The Revenue Command Layer

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Lily Austin: Just get started, is my advice.

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Julia Nimchinski: Thank you so much again, and we are transitioning to our next session. Erin Mcreynolds, the co-founder, and CEO of Alysio.

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Julia Nimchinski: We are going to dive in into the revenue command layer.

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Julia Nimchinski: It’s a different session, super unique one, so excited to have you here. How are you, Aaron?

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Aaron McReynolds: I’m good, Julia, how you been.

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Julia Nimchinski: Been great great day. Lots of exciting use cases

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Julia Nimchinski: on a gentic scaling, so curious to see your take.

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Julia Nimchinski: and how you really connect it all.

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Aaron McReynolds: Perfect. Let me

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Aaron McReynolds: We’ll jump in and share my screen.

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Aaron McReynolds: Hi.

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Aaron McReynolds: perfect! That coming through.

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Julia Nimchinski: Awesome. Yep.

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Aaron McReynolds: Brilliant. Yeah. Nice to meet everyone. Appreciate the time we get to spend with all of you. Thank you, Julia. You know as as we think about the age that we live in as as go to market executives. You know I’ve spent the last decade of my career both as a sales rep, as a manager, as an executive. And when we started, Alessio, you know we wanted to set out with one mission like, How do we help drive revenue growth within organizations?

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Aaron McReynolds: this age of AI is moving so rapidly. You know, I’ve been listening to some of the sessions this morning. Everyone has different takes on where we’re going, how to build. I’m actually almost going to jump in and answer the question you ask. At the end Julia and I would say, learn to cut through the noise right. And I think that’s been my biggest takeaway from this, just as we kind of did a similar approach with Sas applications as they came out. We’re adding tools, left and right.

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Aaron McReynolds: You start to see this overlay, and you’re spending time operating out of too many tools and people trying to build too many agentic workflows. Try and understand what the use case is and what the outcome is that you’re trying to drive towards, as we think about the way that Alicio is positioned. We call it the revenue Command layer, and we built it for one purpose. It is to ingest

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Aaron McReynolds: all of your go to market data from all of the different tools that we now live in into one very single interface. And the way we think about this is simplistic in nature. Revenue operations is broken, and I know this is a bold statement to come straight out of the gates with. But we wanted to build a tool that helped revenue teams who are living in tool silos

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Aaron McReynolds: in team silos be connected in one place.

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Aaron McReynolds: and when I say, revenue operations is broken. What do I mean? I’ve hired revenue operations leaders. We have a revenue operations leader. The purpose and intent of having a Rev. Ops team is for them to be strategic right? They are supposed to help drive revenue growth.

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Aaron McReynolds: Unfortunately, what has happened is they have become task takers and order fillers for the sales organization, usually because of us as sales reps, being somewhat incompetent when it comes to tooling. And in technology, we just go and seek out the help of the Revops team. I need a new dashboard. I need some new data points. I need to understand Xyz today.

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Aaron McReynolds: And then all of that ends up going into tickets and into workflows that the Revops team has to then just go and close out, and they don’t get the time to be strategic and do the things that they were hired to do in the 1st place.

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Aaron McReynolds: So when we look at the state of go to market teams right now, I wish this was more interactive, and I get a show of hands and understand, you know, the the kind of disparity that we have here in the tool stack. But Zoom Info came out and said, There’s an average of 31 tools across enterprise. Go to market teams and that sales that’s marketing. That’s Cs.

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Aaron McReynolds: and what happens is, we now have so much data within our go to market teams. But we don’t know how to interact with it. And so what have we done for the last 1015 years? We’ve created data lakes, and we’ve created dashboards. And we’ve hired revops, analysts and data engineers to come in and help us understand that data.

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Aaron McReynolds: What we set out to do is to create the most seamless, simple, yet complex on the back end way to interact with your data. The most frictionless way that we could figure out how to do this, and what we fell on is like I mentioned one interface for every single tool.

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Aaron McReynolds: Another bold statement that I’ll make is, you know, I see these Saas applications that exist today that I’ve lived in as a sales Rep and a manager for the last decade as now. Back end applications. Right? The data is in there. The historical data is in there. I don’t see them going away.

