Andreas Welsch: 0:21

Today we'll talk about scaling go to market for enterprise Generative AI. And who better to talk about it than someone who's actively working on that? Nicole Wieberneit. Hey, Nicole. Thank you so much for joining.

Nicole Wieberneit: 0:32

Hey, great. Hi, Andreas. Thanks for having me. I'm Nicole, what I'm doing? I'm building businesses. So my love really sits in the go to market space. I have done that for several years at Microsoft, really in the area of incubation products. And then how can we sell better together and lead with AI and bring that to our customers? And nowadays I'm with a Microsoft partner, Digital Agencies, and actually look into partner ecosystem-led growth and how I can grow our business together with Microsoft and really being at the edge of data, AI and add modernization. Great being here.

Andreas Welsch: 1:16

Wonderful. I'm really excited for our conversation, especially because it's a little different than the topics that I usually cover that are more centered around stakeholder management, governance. So now taking it from the point of view of a software provider, what do you need to do to get your go to market right to help your sales teams really have that conversation with your customer and be educated and be informed. So I'm really super excited for our episode today. So folks, don't forget to get your copy of the AI Leadership Handbook on aileadershiphandbook.com, if you don't already have one of those. And subscribe to my newsletter, The AI MEMO, under intelligence-briefing.com/newsletter, so you can stay updated how you can successfully run AI projects in your business. Now, with that out of the way, Nicole, what do you say, should we play a little game to kick things off?

Nicole Wieberneit: 2:07

Yeah. Should start. Go ahead.

Andreas Welsch: 2:10

This game is called In Your Own Words, and when I hit the buzzer, the wheels will start spinning. When they stop, you'll see a sentence, and I'd love for you to answer with the first thing that comes to mind and why, in your own words. To make it a little more interesting even, you'll only have 60 seconds for your answer. Nicole, are you ready for What's the BUZZ?

Nicole Wieberneit: 2:30

Yes.

Andreas Welsch: 2:31

Perfect. Then let's go. If AI were a fruit, what would it be? 60 seconds on the clock. Go.

Nicole Wieberneit: 2:41

A mixture between a strawberry, a raspberry, and probably a kiwi. Reason why? I really like sour, everything sour, and I think these are the fruits which provide that.

Andreas Welsch: 2:57

Let's hope the industry doesn't go sour on AI because a lot of analysts are already talking about the disillusionment. But even sour can have its charm, like you said. Awesome answer. I've heard different things before including durian, the king of fruits, but it's the distinct taste, but a mix, that's awesome. Now, I think when it comes to AI, we see a lot of marketing, we see a lot of sales. Teams going out there talking about AI is this next big thing. And I think a lot of times also, especially marketing in tech gets a bad reputation for over hyping those capabilities or on the sales side for being overly shallow, right? You give them a couple of snippets, they run with it, they talk to the customer, and then once it gets a little more technical, we need to bring in additional people who can have the conversation on a more technical level. So what are you seeing? What are the challenges there? Why are marketing and sales getting a bad reputation. I

Nicole Wieberneit: 3:56

think in general, it is actually it's marketing's task to lead the way and, like brand building, build, if you're going into a new kind of functional category, you need to build that category. So you need to lead a little bit that, and that is what you have seen and, companies doing now with Microsoft, AWS or Salesforce that are trying to go that way, leading with what does a copilot mean? What does an agent mean? And going and that. And good sellers will jump on these kind of things, especially if it comes close on what they hear and I emotionally connected to. I can give you an example. I come from 16 years background of implementing CRM systems. And when I heard the topic of a customer data platform, I could so resonate with it because 16 years I heard I want to have customers 360 or even 720. If you think in a consumer world of finance and household data. I could absolutely see it and then you jump on it and then you want to sell that. So that is the leading with it. On the other side, to be very honest, if I would go into a customer today and say, let's talk about a boring Data Foundation project, they actually don't want to talk to me about that. They want to hear about the AI piece. I think what happened is that especially in AI over the last two years, I think we are in a hype that goes down and it's because we haven't really understood what does it mean to sell AI and what other topics do you need to bring along to get the customer to use it in the right way and get that business value that they want. So topics that come into the security parts. So it's great. I can ask all the questions, but I had one project I heard was stopped when I was at Microsoft because somebody asked, can you give me the salaries of our board? And it previously was sucked somewhere in a SharePoint site, nobody would have even found it. Generative AI can now, because it was connected, found the answer. But that, the project was stopped. So how can you get risk security in a project into line and that is where customers are worried about and saying, okay, that's not where I want to go. So that's what companies underestimated. And then what they overestimated was the willingness to go all in. So that, hey, I can sell Copilot licenses across all the seat base. That is not happening either. So it's they want to test going into with one or two use cases and then see how it's going. And then because of these risks and security parts, we don't want to expose it, for example, to customers, only internal first. You're getting into that pilot paralysis that I can see in which we also have seen like an IoT and mixed reality or virtual reality is that it takes a while to get that out to really then start seeing deployments across the whole world

