Sheraz Bhatti: Land and Expand

In this episode of Selling Signals, we’re joined by Sheraz Bhatti, who led Customer Success at Similarweb and now does the same at Quartr.

We discuss what Customer Success means in a data business and why it differs from the standard SaaS playbook. Sheraz explains what good adoption looks like, why usage metrics can be misleading, and how data vendors can tell whether their product is making it into real investment decisions.

We also cover churn risk, internal champions and what “land and expand” looks like when the product being sold is data.

Transcript

SPEAKER_01 0:02

Welcome to Telling Signals, the podcast focused on how businesses actually monetize and sell data. Each episode, we interview an industry insider to hear their experiences and lessons learned. If you enjoyed the episode, please subscribe from wherever you get your podcast.

SPEAKER_02 0:22

Today we're joined by Theraz Badi, who led customer success at CinemaWeb and is now doing the same at Quarter. Shiraz has spent years helping data businesses drive adoption, retention, and expansion. So this should be a great one to unpack what good customer success really looks like in data. Shiraz, welcome to the podcast. Yeah, thanks for having me. Excited to be here and chat with you guys. Welcome. Yeah, absolutely. I I feel like listeners would be quite familiar with SimilarWeb, but maybe less so, of course. I'm a user of Quarter, so um definitely an advocate. But do you want to give a quick introduction to, I guess, both businesses, but maybe a little bit more of an emphasis on Quarter and what you want to truly there?

SPEAKER_03 0:59

Definitely. I uh for those that are familiar with SilmarWeb, right, they provide web and app data, analytics, and insights, and really empowering data buyers to make critical business decisions, right? Uh Silmaril Web's fantastic company and works across a variety of sectors, whether through uh finance and corporates uh as well as data partners. Uh and then Quarter is really interesting, right? They're what I like to say the intelligence layer that financial AI runs on. Uh the founders uh spent five years building something really specific and really focused around uh kind of the complete structured data set of public company IR data in the world, right? So similar web being kind of that third-party data provider. And then if you look at someone like Quarter, that's really that foundational piece of first-party IR material. Uh so we cover live historical earning calls, fester days, capital market days across 65 markets that includes audio, transcripts, slides, speaker ID, and extracted metrics. Uh, we cover over 230,000 earning calls, recordings, uh speaker diarized and timestamped. Uh Quarter started off as a uh free app. Uh the original positioning was Spotify for earnings and very quickly uh segued into a desktop app, which we call Quarter Pro, where anyone can go in, say an analyst or someone from the research team and start to build out watch lists of the sectors that they cover. Uh and then we started to roll out uh soon after that uh the data set. Uh so that's available through API and recently just launched an MCP through Cloud and actively working on kind of getting that rolled out.

SPEAKER_02 2:49

Interesting. So you guys were in, I like the the analogy of Spotify. So what was the in the original monetization strategy of on the consumer side? Or wasn't was there not one? It was monetize the the the desktop for for institutions.

SPEAKER_03 3:03

Yeah, uh the app was definitely something free, right? The the founders met on kind of finance Twitter, uh, and but you know, a few of them were on the buy side and traders, and it very quickly blossomed into this actually could become something much bigger. So the original monetization strategy was the desktop platform uh available through a subscription on a user-seed basis.

SPEAKER_01 3:26

And should should we think of that as uh in some ways competing with the fundamentals data products of a Bloomberg, a fact set, an SP global? Is that is that a fair characterization?

SPEAKER_03 3:38

Yeah, yeah. I I would say there's obviously differentiations. Uh, you know, Bloombergs and fact sets are behemoths and and very well implemented into you know most places uh where you know our focus has been really on kind of speed and quality of that first-party material. Uh, and then also providing it in a well-branded, well-executed UI that's super easy to use, right? That's some of the best feedback we get from our customers is, you know, starting with the app, it's really easy to use. It's really easy to kind of log in and listen to a live earnings call. Uh, and then the same goes for the platform as well.

SPEAKER_01 4:17

Yeah, because we in a sort of former iteration of Valsys, we actually built a system to do something probably nowhere near as we didn't get anywhere near as far as you've got at quarter, but we were going into 10K, 10Q filings, pulling out the fundamentals. And so I'm very familiar with just how painful it is trying to stitch together quarterly and annual data that changes in its structuring um even over you know the course of one year, let alone multiple years. And when you're servicing uh an industry like financial services and investment funds with where that has have the level of obsession with data quality that they do, it's a really hard problem to get right.

