No more free trials (Chris Pasquier from Slite)

Free trials don't work for AI products - so... what do you do?

That's what we asked Chris, CEO and founder of Slite.

• (00:00) - Introduction
• (03:36) - Challenges in Selling AI
• (04:53) - Introduction to Slite and Super
• (06:31) - AI Implementation and Use Cases
• (08:50) - Customer Onboarding and Trials
• (10:15) - Why can't we just do freemium
• (13:10) - Overcoming AI Adoption Barriers
• (22:15) - Future of AI in Business

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Creators and Guests

Host

Mikkel Plaehn

Marketing leader & b2b saas nerd

Host

Toni Hohlbein

2x exited CRO | 1x Founder | Podcast Host

Guest

Christophe Pasquier

CEO at Slite (YC W18)

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Hosted by Toni Hohlbein & Raul Porojan, together they look at the full funnel.

With a combined 20 years of experience in B2B SaaS and 3 exits, they discuss growing pains, challenges and opportunities they’ve faced. Whether you're working in RevOps, sales, operations, finance or marketing - if you care about revenue, you'll care about this podcast.

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[00:00:00] Toni: Free trials for AI products don't work.
[00:00:03] So, what do you do instead?
[00:00:05] Chris: we have a lot of upfront cost for us. Like, you know, like the ACV needs to be higher because we spend so much more time with customers just to bring the data.
[00:00:13] And, you know, we do the job to kind of create a library of recipes so that you can, as much as you can, plug and play. But yeah, like there is some work to assist you building the right space, putting them in place, and building the habit with your team
[00:00:26] Toni: That's Chris, CEO at Slite, he shares why they couldn't run free trials, and what they did instead.
[00:00:34] Chris: So I'm very much like back into startup mode we are spending as much time because it let us learn as well. So it's not just for the customer, it's also for us. Which is maybe, like, an interesting thing. And I actually have my sales team that does the same.
[00:00:47] Toni: Before we jump into the show, today's episode is brought to you by Fullcast. The only AI powered platform that streamlines your entire sales cycle from plan to pay.
[00:00:59] Customers report up 80 percent cost savings, 20 percent growth in pipeline, and 30 percent boost in RevOps efficiency.
[00:01:07] With modules like Territory and Quota Management, Routing and Capacity Planning, Fullcast adapts to your unique needs whether you need one solution or an all in one platform
[00:01:19] Visit fullcast. com, book a demo, and mention the revenue formula podcast. To unlock an exclusive premium gift just for listeners
[00:01:29] And now enjoy the show.
[00:01:32] Mikkel: So, Chris, do you enjoy watching handball or not really
[00:01:35] Chris: Watching what?
[00:01:36] Mikkel: handball?
[00:01:37] Yeah,
[00:01:38] Toni: that was correct answer. Watching what?
[00:01:40] Chris: Handball. Okay, I'm, I'm, I mean, like, you know, not that much, no, no. In Olympic Games, maybe I watched, like, a couple of them, but yeah, that's it.
[00:01:48] Mikkel: it's validated. It's not, no, we were just, we were talking earlier today. Denmark. World champions now, but it's like, who cares? Yeah, exactly.
[00:01:56] Who cares about this sport? Is it just Denmark probably? And maybe Norway a little bit
[00:02:00] Chris: I mean, no, France, France actually like, you know, like historically was super good in handball and bad. And I think Croatia? What's the, I think that's the kind of like the best, I mean, they are supposed to be like the historical best, right? Yeah.
[00:02:14] Mikkel: But it was just funny because we talked about, so they've, Denmark has now won four times in a row world championship. And I remember, I think it must've been last time we lost. I was in France in Tignes skiing and we lost to France in the final. So that was really painful, especially because then you get teased by folks, you know, just don't care about it at all.
[00:02:33] Chris: Yeah! Yeah,
[00:02:36] Mikkel: level of, of defeat. I gotta say, I gotta say,
[00:02:39] Chris: I can, I can imagine. People
[00:02:42] Mikkel: we have another parent on the show today. So I guess we have plenty of subjects we can we can dabble into if we want to.
[00:02:49] Chris: Are you both parents?
[00:02:50] Toni: Yeah, yeah, yeah.
[00:02:52] So we're actually talking about the show always about our kids for some reasons. Always at the intro we talk about like, oh, you know,
[00:02:57] last night, this and this. But instead of talking about kids and handball, Mikkel, what did we want to talk about today?
[00:03:02] Mikkel: We wanted to, yeah, that's a crazy segue, by the way, we wanted to talk about basically how AI is changing sale selling and kind of the requirements necessary to actually really start selling AI and with us, we have Chris from slide. Thanks so much for joining. You had a. Pretty great post on this except sex subject sharing your, your experience selling AI for for some time.
[00:03:26] And I just wanted to start off by asking you, Hey, why, why is it we cannot have trials anymore with AI? That was kind of the main concept of, of your post.
[00:03:36] Chris: Well, I think because I doesn't work yet, I guess if I am trying to be a bit polymystic, like, you know, like that's probably the reason, like, if you look at the potential change of AI right now for knowledge workers, it will be massive, everybody knows that. And I'm a developer and I see the, in the developer committee, you know, it changed the work already.
[00:03:56] But for all the rest of functions sales, support, success you know, marketing, most people still use like AI to just, you know, translate or, you know, correct their documents in cloud and charge a biddy. And like the rest is just like marketing promises and sound, but you don't see them apply that work.