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Aaron McReynolds: But as we move into this, you know AI world, they are now going to become background. Right? I’m gonna log into a call. My call record is already in there. Great! It’s going to pipe my notes into salesforce. Great! That’s my back end.

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Aaron McReynolds: What we wanted to do is give you the most seamless front end.

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Aaron McReynolds: So how do we do that?

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Aaron McReynolds: The ability to reduce latency? You know I’m I’m thinking of, you know the Life of a Cro. We’re talking to a Cro the other day we asked them to walk us through in a live demonstration.

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Aaron McReynolds: Think of any question you can think of that. You ask, maybe on a daily or weekly basis, and walk me through that workflow. What do you have to do? And it was as simple as Who’s the Csm. On ABC Box Company? To answer that very simple question had to open a browser, had to log into the salesforce account had to remember the opportunity. Search that opportunity, go into the opportunity, record scroll and find the Csm.

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Aaron McReynolds: What we wanted to do is allow you, in one interface to just ask that question. Anything you think of.

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Aaron McReynolds: Just ask it and get that data returned to you instantly. So we help reduce that latency, that workflow headache that we all live with, remembering which application holds which data source and trying to go in and take action in a certain application. How do we put that all into one interface? So we’ve actually attempted to unify the entire go to market organization.

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Aaron McReynolds: Every data point sales lives in their own tools. Cs lives in their own tools, marketing lives in their own tools, and none of them speak to each other in an easy way. When you’re a sales rep. You want to know what marketing campaigns the marketing team is running. I want to invite my economic buyer to one of those events, but I don’t have access to their marketo instance to go in and search that and find that information.

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Aaron McReynolds: We can now do that. So we connect every single go to market tool into one simple interface.

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Aaron McReynolds: So the way that we do this, like I said, we wanted to create the most simplistic user interface and experience. But behind the scenes extremely complex. What we’ve built is the ability to have the largest distribution of Mcps in go to market with the most context, rich and deep integration that we could provide. So we, you know, struggled always

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Aaron McReynolds: to understand. How is my salesforce environment set up? How’s my Hubspot environment set up. Is it different? How do I connect 2 different tools when they don’t speak the same language we have solved for that. So we integrate into any tool that you have in your stack. We understand the context instantly. We see everything, and we allow you to go and act instantly as well.

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Aaron McReynolds: So 3 phases to this, and the way that the application works 1st is, ask so ask any question that you have anything you’re thinking of. Just ask question. You’ll get the response. Secondly, is, do anything because we integrate with these applications. I haven’t been in salesforce since we rolled out Alysio.

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Aaron McReynolds: I create every opportunity. I update the records. I change the stages autonomously. We’re rolling out voice. So imagine being on the road finishing a meeting and just saying, Hey update the stage to stage 5 instant autonomous action. And then the 3rd piece is is, you know, essentially being able to tell you

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Aaron McReynolds: in real time and ahead of time any of the questions that you historically have asked the application. Now, when we think about this, we do ask very similar questions, we have dashboards because we’re looking for the same answers over and over and over again. But we have to update those we have to maintain, those we have to have a team to build those

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Aaron McReynolds: we want to reduce the way that go to market teams run, which is very, very reactive.

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Aaron McReynolds: We missed quota. Let’s go find out why a rep. Just quit. Let’s go find out why our pipeline is inaccurate. Let’s go find out why and that’s the way that revenue revenue operations acts. How do we make that be as proactive as possible? It’s by understanding the context behind every single data point in our entire organization, the ability to stitch it together, and then be proactive, and surface those insights for you.

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Aaron McReynolds: So again I I know, I said. It’s complex in nature on the back end. The way that you interact with it is really simple.

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Aaron McReynolds: Connect every single one of your go to market tools. I’ve done 3 onboardings this week. It’s an average of about 4 and a half minutes to connect every tool within the platform, and then you instantly have access to go in and query. Now we’ve built this in a natural language interface. So think, chat, gpt the way you would question. We use Chat Gpt, for whatever questions on our minds as a human. We now do that with all of our data points. So natural language

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Aaron McReynolds: interface.