Andreas Welsch: 7:12

That's really interesting because I remember seeing that when we're talking about machine learning five, six years ago and customers would say, sounds great what you're telling me, but can I see this with my own data? And then to your point you end up in a longer proof of concept or pilot cycle where things might pan out, might not, it might be difficult to get the data. It might be difficult to get stakeholders around the table and to agree. My hope and expectation was actually going into this whole Generative AI wave that things are going to be a lot easier because we no longer need a lot of that data, at least for the quick win early type use cases. So that's interesting seeing that that's still a concern. And I think, that comes back to how do enterprises work, how do enterprise leaders work and think and behave and what do they need to get right.

Nicole Wieberneit: 8:01

Yeah, and I think that is really where, if you think about a go to market piece, at the beginning when you saw it, what was really great in Generative AI, it got the buzz going and everybody saw Generative AI as AI. So you then got predictive analytics got really great. We should do this and that. That's actually predictive analytics. We have done it since years, but nobody talked about it. So you've got Generative AI, got the whole kind of focus on AI, and that's really great. However, companies are Looking far more on their budget, they're looking far more what they can be using. So what is the use cases? What is the business value? You can actually run very early on and which you can bring to the table for these kind of customers. And actually, the question is, who is your customer? Who is the ideal customer you want to go after? And with everything, when you are in innovation and you're trying to build a new category and you want to go into there, you need to find, first of all, companies who love to be innovative and up the forefront and not going after the legons. Trying to sell something if somebody already doesn't have that data foundation is actually the wrong thing so you should get see in your segmentation okay already have data foundation already are connected like iot sensors have the data space so that you can build on it so you can create a critical kind of mass, what I call a positive energy. The second question is who's your buyer? And what we've seen, I think oftentimes different departments had their own budget. Companies started to bring a forward Generative AI, OAI, the budget together, often CIO, CTO was then the holder of that budget because of the security risk. And then topics like an AI center of excellence around governance and how we be building that up. Got a big topic, which probably delayed a little bit. That really these kind of go to market, you can start seeing scale happening across a bigger customer base. So how do you talk now to the BDM? And when we discussed that before, it's you have to have different people. So now saying the CIO has to budget, but you still need a business use case and talk to the BDM because that is what you need to bring. So how do you then go to the next step? What is the use case you want to go after? My learning since is, it's actually old, boring use cases. Things I've implemented 16 years ago, document automation. Yeah, so finance department, you'd think invoices coming in instead of just having invoicing, basically scanning them and then automate them, save them somewhere. You now use AI on top of it, which reads Generative AI through, gets better indexing them so you can find it back and then you automate the rest of it. So for that kind of use case, you then need to bring your finance department with you and the CFO and need to align that. So that makes selling more complex in that sense that you need to talk to different kind of stakeholders. I would say that's probably true with every larger transformation project that is happening. So companies, vendors are used to that playing in the enterprise space, but it go, it's a little bit different than when you had these kind of very simple coming into it. You could describe it like Dropbox or Conva is a great example, which just came in to people starting using it and then you start growing it. That's not possible because of that budget merging and Generative AI, that center of excellence and these processes around.