[00:04:13] And so, yeah, I just think that right now we are still in the kind of building phase and it's a very, very strange phenomenon in the industry. where you have, like, all the customers that are already convinced it will change their work and so they are willing to invest, but at the same time, like, none of them actually have impact and it's actually not working.
[00:04:30] So it's a very, very strange kind of time and for these years to come, like, we'll have, I think, trials where people are, at the same time, building their use case, selling them internally, you know, making a case for, like, the, what they are already starting to pay, being worth it and so on.
[00:04:46] Toni: Very cool. The, Maybe it's kind of to focus a little bit of context of where you're coming from and where also your, your perspective is coming from.
[00:04:53] Can you give us a little bit of a, kind of a glimpse into slide and the and the new company you're building kind of to, for, for folks to have that context.
[00:05:00] Chris: Yeah, so, I've started Slite. So Slite is a documentation platform for teams. Like it's a knowledge base. We built it since 2017. And the idea of Slite is very simple. It's like a knowledge base that is extremely simple to use for all your teams. So typically for teams of hundreds, thousands of people, it's something that is a big problem that the documentation is extremely complicated to use.
[00:05:22] And at the same time very powerful. for the administrator. So that's a business that, you know, keeps running with like thousands of customers from, you know, like, well, actually a very small team of two or ten people to up to 3, 000 wide companies. And in 2022 23, like when AI basically kind of rised, we were the first to release a feature called Ask, which is basically a an AI search on your private company data, your knowledge base.
[00:05:50] It worked very well. It added a lot of limitation and over the years we saw that, you know, people wanted more from it and that their knowledge was not just in slides. They added their Slack, their HubSpot, their Salesforce or whatever old, important data. And so we decided to build a new product called Super.
[00:06:07] Which makes AI ready to use at work. And the way we do it is we simply sync the data from all your company sources. It's very much plug and play. Like you can do it instantly. And then we give you and your team recipes and tools to get instant value. So we let them ask in bulk, we give them the best AI search out of the box.
[00:06:27] We let them build automation and so on in a very kind of easy to use interface.
[00:06:31] Toni: And just listening to this, right, and kind of getting some of that context is the immediately is this Hey, is it going to work for me? Is it going to work for us as a business? Right. Because I think this is a little bit where the rift is starting to show now for the traditional SaaS sales motion, you know, whether that's, you know, sales lad or inbound lad or whatever you want to go for. It's usually like, Hey, look at this thing. Hey, you can press those buttons and it's going to do this other thing, right? Kind of, that's usually kind of the way, you know, all of that the, the SaaS playbook basically has worked throughout many different iterations and longer and shorter and what have you. I think what's now happening on the AI side is well, okay. You're kind of pressing this button with your data, but what will it say when I press that button with my data?
[00:07:18] Is, is basically that, is, is that, is that the change? Is that what are you seeing?
[00:07:22] Chris: Yeah, I think you're absolutely right on the fact that data is a massive factor. Like not everybody not every company has the same kind of policy around keeping their CRM clean, for instance, or, you know, using the same status in their CRM. Not every company has the same documentation and I think written culture.
[00:07:38] So maybe your information is locked in meetings and you actually need. Before anything else to have like your meeting recorder transcript being synced with such a tool, for instance so you're right. Like, the collection of private data is one of the biggest kind of like, blocker for AI at work.
[00:07:53] The thing that we see is that there are some tools, like typically if you have Slack, if you have your HubSpot, if you have GitHub, Linear, whatever, you know, like, some tools can bring instant value immediately. So for instance, we have this feature that is built in super that analyze your slack conversation from the last week and give you a digest of the top information.
[00:08:16] And that has proven to be like one of the killer feature of super so far, where people, you know, like, even without specific instruction, like literally just like these two top three topics and give you a summary. It already gave you a value, but then yes, like if you want to kind of have like a better application and, you know, solve more specific problems of your work you need to adapt, you need to work in prompt engineering, you need work in term of automation, plugging it to the right tool, and yeah, like it basically, you need to rethink your whole pipeline of tools and instruction and so on, and, and that's what we try to make it easy.
[00:08:50] Mikkel: I kind of want just also want to take a step back here. One thing that's also probably great for the listener to hear and understand is, so who are you actually selling this to and how are you selling it at the moment? I think that'd be really good to hear as well.
[00:09:02] Chris: so what happens most of the time right now is, and that's actually interesting. Like I think the most, the biggest use case is for customer facing teams. So, you know, support, customer success, sales, and, you know, revenue operations. But very often like the person that is appointed to work on this topic will be product.
