Maksim Ovsyannikov Podcast Transcript
Maksim Ovsyannikov joins host Brian Thomas on The Digital Executive Podcast.
Brian Thomas: Welcome to Coruzant Technologies, home of The Digital Executive podcast.
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Welcome to The Digital Executive. Today’s guest is Maksim Ovsyannikov. Maksim Ovsyannikov is an enterprise product leader with over 25 years of experience building some of the world’s leading business productivity solutions across supply chain management, HR service management, Salesforce automation, marketing automation, and customer success.
Maksim served in leadership roles at a DP, Saba Zendesk, Salesforce Grove, and most recently, Ian Cobb was an executive Vice President of product and Design at Gainsight. Maxine brings passion for beautifully simple products and latest AI innovation to sugar.
Well, good afternoon, Maksim. Welcome to the show.
Ovsyannikov-Maksim: Thank you, Brian. Nice to be with you.
Brian Thomas: Absolutely. I really appreciate your time today, and you’re hailing outta the San Francisco Bay Area. I’m in Kansas City, two hours difference. But again, I appreciate you navigating calendars, time zones to get on a podcast with me. So thank you. And Maksin, you’ve led product teams and supply chain, HR service management, marketing, automation, and much, much more.
Then moved into CRM and go to market technology with SugarCRM. What was the thread you saw across all those domains that brought you to focus on CRM next, and how did your experiences in different verticals prepare you for your current product challenge?
Maksim Ovsyannikov: Yeah, I appreciate this question. I think if you look at everything that you just said, one of the common threads is that all the tools, all the technology that you mentioned, all of it is enterprise software.
So, if you kind of look at what I’ve done over the last, more than two decades is ran different versions of enterprise software and different compositions of. Organizations that built different business productivity software. And one of the challenges across all of ’em is building business productivity software, which is actually what enterprise software is that actually improves productivity.
So, it’s funny, Brian, when you mention marketing, HR service, et cetera, right? The goal of enterprise software in each of those categories is to improve productivity and. Wouldn’t it be awesome if we could also improve productivity among our sellers, among everybody that has customer facing interactions, right?
That’s kind of what brought me full circle to CRM and, uh, to my current focus on helping sellers sell and helping customer success teams keep customers happy.
Brian Thomas: That’s awesome. I love your backstory. A lot of experience there across different verticals, but the common thread, as you mentioned was that enterprise software, and the big challenge is improving productivity in these enterprise softwares, and I appreciate that you’re focused on the customer and helping them improve their productivity as well.
And Maksim, you described Sugar’s ambition as building the first AI native precision selling platform for go-to market teams. What does precision selling mean in practical terms for a sales team today? And how does AI need to be architected to deliver it? Not just insights, but workflow enabled action.
Maksim Ovsyannikov: Yeah, that’s an awesome question. And in order for us to kind of really dissect it, we need to step back a little bit in my opinion and ask ourselves when we want to implement tools and software to help sellers sell, what type of software comes to mind? And I think that if you ask Chief Revenue Officers, I think the first answer you’re gonna get is a CRM.
Right. There are very few businesses that can. Leave their customers behind and not have the CRM, that is a customer relationship management system for them. And if you look at the original promise of the CRM, which is companies like Siebel, Salesforce, and their originality, the original promise of the CRM was to help the seller sell.
And if you really look right now, and if you ask sellers that use these CRMs, whether or not CRMs help sellers sell, you’ll be shocked because most of the people will immediately tell you that A CRM has practically never help the seller sell. It has never helped a sales leader lead a sales organization.
And therefore it has never really delivered the outcomes for which it was originally purchased. And then the question becomes is, well what type of CRM or what type of technology can actually help a seller sell? And that’s what we call precision selling here at Sugar. That’s a framework that we arrived at.
And there are four components to the precision selling framework that we advocate for. The tools in precision selling that can help your sellers actually sell are one that can help them bring good leads. That sounds like a no brainer. But CRM has never really helped seller bring good. Leads with a lot of intelligence.
And so the first component of the precision selling framework is to help bring good leads into the hands of the seller. Second pillar is to identify risks and opportunities within those leads, right, so that you know what to manage with what urgency and what priority. Third component is to be as prepared as you can.
