Austin Hughes, CEO and co-founder of Unify, on the death of the SDR

Yeah, 100%. A really common situation that we will see is that someone will be running this workflow where they already buy 6sense, where they already buy Clearbit Reveal. And the way that their reps are consuming that information is that they've either got an iframe in Salesforce or they've got a Slack notification running. And the Slack notification just says, "Hey, Acme Corporation was on my website demonstrating intent."

And from that point on, the workflow that a seller will do is they'll take that data point, they'll go over to LinkedIn, they'll plug in the company, they'll apply their persona searches, they'll try to find the most relevant people to reach out to. They'll take their plugin from Apollo or ZoomInfo, and they'll look for contact information there. And then they'll click enroll in sequence. They'll pop over to SalesLoft or Outreach, then they'll finally personalize their message, and they'll finally push send.

That's the workflow that we very often see. This takes 5-10 minutes per contact for a human to do manually. And as you can tell, it's just so complex and so long that the fact that we do all of that in a fully automated fashion just means that teams are willing to do more in this space. Oftentimes, the teams that we're talking to are actually not getting full value out of their signal data because it has this entire process stacked on the back end. By removing that friction, we find that we're helping companies book opportunities from signals at much higher rates.

Can you talk about your early product market fit? Who would you think about as your core customer? Who's actually buying Unify? Is it the way I heard you positioning it, like, maybe it's not the sales team, maybe it's the growth guy or she. And, who's using Unify inside of the org?

We found product-market fit pretty early on with a combination of founders, sales, marketing, and ops folks. And so I would say that generally speaking, the folks that are the best fit for Unify are the ones who are interested in being a little bit more forward-leaning, a little bit more experimental. The idea of automated outbound is a little bit unnerving to teams because there's a whole bunch of questions under that, but some folks are really convinced that it's going to work, and those are the best early customers for us.

We were super fortunate. We actually found early product-market fit just on our first customer OpenPhone. We launched a very basic MVP with them, and it was basically a little workflow engine that hooked into Salesforce and did a lot of the prospecting for them. And within the first couple days of launching with them, we were already booking meetings consistently. I think we put up like 3 to 5 in the first week or something like that.

And so there was pretty immediate pull from that point forward where it was like, okay, this thing is working, people are seeing value in this. Then it was, how do we extend that value? How do we make it so much deeper and more robust? And so that's kinda what we saw product-market fit look like early on.

We are approaching 100 customers today, so we've grown really quickly there. And our core customer, from a team composition perspective, is really how we think about it. It's somebody who wants to launch automated outbound as another growth channel or as another top of funnel channel for them. That's the core ICP.

There are a lot of other teams that sit more tangentially to that ICP. Maybe it's a sales team that's really struggling to operationalize intent data and they see the value, but they can't get it out. That can also be a really good fit for us. And so a few angles that will slot in and help teams here.

Does Unify threaten SDRs in any way? Do any SDRs see someone else on the team adopting Unify and think "Oh no”? How's that dynamic?

We do see that a little bit. The way that we think that this is gonna play out is that the $40-60K a year SDR job is something that we're gonna fully be replacing. We already do for a lot of orgs. Companies like OpenPhone actually don't have BDRs, and we do all of their outbound prospecting for them.

So we already see that. And so I would say the lower end, the less strategic reps who are just quite literally being given a playbook and going to execute, that's gonna be where we're gonna be able to come in and rip and replace. There is, I would say, so we actually have a BDR on our team, Naveen, and he crushes it. He does a lot of stuff that we can't do and we won't be able to do for a while.

And I think what we're gonna see is the dying out of this lower value SDR, the rise of this higher paid, higher value SDR who's kind of like an AE junior. And then what Unify or other solutions in our space will do is actually take the job to be done of those lower value SDRs. That's how we see this playing out. But depending on the org, yeah, we can actually replace people. It's a little bit awkward sometimes with sales teams. And so sometimes that's why we're in marketing.