[00:09:23] IT, CTO, like technical folks, which is, it doesn't necessarily make a lot of sense, but you know, like that's just the way it is. Like, you know, people assign affiliate AI to technology and so they put like their technology specialist leading this. The thing that is useful with this is that these people usually are in charge of tooling and once again, the biggest hurdle to deploy at work is access to data.
[00:09:46] So typically if you have like a CRM and you need information from your CRM. You will need engineers to pipe it correctly, you know, to whatever tool will use AI to generate value from you. So yeah, for now, like, we, we, like, we still have the entry point being the technology person. And then, like, you know, when we build recipes and, you know, agents, so more kind of, like, specific assistance for certain use case, would be with the, you know, whoever, like, the team leader on this topic.
[00:10:12] So, revenue operation customer specialist, this kind of thing.
[00:10:15] Mikkel: When it comes to selling this let's dive a little bit deeper. Why is it? Why is it? We can't just have a regular approach of freemium and free trials. What is it that starts breaking there? What are some of the learnings you've made in this process of, of of selling your AI offering?
[00:10:29] Chris: slight originally is a freemium product. So it's literally self serve. You can start, create your workspace you know, bring your data, start kind of building your knowledge base. And at some point, like upgrade and, you know, bring the rest of your team and so on.
[00:10:41] And then we have a sales led approach for enterprise where we add them, bring their data, structure them and so on. The thing with this is that you pretty much know what you are paying for. Like, you arrive, you have a knowledge based system we have some features that are dedicated to knowledge management, like verification, reminders well, ask, which is our AI search that comes built in the way to see, like, what are the gaps and so on.
[00:11:01] So it's very much like, of course it's advanced, but it's very much expected, you know, what you get out of it. For AI at work, it's very, very different. You need to have the right data source plugged in. Like most of the problem that we have with people not finding the right information with super, it's just linked to the fact that you have not linked the right data source or that your data source is not well used.
[00:11:22] So typically people dropping like massive documents unstructured, it's very hard for AI to make sense of it, as an example. So. So that's, I think, like one of the biggest reason to, you know, like change the mechanism. We need to have like, we have a lot of upfront cost for us. Like, you know, like the ACV needs to be higher because we spend so much more time with customers just to bring the data.
[00:11:44] And then the second thing is on building the assistance. You know, like, it's great to have, like, like, the thing that is nice with Super is that out of the box, you will be able to ask any question about, you know, whatever you have synced. So, you know, your customers your pipeline, but also, you know, your documentation, how to, SOPs and also stuff that you wouldn't expect to ask.
[00:12:02] Like, you know, from Slack, you have so much information. from, you know, like a, a case, like a support team that is speaking about how to do X. It has never been documented, never since. And you actually ask the question and you find the information from a nine months old thread. And that's the beauty of, like, this product, I think.
[00:12:19] Like, built, like, out of the box, it would kind of give you that. Same thing, out of the box, we give you security form. So we have a bulk mod where you can literally fill forms in instant. And that's the kind of thing that we keep you out of the box. But if you want, like, and you need, you know, like, more specific use case for your team, like, you want to have, like, you know, like, given this user, this customer question, I want you to generate a draft of email to reply, with, like, you know, like, an attempt to upsell them or something like this, you need to build specific assistant.
[00:12:52] It needs some work to kind of, like, have the right templates. And, you know, we do the job to kind of create a library of recipes so that you can, as much as you can, plug and play. But yeah, like there is some work to assist you building the right space, putting them in place, and building the habit with your team.
[00:13:10] Toni: And, and do you think this additional work and those additional proof points that you need to show to the customer, do you think this is because maybe your company is still new on that part or the product is still new or AI as an, as a, as a technology is still new? Do you think that, you know, what, what of those do you think are the drivers?
[00:13:28] And, you know, I'm kind of asking for, for people listening to this, trying to, to, you know, triangulate to their own approach. Is this maybe something that also translates to them, right? Is, is, you know, if it is the technology and I'm guessing it's probably part of the answer here taking, taking, you know, jumping ahead to a little bit you know, is, is this concern voiced by the customer that kind of like, Hey, you know, I don't know this thing is going to work for me.
[00:13:51] So therefore we need to do all of that, you know, work up front, right. Is that, is that change in buying behavior or selling behavior rather is that driven by the buyer basically.
[00:14:00] Chris: Yeah, 100%. Like, the thing that is so interesting right now with almost all my leads is that they want AI at work. They have problems that they know could be solved in some way. But then like, you know, it basically stopped there. It's kind of like, you know, we know that, you know, like it could automate stuff, but then kind of mapping out the exact use case that we could.
