know, did you have any questions about this? So I'm not taking your time. Right, you can keep watching Netflix. You can keep working. You can keep watching your kids. You can do whatever you want. So that's the trick, so to speak, with conversations. Right Is that it's an asynchronous thing. So I'm giving people a voice that they can respond when they want to respond. Right, and the interesting thing is they respond with all kinds of stuff, right? You all of a sudden learn that you know the person doesn't want to pick up the medication because they're having an allergic reaction or they can't pay their bill because they got laid off or they already picked up the prescription and there's something wrong with the data. So by opening up and asking questions, you give these audiences a voice that they didn't have before, right? Because if you just keep calling them and they don't respond, you're not hearing what the problem really is, right. So that's kind of the trick is to opening up conversations, listening people, giving them a voice.

Speaker 2:

The hard part is it's hard to know what they're saying, right. So we've been doing NLP and machine learning modeling for many years now. It's definitely easier now with LLM, chatgpt, openai et cetera. We can get better accuracy. But the problem with generative for most companies is that it is probabilistic in nature, which means it's probably going to do what you want it to do. It doesn't mean it's going to do what you want it to do, so we actually stay in a full deterministic model.

Speaker 2:

Currently we do use, you know, nlp and LLMs to do intent mapping to figure out what the person said. So they say I'm driving, I'm stuck in traffic on I-77 South heading into the office. We know that doesn't mean I'm at work, it means I'm driving, so that we would then send a deterministic, pre-prescribed response that says oh sorry, we caught you driving. Please drive safe. Let us know when you get to where you're going, right? So the trick is, you know figuring out what they're saying so you can respond in kind. That way you don't have to sound like a chatbot, right? So the difference is with chatbots, it's uh, hey, evan, uh, it's time for your annual wellness visit. Respond c if you would like a call to confirm to blah blah blah. Respond r if you need to reschedule it. And you know what a human does when they feel like they're being talked to by a robot. They ignore it.

Speaker 2:

Right, they're like yeah I'll do this later, you know what I mean. Like it's the equivalent of getting a phone call or saying like hello, this is Walgreens, I won't use name, this is your pharmacy, right? It's not as empathetic, right? So, but if a person calls me, or something that sounds like a person calls me or texts me, I'm going to have a little more empathy to hold a conversation.

Speaker 1:

Well said. Yeah, I don't even answer my phone anymore, so there goes that. Don't even answer my phone anymore, so there goes that. But why do you think so many companies, even big companies, big brands, with deep pockets and lots of tech in-house, are so slow to evolve in this space? They're still using email blasts and text blasts and outbound call centers. Why haven't they jumped on the Gen AI train?

Speaker 2:

It's a good question. Again, with Gen AI, there's a lot of risks, right, and there's a lot of uncertainty right now. So most big companies just don't want their data touching those models. Yet, right, most large companies, they are, you know, I would say, implementing AI. I was just with the CIOs of a large, one of the largest national health insurance companies. I asked them how they're implementing Gen AI and they said they're actually focused on implementing it in-house, meaning for operations, right, like getting it so that their teams are using these tools so that their company can be more safer and more obvious place to start with Gen AI than is using it to outreach to your audience on regulated channels. So email is regulated, but it's relatively pretty safe. Direct mail you pay for a stamp, you're covered under the law.

Speaker 2:

Telephony calls and texts are governed by a litany of different laws. You have CMS laws for Medicare, medicaid. You have TCPA, which is the Telephone Consumer Protection Act Under the FCC. You have the telemarketing sales rule Under the FTC. You have the campaign register, tcr. You have HHS for healthcare type things. You have different state level rules, right, for telemarketing and for collection.

Speaker 2:

So there's a really nasty patchwork of rules, regulations, laws, best practices that a company has to navigate to do texts or calls, and what happens is, because it is so confusing and conflicting, most legal teams relegate their business owners to doing the lowest common denominator, which is a phone call, right, or maybe a push text message. That's not very engaging because they know that you know one text one day, whatever it is, they can get it. So it follows all the laws. Holding a long tail conversation and doing text and calling, and you know, responding to people. It's just hard to do while following all the rules and regulations.

Speaker 2:

And I'll give you a practical example. So bill pay reminders right, like to do a bill pay reminder saying that a bill is coming up. You're allowed to mention the amount of the bill, right, because it's not a collection yet, it's just a bill that's coming up the moment that that bill is due the very next day. In many states I think it's like 23 or 24 states you're not allowed to do what's called third-party disclosure, which is essentially mentioning that there's a debt or a bill due, right? So you would have to say like, hey, we need to talk about your account, right. In other states you're allowed to mention the bill, right, it's not a problem. In Massachusetts, you're only allowed to reach out three times within one week about something that could be considered a debt collection. In a lot of states they follow the 777 collection rules, so you can only reach out seven times within seven days. So there's, just like all these different rules, federal state that you have to be able to follow, depending on the use case right.