To set up Unify, you connect with other SaaS tools that you use like Salesforce and your CRM, you drop a JS snippet in your site or connect your CDP like Segment and you connect to sources of intent data like 6sense, Clearbit and G2. Can you talk about each of those pieces and how they come together in a platform like Unify?

We think of ourselves as a data product at the core, not a data product in the sense of reselling data, but more a data transformation product. And so we found that one of the ways that we provide a lot of value to our customers is that we take a lot of intention and care, when we ingest data from a provider like Salesforce or Segment or your website, we actually transform that data into a couple core data models. One is companies and the other is the people that work at those companies.

And then lastly, it's just the activities that are happening around either of those people or companies. And the fact that we take that really opinionated stance out of the box just means that when you plug in your data to Unify, we make sense of it really quickly, and you don't need to actually do much setup at all. And so we've had companies that are more than a thousand employees set up Unify and be booking meetings within less than 7 days of integrating their systems for the first time, just because we're that quick at transforming the data and making sense of it. And so that's been really powerful.

Once we model all that data effectively, the workflows are pretty simple. It's kind of like running a SQL query, but we have a UI that makes it a lot easier to do that, where you can say, "Hey, based off of someone hitting my G2 page and hitting the pricing page on my website and not being a current customer in Salesforce, I wanna reach out to this person and engage with them." All those workflows are just a couple button clicks once we've ingested that data and can run the workflows on top. So that's what we're seeing folks plug in to make sense of them.

If I were just using Clearbit Reveal, I would have the sense that someone from Ramp visited my website. But with Unify, you would give me a few people and the outreach information so that I could just easily populate a message to the best approximate person and send it with a single click? Is that the power of the data engine—that it reduces and de-anonymizes the data and then funnels me into the workflow to make it easier for me to just send the outreach?

Exactly. So we've got all the data to basically make a decision on should I reach out to somebody, and usually that's involving all of your first-party data, but definitely your Salesforce data, maybe even other activity data. And so we'll want, at the very least, to compare those data sources and decide yes or no, do we wanna reach out to this company or this person specifically?

If you know who you wanna reach out to on the person level, it's pretty easy. Launch a playbook in Unify that would talk to that person, put them into an email sequence, and then the rest is history. For a company level, what we do is if you decide you wanna reach out to a company, we let you access your existing Salesforce or CRM data, and we also give you the ability to call out to all of our data vendor partners, pull in contact information. So instead of having to have humans go do that, sellers go do that, we do that for you in real time after we made the decision that we wanna reach out to this company.

And so the idea is that by being able to be thoughtful about when we do these things, we can be efficient on the data side and also, one of the most common concerns of a customer of ours is, "Hey, that's great, you're doing automated outbound, but you cannot email my current customers. That's gonna cause all sorts of chaos for my team internally." And so we prevent that with some of these workflows that we build.

Can you talk about the market for intent data? I'm just really interested in that. What are some of the strongest intent signals that you see? You mentioned Clearbit Reveal, 6Sense and G2. Are there other intent data brokers out there? What are the most effective people who are using this data? What are they doing?

What's interesting is we found that every go-to-market team, they may not recognize it, but their good sellers know these signals already. Oftentimes, they'll be like, "Oh, yeah. When I notice that somebody posts this on LinkedIn, I immediately reach out to that person and send them this." And that's quite literally the same sort of intent or signal data that we would want to pull from.

Some other big intent data sources that we really believe in are things like champion tracking. When one of your current customers moves jobs, that person understands your product and could be a great buyer of it again in the future.

We really believe in email intent data. That's one of the unique bets that we've made with our product. When someone is oftentimes coming back to your emails multiple times, looking at them, and clicking through links in them, that's actually a really good sign that someone is interested in what you're saying, even if they didn't respond. We're returning that into a 1st party data signal that we offer.

