#109 Making RevOps an AI Orchestration Layer – with Alexander Müller, Founder at Revenue Enablement

[MUSIC] Welcome to the RevPslap, a podcast exploring the art and science of revenue operations. To find more episodes and resources on scaling your revenue engine visit get weflow.com/revPslap. [MUSIC] We know, we know, there are plenty of AI note takers out there. But there's only one purposely build for Salesforce. And that is Weflow. Weflow doesn't just record, transcribe and summarize your meetings. It also suggests Salesforce field updates, phonetic, spies, next steps, or any other custom framework that you want to implement. This works across any of your standard or custom objects and across all field types, like multi-pick lists, text, number, and currency fields. Weflow also writes AI-based follow-up emails, saving your reps even more time. And the AI coach analyzes recordings to help your reps run better sales meetings. And the best part? Weflow's real-time two-way Salesforce integration works out of the box. No manual field, my pain, no complex setup. You'll be up and running in 30 minutes and you benefit from our create support. It helps you customize the prompts based on your business requirements. If you want to see what hundreds of your bread-rops peers use Weflow to get better sales for Stata and Rep Productivity, just go to GetMeFlow.com to get your free trial today. [MUSIC] Hello and welcome to another episode of the Rappup's Lab podcast. I'm actually alone today, but I'm super excited to welcome Alex Mulla back to the podcast. Alex was actually our first guest ever. We've recorded over a hundred episodes by now and yeah, so super good to have you back. Thank you. It's so great to be here, Janice. And I have to say, I felt a little bit old when I looked at our podcast that was already two and a half years ago. And it's crazy how many things changed in the meantime. Oh my god, I actually didn't know that it's two and a half years ago. Yeah, I do feel very old personally, but that's a different story. I mean, so actually Alex and I, we are almost neighbors, so we see each other quite regularly. And we regularly talk about how it's AI changing Rappups. And so today, what we want to do is we want to jam on AI use cases and then basically draw back to how is that changing the team composition of Rappups. So, you know, topic where I think both Alex and I would say we have a lot of opinions, but it's all a bit unclear. And in the works, right, so it's work and progress of what the best practices will look like. So I'm super excited about this episode, but maybe for the guests who don't know you as well as I do, you know, like for the audience, like, you know, who are you? What do you do? What have you done in the past? Sure. So I run a small Berlin-based consultancy for revenue operations. We are really like a particular consultancy. We help companies to set up their revenue operations. We take over any kind of projects that they will come to by themselves because they need extra workbench or because they don't have the right people in place. It could be that for instance, they have a very, well, tool-minded team and they need somebody who is a little bit more people driven, so then we come in or also the other way around. They need like a specialist for new tools and we help them to set this up. And the company is called revenue enablement. I said very small helping B2B companies about myself briefly. I have been in the B2B space for the last 15 years, originally started in banking, then came to Berlin to the startup scene and built up a lock-tech company in Berlin for it. So I was one of the first 20 employees there, stayed with the company until we were, I think, valued at 2.3 billion. Took the COVID, hockey stick for us as a e-commerce close company. And then I joined Cochney G as their vice president of revenue operations where I owned the global SER team, the global revenue operations team and the data team. Cochney G was sold to a US company called Nice and the customer service sector for 1 billion, the largest AI exit in Europe to date. And yeah, now for the last 30 years I've been working on my own consultancy here and very excited to see many, many different companies how they scale, what they do with AI, how their tools are changing and the processes are changing. So for everyone who is not in Germany because I think most people in Germany know you by now, but like for everybody who's not in Germany, you know, go to LinkedIn, follow Alex, he also creates some good content and is overall just a super awesome human being to hang out with. But enough of the praise, let's dive into something even more interesting, our topic for today, AI use cases. So I mean, maybe let's kick off with the first use case, like, what's hot right now? Where's AI really changing go to markets? Yeah, I think right now over the last couple of, well, 12 months, the refops role changed so dramatically when we speak about AI use cases, we spoke I would say in mid 2020 or 25, a lot about clay. Clay was kind of the name of the game, right? Everyone wanted to enrich data, find new contacts, automate email and SER. And I think right now this is changing a little bit. We see more people working directly with the providers such as Anthropic or OpenAI. And I would say when I was at an event just recently, the most discussed tool was actually Claude and Claude code, of course. And yeah, so I think the use cases here are pretty broad, I would say, for refops, it's still a lot about data enrichment as number one, I would say. And typical refops responsibilities, that you say. But it's changing. And I think that's a very interesting part, you know, it comes along that the orchestration of agents now is also one responsibility that we see with many refops teams. And that I think is really a big, big change going forward. Yeah, yeah, 100%. I mean, I think every company in the world has a AI transformation mended. And suddenly, you know, there are AI workflow and agent builders out there. And which tools should be better position or are better position than refops to take those and actually make them work. I mean, maybe going a bit deeper into this, maybe we can stay top of funnel, but we can also go into other directions, right? Like, you