Speaker 1:

Is it?

Speaker 2:

collections. Is it healthcare related? Is it marketing? Is it administrative information? On nature and depending on the level of consent that you have, was it an inquiry? Do you have permission to contact? Have you been given prior express permission? Have you been given prior express written consent? It's just, it's a terrible thing to try to organize around In DRIPS. We've actually built it into what we call the DRAE or the DRIPS rules engine, so we have a system that's essentially policy by code to make sure that everything that's coming out of our system on behalf of our clients is compliant at every level. Right, there are policies state, federal and all those different rules, so different members will have a different experience based on where they are, based on what the consent level is.

Speaker 2:

So the short answer is it's hard, right. I mean that's like in a nutshell it's hard to do it well in a deterministic fashion while following all the rules. So therefore, we stick to what's safe right. We stick to email, direct mail, phone calls and you know the diminishing returns are hitting right. Like people, like you said, you're not picking up your call at all. That's a lot of people. I think that's like we did a study recently. I think like 80% of people or something like that, just won't pick up unknown callers. So times are changing. People are getting around to this as a methodology. They're seeing the lift from just doing push text message. So they're trying to do better by, you know, turning that into a conversation. There's a lot of different ways to do it but we feel like ours is superior, fantastic.

Speaker 1:

Let's talk the other hard thing, which is scale. I get a text message from my dentist and I think it's actually a human being. They're actually just talking to me and I'm not sure it's AI, but either way, that works fine for a dentist's office. But you get into millions of users. That changes the game. How do you scale to that sort of magnitude?

Speaker 2:

You just nailed it. I mean it probably is a human right. So there's, that's one of the ways to do. It is one-to-one, uh, cause then you're not regulated the same way. There's a lot less rules when you're hand texting somebody, uh, and that does work for SMBs, right? That's why we don't sell SMBs candidly, uh. But yes, you're right at scale.

Speaker 2:

If it's a high value, high volume problem, there are not many ways to do it. Well, right, there's dialers, uh, there, there's drips there, there's companies that you know would like to compete with us that do more. One way, um, but I think one way, and when I say one way, I mean it's like it's either a chatbot type thing or it's a push excuse, excuse me, a push alert. Those are really good for high volume, low value, right. So if you think of a quadrant, right, you got low volume, low value, which is like web chat, inbound support. You have a high volume, high value, which is what we're talking about, which is essentially usually us, or a call center. You know somebody that is staffed out because these are high value people and it's a big volume. So that's why there's, you know somebody that is staffed out because these are high value people and it's a big volume. So that's why there's, you know, a multi-billion dollar industry around BPOs right.

Speaker 2:

Then you have the low value, high volume, which is alerts, notifications right. So you know, let's use a good example a gate change, right. Like gates change all over the all over the place. United is probably sending tens of thousands of these things out a day, but it's not a high value, uh use case. Because, evan, if you get a text saying that your gate changed, guess what you're going to do? You're going to get your butt up and you're going to move to the gate that you need to move to right.

Speaker 2:

When it's high value, that's because it's something that enterprise needs right. It's something that we need you to get a comprehensive medical review. We need you to do your Medicaid redetermination. We need you to do a health risk assessment. These are things that members or prospects wouldn't do otherwise or wouldn't do as quickly as the enterprise would like them to, had it not been for the call center reaching out, had it not been for DRIPS reaching out. Right, if it's something the customer wants to do or needs to do right finish an insurance claim, do a refund, dispute something they're going to do it Right, there's many, many, many softwares out there thousands of different chatbots and web support type softwares but when it's something that the enterprise wants the consumer to do, that's much more difficult, right, and it's a lot harder to convince them to take those actions.

Speaker 1:

Got it? And what is the role for human in the loop in best of class AI and automation? Different philosophies there. What is yours?

Speaker 2:

I think you know we have a really, really high confidence score. I think it's something like 99 or 98. I should know that when. If it's below that meaning our system, our NLP and modeling score is not 99 or 100% sure that we know the intent of the user. We send it to a human to review, to review, they essentially assign what the correct intent should be. That then re-informs the model right. So many, many years ago it was probably 60, 40 humans. Now, out of all the outreach our system does, I think less than a percent or two is a human. That's essentially assigning and training the model. Because we've done so many of these right. We've done billions and billions of text messages. So we've we've just candidly kind of seen all the different rebuttals and different ways people will say things but, human in the loop is really important.

Speaker 2:

I mean, like you know, you think of that doctor's office, right. So maybe they have an alert that goes out when your you know time for your cleaning is coming up every every months, right, but when you respond back, because they probably don't have really strong AI or NLP types of systems, maybe that's when a human in the loop is there, when they get a secretary responding.