[00:14:20] So for them, like is another kind of piece that they don't really kind of have yet. They are willing to invest in this, but they don't really exactly know why, or, you know, which kind of part of the, whatever, like their workflow they want to replace. So you need to do like as much consulting work.
[00:14:36] And, you know, like, assistance building that for them and showing them what is possible as you need to just, you know, like, deploy the tool in their company.
[00:14:45] Toni: And, and kind of on top of that, right? So if someone trying to figure this out with you and maybe there was a general director from the CEO, we need to buy some AI tools now. And then, you know, they basically kind of land with you. You have that conversation. Well, what should I buy a AI tool for? Is, do you then usually see that these guys need to kind of go back to their boss and boss's boss to and show like, Hey, and here it works.
[00:15:07] And this is how it's going to work out. And, you know, Do you think that that's part of the reason why they want to have this trial and kind of want to really go deep in this or, you know, what, what
[00:15:15] other stuff is driving this behavior?
[00:15:17] Chris: I think there is, like, just an intuition. The thing that is quite nice with this product is, and I mean product with an S, right? Like, it can apply to other kind of type of tools. is when you give a demo, like, we always give a demo on real data or kind of like previous companies, so slides, kind of documentation and so on.
[00:15:39] And you can see the aha moment almost instantly. Like, literally, you ask a question and people will be like, okay, you know, like, I see myself asking this question and I would probably have, like, made a meeting for this or, you know, asked somebody on Slack and waited for two days. And, you know, lost a lot of time from my team.
[00:15:56] So people see the value instantly. They see the potential instantly. The problem is, obviously, like, they wonder, like, would it work with my data? So, you know, like, instantly they need to try. Like, they can't really kind of trust just, like, you know, what you show them. So I think that's, like, one of the biggest blocker.
[00:16:13] And To convince their boss, as you say, like they need like more kind of clear ROI. So they need like one use case that is very kind of painful for the team to be really well solved. So, you know, like an example would be very recurring examples for us would be um, Um, support asking questions on internal things like, you know, maybe they have FIN or whatever kind of like, co pilot of support, you know, like, when they work in their tool in Zendesk, Intercom or whatever.
[00:16:42] But then there is like, at least 50 percent of the more complicated questions, which are the one that takes time, that they need, where they need internal documentation or internal chat and so on. And this is where we, we take place. And so once we managed to set up a Slack channel. where they can mention super, it then sells them, and they can, you know, build this habit.
[00:17:03] Already, like, we have like a massive use case where they know and they can see very clearly that they are winning a lot of time. And the same thing applies to, for instance, RFP. So, you know, like, you have like a solution engineer, a salesperson that needs to kind of feel either like a sales form, security form, RFP, and they see the tool that is built for that where they can just literally paste and you see like all the cells auto completing with all the answers and you can tailor like which filters to use to answer this and you can, you know, drill down each individual question and then they are like, okay, you know, obviously this made my team win two hours or, you know, two hours or five, you know, it's days sometimes of their life and Yeah, that makes, like, one of the best use cases, that they can sell to their, to their boss, like, you know, the value is obvious.
[00:17:50] But they need to reach this point of, like, you know, Okay, you know, like, this moment, like, this is what I'm setting, like, you know, like, I'm removing, like, 50 percent of my time of my support agents looking for answers, and I'm removing, like, you know, like, days of work of the solution engineers themselves that can just, like, you know, take more time closing deals instead of filling these forms.
[00:18:08] Mikkel: I mean, it sounds like a lot of stuff actually happens in this whole. Almost like onboarding of the customers, right? You mentioned there's something around the data, connecting things what recipes to use, how much time do you spend with the customers for them to even reach the point where like, you know, themselves using and go, wow, now I, now I kind of get it, right?
[00:18:28] How much time and effort is, is invested on your part?
[00:18:31] Chris: Honestly a lot, but it's also like, I don't think this is a lesson for the future. Like, we really want to streamline this, but right now, like we are spending as much time as we can. Like, we're very much in founder mode. Like it's a new product, it's a new, like we are big becoming a multi-product company.
[00:18:45] So I'm very much like back into startup mode where I'm just like, you know, like, myself and you know, I actually go from there and so on. We are spending as much time because it let us learn as well. So it's not just for the customer, it's also for us. Which is maybe, like, an interesting thing. And I actually have my sales team that does the same.
[00:19:03] They ask, you know, like, giving us the voice of the customer. And honestly, like, we need it to build the right kind of, like, features like it's such a change of a bit, like you need to buy, to build the right tools for the customers. You need to add the right source to add them the right way as well, because you, it's not just, you know, like an API integration or whatever you need to index the right data in the right format.