know, like what are, you know, workflows and agents, you know, you've seen, you know, being super interesting. Yeah, I mean, I think it's good if we start like from the front of the funnel, right? Because that's the most obvious use case. And then we go a little bit deeper. I mean, I already mentioned the work of the SDR changing, right? Responsibilities for revenue being transferred to refops. So actually the name, revenues also like really has a different meaning now for us, a different responsibility. And we can also discuss that in a minute, it's a little bit closer with one chop at that I saw quite recently, from X AI. And there, I mean, let's face it, I think customer questions, customer interactions, that you're collecting information from your customers is something that we will see more and more agents do that they respond automatically that they give discounts where it makes sense that you especially give the long tail, the smaller customers that you probably can't serve for the human being because it's to, or it's not cost efficient enough, that you hand over those to agents. And I mean, that's something that I have seen quite a number of use cases, not necessarily really AI SDRs calling yet, right? But more AI SDRs responding to emails, writing better linked in outreach and so on. However, being said, that requires still a lot of training in human and the loop, right? But I think we can also get to that. Then on the next step, we have also seen more customers going through their database and collecting information from existing customers or from closed lost opportunities so that they could reuse them. better in the future in that I think that's for me still one of the underlying requirements for any other use case that you enrich your data that you have the right data at hand. Then when we see to or look at the education part, I think there we also see quite a dramatic shift from how content is produced of course, but also how content is consumed, right? Buying decisions are more taken with LMS, with chatbots that you brainstorm that you gather requirements together with them. And then I think at the closing that's still a lot, well I would say especially for enterprise human related where human beings are still building up relationships, but also that of course is changing. And then going beyond the close part when we look at expansion, a charm that we make better use of the signals that we already have that we for instance gather different signals from customers. So let's say they are not logging in anymore or as much anymore. In the past there was like one thing no user locked in for the last week, right? And then you would know like would go okay what what you do with that information. And now with agents you can basically summarize the information from different tools you can combine it and you can actually push it through Slack through whatever channel where your existing teams are back to the users. And I think those are just a few use cases that I've seen recently and are not too crazy also to get started with. Yeah, yeah, I mean obviously as you know we're basically building in the space so we see a lot of stuff. And I think what I find so interesting is that the kind of using agents to orchestrate actions is something that is essentially giving refops the power of resource allocation. Right. And I think if you think about the best companies in the world, they are like really good at resource allocation. And thinking about where should you spend your time. And I think top of funnel is a great example, right? Like you, I mean back in the days we started with people manually creating lists. Then you know enriching them. And then essentially doing the alteration. That's basically the you know first wave of the SCR role being specialized. Right. Then you come into okay there is a workflow automation tool like you say it's engagement tool that helps you automate certain steps. But still you have to write the message right. You still have to think about you know who you go to. And now it's basically you take all your first party, third party, second party, you know signals, you layer them into you know an orchestration layer, you then you know go a lot more detail into micro campaigns and you automate you know that basically the things that can be automated. So I think they're very interesting trend. I'm seeing there right now. It's like you automate you know a lot of the messaging right the emails linked in. But then still calling is done man like manually right. Most often like parallel dials right so you have higher connect rates so obviously that's not AI but what I think is essentially really interesting there is like it basically like you do what is the highest value work for an SDR and you have to do that really really well and everything else gets automated. And I think that is a common theme we're seeing right like it's not that the A is going anywhere. But all these you know 52-70% of non-selling activities those can now be automated and I think that's just so so so powerful. I'm curious what you think about that. Yeah I think to the time that you actually spend with value generating activities is increasing. However I also have to say that I think we are still in the process of finding the right limits there right. So it doesn't make sense that you're cross checking every email five times and run it through three different agents because one formalizes your tone the other one improves it for your reader to sound less salesy and then I don't know you let it run through another one just before you send it out right and suddenly you need for an email that would have taken you five minutes 15 minutes because you let it cross check several times still need to read it. And the other extreme of course is that emails messages go out unchecked right and what I'm saying with that is that we can also keep ourselves quite busy with these kind of things and I think we still need to choose and where do we approach customers if we look at the outbound side and how do we approach them because the interaction between the human beings will be even more important right because I mean you and I we can probably already tell which LinkedIn message is a I generated by now right that you're receiving