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Aaron McReynolds: Like I mentioned, we understand the context across all of your tools. And I don’t think this point can be understated enough, and any team, and I think the session before, or maybe 2 before, was talking about you know how much revenue has been generated for salesforce just by implementation teams setting up instances in certain ways. One sales leader wants to set it up differently to another.

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Aaron McReynolds: We don’t care. Everything to us is actually standardized. We just ingest all that data at raw, understand the context and then can deliver you those responses.

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Aaron McReynolds: So then we go in and identify the trends, the risks, and next steps, and powered by predictive models. Now we have built models that understand the go to market organization. We can go as deep as we need to within that go to market context to be able to understand and know the language of sales organizations, the questions that they ask, but more specifically, the questions that you ask over and over again and understand. You know the data points that you need to surface

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Aaron McReynolds: the actionable answers again, this is the most important piece, being able to not just ask, but be able to go and do and tell all within one interface. You know, excited to kind of

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Aaron McReynolds: detail how that that exactly works.

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Aaron McReynolds: So by being able to detect risks before they hit pipeline, we see an entirely new category within. Go to market. We’ve coined it. Revenue security. Now I came from a cloud security selling background. That entire way of thinking is, everything is a risk.

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Aaron McReynolds: and everything is a vulnerability that we need to go and solve. For before it happens, can we alert you before it happens? Unfortunately, we don’t talk about it that way. Enough within the go to market organization, whether it’s human error, etc. We put it down to the people. A lot of the time we didn’t update salesforce correctly. The data wasn’t input correctly, that cell is not actually that good.

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Aaron McReynolds: But at the end of the day everything is a risk and a vulnerability that can be identified. And so, by essentially allowing you to look around the corner, know which risks are coming down the pipeline which risks are coming across my people. We can then go take action. So it’s not just speed to identification. It’s also speed to remediation

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Aaron McReynolds: and then trigger those OP. You know those actions without your operations team. I can tell my interface how I operate the way I think the questions I ask, and just have that surface to me autonomously. There are no more tickets to the Revops team. You don’t need that. In fact.

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Aaron McReynolds: I know this is bold. But we, we have a clay table running right now that has anyone who has a job posting for revops analyst, you don’t need a revops analyst anymore. All the data is at your fingertips. Just query it and understand it in the most simplistic way possible.

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Aaron McReynolds: So we wanted to reduce the amount of applications you need to live in, and I don’t know about you, but I sit there, and I have 1015 tabs open at all times that I’m hoping in between.

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Aaron McReynolds: But what I can’t do with that is, take the context from one application and apply it to another. And what we’ve been able to build is. When I ask a question, I can query both Salesforce Marketo, my Google Calendar, my drive all at the same time, just in one simple question, and we can go and hit every single environment, combine that context and give it back to you on the most simplistic response

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Aaron McReynolds: possible. That ability to have the context across those different systems is is unique in the ability to get that answer as quickly as possible. We’ve built the entire platform for speed.

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Aaron McReynolds: one interface to reduce the sprawl across those different tools. And you know I’ve been doing this a lot. I I sit down with revenue leaders, and you know so often this conversation of

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Aaron McReynolds: consolidation comes up, you know all the historical vendors and revenue intelligence, etc. All woke up, decided to have a call recording capability. They all have outbound sequencing capabilities, and most of those tools look the same.

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Aaron McReynolds: and that was great where we could just consolidate into one tool. But what have we done and go to market? We’ve sacrificed. We’ve said I bought a tool that has the best conversational intelligence, but their outbounding sequencing is not that great? And the forecasting is pretty average, but I can live with it because it’s all in one place. Well, we don’t have to do that anymore. We can have best of breed for every single use case.

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Aaron McReynolds: Because now there’s 1 interface to query, all of that data. So you can go and get the best conversational Intelligence Platform and pay the smallest price just for that. But it is the best. You can have the best sequencing platform. It doesn’t matter because you’re not actually interacting with those front ends anymore. You’re commanding everything from one interface, one single AI native interface. I want to talk about just some of the use cases and and stories and impact. You know that we’ve seen across our customers. Most importantly.