SPEAKER_03 5:00

Yeah, definitely. And I I would echo um Oscar Consul, our CEO, always says this, right? We are hyper-focused on doing this one thing really well. Uh well, you start to see, you know, maybe other providers start to, you know, I want to do a little bit of this, I want to get into this. And for us to really win and succeed at what we do, it really has to be obsessed with uh what we provide today, which is that first party IR material. Uh and with that obsession comes the quality and the speed and the optimizations that we're making in terms of adding new companies, adding new documents on a consistent basis.

SPEAKER_01 5:39

And just a final point on that, on the latency side, what are we talking here? Let's say you know, earnings call happens, results come out. How quickly in say the Quarter Pro desktop application or the API can I access the financial fundamentals that have just come out?

SPEAKER_03 5:58

Yeah, so for live earnings and transcripts, it's being done as the call is happening. Uh and what's really interesting about Quarter, and I love seeing this live, is as the the it's being transcribed, you can see the following paragraph that was just done being auto-corrected, right? So if the speaker was tagged incorrectly, it's being fixed. Uh, you know, if a number, a metric was like, you know, like sometimes it's just the language and the tone, uh, being able to do that. So that's being done on a fairly uh kind of incident basis. And then there's like SLAs based on specific document types. Uh, but typically, like if an 8K is released, like you'll see it, you know, several hours later. Uh so it is pretty quick in terms of getting those documents uploaded.

SPEAKER_02 6:44

Awesome. So I mean, you're head of customer success there at Quarter, you were director of customer success at SimilarWeb. Maybe a great place to start in this episode is gonna be about landing and expanding um across uh across clients. What does customer success mean to you in data?

SPEAKER_03 7:02

Yeah. Um, so when I first started working with this customer base uh at SimilarWeb, and this was like 2018, 2019, it was a foreign concept to the customers we worked with, right? I think if you think about um, you know, customer support was more the terminology that they were probably used to, and like the likes of like Bloomberg or account management, and even like product experts. Uh, so it did require a little bit more explaining in terms of what the purpose of the role and the function was. And the light bulb would go on. Uh, and you know it's funny because like we even played around with different titles. Like my original title when I joined was like implementation manager. We tried customer success, excuse me, customer success analysts and customer success engineers. Uh, but if we really kind of focus on what the core function of customer success is, it's really to drive value through product, data, industry expertise. Uh, and then it requires us to be more in tune with the fast moving nature of their business, right? If you're too slow to show that value, you will be forgotten. Uh, and I think, you know, if you look at like traditional SaaS, um it is a very sometimes checklist uh job. You know, did I do my monthly check-in, did I do my QBR, did I check their platform usage? Uh, and I think in the data business, you have to be much more aligned in terms of what are they expecting to achieve? You know, are they looking to get a specific signal? Are they looking to implement into financial models, whatever that might be? Uh, it's a very different value that you're driving for them.

SPEAKER_01 8:41

Given the a lot of feedback we get from data vendors is that often buy-side firms don't want them to know how they're using their data. And indeed, if they find an issue in their data and they fix it, they don't want to tell them because they want to be the only people that have fixed it. How do you go about then kind of squaring that circle of you want to understand what success means for them, but they're very reticent to tell you what that is?

SPEAKER_03 9:06

Yeah, I mean, that's always a challenge, uh, particularly when you're working maybe on like the systematic side, like they're definitely not going to share uh the end output, right? It's usually like data good, data bad, uh, and hey, it's good, right? And I think one of the things that I really um started to work with my team on, even myself, uh, and along with like our account management teams, was to, you know, one, get in front of them more. Uh, you know, being able to kind of just like have that in-person interaction uh where you can better understand, like, hey, what are the inputs that are going in? Like I was just in a client meeting uh earlier this week, and we were able to go on site with them and understand, like we got to walk through the trading floor and the systematic teams, and you know, like being able to say, like, hey, how impactful is this for you today? Right. And if they're able to say, hey, this is super impactful, or this is part of our day-to-day, that's like a win for us, right? And and if when in customer success, when we talk about like success plans or wins, that's something you can tie back when you're actually having maybe growth on growth conversations or renewal conversations with them.

SPEAKER_02 10:20

So it sounds like it's maybe a little bit easier for you to do your job with a fundamental investor because of how transparent, not how transparent, but at least it's much more commonly known the names that they're covering, it's a much narrower set of information that you can concentrate on. Whereas I guess sometimes it's even really difficult for a quantitative investor to even understand their tradable universe, let alone what they like or dislike about your data set.