For example, job posting data is a really popular one, depending on the business that you are. You can use that as a trigger mechanism to reach out. For us, when someone posts a new job description for someone on demand gen or someone on the SDR team, we immediately know that's a company that might be looking to boost pipeline or bolster pipeline. We sell under the same pain point.

So it really comes back to first principles thinking about your own business. What does your customer do in the 3 to 6 months before they need your solution? And then once you get to that point, you can think through the different intent signals that will work for you.

What are things that you can do with AI personalization via warm outbound, because you're doing warm outbound versus the messaging that you can't otherwise do because it's cold?

I would say that there are signals that you can explicitly mention and things that are more implicit. An example is, in my mind, a website intent visit, if it's at the company level, is more of an implicit signal. You probably don't want to say, "Hey, I'm reaching out because someone from this company went to my website," because that just doesn't show that you've done any sort of research or things like that.

But in the job posting example I gave, something about that is really interesting. It shows that you're well researched if you reference that. Typically what we find is that buyers are looking for things that are hyper relevant to them. Everyone today is used to extremely personalized experiences. You think about the TikToks of the world and how your feed is so personalized to exactly what you're feeling on that exact day. If you don't exactly resonate with that person in the moment they see your email, they're probably not going to engage with you because it's not value additive to them. The more you can fit into their thinking or their specific problems they might have, the more likely they are to respond and engage.

All of these signals, like the job posting one, but also for us, when you click through a link in one of our emails, we can see what you looked at on the website after. That's really helpful and compelling because it shows what problems you might be trying to solve. But really, at the end of the day, it's about how you can provide value for people even through a cold email.

I'll give you an example of one that worked really well for me personally. I bought a product from Carta in about 8 hours after I got a cold email from them. We buy their core cap table software, but one of the to-do list items I had that week was finding a way to communicate to employees how to think about stock options, because I always felt it was very confusing for me coming from a finance background.

We got an email from a rep at Carta. This was quite literally the top item on my agenda. It was a super simple email saying, "Hey, we have this new product called equity compensation advisor or something like that." I asked what it does and they told me exactly what it does. I said great, give me a 15 minute demo and send me a contract in parallel. Then I bought it about 8 hours later. That's an example of the type of interaction we want to facilitate - someone trying to solve a problem and finding just really relevant advice for them.

There's an incredible amount of activity and a huge number of fast growing companies in the sort of "neo sales tools" / go-to-market / sales intelligence / revenue intelligence / rev ops category with companies like Apollo.io, Gong, Outreach, Clari, 6sense and more. How do you map out the market?

It's a really great question. Ultimately, how we think about it is that there are all these software and data vendors that probably add up to a couple billion dollars of revenue at this point. They've carved out these software markets that are mostly geared around productivity boosts for existing people on the teams.

There are obviously all the traditional categories around sales engagement, contact data, call recording, each with respective winners, etc. That was the traditional way of thinking about the world and those companies are all kind of converging as they're seeing the opportunities the others created and going after that. I'm not sure it's been working all that well, honestly. There's been a huge amount of deployment to build these new products and a lot of times, folks are neglecting their original products that they built to go do that.

When we take a step back and think about the market from first principles, we think about the opportunity as going after existing software budgets. But we're also going after headcount budgets for lower value labor that we think we can actually replace. In a lot of ways, what we're trying to do, and hopefully some of these next-gen players are trying to do, is replace some of that human layer element, probably the actual traditional software layer as well.

In our case, we do have folks who will move to Unify from Outreach as an example. That's our core leading pitch, but we do have that happen. More than that though, what we want to do is take away that human labor piece of someone who would have otherwise had to go into Outreach and click buttons. That's actually a lot of the place where we want to provide value.

When I think about these next-gen players, especially the ones who are GenAI native, I really think about them as trying to consider how humans operate around these solutions. How can you make their lives even better by giving them leverage and helping them replace those manual repetitive tasks? So hopefully that's helpful.