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Aaron McReynolds: the ability to query any question that you have at any time. You know I was on with Cro the other day and and did this.

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Aaron McReynolds: you know, while he was live, just picked up his phone and just talked into the phone. Being able to ask any question as soon as it comes to mind. As I’m walking into a sales meeting. As I’m getting off a call as soon as you need that data. As soon as you need to take that action you can do it. There’s no lag, there’s no latency.

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Aaron McReynolds: The action across all platforms. I kind of highlight and touched on this. The other day I went in, created an opportunity. I set the amount I set the economic buyer. I also said, Send a follow up email. I also said, send a follow up calendar, invite for next week to come in and connect. That is all in one chat, right? I used to have to be in 3 different applications to do that, and that latency between the tabs and

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Aaron McReynolds: queries and the applications obviously is, is why we built the platform.

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Aaron McReynolds: The most important piece at the end of the day is focusing on revenue growth and revenue growth comes from my people. And you know, we actually built a separate application all around top of funnel productivity things, Strava for your sales teams.

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Aaron McReynolds: At the end of the day pipeline comes because of great people, but to be able to identify weaknesses within your team identify strengths within your team, historically, has been a really difficult process. Do we have the right indicators? Do we have the right context around managers doing the right actions. You can now query that all in one single interface.

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Aaron McReynolds: So who’s it built for? This is the question we get the most

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Aaron McReynolds: for everybody in. Go to market from the Cro to the Sdr. From the Cmo. And you know to your customer success team by unifying every single tool within the go to market stack.

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Aaron McReynolds: Everybody has an application of this platform. Now, the way that we interact with it is going to be different. And the questions that we ask are going to be different. One of the questions that comes up frequently is, How do I kind of limit the access to the data for all my individuals. I don’t want an Sdr. Querying our forecast for the entire organization, or which deals are at risk in the entire organization.

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Aaron McReynolds: We go off the context rules and permissions of whatever you have set up in those applications. So if I am an Sdr. And I query, What are my? You know, open opportunities. It’s only gonna hit mine. If I’m the Cro. And I say, my, my, now means my entire organization, it goes off, whatever the context is of those permissions. So again, built for everybody within the go to market organization.

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Aaron McReynolds: we see it as the Iron Man suit for your Rev. Ops team

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Aaron McReynolds: don’t keep building latent dashboards, historical dashboards, the need for extensive data lakes.

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Aaron McReynolds: every single Mcp that we built lives within your environment, that data stays within your environment. And it’s the most secure and safe way to interact with Llms and data in this age right now. And that was one of the most important pieces when we built the application is, how do we keep your data within your environment and make sure that it’s as secure as possible? So we built for the enterprise.

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Aaron McReynolds: Why can we do this now? The shift, obviously with with AI in in recent years, continues to accelerate.

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Aaron McReynolds: I don’t know a cro that I’ve spoken to in the last 5 months. That isn’t AI. First, st if you’re not, you’re going to get left behind. The speed to execution within. Go to market has changed so rapidly. I was trained on medpick right? Every single deal that I’ve done in my entire career is following this rigid, strict, medpick process.

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Aaron McReynolds: spoke with our head of revops yesterday and said, I don’t know how that applies going forward. When you think about companies like repla going from 10 to 100 million in 6 months.

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Aaron McReynolds: They cannot be running an entire Med pick process to go and close those deals, and the state of sales is just changed. So if you’re selling an AI product, if you’re selling to an AI buyer, the speed to execution has just increased so dramatically, we have to be able to adapt, and we have to be able to run that fast. The other piece is, the technology is now there. We’re building on the forefront of what is possible with AI,

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Aaron McReynolds: and to be able to do that, you know, we have to stay ahead of where the trends are going. You have to be able to adapt and move quickly, and I was at a conference recently. They talked about 2024 being the year of the co-pilot that is now dead, because you don’t need a co-pilot in every single individual tool that you have, you need a companion across every single tool that you have.

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Aaron McReynolds: This is the year of agents, and we continue to focus on scaling agents within workflows and and whatnot. Where do we go next? How do you stay ahead of those trends.