Andreas Welsch: 11:59

I think you bring up another great point especially around the boring use cases, things that we've done, many years ago, or that we've done for many years, and I remember working on things like invoice matching and document processing six, seven years ago, when machine learning and RPA started coming on the map. To me, just the fact that we're still talking about this, but it's a different, a new and improved way of doing this. I think also shows again how transformation actually happens in companies. And I think a lot of times it's relatively slow. It's relatively timid. Let's try this out. If it really works, then we can do another thing. And then we can do another thing. But I also see, in, in the audience are a few members that regularly if you have a question for Nicole, please feel free to put it in the chat as well, and we'll pick those up in a couple of minutes. But, with this part about having to educate your customers to some extent, having to work with them more closely and figuring out those hurdles, those barriers, what do you think You know, even in designing a go to market, what needs to be done differently when it comes to AI compared to your traditional software as a service?

Nicole Wieberneit: 13:07

I think what You cannot do, you really go to market planning and then you put together your, marketing decks, your sales your territories your orchestration along the line, and you talked about it, how many different people you need to bring into these things, you cannot do it once a year anymore. The innovation that is happening is super fast, so you need to stay on what is resonating at the moment. And that is true, if you're a small startup or you're an enterprise customer, you need to get the signals. And meaning, how do you get these signals? You can use product usage and functional usage that is used so that you resonating. It's not talking to your customers, what are their use cases? It's still a big problem in the end. What is it about? Solving a problem for a customer and how can you use AI with that? Let's be clear. Selling AI, selling functionality is not the way to do it. So solving a problem. So what is the problem? And is that moving even? Think about when COVID hit. From one day to the other, the problem changed. So that's an extreme example, but keeping track on what is happening, being basically testing, experimenting on what resonates, what not, and being able to quickly change. Now this is for big companies actually quite difficult to do because the machinery to even build pitch decks, to build marketing messages, takes a long time. And. But I believe that is the way we need to go, being actually more customer focused, customer experience focused, what do they want versus selling a product. And that companies who will do that well, you will see that they will grow exponentially better than other companies. So that's for me the main difference on how do I need to sync and how do I use data feedback to feedback into my go to market, understanding the KPIs and the leading KPIs on how do I need to change it. And let's go GoToMarket is actually very big. It's marketing, sales, product, it's even customer success. So it's aligning and working very closely with these different departments. So as sales, I always say, took responsibility. We need to have the ear and the crown to the customer and to our sales teams, listening what needs to be changed, basically at the initiate of the feedback loop, and then put, bring it back to the responsible other teams. So let it be, hey, that product feature doesn't make sense. We need to change it, or we need to close X, Y, Z on security type. thing is not secure enough. So you need to do something. That's what's happening then, which comes into the news, but it could be smaller stuff as well. Hey, marketing, we need to change our problem that we described for our idle customer profile. And we need to change our pitch decks. We need to orchestrate differently.

Andreas Welsch: 16:28

Let me jump in there real quick, because I think it also takes the right kind of culture and the right kind of process and support system around it, if you will, to make that happen. I think it's relatively easy to get feedback from your customer. They will at a minimum tell you if something isn't working or isn't working the way they expect it. But finding the internal stakeholder, finding somebody who listens with open ears, and that just says, yeah, fine, we'll archive it but actually acts on it. I think that is a whole nother level, again, probably easier to do in smaller companies or in companies where that, that culture already exists and is fairly strong that we need to talk to our customers to get that feedback so we can improve and improve for them.

Nicole Wieberneit: 17:16

I actually would say that it's such an important point that larger companies or vendors, even the market leaders can learn so much from startups. That's why you're actually often the incumbents then gets disrupted because they had the listening, they had, they got the signals, they just didn't react on it. When I was, for example, at Microsoft, we did an experiment where we wanted to get more into that agile founders led mentality to interrupt but also to be agile and test and experiment on where we need to go to your go to market. And I can tell you it's not only, even if you tell you here is a department and you should be, it's your job to do that, people's mind was still stuck in that way. Because for example, your measuring of sellers needs to be very different because you cannot say, Hey, you, that's your quota. You need to sell that product with 70 percent on that kind of product. And that's the amount of money you need to hit because it could take that product is not and we need to adjust and they're not used to working in that kind of more agile way

Andreas Welsch: 18:28

Now again I think the agility changing the way people work and how they think is certainly a key piece and you already mentioned you've led go to market enablement globally at Microsoft our largest software company in the world. How you strike that balance between providing enough knowledge and depth that everybody can interact confidently with their customers and not only get them excited, but also show them real examples and real value? How do you strike the balance between again, knowledge and depth when there are these quarterly incentives? And quarterly quotas that people need to hit.