We're definitely more in the sales engagement space. We use Attention, which is a great company as well. They're in the call recording space, but we have these LLM elements that emulate more human activity than the actual traditional software vendors.

In terms of next-gen sales tools that might be AI native, who do you see as part of that stack that you might bundle together to use with Unify?

We use Attention ourselves for call recording. You can think about it as Gong plus a bunch of LLM analytics on top of it. What we use it for is to automate the coaching work that I would otherwise be doing for sellers and AEs, as well as a lot of the data transcription back into Salesforce. It's super powerful for them. I definitely recommend Attention.

Default is what we use on the inbound side. Default is a super cool product that replaces a lot of the really annoying and not that useful engineering work that used to have to happen on the website to handle an inbound funnel. I was the PM at Ramp who owned the inbound funnel experience on the website. Just updating the questions we were asking, routing, and whatnot was way too hard. So we use Default to replace that.

We're users of Apollo ourselves. We're users of Clay as well, interestingly enough, on the data side. We actually find that there's this long laundry list of tools and go-to-market is a really interesting space where there's budget for a lot of these different players. But those are some of our favorites.

If Apollo and a lot of these other tools are doing this bundling where Apollo added call recording and all this stuff, what kind of fault line stops them from also bundling warm outbound or some of these other go-to-market motions?

What we see happening is that at our core, what we've built is really a data product, and this data transformation piece is really, really important. It goes beyond just creating the product and connecting the dots.

Apollo today does offer website intent data as a product. They released that pretty recently. So you could argue that they're already in the warm outbound space to a degree. You could launch a similar workflow. But where we really specialize is not only the ability to use, in the Apollo case, data that's built around the Apollo ecosystem.

Unify has built much more to pull data from any sources, notably the CRM, and mesh that really well with the data coming from Unify. The space is absolutely going to keep converging and people are going to keep at it. What's been really interesting to see emerge is that we actually feel like the professional services and the white glove approach to these products is really important and a big piece of activation today.

We spend a lot of time with our customers. Yes, we build software for them, but we also spend a lot of time getting them up to speed on that and helping them set up workflows. Part of that's because we're early, but we also find that it's really important to help companies get to full value from these products. Oftentimes, if you're replacing intricate workflows that they have, it's not as simple as giving them a tool where they can push a couple of buttons. You need to map your solution onto how they run their business. So that professional services angle has been really important.

Can you talk about 6sense? Unify integrates 6sense data, but 6sense also does some of these warm outbound motions. When do your customers use you together with 6sense?

It's a great question. We do have customers that use us in conjunction with 6sense. We also have overlap with Koala as well. What we've found is that 6sense and Koala are really at their core data vendors. The majority of what people are buying them for is that intent data. They have some basic workflows around there, but they're really focused on getting the data clean and right, which is awesome. 

We see ourselves more as the workflow layer and what happens once you've got a signal. Where our lens is a little bit different from these folks is that on face value, can we do a lot of similar things as Koala or 6sense? Absolutely. But we really pride ourselves on what happens after the data. How do we give you the best user experience to make use of that, to activate that data without having to go into another tool?

We actually find that we're really good partners with these folks because we'll plug in those data sources into Unify and then use those to power warm outbound. There's a lot more than just the intent data stuff. It's all the contact stuff, the Salesforce data, making all these workflows come to life. That's where we're really focused.

I think where we'll start to look a lot different in 6 to 12 months is that we're going to look a lot like one of these all-in-one data vendors where you can get a lot of different data types from us. Website intent data being one of them, but there are a lot of other intent signals out there that we want to roll up into Unify. So we're punching down that list over the next 12 months to really beef up the signal side.

With G2, is anyone else doing anything similar to the G2 intent data? Are there other G2 competitors that have a similar data intent product?