[00:19:24] Like if you have a CRM, how do you index the data? You have probably custom field in your Salesforce or your, but like, this is a lot of complexity to understand and where you really need to walk any land with the customers. So yeah, like you spend I think like, you know, like in 30 minutes, we'll have your workspace set up and you will get instant value.
[00:19:44] You can ask anything, but then for your team to build the habit and for your team to see the specific use case, as I mentioned before, that really like deliver value and that justified the cost, you know, for the whole company and so on it would take like a couple of weeks.
[00:19:58] Mikkel: So the other element of making this all work out, because this can, you know, This is a lot of cost as well, like the time you spend, right?
[00:20:05] And I know one of your points was also that you want to run paid trials. So how do you get you know, first off, how do you even get customers to agree to that, but then also how do you figure out what to, what to charge here?
[00:20:18] Let's share some of the wisdom and insights you have with the audience who might consider that, dang, we, we probably need a bit more white glove service with this new AI offering, but. We, we're not sure how we're going to justify the cost.
[00:20:30] Chris: Yeah, it came very naturally. I think it's the right way to go for most teams out there. The, the simple answer is that customers are willing to do it. Like they see the potential, but they know that they need internal change. They need to build the habit internally. They need to eventualize on, you know, whatever change of habits needs to happen.
[00:20:50] Because, I mean, let's face it. If you have like a support team, for instance, Obviously, like, AI is going to just change their life. I mean, it just, like, can remove so much time, like, lost in discussions and so much time lost from your engineers, as well, or product that are answering their technical questions.
[00:21:07] But, you know, like, between this kind of observation and them, like, starting to use a tool and, you know, changing their habits and not going to a Slack channel to ask a question to their engineer and instead, you know, asking, like, this tool, for instance. It takes like, you know, there is a change of habits that is quite important.
[00:21:28] So, the decision makers are very aware of this. And, I think, it only takes one good answer for them to realize the value. And then, like, you know, their whole question is basically how to deploy it, how to build the, the habit in my team and so on. I don't think it's that much about, like, justifying the cost to their supplier, because we are, like, in SMBs.
[00:21:48] Most of the time we are with the decision makers already, or, you know, close. The biggest challenge is rather security. Like, you are talking about customer data, so that's a big, big you know, like, point of attention for people. But beside that, yeah, it's not about, like, the decision, it's more about, like, you know, showing that okay, the, the tool can deliver the value, but now you need to kind of, like, change the whole company, and, you know, have the habit of the whole company around it.
[00:22:15] Toni: So, so I'm actually wondering what's, what's your take actually, do you think this is this extra scrutiny, let's just call it that, that extra carefulness, basically that's being deployed there. Is that because AI is new? Just like SAS was new 20 years ago. It's like, Ooh, you know, we don't have this on prem.
[00:22:35] We have it like somewhere in a, you know, it wasn't AWS back then. It was somewhere else.
[00:22:39] Or do you think it's just different because it's AI, right? Kind of, is it, you know, what's, what do you think is going to happen in the next? two, three, four years while you guys and a couple of others are trailblazing right now.
[00:22:50] Will this get easier? Is this a transitional thing? How should people think about it in terms of what, what they need to adapt to now versus, you know, what maybe is, is going to come in a couple of years from now?
[00:23:00] Chris: I, I think the, the, the um, danger uh, um, That some companies perceive is more like, some people perceive is more for almost their own job. Which is fair, honestly. It's hard to kind of like change a bit when Well, you have two things, like, you know, like some people are reluctant to change and I think for good reason, you know, like it might very much change the, you know, like the way their team is composed at some point.
[00:23:28] The security part, like, is obvious and I don't think it will change over the years. I mean, there is like a, you know, if you touch, like, company data, like, the, the big barrier of AI at work, and that's what we work on, like, that's the biggest first step, is access to private data. If you want access to private data, you need to sync it to have semantic search.
[00:23:46] I think that's, like, you know, like, doomed to to be challenging. And if anything, like, I believe there probably will be one actor that will emerge. More of a developer tool that will offer you like one rag system. So one semantic search system that then other tools will tap into. That's maybe an idea for a company.
[00:24:02] Like if entrepreneurs like listen to it, like I do think that there would be like a one actor doing this just because it makes more sense to have a company that says, okay, you know, we want one assistant for CS doing X, and then we have one assistant for products doing Y. But we don't want to have like, you know, 10 dependencies where everybody's replicating the entirety of our company data and, you know, you multiply the risk.