SPEAKER_03 10:45

Yeah. Uh uh going back to the fundamental side, you know, knowing that we have, you know, they share their coverage list and in quarter you can upload your watch list. You know, we know when earnings is because we want to make sure prior to earnings that they're going in and they're getting the data points that they need based on prior performance. And then are they actually coming in and listening to that live call or transcript, right? Uh so having like that earnings calendar available, like we at least have some signals of, hey, are they actually using our data based on their coverage list? And then it's just a matter of like, hey, how well did that you know particular stock perform uh for their earnings?

SPEAKER_02 11:26

And is any sort of like in terms of being like proactive or reactive, uh you uh thinking about your day at your your your life at Quarter now versus similar web, I feel like uh the fundamental side is much more about maybe less so these days, but more like calling uh earnings and sort of front-running what maybe Quarter's about to publish at some like a similar web. But how proactive are you guys trying to be in that sort of customer success role?

SPEAKER_03 11:53

Yeah, so one of the things that we started to do uh at Similar Web was we started to do like these pre-earnings webinars. Uh so my customer success team would actually go in and share insights ahead of runnings, right? And like this was their idea. I'm not taking credit for it, like it's a fantastic idea, because they were getting a lot of demand from customers, you know, in preparation for you know, Netflix reporting earnings. What's the what are you seeing in the data, right? Like what's some helpful um, you know, metrics that we should be looking at? Uh and that kind of spiraled into a larger uh pre-earnings webinar that they were doing. Uh, from like a quarter perspective, I'm trying to bring that same energy of what are we doing ahead of that company reporting and what are like the the kind of leading activities that we could be doing, right? Sometimes it's just making sure uh and reminding them that we exist uh because they could be using multitude of data sets and they're caught up um you know in their day-to-days. How do we stay top of mind for them?

SPEAKER_02 13:00

And Vue, did that research function sit within your team? Like were you sure as you and your team doing the research, or was there an adjacent team that was doing the research and you were thinking about how to apply that to different customers?

SPEAKER_03 13:10

Yeah, it was it was a combination. And I think this this goes into like how you hire and build uh your customer success teams, because you could do it the traditional way where you find someone uh that's worked in SaaS and maybe worked in like a similar field, uh, and they know how to do kind of the day-to-day function, which is fantastic. Or you actually even think about hiring people that used to be in those roles. Uh, so I was fortunate enough uh at SimilarWeb and even now at Quarter, where equity research folks are really good hires for this role because they can actually go really deep into a particular name. They know the research process and it brings credibility to the role uh when we are introducing our customers and saying, hey, so-and-so is your customer success manager. They spent X amount of years at this Southside shop, right? So, like the relief from the client perspective is okay, this person understands, you know, what I'm looking for. I don't need to sit there and explain to them my workflow. Um, and they can instantly help me. Uh, and then so from that perspective, like they were already doing the research. And part of, you know, the value of like SummerWeb is a pretty massive data set, you know, having someone that can actually translate those insights for them. And obviously they work with like the product teams and like solution teams. Uh, but at the end of the day, like the customer says, Hey, you're the person I need to be talking to on a daily basis, therefore, I require or expect you to, you know, be sharing insights with me as well. So there's a lot of insights being shared, yeah.

SPEAKER_02 14:44

It's almost like um a proxy solutions engineer if you think more about the SaaS context, where you're trying to create a peer-to-peer conversation. And I think in this instance, especially in the investor world where they are quite well, time's a premium for one, but also they're not the most forthcoming, especially as you sort of start going to more the quantitative strategies. And that peer-to-peer conversation definitely enables them to open up, or at least, yeah, it seems like there is more transparency when they feel comfortable that there's something to learn, maybe.

SPEAKER_03 15:16

Yeah. Um, and and part of that is I I at some point I did manage solution engineers. Uh, so I I had that mindset already of how I wanted to build that team. And then even that quarter, right? We I have former equity sales, former equity research, uh, and it's actually translating really well in those customer conversations because it's it's not only just the product and what did I buy, but what can I do with it, right? What's that uh in-depth layer? Uh so like a good example is if we're working with a large sell side shop and there's about 30 analysts in different sector teams, you can't just do a one-size-fits-all, you know, training session with them or a workshop with them on site. You really need to understand the nuances of, you know, industrials in Scandinavia. How do they look at stocks versus someone that covers consumer?

SPEAKER_01 16:13

You mentioned um hiring um sell-side, former sell-side research analysts into customer success roles. That's obviously more on the fundamental side, but you mentioned obviously that on the systematic side, they tend to be uh more um maybe cloak and dagger's a bit extreme, but that they're certainly uh less, they're more reticent to tell you what they're actually doing with the data. Have you considered doing a similar thing and finding a former quant and bringing them onto the customer success side?