That’s a very important AI component that we can dissect and talk more about. And fourth is incredibly important as well, is feel coached and supported. And these are tools for your manager and the executives and the sales organization to help coach and support sellers so that they can win. And all of these components, all of the four components of the precision selling framework really benefit from AI in order to make them effective.
If you think about it, if we wanted to bring really good leads and analyze them without ai, let’s say a CRM five or 10 years ago, we would have to rely on workflow rules and automation that are in most cases outdated and don’t really use intelligence of artificial intelligence. Certainly don’t use intelligence of generative AI.
To make that effective. And so, across each of the pillars, bringing the good leads, identifying risks and opportunities, building playbooks about how to engage in those risks and opportunities, and then feeling coached and supported AI, generative AI, a gene AI. Augmentation AI plays incredible role and that’s why AI is so center in, in our solution.
And that’s why there is really no precision selling framework, or I should rather say there’s no precision in the precision selling framework without ai.
Brian Thomas: Thank you. And AI certainly does augment a lot of things, so talk a lot about that on the podcast here. But just to highlight a, a few things, I think it’s important.
You mentioned that CRM is a key part of any business helping the seller sell. Of course, improve that customer experience. But most people, as you said, would probably disagree with that because they haven’t really seen a true CRM that can do that. And that’s what Chi CRMs all about if you’re trying to take it to that next level.
But the four tenets of precision selling, as you mentioned, just again summarize for our audience bring good leads, identify risks, be prepared as you can, and then coach and support the sellers that are using the CRM. So I think that’s awesome. Thank you. And Maksim, with increasing automation and AI embedded into product workflows, how do you see the role of human user evolving in enterprise apps, especially in sales or CRM?
What tasks should AI take over and which ones must remain human driven to preserve context judgment and empathy?
Maksim Ovsyannikov: I love this one, and I’ll start at the end of the question. First of all, I think there’s a little bit of confusion going on around that AI removes from preserving context, judgment or empathy.
And let’s just take one example, for example. What is one example for example, that’s funny, but I’ll still, I’ll use that. Let’s just take empathy as an example. So when I think of empathy, right, empathy has a lot to do with understanding. If anything, I think generative AI tools give us more, more information and more perspective in an understandable way.
So, if anything, generative AI helps with empathy. At least that’s my theory, because if you give humans. Better perspective, that’s more understandable, which is what generative AI does. It gives humans more empathy. So, I really feel that we cross context judgment and empathy. As you say, generative AI is not sort of. Instead, it’s very much in addition and is a huge enhancer of those qualities, of those human qualities.
Another point that I’ll make is it’s very frequent that you’ll read in the news every day, frankly, that there’s this worry that AI will steal jobs almost, that it will take away and it will make you as a human useless in the position with the specialty or the skillset that you currently have. And I have a slightly different theory.
I almost have a call to action here to your listeners that you are not going to lose your job to ai. Instead, you might lose your job to a human that knows how to use ai. And so the call to action here is, don’t think. Of sort of certain sales roles going away or certain BDR and SDR roles going away, or certain customer success roles going away, think of how your role, the role that you’re in now can become better and more effective more productive, as I said with ai.
And that’s pretty much what AI is meant to do. How are we evolving? I think was another part of your question is what tasks should AI take on and how is it evolving? There are sort of two kinds of AI that we need to think about, and both kinds of AI help us evolve. One is. Augmentation ai, and that’s the AI that gives human user in this case a seller in our example, a better, more targeted perspective.
And, uh, gives them information that augments what they’re doing in their daily experiences. And so that’s a very useful kind of ai because I’ll give you one example. Let’s say as a seller, you’re interacting with a very high touch account. It’s a 10, a million dollar a year account for you. So requires a lot of human conversations, a lot of relationship building.
So, it’s a very high touch account. So. Augmentation AI can help you be more prepared for those conversations that you will still have as a human. So still complete most of the tasks in account management as a human, but this type of augmentation AI will give you better perspective frankly, help you be more ready for these interaction.
The other kind of AI is an energetic ai, and we hear that a lot, and I think a lot of people don’t really think about the difference, but we have to mention in here because this is the kind of AI that will complete the actual task for you or complete series of tasks for you. And that’s the.
AI that we already see making a lot of impact in what I call level one of very much every job. So, imagine a level one support engineer or a level one customer success manager. Level one is sort of that first dial tone initial interaction that you have. So, if I have a question, if I reach out to a support system or a support line of a company from whom I bought a goods and services this level one.