every day and you're like okay I'm not even reading that anymore right. And I think there we really need to keep the human and the loop and that's also why I'm thinking the teams will not completely go away the roles of sales the roles of CSM's the roles of SCR's they will not go away but they will be better they will also be a little bit more fun for us I think because we can actually do the tasks that we like on doing but we can also get like immediate responses to our customers we can finally start working with all these signals that we see and what do they really mean who should we actually talk to and yeah. Yeah yeah I mean I maybe just a few more like you know additions to this right like obviously this is always in like context of size and segment right so what I'm hearing for example is like inbound SMB right like that's actually quite automatable but like you know outbound enterprise that's still heavy human in the loop and actually you know like calling below the line finding information that you then present above the line and those are all things that have been done like they were true 10 years ago they're still true and I just just hired a SCR yesterday and you know throughout that process what I just you know it to me it was like really big I mean not a revelation but like it's like basically every SCR I talk to said look I mean you know yes we have a lot more tools but in the end what works best for me is calling right and I think that's just that's just really I mean it's not so surprising it's actually it's just basically tells us that all these other channels are highly crowded and very difficult right now because you can automate them and everybody's doing it so to certain extent right then the question for refops is like if you if you want to enable the SCR teams right like okay what can you basically present as a unique research data point when people sit in their dials so that in my head have a higher success rate the other piece I would say is like this the old like you know openers and what do you say in the first 10 seconds it's still true right and I think there's always been a disconnect from you know refops not necessarily managing that right this is typically the SDR managers coming up with the call scripts with the email scripts back in the days so I think you know there's kind of you know the like when we I don't want to like like like dig to deep but like when we think of the go-to market engineering role itself right like yes one super skill is to automate all these things and make it more efficient in blah blah but there's still the other element of the messaging and positioning and so I think in the end if you want to have real impact real outcomes and change the outcomes you have to be good at that as well and I think that's to me still a big question mark is that is that part of the you know role description for you know I always call it go-to-market engineers modern marketing operations people I don't know I maybe it's the wrong way right and people will hate me for that but like you know but like clearly to me it's like part of the refops team it's just a new role and then where does this role start and where does it stop for hey Philip here are you enjoying this episode? well good news because you can find more free red ops and go-to-market resources on get reflow.com/redops access over 20 cheat sheets reports and guides that will help you become a better revenue operator or join over 2000 subscribers who already get the latest resources right into the inboxes with our free newsletter just go to get beflow.com/weather I think this is becoming a little bit blurry over the last ones especially, right? Because I mean, go to market engineers, they've worked quite hyped over the last year. When I always explain or look at how sales ups, ref ups, evolved, we started with in the 70s somewhere in the US, the first sales ups teams being founded, right? And kind of goes on like that in the mid 2000s, 2010s. This term revenue operations comes up and then early 2020, 324 probably go to market engineers kind of the new thing. And I think also I do agree with you that time selling with actually human beings will become more important. I think it's not about the blurbs anymore that we have seen in the past like, hey, you should say this and this about the customer, right? Because if it's really mid market, you're probably that specialized, the most problems within the vertical, within the industry, they meet all of the customers that you're speaking to and you don't have to go back and get like a summary of the LinkedIn history of the person that you're speaking, you can still do that quite quickly through scrolling. But I think we can make that whole process of actually doing the research much quicker. So for instance, I have a discovery bot that I always use that tells me everything about the company. Same stuff that I did in the past myself, took me probably 20 minutes to, if I wanted to do it in a detailed way, now it doesn't really take me five minutes. I get very good responses. And then I can think a little bit deeper there about the person or about the company and so on and so forth. And to come back to your question, how does the role change? What I find really, really interesting is that suddenly we see responsibility for orchestrating agents as part of the chop description of revenue operations. I've seen that I've read that now, as I said with XAI, I've seen it with other companies as well. And I think that will be a very interesting trend because what does it mean? It means that the role of RevOps will change, will become not only more important in terms of who actually is responsible for the different AI tools that we bring in, but it also could mean how do we make them a channel, right? And probably revenue operations will be rather responsible for setting these agents up. And then we will see who is responsible for owning them. Maybe there will be a new role around that. Maybe that's going to be a go-to-market engineer or whatever. But the way that I see it is that there is just simply no other role in the whole go-to-market team that's better suited to own this than the RevOps team. Yeah, yeah. I fully subscribe to this. I mean, we've also a revenue AI and orchestration