[00:24:24] So that's, I think, just like a natural, I don't remember the name, the word that you use, but you know, natural kind of point of attention for, for teams. But then for the rest, it's just that, you know, like as I said at the beginning, like it just, AI doesn't work out of the box for most of the team out there.
[00:24:40] So it's basically you have a wow effect very fast. The problem and you have a lot of UX problem around this is, you know, like, making it like properly work. So I, I can give you example, like one thing that we do for instance well, one for, for the most basic use case of super, you ask a question you know, like, for instance, something like what is our pricing, right?
[00:25:00] The most basic question. I mean, it's a bit weird to ask it, but you know, why not? And then like, you know, you realize that you have like two products. You have three pricing plans for each, plus a lot of custom data. Like, you know, you have like one customer that you did a custom price for, and AI gets all this data.
[00:25:16] And, you know, like literally it's very hard for it to answer. So it can very easily give like a wrong answer and be extremely confident saying so. Saying, well, you know, the price is x, and x being like the custom price that you did to the last customer, which is obviously incorrect. So if anything, you know, this, like the technology works.
[00:25:34] But the experience for the customer, like, might not. So, you know, we needed to build a UX for this, where we explain, and we let you refine, and we let you filter, and we let you build specific context for people asking this. Like, if the customer support team asks that, it shouldn't tap into the custom contract, for instance, or this kind of thing.
[00:25:51] So yeah, you have, like, so many kind of challenges along the way that I think, like, teams realized both the potential and the fact that it doesn't work out of the box and they need to do a lot of upfront work.
[00:26:03] Toni: But I also think, you mentioned a couple fo times now, kind of changing habits. And I think changing user behavior, in general is really really
[00:26:13] difficult. It's just really difficult to actually achieve that. Right. And when you think about traditional SaaS, it's, you know, sure it's, you know, different system you need to log into, but it's kind of the, the thing that you want to get done stays the same.
[00:26:26] You're just using, you know, a different color hammer, you know, you know, at that point in time, right. But now with the AI jump. At least we're kind of all believing it's kind of a jump. Suddenly that changes, right? So I'm actually wondering, maybe it's not necessarily a technological shift that's driving the skepticism and the scrutiny. Maybe you kind of, what you kind of also seeing there is a lot of like, Hey, dang, you know, actually this is a different way of working and, and getting that change into the organization. By way of buying a product, it's just really difficult to pull off, right? Kind of, it's just really difficult to nail that.
[00:26:59] And it's, it's almost makes me wonder is this maybe some of the, the, the driver here, right? Versus sure. Yes. We have a new technology. But actually trying to get this change in the organization to happen.
[00:27:11] That's actually the real problem here.
[00:27:12] Chris: 100%. I think you, you're absolutely correct. And I think like, you know, like, it goes even stronger than that, like, as I said before, you need, you know that there is a change that will happen, you can have like a glimpse at what the future will look like, and at the same time, the future is not there yet, so, you know, whatever you use is not perfect for this use case, so it's kind of like, you know, you need to kind of like build conviction on, you know, like, this will be possible in two years, and we need to kind of prepare for that or, you know, like, in six months, but And at the same time, like, you know, well, you know, you see all the problems along the way, like you wish, I don't know, for instance, I'm a product person, I wish like a tool was able to prepare a report on product requests on a certain area of my product and to read all my product board or my cycle, whatever kind of like backlog you know, feature requests or customer feedback platform I'm using.
[00:28:01] And the right is that right now, AI is not built for this because it's unlimited context. So you can't really kind of like feed everything, right? You need to do like some work before and the UX around this has not been cracked yet. So there are a lot of you know, like, there is a big gap between kind of like what is the future and we all know it will be this.
[00:28:19] And like what the reality allows right now and what the quality of the tools allow right now. So building the change of culture and the change of habit. Given that you are not there yet, you know, is obviously very difficult.
[00:28:31] Toni: Yeah. And, and trying to kind of pull it back into the practical realm for some of the folks out there. Do we have like some very specific, Hey, this is, you know, we, we saw this problem and I think this is so valuable here to have the founder here actually talking about this because it's a multifaceted problem.
[00:28:47] It's not just a problem at the VP of sales or something
[00:28:49] like this runs into. It's like, it's kind of all over the place. Right. But how did you actually change your approach to acquiring your customer? So specifically around the onboarding trial period, right. Kind of. You mentioned already you mentioned already kind of it's paid. What other things did you kind of do in order to try and, you know, frame this thing and make it, you know, make this motion work for you?
[00:29:09] Chris: So I think like, I'm thinking of ways like acquisition first, like marketing first. The thing that we see is that I don't believe that you would have a lot of tools tapping into your, you know, like shared kind of data of information. So there is this kind of like paradox where we will sell vertical use cases.