SPEAKER_03 16:43

In an ideal world, I would love that. Um, knowing someone that's kind of been in that role. Uh so even someone that maybe was uh on the data science team or data analyst or a quant analyst, like working my way to that uh equarter. I think that's going to be super valuable for us because that having uh that not only that technical knowledge, but then how does it couple with you know the actual practical application of it? Right. If they understand model creation and signal generation and sharp ratios and and uh you know all those kind of like key terminology of understanding what goes into it, I think it will be super valuable.

SPEAKER_02 17:22

There's the obviously cost element of hiring uh people in those roles. And I I asked this question quite a lot on the podcast, but actually in our research session, I thought you had a really interesting answer. But yeah, how did you manage the I assume similar where maybe they were and uh paying sort of by-side salaries, but um, how did you manage that conversation?

SPEAKER_03 17:41

Yeah, I think part of it is finding them at the right point in their career where they might be looking to make a pretty big shift in terms of their career trajectory. Uh so I had someone on my team um who just needed a change, right? Like particularly on the sales side, you're working a crazy amount of hours, particularly around earnings. Uh, you don't have a life, right? You're working weekends, and and for this particular person, they wanted almost like a reset, right? And part of that reset also comes with, you know, what's in it for them, which is now they get to develop more customer-facing skills. They get to polish and develop um, you know, commercial skills, you know, talking about contracts and and uh positioning a product that could actually increase how much they spend with us. Uh, and that that particular person, I think she spent well, like three years with me and now works in private equity, right? Like it's really cool to kind of see someone come in, you develop them and and make them much more well-rounded, and then you know, send them off because you can't keep everyone uh forever. Um, and I think that's super important too, right? And there's someone that I'm bringing on uh at quarter, and very similar thing, you know, this person wants to develop more of that kind of outward-facing skills. And being an equity research analyst, you know, you're you're you're taking orders, you're conducting the research, but you're not necessarily, especially in a bigger shop, the the growth opportunities might be limited. Where if you take a sidestep, there's a lot more opportunities on the data side of things.

SPEAKER_02 19:23

Yeah, so you say it's more of a career projectory, sort of rounding out people's maybe soft skills.

SPEAKER_00 19:29

Yep.

SPEAKER_02 19:30

Yeah, I mean, it's really smart, right? If you can find the right candidates, you can take advantage of the skills that they had previously and impart on them skills that that you know sets them up, as you say, to go on to maybe the next step in their career that that makes sense. For the um for the rest of the podcast then, um, for this episode, maybe to lay out for listeners, uh in our sort of pre-recording session, we discussed maybe three points of customer su uh customer success. Uh and that was adoption, uh retention, uh, and expansion. So maybe let's talk through those. So if we start with with adoption, um, so you've signed signed a new customer, maybe easy for now to be fundamental rather than quantitative given the the more transparency there. But what does good adoption actually look like for you in your role?

SPEAKER_03 20:13

Yeah, so I think one is there's a couple things I would look at in terms of adoption. One is how quickly are they utilizing the data, right? So if it's a you know pro customer, how often are they logging in? You know, have they customized their instance of the platform? Because that's a good indicator that they're investing time into getting the output that they want. Um and the other component of it is are they actually actively speaking to us during that timeline, right? So usually like the first 30 to 90 days are most critical uh because if you can't ramp them up in the first 90 days, this poses potential risk, which we'll talk a little bit more about on the retention side. Uh, but that's where like they are actively reaching out, we're connecting with them, we're doing individualized sessions, we're doing a larger group session, uh, and then making sure, like, hey, have you been utilizing this in your day-to-day? Um, and then there's like other indicators you can look at, things like MPS, if there are you know too many like questions around you know data and validation, like maybe they just didn't get it. Um, and that could be a potential risk because if they're asking all these like uh clarifying questions, one, they're not paying attention, two, they don't get it, three, they're probably not seeing the value limit.

SPEAKER_02 21:31

And I I have some uh maybe some explicit questions about this. Yeah, it is my day job, uh I guess is selling into these people. And I I find it really difficult sometimes to um you sign the contract, great, everyone's happy, and you're working with a data scientist or um you know someone on the fundamentals team that's dealing with the data. But one, you're not the only vendor that they're working with. Two, they're very, very busy people. Do you like contractually make it that they have to sort of join these sessions? Uh Uh like these uh kickoff sessions. How do you structure it that make sure that these people show up, that they engage? How does that actually work?