platform, right? We don't focus on top of funnel, but for essentially automating data capture across emails, meetings, conversations, field meetings, right? And then map that to your custom data structure. And I think what we are seeing is that the unification of data across different systems is basically the infrastructure. And that's actually often very broken. And then you layer your R-Scree-Floy AI or your AI workflow and agent build on top of that to then basically orchestrate actions and automate repetitive workflows, right? And this is exactly your example is like, okay, you go into meeting, you have a pre-meeting brief, right? After the meeting, the Acerium is updated. You get the follow-up email, you get the summary, you get the AI to coach you on your medic or med-peer compliance, right? And I think that is already happening. And in my mind, it's like, Rathops suddenly has a superpower to drive from, let's say, 60% non-selling activities to 80% of the Rath's time spent on selling activities. And instead of five to eight meetings a week, you do 15 to 20 or even 25, right? And I think that suddenly changes, if you think that through, right? You have 500 reps. That absolutely changes the game for the companies. And that is, I think, to me, that's basically what Rathops' future looked like and what should, like, everybody of us should embrace because that is, that in my mind hasn't been pos, I mean, to a certain extent, right, that's always been the goal. It's just now the tooling has become a lot better to do it. It's not all about the tooling, right? I think there's obviously other challenges. But I think we try to, for example, make sales for the system of truth for 15 years. That's always been true. But now it's generally a lot easier and a lot more automated. And I think this was the hard way, we learned this the hard way because we started with something that was like notion like initially, right, like your workspace on top of sales for us, was still fairly manual. And what we realized is like, you just have to automate as much as possible because otherwise it just doesn't happen. And I think that that was just such an interesting learning for us. And, you know, what I just thought about is also how we use those tools, changes, right? I think it's probably a little bit far stretched that we go to like 70% of our time with sales activities, right? There would be such a huge bump. Such I think even if you would get it like 5% up, 10% up, that's already like a great achievement. And I mean, I'm also like thinking more about the typical refops works that we've done in the past, when we had contacts where we didn't know if the number was still right or it was flagged by OSDRs that something is not right anymore, a person of working in the company, any more person having a different phone number or whatsoever. That was a process than the past. We did literally max every quarter or every half year. And now you can do that instantly, right? You flag it and sales force or near CRM. Your appart fetches that information runs through it instantly, checks your first data source, checks your second data source. Looks if there is maybe a change in the position like different employer or different phone number and then sends that back and ideally sends it back to the system that you're already working with, right? So be it teams or select that you use for in-house communication, you get a notification right there. Hey, by the way, this lead was updated in our CRM. Go back to the CRM and try to call them again, right? And just think of the many good use cases of it, not only that you increase the reachability but also that you find out where did your previous users actually go and what other companies that they that you should place higher in your target list because of that. And I think these are the things that every company can get started. I think what's a little bit harder is than really big automations because what we usually do when we come into companies that we look at the data first and in most cases we say as them to do a little bit of homework first together with us often to improve the database. I mean, I think this is so true, right? It's actually, I mean, if you could just hook, you know, claw it into Salesforce and it gives you the truth, right? I mean, in theory, if it's a system of truth, it should be able to do it. But the reality is just doesn't work, right? And so I think you have to be really good at the data foundation, your custom data structure, right? Like the quality of the data and then also the consolidation unification. That is basically the infrastructure. And I mean, similar to you, right? Like I talked a lot of teams about this because we also solve this and it is almost always always a problem. And something that I think you need to get started on to be really successful in this transformation. And I look, I understand it's actually way easier said than done, right? Like I get that, especially if you have 10, 15 years of technical depth in your system architecture. It's not just something you flip the finger and it's done, right? But yeah, fully agree. But you know, what comes to my mind when I hear that, the Forward deploy its engineer that's a palantir in the likes have laid out, I think also Forward deployed refops, and that's like thinking a little bit of course of the WeFlow use case, right? I don't want to make this advertisement show, but I think that's becoming like super critical that companies, before they use a new system, actually get their data right, and if they don't have the capacity themselves, that they use, for instance, such a Forward deploy refops team to fix it, so that you can actually get started with the implementation of new tools. And I think that's kind of a trend that I'm expecting that new tools or new applications, they will probably partner with the providers of what you want to call it, refops service or whatsoever, to bring such a Forward deployed revenue operations manager in and help you set up a specific process. And yeah, so a lot of the groundwork I see also being done there, and that's kind of why I'm thinking overall, of the refops role itself, it'll just be super interesting for the next 10 years, probably still. Let's see. Yeah, always