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Revenue Builders

30 Aug 2026 · 11m · 6 chapters

Episode artwork

The ROI of Multi-Persona Selling with Daniel Simon

In short

How to sell enterprise AI by “multi-threading” across personas and building a measurable ROI, using Glean’s context/search and security features.

Guest background

Daniel Simon, from Glean; previously at EMC. Focuses on enterprise AI deals, connecting use cases across product, engineering, finance, legal, and AI program teams.

Key claims

AI deals fail when only one executive likes the idea; they stick when multiple stakeholders tie the solution to their workflows and business metrics. In-person discovery helps differentiate in a noisy market. Multi-threading enables a stronger ROI story even when buyers already tried ChatGPT/Copilot.

Notable examples

Large e-commerce deal where CTO routed him to an AI program lead (with links to PMs/eng/finance/legal). Use cases included PRD drafting, HR onboarding, job description drafting, and finance variance analysis (10–14 hours each). Quantified time savings showed a 7–10M loss avoided and 50–100X ROI. Security example: Glean Protect detected publicly accessible executive salary data in SharePoint during a pilot.

Written by AI. May contain mistakes.

Chapters

0:45

Understanding Multi-Persona Selling

Daniel Simon discusses the importance of engaging multiple personas in enterprise AI deals.

“You know, you said there's a difference between being, and Johnny said, Like a domain expertise in an application versus the ability to connect hundreds of applications and get that 360 view.”
3:00

Building Use Cases Across Departments

Exploration of how to create tailored use cases for different business units in an AI project.

“I sold at a really large e-commerce company.”
5:02

The Impact of Strong Relationships

Daniel shares insights on the significance of in-person meetings and relationship building in sales.

“because we've been able to multi-thread.”
7:29

The Role of Metrics in Selling AI

Discussion on how to quantify use cases and the importance of metrics in making a business case.

“Like there was an instance in a pilot that we were running, which frankly helped us sell the deal.”
8:27

Navigating Competitive AI Landscape

Insights on positioning Glean against competitors like ChatGPT and managing customer expectations.

“And a lot of them have tried to build their own platforms.”
9:12

Targeting the Right Power Base

Daniel explains the strategy for targeting different roles within organizations for effective selling.

“But instead of having data scientists have to kind of create their own Glean, we can actually automate a lot of that for them.”
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Transcript

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0:10Welcome to the Revenue Builders hosted by John Kaplan and John McMahon. In this clip Daniel Simon from Glean breaks down what strong multi-threading looks like in an enterprise AI deal. He walks through how he moved beyond the CTO and built use cases across product, engineering, finance, legal, and the AI program team. The point is simple. AI deals do not stick because one executive likes the idea. They stick when multiple people can connect the solution to their own workflow, their own path, and a measurable business case. For revenue leaders, this is a practical look at how to turn interest in AI into real internal demand.

0:45Let's dive in.

0:49You know, you said there's a difference between being, and Johnny said, Like a domain expertise in an application versus the ability to connect hundreds of applications and get that 360 view. And that is, I think that's extremely interesting for customers right now. I do. For sure. Where have we sold deals like this before? Right? Like what are some roadblocks that I could face? Like maybe that's not in Slack. And there's even like you're pulling stuff from the public domain too. Like, hey, help me do some research on this company. What are the different business units that I'm going to sell to?

1:24What are the different outcomes that these individual personas would then focus on? And I can craft my very tailored messaging to each of those people. That's not just going to live in Slack. So you really do need something that's much broader. And of course, there are great, like there's legal tools out there. There's call center tools out there. And they're going to do things that Glean cannot do. But you're always like the first thing that everybody does in a company. And I'm sure we've all had an experience with like Google Drive or SharePoint. like their search quality is terrible. And what a lot of the MCP, MCP is the connectors that a lot of our competitors use.

1:57And MCP is inheriting that terrible search quality. So if you don't rebuild the context engine, you're going to have a really tough time finding the most accurate answer. Which again, is going to go to how the user uses, you know, at the executive level. So talk to me a little bit about like, I think selling in your environment is not just selling at the executive level. It's like, if I was selling your product, I would be selling to Dan almost as much as I would be selling to the CEO or CFO of a company. Because at the end of the day, how they are going to look at a success of any AI strategy is, if I turn it off, will Dan screen?

2:41Will Dan have a problem? That's my, right now, that's my ultimate, my ultimate measure right now. If you take away any of these tools, will the user, will the end user scream? For sure. And I think that goes back to multi-threading because I want multiple people to scream when that turns off. So I'll talk about a recent deal. I sold at a really large e-commerce company. So the way I landed at the CTO, he then passed me down to a couple of different personas. There's somebody who leads the AI program for the organization. She has a plug-in to the product managers, the engineers, the finance team, and then also legal.

3:17was another domain. We build a use case for all of them, right? And there is something that we can solve for each of those personas. So I like to sit down with each of them. One of the biggest differentiators that I learned early at EMC too, with a very crowded competitive space is get in person. In person is going to differentiate you very quickly. And with all the noise out there in AI, I think there's also something to be said of like, go build a real relationship. You're going to get a lot of like outreach that looks very similar. Go build a relationship. You do that better in person. So my engineer and I flew up to this customer and we met with each of these people for about an hour.

3:54Identified what their current state is. What are some of the different metrics that we had on some of these use cases? So maybe it's like I'm drafting a PRD, product review documentation, an HR use case around onboarding new employees, like drafting open recs, for example. There was like a variance analysis agent that we had to build for the finance team. We quantify each of those use cases. How long would it take you to do that today? In some cases, it took maybe 10 hours, 14 hours. And part of that would be like, oh, well, now I have to go wait on an update from this person that sits over in EMEA.