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Aaron McReynolds: So I think the biggest takeaway is we have moved from dashboards to autonomy. I want to command my own data. I want to have instant access to my own data. I want to have the ability to take instant action on on my data across every single tool that I have.

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Aaron McReynolds: So we see this is the future of go to market one interface. That your entire stack has been missing. But you’ll be happy to take any questions.

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Julia Nimchinski: Fascinating session. Thank you so much, Erin.

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Julia Nimchinski: There is a question about revenue security here. And curious your take. So Steven is asking how long? Until the bigs gong salesforce hubspot, etc, block out the companies being featured here today?

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Julia Nimchinski: How will the most likely? How will that most likely happen, blocking or increasing, pricing on Api access, charging for data, scrape or past, etcetera.

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Aaron McReynolds: Yeah. Fantastic question. You know, I think about this as well from a sales perspective, right? And it keeps me up at night. Of how open are we going to be to sharing our data? I think at the end of the day organizations have been somewhat hesitant to adopt AI. We talked to a company this week who said, You know, we can only use Google Gemini because it’s the only one approved.

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Aaron McReynolds: Okay? Well, at some point, you know you’re gonna get left behind if another model advances and you’re now behind the 8 ball, how do you survive? And it’s I think it’s gonna be a continual war based on this is the data within our platform, and no one can have it. Look at salesforce with slack. I saw a post today talking about. Hey? Here’s an alternative. Get off slack and go run this application. It’s open. It’s open. Source is, gonna make your models better.

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Aaron McReynolds: And so I think it becomes this internal discussion that has to take place across every organization to say, Are we AI friendly? Do we want to stay in this race? And what are the best ways that we can still remain valid. I think this concept of like, let’s hunker down into our own platform. Our data is our data, and we’re not going to share it. We’re not going to go anywhere.

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Aaron McReynolds: Honestly, I think it’s a death sentence, so I may be right. I may be wrong, but I see that that kind of being the direction that everybody is going, the tools that are playing nice, the open source mentality. They’re actually going to be the ones that I believe win

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Aaron McReynolds: great question.

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Julia Nimchinski: Great answer. Next question, where do gentech systems tend to break down in Gtm works? What are you seeing.

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Aaron McReynolds: Yeah, I I think

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Aaron McReynolds: when we think about the way that sales teams operate again, I come from a sales background. I’ve been a sales rep. And the difference between a Cro that you know has been told he needs to go and be aggressive on implementing AI down to an Sdr.

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Aaron McReynolds: It’s a massive scale, right? And the way that we can go and adopt AI, when I think about those workflows like, I said at the very beginning, how do you cut through the noise? If I’m a Cro today, I’m literally going to my Sdr. And saying, What can I do to make your life better and easier. I’m not just going to throw things at you. I think about this from a tooling perspective.

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Aaron McReynolds: 10 years ago I was at a large sales organization. We were piloting a tool.

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Aaron McReynolds: It wasn’t just the Rev. Ops team that sat down with that tool. They brought in 3 different groups. They had Sdrs trial it. They had aes trial it, and they had managers trial it. The managers all wanted the tool, the Aes and the Sdrs. Didn’t they ended up purchasing the tool for the managers, and it churned in a year because nobody adopted that tool. So when I think about these workflows, we spend so much time trying to implement them and

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Aaron McReynolds: try and build it the right way. But talk to your team so that you’re actually building the right thing that they need at the end of the day. And and again, I think there’s gonna be consolidation of workflows right like they’re just gonna get more powerful in time and be able to cover more.

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Aaron McReynolds: And so, yeah, I would just say that communication with your team of like, what is the use case that we’re trying to solve. For which piece do we want to replace? And I also think again, probably another bold statement.

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Aaron McReynolds: Do you want to get to a point where you have these agentic workflows that are maybe replacing people

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Aaron McReynolds: right? And I think that’s a question we need to ask ourselves, how do we get, you know, sustain the human in the loop aspect when these workflows are actually getting so powerful that I see roles going away.

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Julia Nimchinski: Another question here about Alicio. How do you handle context, transfer across tools in multi-step processes.

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Aaron McReynolds: The secret sauce, maybe have a conversation offline about that. Yeah.