Speaker 2:

Problem at big scale is you're just shifting a call center from being on the phone to a call center being on keyboards, right, and that's still a really costly thing. So certain things you know aren't ready for our types of automation yet. You know, like really really nuanced conversations, conversations about, you know, medical type issues, that needs to be done through a secure channel. So we don't, we don't do that over text message. But you know, scheduling things, reminding people, getting them to show up to things, making sure they understand what's important helping them along their health care journey is. We've pretty much cracked that code.

Speaker 1:

Brilliant Speaking of cracking code. You know there's no textbook about best practices here. There's no textbook about best practices here. What advice do you give a CMO, maybe a CIO, who knows their outreach sucks but doesn't know how to get started?

Speaker 2:

What is a way to get started for wherever they are in the journey.

Speaker 2:

That's a great question. My favorite way to get started, like, a lot of companies are doing great with calls already, right, a lot of companies are doing some texting, right. So I like to tell people to try to marry those two things. So they use texting generally for alerts, right? Like, hey, we need you to do a thing. They treat it as a direct response, which, again, I think is not a good use of the channel. I think you need to hold conversations to asynchronously, take somebody down a journey for days or weeks. But if you don't have that type of technology, you don't have a tool like DRIPS at your disposal, then why not marry the awareness that a text brings with the efficiencies and scale that a call center brings? And the way you do that is by priming. So you send a text message first, right? Hey, evan, this is your healthcare provider. We're going to be calling you here in a minute to talk about scheduling your annual wellness visit. It's important for X, y, z, right? That alone. That one text message alone, I would almost guarantee, could, you know, increase your pickup rate or your contact rate by 20, 30, sometimes even 50%. Right, because at least now the person is aware and it and you can play with that, right? You can say, hey, we're going to try to call you in 15 minutes, right? Or 10 minutes. So now the person gets to maybe stop doing what they're doing. You know, put the kid away, take it, take a walk from the office, whatever it may be, and take your phone call right when before, if it was just a phone call, they're not picking it up, right. So that's an easy way to get started, you know.

Speaker 2:

But you know there are, look, there are partners and platforms out there that specialize in this. You know that are single-focused, best-in-breed, like DRIPS. I think the best way to get started is look at what others are doing, you know, look at the case studies and test these types of technologies. Like I said, gen AI isn't there where big companies are, you know, ready to trust it. You know essentially, but there are. You know deterministic ways. Even if you start with a chatbot type technology, that's better than nothing, right? It's better than phone calls, in my opinion. But if you can find a conversational outreach partner, like DRIPS, or test out that type of thing, I think that's a great place to start.

Speaker 1:

Brilliant, and for your more advanced practitioners, customers of yours, they must be seeing some pretty incredible ROI in terms of revenue attrition retention. Do you have any anecdotes or stories there? What do you typically see on?

Speaker 2:

the investment they're making.

Speaker 2:

It's been great. I mean we have a lot of case study. It's been really exciting. I'm trying to think of some, one of the most, a recent one that was really exciting and will be important in a couple of years. So we do a lot of work around stars. So this is how these plans are rated right, and they have many, many different measures. Right. How many people are doing health risk assessments? How many people are doing conference medical reviews? How many people are doing medication? How many people are medication adherent? Right, they're picking up and taking their medicine. We were able to increase one group's one of the big national payers they're stars by, I believe, a full point in all their contracts.

Speaker 1:

Essentially all the states.

Speaker 2:

They moved from a three to a four point just because of our work in comprehensive medication reviews, comprehensive medic uh medication reviews. We also have started doing uh digital assets. We're building out essentially endpoints to help uh do surveys for these payers, these insurance companies. So we do health risk assessments now. So we were able to show I believe it was a 10x uh response on health risk assessment. So instead of getting a few percent, they're getting you know upwards of 30 percent of people and these are hard to reach. These are the people that don't pick up the phone, don't do the direct mail, don't get the email. So it's been very compelling. I really do believe that when you give people a voice and you're able to understand what they're saying back and you're able to pivot and adjust the conversation to meet them where they're at, while still nurturing them for days or weeks, like I said, the average conversation takes more than a week, right?

Speaker 2:

So this is not a direct response. Hammer them till they pick up. It's a very nuanced, you know relationship that you build with these members so that you can be empathetic and so that you can really understand, you know where they're coming from, while helping them get to where you need them to be.

Speaker 1:

Wonderful Well tech for good and helping a much underserved area of the consumer. Well congratulations on all the success. Ac Thanks for joining and sharing the vision.

Speaker 2:

Yeah, thanks for having me, evan. I appreciate it.

Speaker 1:

And thanks everyone for listening and watching. Check out our new TV show yeah, broadcast TV. That is this techimpacttv starting this Saturday. Thanks,