There are some really interesting companies doing stuff in that space. Even Ramp today offers a pricing intelligence tool, which is super powerful because they've got enough transaction data to make that useful. So we see companies like Ramp doing this, companies like Vendor are kind of in the same category doing really interesting things.

There are some of the more traditional review sites still, like TrustRadius, Gartner's got a product, Capterra. Those are other examples of those more third party review or third party aggregator sources. I think G2 has been the longest established and has really built up companies having real motions around getting G2 badges and things like that. But we do see some other folks there.

I'm really bullish on the Ramp approach. I'm pretty curious to see how that plays out as the company gets more and more transaction data. The insights should get better.

One of the things that you led with in this disruptive angle of really trying to go after headcount budgets. Can you talk about this as a tailwind for Unify?

I think efficiency is just really top of mind for everyone today. You can see it in our customer conversations, but you can also just see it in public market data. There's been a bunch of big misses from big public SaaS companies like Salesforce, Workday, etc., over the past couple of weeks. There's just a lot of scrutiny around spending today. There are questions about sales productivity. I just think that people are more reluctant to spend dollars today.

It's not that people aren't planning on hiring and whatnot, but everything gets a lot more scrutiny on the go-to-market side than it did 2 or 3 years ago. So we definitely see that in our space. I would say that more broadly, we see that as a headwind for Unify. I've never sold as a seller outside of the 2023, 2024 era, so it's really hard for me to compare what the good times were before.

But if I had to guess, I would imagine that selling today is just broadly harder than it was 2 or 3 years ago. With that being said though, I do think that one of the beauties of our business is that we are really tightly coupled with clear attributable revenue. So we can build really clear business cases on the incremental value we bring to a company. That's been a really great mechanism for us to still grow really efficiently, be really thoughtful, and land great customers. We'll keep leaning into that.

When we started, I asked you to explain Unify. You said it's sort of an autonomous SDR that operates on top of your own data, and warm outbound might be one component or playbook. Can you talk about what other playbooks there might be within that framework, and how you think about capturing those different playbooks?

At our core, the fundamental building block of Unify that powers all the value we create is this concept of a play or playbook. It says: given some trigger, go ahead and take an action against that trigger.

Anything that falls into that bucket is something we think we're uniquely differentiated to power. That can take a couple different forms. There are workflows that kick off from inbound sales triggers. Someone will come inbound off a website, and it's a best practice to get in touch with them as quickly as possible. We think about that as fitting into the same playbook construct we were building at Unify.

A lot of the same frameworks we use can be applied to things like Slack alerts, letting humans know of certain key actions. At its core, it's really built around this concept of a playbook.

There are a few other things we'll slot in there, but we're narrowly focused on warm outbound and signal-based outbound for at least the next 6 to 18 months. You can imagine a whole world of other signals or workflows we can get into later.

One of the big drivers for Apollo's insane growth and efficiency has been self-serve. Before, with ZoomInfo, access to this data would be heavily gated. Right now, with Unify, if I go to the site, I have to book a demo. Do you think self-serve is going to be a big part of your growth story, and how do you think about that piece?

When we started out, we saw the self-service path and the sales-led path. We wanted to prioritize one thoughtfully because we wanted to give it all our energy, and there was a slightly different organizational muscle around each of those motions.

We started with the sales-led approach because we felt it would be valuable for us to learn more quickly from our customers and spend more time with them. We also saw it as a differentiator in our category where most folks at the time were very self-service oriented.

We are now at the stage where we think it makes sense to do both. It's a near-term priority of ours to build that self-service track and make it easy to onboard. We see in our inbound funnel there are a lot of companies who come inbound wanting to use Unify that we don't have time to talk to all of them. So it's the right jumping off point for us to open that up.

One feedback I've heard on Apollo is that while their growth has been high velocity, they haven't been expanding customers and ACV well because a lot of it is seat-based. How do you think about net dollar retention and expanding that over time?