Nicole Wieberneit: 19:05

I think when you're going in and incubate new products on your functionality of part products, yeah, you can not just do it with, Hey, let's rule it out completely to everyone. Because the problem is if you have it wrong, you have quite a negative impact. And at the beginning, you don't really know all the points that we discussed before. So it is normally you're doing like in a startup, you're doing like steps. You're saying you're doing incubation. Try to get product market fit. Try to get 5, 10 customers live. That's what you normally have when you hear a product or functionality goes GA because that is when you really hit it. That's often led out of engineering or product teams who then have The next step is really what I would say is your typical scale up phase that you're going into. That is when you really start coming into and now trying to make it bigger and going out with a sales team. However, depending on what, how important that is. If you want to go all in into feature embed everything, you would roll it out and try to educate and enable the field. That has for example happened with Microsoft Copilots when M365 Copilot came, they went with an all in approach. You don't do that naturally always immediately, so you could do like other products and you didn't say, okay, we have an overlay team. Microsoft calls them global black belts. They're happening in all other kind of bigger companies to have that as well. Sitting either within corporate sales or even still within engineering, depending how, what the balance is, where it's more. And then what you're trying to do is to bringing and winning big deals or going after a certain kind of vertical, going after a certain kind of customer profile, which to test that out, creating momentum because you need more than just one case study or two case studies. You need to learn, how do you sell that now with your sales? And that is where the balance comes into. These are getting calmed really far more on driving, for example, big deals, winning these logos, going after that kind of technical market. Where else of the rest of the sales team is still comped like they would be with their old products, maybe have 70, 80 percent on their normal products, and maybe only 20 percent on on 20 to 30 percent of that kind of new products, depending on how it is set up. Because you need to keep that balance and learn because. Let's be clear. The money makers are normally the old incumbent products or the side, not this kind of new ones. So that's how you can strike the balance and what I call them. When you're starting to create positive momentum, you learn. You're trying to hook into naturally Ninjas within the field who have a tendency, like back to that example for customer data platform. I was one of the sellers who loved that. So I then started to create a bus. So you start getting regional kind of regional momentum where you then can go into and say, let's build on that. Can we start rolling out more, running it, maybe even with a sales campaign? You're going to an event, you talk about that kind of use case, customer on stage, and creating buzz within the sales team so that other sellers say, Hey, I want to jump into, because reluctant from customers to go into new tech, the same kind of issues you have with sellers. So I've done it. I sold CRM software since 30 years. I know what I'm doing. So why would I need to know, need now a copilot? So you have some of these sellers. So using some which are Innovative, want to have, be on the change, and then creating that. So the other thing, okay, something is going on there. I want to be part of that. And then you, once you get that, you run these campaigns, then you can actually start thinking about now going out to the whole sales team and then enablement. Enablement needs to hit five times. So that's why I think it is important to start with an overlay team, because if you're not having a topic that constantly comes up, you learn it, you hear it. If you don't use it, you forget it.