SPEAKER_03 22:08

Yeah, so this actually starts in our sales process. We run a really rigid, uh, I'm gonna say rigid, but a really thorough sales process. Our sales team does a really good job. And during that process, there's a mid-trial check-in. And in that mid-trial check-in, my team's actually joining that call to reinforce that hey, once we're through this trial and you sign, you'll be working with me. Here's how we're gonna work together. You know, we're going to be doing a kickoff call where we align on goals and expectations. I want to make sure that we meet. Two, there's going to be onboarding sessions. This is what I recommend. Uh, so a good example is like if we're working with um, you know, we brought on a pretty big Southside shop. During that mid-trial check-in, it was super important that we articulated what is the timeline. You know, just 30 days, 60 days, 90 days. Who are the people that are going to be users? It's usually the trial users. Um, sometimes we end up adding more. And then from that trial check-in, they now get to meet the person that's going to be working with them. So we actually have a higher uh rate in terms of people joining that kickoff call and the training sessions. If we're not included in that mid-trial check-in, it's a lot harder uh because you're chasing them down. And I've seen this in the past where they say, no, we don't need onboarding. We'll reach out when we need you. Uh and I think I've always had a tough time with that, uh, because it's like you'll need me. I know you'll need me because you're gonna have a million questions. I'd rather just front load the questions today. Uh, so this particular cell side shop, um, I think it was like, you know, 20 or 30 users. We need to have a thorough plan. Otherwise, not everyone's gonna be able to um to be able to join these sessions. Um and to your point of like, yes, they are using other tools. We try to find out what their tool stack is. Like sometimes they don't share. You know, you can assume, like, okay, like everyone uses Bloomberg. You know, how often are you using Bloomberg? You know, if we replaced another data provider, that's always helpful to know. Uh, because we understand, like, okay, their customer success function might be very product expert focused, or you have to rely on a support chat. Uh, so they're gonna be a little bit more passive. And our differentiator is like we're gonna be more proactive with it.

SPEAKER_02 24:30

I like that because it sounds like you're setting the expectation throughout the new business sales process that we're here, we're going to be here, and we're going to have these sessions. And it kind of reinforces that rather than deals closed, everyone's kind of somewhat figured out, and these new people have come along and started requesting meetings. It's kind of like in their head, that's already the natural next step. Maybe it's already in the calendar pre-signing contract, etc. Um, that's a really awesome way to use that.

SPEAKER_01 24:59

When you um when you are displacing an another data provider, do you find that there are kind of a a spectrum of migration issues that that um they can face? Let's say from they've got a plug-in in their Excel models and to move from provider X to quarter, they need to replace all of that. And is that a thing that your team would assist with?

SPEAKER_03 25:20

Yeah. So there's one clear example. We brought on this research firm uh a couple months ago, and one of the I joined the mid-trial check-in too, uh, because it was like super, we were replacing another provider, and it was very clear to them, the main decision maker, that we need to we have until April to uh our contract with that other provider is up in April. We're gonna start ramping you up now. There's three or four people that are power use of users of it. You need to convert them, right? You need to like really replace that with them. So we actually got now is uh a good example of like having a really good champion or decision maker that understands the value of it, but needs us to work with him on you know, kind of offboarding that other uh provider.

SPEAKER_02 26:13

Interesting. So it's like bringing custom success before they're even a customer, I guess.

SPEAKER_03 26:18

Yeah. So even at SimilarWeb, that was a really good uh tool for us where you know, if like a deal was like um stalling or you know, we were having a tough time in terms of like just progressing it along or like legal was taking too long, is let's introduce the team much sooner. Like we didn't do it every time. I w I wish we had a a much more uh kind of baked out process with that, but it made it made a difference because it's like, hey, not only are you buying this data set, you're getting a certain level of expertise, right? Or you're getting like one of our top CSMs that come with this.

SPEAKER_02 26:54

And one of the so uh working at bigger companies, especially someone like a similar web, people are obviously quite verticalized, regionalized. Uh there's very predetermined compensation structure. Was the compensation structure set up in a way where customer success was encouraged to get involved in a sales cycle? Naturally, new business reps would be the ones that would be compensated for that. But it's typically the renewals and the retention rates that trigger um the compensation bonuses, commissions, et cetera, for um post-sale support, et cetera.