[00:29:28] But at the end, like what will work will be one tool where your entire team. You know, get value from. And so the way we approach things, and we are literally building, like, you know, like our marketing campaigns right now, but we do manual outreach for now, is like, yeah, as I said, like, you know, vertical use cases.
[00:29:44] So, you know, I mentioned, like, support, like, internal documentation, internal Slack access with an AI search is just incredibly powerful. People usually need it either through Slack, so we have, like, a Slack bot that is for that, and we have, like, a Chrome extension that let them access when they are working on Zendesk or Intercom or whatever.
[00:30:02] And so we build, like, an acquisition campaign around this use case. Same thing for bulk, RFP you know, like, you have some specific personnel that need it, that lose days of their work on this. And so, you know, it's very easy to kind of, like, sell to them. And then when we are, like, with these people and, you know, building the pilots, same thing, like, we over focus on these two.
[00:30:23] or, you know, whatever, like this N use case that we've detected with them. We help them build the right prompt, the right kind of setup, the right tools. We make sure that it works for them and so on. And then, you know, we'll speak about expanding to the rest of the team. But, you know, like, we spend a lot of time just making sure that this setup, these tools, these use cases are really, really well solved.
[00:30:42] And then we expand to the rest. And so, like, the way it works is very much like, you know, like, we have a trial of like, you know, like, which is very much a setup time of two weeks where we just like, you know, like have their, their tool synchronized. And then we kind of like set up like assistance with the right prompts and so on for them.
[00:31:01] We help them kind of set up like whatever integration if they need to. So in their Slack, in their column and so on, we do office hours with their team. So, you know, like all, you know, this probably takes like three hours of our time and a lot of, you know, just like. chat live, like we have shared Slack channel, which is each of our customers for now, and I think we'll keep that for a long time.
[00:31:20] And then at the end of the two weeks, like basically we are still in a test phase because we know that this thing has not been deployed to the whole team. But they are willing to pay for, you know, usually like the double of activities at the moment, like they know they are, they are starting to, to release it to the whole company.
[00:31:35] And so we keep kind of like helping them deploy more use cases and so on. Yeah, so we have like this, you know. paid trial phase that happens, like, organically for, you know, two months, three months before they set to yearly.
[00:31:47] Toni: Did you, did you kind of reach a point now where it's like, Hey, this is the process. And you tell the customer proactively like, Hey, listen, if you want to buy this thing. Those are the steps it's going to take two to three weeks.
[00:31:58] There's going to be, you know, something paid on top. We're going to focus on those areas. You know, how much, how much do you I want to say guide you know, guide that face, right? Because it's, it's very easy. And I've seen this mistake being made many times in, you know, traditional SaaS as well. So like, sure, let's just plug in and let's do a trial.
[00:32:15] And then there's, then you have like a start and a, and a mediocre outcome. But here it's just simply necessary. Right. So did you, did you you know, get to the point of being extremely structured around this and basically kind of asking the customer kind of, what are the things we need to prove to you for you to buy, right?
[00:32:31] Kind of, it's a very, very hardcore sales question to ask. But while we look at through this kind of how deep into that structure did you go already?
[00:32:37] Chris: I think you, I mean, you say it's super well it's exactly what we need to do. For now, like, we are still at a phase where we are learning. So, yes, we are very directive. For each new customers, but I can tell you that we don't change it every time like we basically adapt and learn but yeah like the, the, the boundaries like become clearer and clearer, like we have like this thing about defining the use case, exactly what you said, like what do we need to prove you for you to buy and the, the, the answer varies so much, like some people have very, very clear use case and they want to nail this, some people will be like much more, you know, like some people for instance like a customer that we had like recently like told me If you manage to kind of, like, have like three questions answered on their own, like, without access to the team in a week, that's enough for me to pay for 50 users.
[00:33:24] And, you know, it's interesting. It's basically people that really see the value of the time, actually, of their employee, which are all, you know, very well paid folks. So yeah, like, asking this question, like, you know, whatever is the answer, huh, is like one of the, the starting points defining the use case.
[00:33:41] and then like setting a timeline for the two, three weeks of the trial.
[00:33:45] Mikkel: the last piece I'm missing is just how do you then go from having run that six, let's say successful proof of concept, what, what even that means to, okay, let's now move over to contract and get you on as a, as a full on customer. Because I, I have lots of questions there where it's like, well, do they already know, is there already a pre negotiated deal?
[00:34:02] Is there transparency on price? Or do you kind of take that at the end and when, when do you start it? I think that's also pretty good to, to get a feel for.