Monetization and charging customers is just trying to take a piece of the value that you create. Positive net dollar retention signals that you're creating more value for that customer year over year.

Historically, people would grow into more seats, buy more of the product, and get more value out of that. But there are different ways to think about it. Our North Star Metric internally that we really care about is pipeline created for customers. That's what we focus on maniacally.

As we launch new product offerings that still serve that same goal of driving more pipeline, we do that consistently and keep driving that number up. We've seen success in getting customers to commit more to using Unify. Some of our earlier customers have already expanded 2 or 3 times through being able to offer them new products.

We started out with a prospecting workflow layer, but now we do end-to-end descending. We've had a ton of adoption into the actual sending layer, which gives us an upsell lever.

Net dollar retention is about: for the customers you have today, are you building what they want and are they willing to pay for it? The rest should sort itself out. Our pricing levers are the number of seats on the product and the number of credits used, which align tightly with the value we create.

OpenAI is an investor in Unify, and you use it to personalize messaging. How big is the opportunity for Unify with the concept of AI-native sales tools over the next year and 5 years? Is it incidental or really core to what you're doing?

It's a really big driver for us. AI by itself is not enough for our solution, but it certainly takes you from a 6 or 7 out of 10 to a 15 out of 10 in terms of the value you create if you can embed AI really thoughtfully.

We think about it in 2 frameworks:

First is the workflow layer element where you can embed LLMs to understand highly repetitive workflows and solve those at the same level of quality as a human. An example is account qualification.

Someone comes inbound, and the first thing a seller does is check their LinkedIn profiles to get key details like who the company sells to, if they have a public pricing page, what to notice from their job descriptions, etc. All of those questions are answerable with AI today in a way they weren't with traditional workflow software before. That's AI embedded in the workflow.

Then there’s the more creative, generative elements, notably copywriting for us. But there are other ways over time, like picking up the phone to call somebody or sending a direct message. Really what you're doing is trying to give LLMs all the data possible to make a good decision and coaching it on how to make the right decision with that data.

We're really excited about both those use cases. Having OpenAI has been an accelerant on both, so we're super grateful for that partnership.

If everything goes right for Unify over 5 years, what do you imagine it will become? How is the world changed as a result?

We think that in 5 years, if we do our jobs well, we will have replaced a lot of spend that's being wastefully deployed into things like 3rd tier Google and Facebook ads. We think autonomous warm outbound should be a de facto channel for people 5 years down the line.

That should be a better experience not only for our customers who are creating meaningful interactions and engaging at the right time, but also for their customers who are only getting messages, content and things that are personalized to solve their unique problems.

We have a bullish and positive perspective on where AI will take sales. Not that it will end up in this place of all this crazy spam, but rather people will focus on what's relevant for that person and what creates the right experience for them. We think sales will move there over the next 5 years as AI lets you do those things more effortlessly.

We want to function as an autonomous SDR operating on top of your warm outbound data today. Later on, we'll see what sources we plug in. But the goal is a lot more relevance, timeliness, and a lot less repetitive busy work.

What changes when AI-powered warm outbound meets AI on the buyer side, where my AI double is receiving outbound and getting me further along in my buying process?

I'm not that bullish on the AI parser of your email or whatever it might be. I work with a great EA who does a good job parsing through my inbox and deleting obvious things.

But often there's a lot of context someone needs to make a really good decision about something they could delete for me. The problems that come with a false positive on that are pretty bad. Imagine you get a really important message and your AI agent deletes it. You don't have anyone to blame and you've just missed this great customer email or whatever it might be.

I think there's a long way to go. I'm optimistic for that way of the world to eventually get there, where you have this EA that sits in your inbox and is AI-assisted to help you out. But I think there will be an important human review process, where AI needs to know your goals. We're still pretty far away from knowing that.

We'll see where it shakes out, but the hope is that we're relevant enough at that point and hitting the right people that we're getting sorted into that really relevant bucket for folks.

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