Agent in this case, a gene AI, can fully answer my initial question or fully complete the first task and then escalate it to a level two. So, it’s, so there are these two kinds of evolutions that are happening right now with ai. One is augmentation and that’s helping humans in the high touch interactions that they have.
And the second is very much. Generative, and that’s the one that can pretty much complete tasks for humans in their current roles.
Brian Thomas: Thank you. I appreciate you sharing some roles that where AI can obviously assist in there, but I liked what you highlighted early on. When you said, they say AI can’t preserve context judgment or empathy, and really as you got down into it, gene AI can really assist the human in these areas which I think is important, that human machine combination or partnership.
But the one I really liked was your perspective on ai, not really taking human jobs, but how your job could be at risk potentially to those. Humans that are fully leveraging AI in their role. And I think that was really interesting. So, thank you. And Maksim, the last question of the day. Looking ahead, how do you see the intersection of CRM AI and seller productivity evolving in the next five to 10 years?
What product shifts do you believe will become table stakes? And how should organizations begin preparing today if they want to stay ahead?
Ovsyannikov-Maksim: Yeah, I love this question because I’ll just go ahead and proclaim that all of enterprise software not just CRM, but any other function, marketing service sales, HR, majority of enterprise software will be centered around AI and what AI can do, and that’s a very incredibly fundamental shift because.
It’s not really of intersection of CRM and AI and seller and these kind of workflows but it’s, it’s AI instead of what we used to think of the CRMI think, and I think that the right, approach for vendors, especially like sugar, is to really have this incredible shift in saying that your.
Your market is no longer looking for a workflow. Your market is really looking for outcomes. Outcomes in this case, right? I want to sell. I want to win, deals. I want to grow as a business. And if you’re looking for outcomes, then you’re no longer looking for what used to be the CRM. If you’re looking for outcomes, you’re really looking for workflows that are entirely powered by AI in this.
Augmentation way, as I mentioned just a few minutes ago, went away, because that’s the only value that we can build that can really deliver outcomes. So that’s this huge fundamental shift that’s going on within roadmaps of most of the vendors that you can see across the board in the mindsets of the CIOs and CROs that are buying these types of tools.
And most fundamentally. In the minds of the user as well, an actual user into whose hands these tools are finally landing in, imagine Enterprise software 10 years ago. And I think up until recently it had really bad rap. The rep was that some CIO bought it and then it was put in my hands and I don’t know how to get data out of it.
I don’t know how to build a report. I don’t understand my dashboard. It was built for me by someone else. I’m not sure how to complete an interaction. In other words, let me just create my own document or manage my workflow in my email. Which is a huge reason for why email is not dead as many analysts predicted many years ago when social was being born, right. So lemme just go ahead and manage it in my email. Lemme manage my customer via email as an example. Again, instead of managing it via CRM that was bought from me by someone else, using workflows that I don’t understand in using reports and dashboards that I can’t get any value outta. Instead, right now, if you put more of a conversational agentic.
AI experience in my hands. Then I, as a human, instead of building a report, can ask a question. And having AI answer the question in a very human-like way that’s very productive and helpful and doesn’t require me to learn the software, it immediately guides me towards the outcomes that that software was originally built for.
So, I see that that is a huge shift. I see that that’s the future, and I think that as a vendor, as a software vendor, especially if you’re not building for that future now. I don’t know what you’re building and I don’t know what the use of what you’re building. Will be in the hands of your customers as soon as right away.
Brian Thomas: Thank you. I appreciate that. And you mentioned early on, nearly all enterprise software will be centered around AI and what AI can do, and I thought, I think that’s important. But we really, as you said, at the end of the day, you need outcomes in your software, especially your CRM. And in this case, you’ll need to leverage and embrace AI for all the tasks and workflows in there.
And with AI providing answers in easy layman terms so that the user feels empowered and is easy to tackle things that they may have not had, uh, much experience with. So, I really appreciate that and Maksim, it was such a pleasure having you on today and I look forward to speaking with you real soon.
Maksim Ovsyannikov: Yeah, thank you, Brian. Nice being with you.
Brian Thomas: Bye for now.
Maksim Ovsyannikov Podcast Transcript. Listen to the audio on the guest’s Podcast Page.