SPEAKER_03 27:31

Yeah, I I I wouldn't say like a monetary incentive, but a thinking longer-term uh incentive, right? So if I'm looped in, if I'm a CSM on my team, I am very much incentivized to be introduced sooner to ensure that the adoption happens quicker. Uh, and then I'm not going to be dealing with the lagging effect of a potential churn risk, right? If I wasn't looped in or like the sales cycle was too quick, we didn't do the proper, you know, kind of sales process. Like for them, it's like a, and for me too, it's a it's a flag because we actually haven't one developed the relationship, we haven't understood, you know, what they're trying to achieve, uh, we haven't met the right people. Uh, and that ends up being a potential risk. Like all the ones where I saw where it was like a fast moving sales cycle, you know, like one person's managing it, no one's been really looped in. Um, client doesn't respond to any of the emails, they don't uh, you know, see the value of getting onboarded, whatever it might be. And like three months in, you know that client's gonna turn. Right. And now you're flying fighting this uphill battle trying to save them.

SPEAKER_02 28:42

One of the things I want to talk about before we move on from adoption uh was your point around uh usage. Um I thought it was really interesting that typically in SaaS, I think you're looking for consistent usage throughout. Whereas, especially when we're talking about fundamental users, there's kind of picks and troughs in and around earning seasons for the maybe the tickets that you like, which I thought was a bit counterintuitive. But um maybe talk me through how you would set that up, what you're looking for explicitly there.

SPEAKER_03 29:10

Yeah, I think you know, usage around um, you know, kind of coverage based on earnings. Like you obviously for me, I would want to see a uh an increase pre-earnings, right? That means they're coming in, they're doing their research, they're looking at, you know, prior filings, prior earnings data, and they're starting to kind of formulate, you know, their investment thesis. Like that's why I always say hoarders kind of like that foundational layer uh within their research, and then how else are they gonna build on top of it? And then during earnings, what we really want to look for is are they going in and listening to those live earnings calls? Right? Are they listening to the live transcripts? Because that's incident, right? That's at the moment. You know, I don't want them going and and and and listening elsewhere, I want them listening here, and then obviously a little bit of a decrease post-earnings. Um, however, you know, quarter is not meant to be this massive like spend a ton of time here. It's supposed to speed up the research process, right? So time within the platform uh isn't you know the best indicator. It should be like quality of time, right? And thinking about how much uh time we're saving from uh the analysts' day to day, right? If they're spending too much time, like they're probably getting lost. Uh, they're not finding what they need or they've left it locked in, like whatever it could be. Uh so that could be like a misleading um indicator. Interesting.

SPEAKER_02 30:39

So it's almost like a sweet spot.

SPEAKER_01 30:40

Yeah. Is it that is it really hard then to assess usage for a like a quant a quantum fund? Because I mean, I guess you could look at like API calls and things like that, but I imagine those can be misleading as well.

SPEAKER_03 30:53

Yeah, so a really good thing to look at is not just consumption of the data, right? And looking at like data credit or you know, how many polls are they making, but what metrics are they pulling in the most, right? So if they're just pulling in like top line metrics, is that impactful enough for them to be you know utilizing in their like their models, for example, right? Or are they actually going deep and actually looking at um kind of more nuanced metrics that actually can help identify different signals based on like the sector they're looking at, right? So for example, if it's like similar web data and it's a consumer company, you know, looking at top-line traffic, cool, right? Like it's you know, traffic's going, but you could be looking at additional metrics like conversions, for example, right? And that's probably a stronger signal. Uh, on from the quarter perspective, it's like beyond transcripts, or you're also looking at slides because there's data extraction that you can get from there.

SPEAKER_02 31:56

That makes a lot of sense. When you start looking at the really massive funds and they've got, yeah, I mean, it's engineering teams essentially pulling in everything and storing it and prepping it ready for use by whatever teams are then using it internally. Does that just become impossible to measure that way?

SPEAKER_03 32:12

Yeah, it does. It's it's really hard to gauge because you mentioned before there's that bit of black box of like what's happening with this data once they have it. Uh, and I've I've run into a scenario before where like the consumption was super, super high, but then the client's not responsive, they're not uh kind of sharing how they're they're using it, and like you know, they can always use like we're building something proprietary, we don't share it. Uh so it makes it really hard to understand like, are they getting the value out of?

SPEAKER_02 32:42

Yeah, maybe this takes us quite nicely into the retention part. So, like, what are the moan moan? What are the main drivers of of churn? Not the moan drivers of churn.

SPEAKER_01 32:52

I suppose moans do drive churn. Yeah, they do.