[00:34:09] Chris: Yeah, I, I think this is where, like, you can see also the DNA of Slite, which is like a self serve company. So we are also learning more and more, like, you know, the sales land motion. But yes, to answer your question, the price is very transparent since the beginning. It's kind of the same when you hire, I don't know if you do that, but I like to be very upfront on, you know, the first interview, almost like the salary will be X, are you good with that just to, you know, get off the wave, like the expectation are completely misaligned and to not have like a necessary negotiation down the line, especially when we spend so much time with them.
[00:34:40] But then what happens usually is that we never on board, like at least so far, the entirety of the organization. And I think that speaks for us not being necessarily like a ultra sales driven organization. I think like that's my goal at the end of the year is to have like, you know, signing contract of like whatever, like thousand people up front.
[00:35:01] And have like, you know, like a continuous customer success program where we help them deploy rather than expand like progressively. But for now, like, you know, like, we basically sign, like, half of the organization and then, you know, of, you know, 200, 500 people, and then it grows naturally I mean, at least that's the, that's the code for this year.
[00:35:19] But yeah, like, it, it also makes sense, right? Like, and we don't really kind of, I mean, I'm not over focusing on this, like, like, the focus is really, like, building the right tools so that this motion can happen, like, ten times faster in six months.
[00:35:32] Mikkel: That's it. Awesome. It's, but it's super interesting. I think to just hear from someone operator, someone with feet on the ground how that's being run. I think there's so much happening in this space right now. It's kind of hard to keep up. The other day Toni and I were talking about the application layer was dead.
[00:35:47] All of a sudden deep seek arrives and then everything just changes. Right. But at the end of the day, you still need to bring it in the hands of users. And I think this was super interesting and I hope. The listeners out there who are going towards AI picked up a few things that's going to help them succeed better with that, bringing that offering to market.
[00:36:04] Toni: I think things I picked up just to maybe kind of, you know, sum it up from my perspective, I think there is there's a different buying behavior happening right now. And I think it's driven by, Hey, someone in the company tells you to kind of investigate this AI thing, but I also think it's driven by. Some fear and certainly doubt around, okay, this works really well in your demo. Is it going to work with my data? I think, I think there's some stuff around that and and really nailing that is really about, okay, prove it to me that it works on my data.
[00:36:33] Which is kind of near the approach from them. I think what you then also, in addition to that picked up from a selling motion is. Well, really what we need to achieve is a change of habit on the other side. So, you know, while, while the buyer thinks, oh, we just need to prove that I put in the, you know, a prompt and it gives me the right answer. Really what you as a seller need to prove is like, you know, is, is that really changing the habit of work for people?
[00:36:59] Because otherwise you won't be able to unlock this, the ROI calculation. That you
[00:37:03] need in order to close, you know, close this deal with sea level basically. Right. So there are a couple of different things here that are happening at the same time, which I think is super confusing for everyone out there.
[00:37:13] That's why everyone's like, this is that, this is that, this is that.
[00:37:16] But I think because so many changes are happening at the same time we also wanted to have Chrissy as, as kind of a founder CEO that. That see some of these, you know,
[00:37:24] tectonic plates shifting and kind of giving, giving the perspective.
[00:37:27] You know, I think if you're a VP marketing, if you VP sales, if you have revenue operations, like kind of listening to this, it's really being aware of those different trends that are, you know, overlapping at the same time. And if you, if you don't see the differences in those trends, then kind of everything is being modeled. But I think after this, this chat here, I think it even, even myself, I feel a bit more clear why some of that stuff is just. different than it was with SaaS. And, and if there's anything that I'm thinking, kind of adding some of my own perspective on this, I think we are in a technological shift. And there's lots of, you know, uncertainty because of that. I think some of that pain and changing and friction in this process, I think it will go away over the years, both because people's experiences changed and maybe I've bought a one or two AI products previously. Maybe there's some more infrastructure place that you just mentioned, Chris, in terms of like, Hey, maybe there's this one data provider that you plug in and get the data from there and then, okay, easy peasy. There might be a couple of things happening that make this smoother. But we're not there yet. So in order to kind of sell your AI stuff now, I think you need to just be aware and kind of navigate this in the, in the right way. I hope I kind of summed it up in, in,
[00:38:38] in a, in a proper way here, Chris, but thank you so much for having you here.
[00:38:42] Basically it's kind of spending, spending time with us. That's what I was trying to say.
[00:38:45] And Yeah, good luck with your, with your new product launch. Sounds really exciting.
[00:38:49] Chris: Yeah, thanks so much for having me, Tony. Thanks so much, Mikhail. It was great.
[00:38:53] Toni: Wonderful. Have a good one. Bye
[00:38:54] Bye.
[00:38:55] Chris: Bye.