4:29We're on a different time zone. So I'm waiting and waiting. That's stalling business. It's stalling revenue. So we have all of these little quotes as well embedded into this with the metrics, which I think really amplified the business case when we went back up to the CTO who had already brought in chat GPT, mind you. So we showed him a business case of like, yeah, you have chat GPT, but you're spending 10 hours on this task, seven hours on this task. This is how many different people that this is affecting in the business. It was like a seven to$10 million loss for them to not buy Glean. We were a fraction of that, of course, but our ROI was something ridiculous, like 50, 100 X, because we've been able to multi-thread.

5:07If I only landed with a single team, I wouldn't have had as compelling of a story. Now, do you think if they hadn't taken in ChatGPT and you showed up that you could have gotten the deal because they might have said, well, let's use ChatGPT first because we hear that that could do it? So is it almost better that for salespeople that are selling a real good AI tool that they've already used one of the large LLM models to try to achieve their business outcome and you come in afterwards because they're more educated? I mean, I'm confident in my abilities that we could have got a deal done there, but I think you're right.

5:45I love that, Dan. There's no pain. There's no deal. Like there probably wasn't a lot of pain yet. And that's what I've heard in my first year of selling is like, oh, co-pilot's our strategy. Oh, ChatGPT's our strategy. Like I'm kind of feeling today like it was back at my EMC days. Like nobody gets fired for buying Cisco, buying EMC. Like people are like, oh, we're not going to get fired for buying Copilot or ChatGPT. Everybody knows about it. They're the biggest company out there right now. And I'm starting to feel that a little bit with Anthropic too, but they all have the same challenges as token consumption, accuracy.

6:17They're just not there. And now that they have the pain, my message has become much more compelling. And it's also helped us sell into a lot of Fortune 500 accounts now who have tried to build this themselves. They have two or three different products that are still not working. And it makes our story that much more compelling. They're not worried about security. That doesn't come up where you're taking all your internal data and it's getting consumed by these models and even customer data, personal data. They're not concerned that much about security and compliance. I mean, I'm sure they've got some good sales reps telling the story.

6:51And then on the other side, like they're six to 12 months into that implementation. Like, hey, this isn't really what we're expecting yet. So, yeah, I think what's cool about Glean too is we actually do have a security product embedded into our platform. It's called Glean Protect. So it actually will scan for sensitive content. So say you have credit card information or any type of PII that you don't want in there. There's a bunch of rules embedded into that or you can create your own rules to remove that from your index. So it also, like some of my strongest champions have become CISOs. they're like i was looking at some data data security protection tools and like i'm a little scared of chat gpt them making sure that they get this right and you're telling me glean not only could help me alleviate the need to buy a separate a separate product but they feel much more comfortable rolling out glean with the way it's not it is permissions as part of that we obviously inherit the permissions of that source application but also making sure that their users can't search for something that's overexposed in SharePoint.

7:51Like there was an instance in a pilot that we were running, which frankly helped us sell the deal. They had the salary information of all the executives and it was publicly accessible. So somebody like me, a seller, if I knew where to look for that in SharePoint, and it was probably hidden in a bunch of folders. But if you're in a chat GPT and a co-pilot, like I'm not so sure that they would have been able to catch that. And that's something that Glean can find. and who have you found in these deals where's the power base does i mean you have the technical buyers like the cios you talked about a cto you get the chief digital officers yep and you have the business buyers you got sales you got ops you got cs where do you like to go first second and why first i'm always calling in the tech organization because i do believe that they are the ones that are going to roll this out.

8:44And a lot of them have tried to build their own platforms. There's also a lot of opportunities I've had around the data teams. So people that are working with some of the warehouses out there, like a Databricks, like a Snowflake, they tell a very compelling message too. They actually both use our product for their own internal use because what they do really well for structured data, Glean does really well for the unstructured data. So they're a customer and a partner of ours. We can integrate with their platforms to tell a much better together story. But instead of having data scientists have to kind of create their own Glean, we can actually automate a lot of that for them.

9:20So I'd say tech organization is a great fit for us, like engineering, data teams, and then go to market is also a great one. If we can drive revenue faster, help with better conversion rates, help win rates against your competitors. What I'm, I mean, it's QBR season right now. So I'm actually using Glean to build my QBR deck. and they're urging us to do that. And it's not even a deck anymore. We actually have interactive HTML pages where I can say, hey, what's my forecast? What are the white spaces in my accounts? And it's like a presentation, but in a website format. And I can just type that all out into Glean and it'll create an HTML website for me, which is really awesome.

10:01Wow.

10:04Daniel Simon: Thanks for listening to today's episode. If you enjoy the content, please subscribe. rate and review the show to help us reach more people. This show is brought to you by Force Management, where we help companies improve sales performance, executing the growth strategy at the point of sale. Check out forcemanagement.com for more information.

From the publisher

Winning complex deals requires more than executive sponsorship. The strongest business cases are built by connecting value across the organization. Daniel Simon shares how he worked with stakeholders across product, engineering, finance, HR, and legal teams to uncover specific use cases, quantify time savings, and build an ROI story that resonated from end users to the executive team. The result was a business case that transformed AI from a technology investment into a measurable business outcome.

Daniel Simon is an Enterprise Account Executive at Glean, where he helps large enterprises deploy AI solutions that improve knowledge discovery, productivity, and decision-making across the organization. He brings experience selling complex technology solutions into Fortune 500 companies and navigating multi-stakeholder enterprise buying processes.

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Hosted by five-time CRO John McMahon and Force Management Co-Founder John Kaplan, the Revenue Builders podcast goes behind the scenes with the sales leaders who have been there, done that, and seen the results.

This show is brought to you by Force Management. We help companies improve sales performance, executing their growth strategy at the point of sale.

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