SPEAKER_03 32:55

Main drivers of churn uh definitely come down to a few things. And I've done a bunch of analysis on this, uh, past and present. It's usually loss of stakeholder or champion, meaning the main person that bought uh the data is no longer at the firm. And as you can imagine, like people change jobs, they're not going to be there forever. And that one person was the one that really advocated for it, and we've no longer have additional advocates strong enough. Uh, data needs shifting or consolidation, right? I think like budgetary constraints or you know, strategy change. We're like, hey, we actually don't feel the need to have this, and we've been going through our budgets, and like this is something that's you know not worth having on our books. Um, and then just even like budget constraints due to company performance or like macro conditions, right? Like they don't I've had a client share with me recently, you know, like, hey, funds not doing well. I'm gonna be honest with you, right? Like, we obviously need to tighten things up. Uh, and I'd rather hear it, right? Like sometimes they just completely ghost you, and then you find out the main person that you were dealing with doesn't work there anymore.

SPEAKER_02 34:05

I mean, uh I guess you can't go in and help them perform better, but the things like um sort of loss of champion, changes in budget, changes in strategy, how do you mitigate for that? You know, uh yeah, what what are your strategies to be able to control some of the uncontrollables?

SPEAKER_03 34:23

So one of the things is like uh a single user or a single stakeholder, typically when it is being sold in the sales cycle, like that's a flag of hey, is this a land and expand move? And we're just gonna start with this one person, uh, or is it the fund is so small that it's really just like one analyst we can work with? Uh, and then for me, it's like a flag already of okay, this is might be a riskier account. So, how do we deploy you know my team effectively on that? Now, if it's a small team and like it's gonna be three analysts, um do I want my team to be spending so much time on that account versus like they should be spending it on like a 50 user account? Um, the other, the other component too is if we've gotten in the door with one person on that kickoff call or on that initial conversation, hey, who else do you interact with? Right. And really thinking about like their org. And maybe there are other departments, and how do we turn them into advocates to actually introduce us to other people on different teams? Right. And that is kind of goes in more to like the expansion side. Um one of the things that we did at SimilarWeb, and and this was not my idea, I'm not gonna take credit for it. One of the sales leaders brought this in, which is this concept of having basically three different contacts at three different layers. So one would be like the analyst level, one would be like, you know, say the head of research level, and if you're lucky, uh, you know, a PM or a CIO, right? Because if you're actively talking to them, and it doesn't need to be on a consistent basis, it could be monthly or quarterly, or you always copy them on email communication. That one champion power user leaves, you still have a relationship with someone at the other two layers, right? And so that actually helps mitigate risk because you can easily go to that next person. That's quite a nice structure, actually. I quite like that.

SPEAKER_01 36:21

Yeah, I was actually gonna ask how you have that con what do you what do you ask? You did you just say, is there anyone else I should be speaking to? And how comfortable do you find people are with introducing you to kind of their colleagues, particularly if they're more senior, etc.?

SPEAKER_03 36:36

Yeah, so it it goes back to my job, my team doing their job, right? Right. If they are demonstrating value and and they're making impact in terms of like getting them set up, they're always responsive, they're helpful, you know. Maybe they actually met them on site for the call. Um, it's a it's a much easier ask to be like, hey, we're trying to get in front of you know this particular sector team. Do you mind just sending an intro? Uh and and more more often or not, like I think we've had this recently, um, where I asked for a reference. Uh I was like, hey, we're we're only working with you. Can you do you mind just sending me an email? Uh and even just sending that person's name, like, can you intro me to them? Um, it actually goes a long way. So they have to be like an advocate uh before you ask. Yeah.

SPEAKER_02 37:24

Yeah, that that's fair. Yeah. I guess that makes sense when you're sort of expanding wider. Is there some I guess it comes from the expectation of the new business sales cycle to sort of start at the higher power levels and work your way down? Does that make your life easier as customer success if they've already got engagement from those tiers? And is that being driven into the new business org so it makes customer success easier in its nice sort of self-efficating cycle?

SPEAKER_03 37:48

Yeah, definitely. So like in our sales process, right, like one of the key drivers is do we have a confirmed champion? Um, you can't progress the deal further until you have someone. Uh, and having that confirmed champion and then also just knowing their role. You know, are they just uh you know a singular analyst and they're you know be able to get uh budget approved for just themselves, or is it they're getting approval from someone else?

SPEAKER_02 38:16

Awesome. Maybe conscious time this let's move on to expansion. Um I think people talk a lot about land and expanding all the time, but what does that actually mean to you? And uh yeah, what does that mean in practice, I guess?