changing. So maybe find a question from my side, a question, a topic. So when you joined us at our first episode, you basically laid out how you built the photo team, growing that to 2.5 billion in valuation. And so I'm curious, if you would create a team today, how would you think about the skill set and the type of roles you would include in that team? And again, I think this is absolutely not set globally. That's very different in a lot of influencing factors, but you're curious how you think about it. Yeah, so I would still say that how I approach it in general wouldn't or didn't change a lot. I still have the three steps for those people who didn't listen to you for that episode. I think I said something like get operations right, put your analytics on top and then get your enablement done. And that's still how I see it because operations is kind of you built the system, you built the formula one car, now you have a very fast car, hopefully, then you need the analytics people to tell you, hey, in this corner, you're losing a little bit of speed and then the enablement people there eventually telling yourself to go to market teams, whoever's customer facing, hey, hit the gas here a little bit earlier so that we save a few seconds on the overall lap time. And I think that hasn't changed. Again, coming back to what we just said because the process, the data is just as important. So we still need to do get our operations right. But I think it changes a little bit with the gods to who I would hire first. And also when I look at the different teams that I work with, who they are actually hiring and how many people they are hiring. So I see smaller companies that were established quite recently, having usually a bigger tool stack, having more different applications and they therefore also need more people to orchestrate those. So I always tell the little anecdote, I was sitting at a dinner that we hosted with the CRO of a company that has approximately I think 500 employees and another ref upsmand that you was working in a company with 50 employees. Even though they were 10x difference in size, the ref ups teams were almost the same size. And now you could call that inefficient on the one hand, but it comes back to what kind of tasks are they doing and how much quota do eventually the go-to-market teams carry. And I think here the changes really happening that smaller companies are hiring operations people earlier because you don't want or it's more than just a side job to set up the CRM to set up the other agents. And then you're having usually more tools that you can easily plug in at an early stage where larger companies have just more to consider. And also whom we are hiring changes in the past, I always said, hey there's two types of ref ups in general, more than the tool guys and more the general lists. And in the beginning I said, hey, I would first get rather general lists. Now I would actually say try to pair them, get two people quite early on, get a general list, get somebody who's tool savvy who likes to play around, and then actually I think together they can be a real dream team, because you don't want to have a new tool every week. You actually want to deploy it well so that everyone can actually use it and you by the end improve your revenues with it. Yeah, awesome. Now I mean I think that a lot of people I talk to, they're like, there's efficient growth, ref ups teams are fairly small compared to the company size. Now AI comes on top, it's really stressful. So for everybody who has stressed out, you're not alone out there. That's the reality a lot of people are facing. But I think I hope this episode today also brought a bit of a ideal state vision where this is going and how ref ups can essentially have even bigger business impact, which I think is what helps you be more strategic and helps really to, then also climb the career ladder and just put some more emphasis on the importance of the role, which I think we very much fight for and root for. Alex, I mean before you go any book recommendation, research recommendation, anything, you know, can be ref ups related, can be also to be a better human being. Okay. Great, great question. And in general, I think. Sorry. I was just, what am I reading? I'm actually reading right now a 10 year old book from Akiyinsa, who used to be a doctor for athletes and that's totally not ref ups related. So I was just thinking should I tell you about it? I think still it's a great book because it has a lot of the name of the book. And it's called Overperformance. And I need to look that up if that is actually right. Let me just, sorry. You know, I can tell you what it looks like. I know it's the core. It's called the core. There you go. The core. Performance, better life. There you go. I mean, I'm asking for life advice, right? So typically we ask our guests before the show like, you know, for book recommendation, actually forgot that. It's not magical to you. This one. No, all good. I read, I would say, I read. I have to admit, right? I read a lot of books because it's just I like reading. I just finished a few book on politics. But I don't read that much on revenue operations on sales. Why? Because I have to admit, I think most of it is actually happening in discussion. It's happening for me on LinkedIn. At events that I go to and because everything is changing so rapidly, I think you can actually do a better job with deep research. That's what I always recommend. People who are starting a new job, a new assignment, go to Cheminai, go to Chattabit. Do a deep research on the thing that you're starting with. And then you can bounce your thoughts back and forth. To be honest, I think that's for me better than getting yet another book. And I have a big bookshelf here next to me. I think that's great. I mean, for sure. Alex, thank you so much for joining. It was awesome. As always, good speaking to you. Wish you a great day. Thank you so much. I speak to you soon. Bye. Thank you for listening to the Revops Lab podcast. If you enjoyed this episode and would like to support us, share it with a Revops friend or try us five star rating right now. And if you have feedback, questions or guest ideas, just send a message to Janice or me on LinkedIn. Thank you and see you next time.