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Julia Nimchinski: Awesome. Yeah. Another question. How do you decide what should be agent led versus human led, speaking on

03:25:08.290 –> 03:25:09.839
Julia Nimchinski: building on the last one.

03:25:10.090 –> 03:25:14.406
Aaron McReynolds: Yeah, yeah, I I think you know, kind of to the the point that I was making.

03:25:15.460 –> 03:25:19.023
Aaron McReynolds: I’m I’m faced with this. I I have an Sdr

03:25:20.080 –> 03:25:27.700
Aaron McReynolds: how do we make sure that I can essentially extract the skills that he has as a human

03:25:27.700 –> 03:25:56.420
Aaron McReynolds: versus sitting there and watching him doing these mundane tasks that I know can be automated. So I think you have to sit down, and with every role within go to market. Say, what is the dream state? If I could have this person spending a hundred percent of their time on one thing, what is that? About a year and a half ago I was on a podcast. Speaking about how I see sales becoming like the Nfl.

03:25:56.570 –> 03:26:08.299
Aaron McReynolds: And what I mean by that is, everybody in high school wants to play football every you know. Select few, then get to go and play in college, and even fewer actually get to play in the Nfl.

03:26:08.300 –> 03:26:33.159
Aaron McReynolds: And I see that happening across go to market. I don’t know too many organizations right now that just have this massive open ae headcount or massive open. Sdr. Headcount, we’ve been very selective. We’re now getting to a point where we all believe that we can have the best of the best. We need fewer, and you start to handpick those individuals right? If I just need a close.

03:26:33.160 –> 03:26:40.370
Aaron McReynolds: And that’s the best role that a salesperson can do. And I can automate the 70% before the close.

03:26:40.710 –> 03:27:06.549
Aaron McReynolds: I’m going to go get the best person that can close. And so I think you start to look at the different processes. And and I guess historical strengths that humans had and say, Well, what part of that can I make autonomous? And if I do that, what’s that last 30% that I actually need the human to do and pick the best individual for that. So I even think, just from the way that we are hiring and thinking about how to construct a sales team.

03:27:06.790 –> 03:27:17.169
Aaron McReynolds: I’m building it like the Nfl. I want the best people on the field that I can get to go do the certain roles that I need, and I’m you know, making everything else autonomous right now.

03:27:17.850 –> 03:27:18.650
Julia Nimchinski: Love that?

03:27:19.439 –> 03:27:25.680
Julia Nimchinski: Another question here. Yeah. So what would you avoid automating? Erin.

03:27:26.320 –> 03:27:40.120
Aaron McReynolds: What would I avoid? I’m a people person, right? I’m a seller. That’s what I do. I believe sales is built on relationships. And that piece I would not replace, and even things like

03:27:40.360 –> 03:27:57.049
Aaron McReynolds: the gift sending and whatnot. How do we make that as human as possible? You know I try and not have the human touch be automated in any way. Now, an email. Unfortunately, AI is writing better emails than the Sdrs can. It’s a fact.

03:27:57.050 –> 03:28:12.710
Aaron McReynolds: I don’t think the AI Sdrs are making better calls than the humans can yet, but I don’t give it that long. We’ll be there very very soon. But that human interaction to me, the closing part of a deal, the trust part of a deal.

03:28:12.710 –> 03:28:27.359
Aaron McReynolds: I don’t see that going away. But again, that’s kind of back to that previous point is, how do you go get the best relationship builders? If I was hiring today, I would look at you know, connections. People have networks. They have the personal brand that individuals have.

03:28:27.360 –> 03:28:57.220
Aaron McReynolds: and that piece cannot be replaced. Right? I buy most things based on trust. Or who do I know at that organization. Do I believe I’m going to get taken care of if I sign a contract. If you were to go and purchase a software and know that everything post sales was agentic. Would you do it? No, but that’s kind of the way that companies are trying to go. I can automate all of Cs and everything it’s like. No, there needs to be that human in the loop, because at the end of the day that is where I think the buyers are going to come in.

03:28:59.080 –> 03:29:05.380
Julia Nimchinski: Thank you so much, Erin. Great session! And what’s the best way to get a test drive of Alicia.