Andreas Welsch: 23:39

So that's great what you're mentioning. It brings up a lot of memories from my own career as well, and how we used to do business development for machine learning at SAP early on 2016 through 19, and also what I've seen now with Generative AI, everything from enablement showing sales teams. Hey, this is what's already available. Here's the value what customers can expect. Here are some sound bites that you can take to your customer. And also, here's the commercial structure and to your point as well, whether it's overlay teams. I know that's what we did with machine learning. Business developers going in with sales teams, having the conversation with the customer, doing the qualification before it moves on to more mature phases. Or now what you said that the 70, 80 percent keep selling your established products, but also don't forget to have conversations with your customer about the new things. I do want to be mindful of time and I see Jody had a great question here. They would love to get your take on this as well. She says, Hey, I hear enterprises describe AI as the art of the impossible, where they identify a hundred plus use cases for AI to innovate and grow their business, but it causes analysis paralysis, which delays results. So they never realized the promise of AI. That's the best way to help enterprises. Narrow down the art of the possible and select one or two use cases that will have the greatest impact on the organization. I think it's such a great question and such a relevant one.

Nicole Wieberneit: 24:59

It's awesome. Thanks, Jodi, for that one. I think, personally, I think you need to go vertical, especially depending on where you are. Think vertical and then think about what's the biggest problems. What keeps in that vertical that BDM up at night? These are the two, three big hairy problems they need, they want to solve. And that's where I would start. And as a vendor and company that going after, I think you need to have a point of view. And that's so using this kind of insight. So if I say financial services the biggest issue regulation, maybe I need to go after. And then. I should go in with that point in view. Hey, we hear these are the problems. Our point is these are the three best use cases that I would go after. And that is to use cases that I would send out to hunt my sellers with. But that goes back. You really need to know your ICP, your ideal customer profile and the problem you are solving. The problem with this type of approach, and I absolutely believe you need to have a focused approach. You need to have a point of view. And you need to roll that out to your sellers to really go for that. It's that people always feel like the broader you are, the more kind of chances I have to win a deal. And it's actually, everything is nothing. It's, it actually leads to exactly what Jodi describes here. Oh, let's do a workshop on what would be your best kind of use case to go after. Yeah. It's more like I, it's what some sales teams are doing. Yeah. I think it's great if you have a customer you trust and knows very well what's going on and can tell you. But a lot of customers want to get your guidance. And that guidance is, these are the three best things. These are the use cases where I see that's how much business value, cost savings, additional revenue you can get. Here we have done it with customer ABC. So basically you drop the logos and the names. And, can we go together with you in the next best step? I know it's simplified here. The world is more is different and it's not going that fast, but that is what I think needs to be done to be successful. And that means also that some customers you can not satisfy because they're not fitting with that. But you don't waste time for your sellers trying to sell something which will never close.

Andreas Welsch: 27:48

And maybe if I can add looking at it from an internal perspective, if you are at a company where you feel you were stuck in analysis paralysis, my recommendation is usually look for the use case that has the least dependencies. So if it is something that you can more or less quickly activate in a product you already use, Let's explore this because you still need to do the change management around it. You still need to rally around people and get your policies in place and security and legal and everybody else in line to support it. But if you started at the very bottom and let's again, dream up what we can be doing and let's build it from scratch. I think that delays it even further. So for me, it's usually where is it some, or where's AI available in a product you already use, but you either don't know about it yet, or you just haven't activated yet. Does that help us increase value? Again, coming back to your point, Nicole, I think that's the critical starting point as well, not just because we can't do it, but what's the value we can actually add. Now folks we're getting close to the end of the show and Nicole, I was wondering if you can summarize the key three takeaways for our audience today.

Nicole Wieberneit: 28:56

So my three key takeaways is think about the focus you want to have based on if I'm looking at enterprise software that I need to sell. on my strengths that I have and that is the focus I need to be can be a specific BDM. It can be a specific industry. It can be a specific region, but you need to be focused based on that focus. What is the problem and value I need to solve? So build your pitches around that. Who is the buyer? Who do I need to bring along the right for that? Based on that, I need to create my sales orchestration, and then it's. It's testing, experimenting, and being open to feedback and to adjust what you basically saw it would be your design and adjust and go try and go after it. You only can learn and get better.

Andreas Welsch: 29:49

I think that's a very powerful message. You only can learn and get better. I wish more people in the field adopted that. And again, but the culture you mentioned are able to bring that back to improve go to market. Now Nicole, thank you so much for sharing your expertise with us for joining us also for you in the audience. Thank you so much for being with us today.

Nicole Wieberneit: 30:09

Thank you.