SPEAKER_03 38:29

Yeah, in practice, I um it is we've gotten our foot in the door, right? So if it's a say it's one of the large banks and we're trying to get in with the Southside shop, what is our entry point? And is that the right entry point? And by right entry point, do I mean is this person going to have enough influence, or as you mentioned before, um, you know, the ability to actually refer us to other people. Now that entry point could be, you know, a singular analyst that covers TMT, right? And they're super excited about it. They downloaded the free app, uh, you know, they got a single subscription. They're already, I would say, an advocate if they, you know, were like our app user, uh, because a lot of uh the the customers that we bring on are that's how they find out about us. Um, and then as we go through the legal process or if it's fairly quick, who's the person signing the contract? And then actively having those discussions with that person saying, hey, by the way, if we bring in more teams, you know, we can be flexible in terms of pricing. We can think about a potential enterprise agreement, right? Now, like a larger agreement like that doesn't happen overnight, right? It requires kind of brick by brick, laying the foundation of user by user, where you get enough attract uh um you know attention of the right people. Uh so a good example is like if you're going after, say, like a multi-strat fund, you know, you can start off by going into a specific pod, you go pod by pod um and kind of find the analysts and get enough traction with them. And then simultaneously, how can you get in front of say the market data people or the data sourcing people, right? Uh, because you ultimately want to make their life easy when you don't want to have like, you know, five or six contracts renewing at different times and they're having to deal with the the paperwork of it, right? How can we start thinking about uh a centralized view? And even with that, it takes a little bit of time. Uh, but in terms of just like land and expand could mean a lot of things, you know, it's just knowing what the universe is of the potential users you can get to. Uh, and that requires a little bit more uh strategy and account planning and kind of sizing the org and understanding where where certain departments sit. And that's a function of not only CS, but also like the sales org and like the sales development teams. We almost have to work as our own internal pod to think about how do we actually grow an account like Bank of America or JP Morgan, where they do have massive um, you know, uh self-ide teams.

SPEAKER_02 41:18

You um you touched on something quite interesting. There's a lot of conversation, at least especially when I was at New Data as well, about how vendors can better engage with both the end user, and we've spoken a lot about analysts and quants, um, but also the data sourcing teams in a new business sales cycle. Um, how does that look when you're already a client and you're trying to expand? Do you feel that there's friction between data sourcing teams trying to sort of um own that relationship and protect their end users as is their job? Um, or do you find it's actually much easier once you're in the door to then build relationships with many more people?

SPEAKER_03 41:55

Yeah, so I've experienced both. I've I've seen it where they tend to be the blocker, right? They're the roadblock, they're scrutinizing every single vendor that's coming in and putting yourselves in their shoes. Like, think about how many vendors are reaching out to them on a day-to-day basis, right? You know, requesting to get their foot in the door. So, you know, being able to position yourself in a way where um you are a value driver and focusing on their pain points. So I mentioned before, if you're starting to get traction with a bunch of different users, leverage that to get in front of them and say, hey, we have a lot of you know, your teams reaching out to us directly. Should we just go through you? Versus like, do we want to just work through them? Right. And it almost like helps them um, you know, validates that, like, hey, I should be coming to you. Um, and then they start to open up and it takes a little bit of time. And then there's times where like you have to go through them, right? You're doing contract, uh like a renewal negotiation where you know, recently I was dealing with it, which I was just interacting with the vendor management person, you know. And she actually told me she's like, you should loop me in much sooner. Um, so now you know, we have this like learning that not only should we be engaging with you know the analysts or the PMs or whoever else, but also kind of keep the vendor management data source and team close, uh, even if it's on copy, so they know how the the conversation is progressing along. And then the other thing I would add, oh good, sorry.

SPEAKER_01 43:30

I I was just gonna ask, you mentioned earlier um how you obviously keep the analysts, the PMs on side, think about how they're gonna utilize the data, get in front of earnings, that kind of stuff. What are the equivalents with a data sourcing team? Like how do you make their lives as easy as possible? You mentioned you know not having six separate contracts, etc. Is it stuff like that that just makes you them almost an internal champion for you because you're so easy to work with?

SPEAKER_03 43:54

Yeah, I think it's like uh kind of centralizing like the agreements and making sure you know that we're not. Dealing with like multiple different contracts. Uh, two, it's also like empowering them. You know, we're we're we're doing a trial right now where I want them to get trial access too. Um, because then if they understand the value proposition that we provide and they get requests internally, they can say, oh, top of mind, Quarter does this really well. You know, I actually used it. Um, so they think they I think that's a really big thing. Uh and then the other component too is like as you're in the customer success function, you should be collecting wins, you should be collecting feedback. Uh, you know, we collect MPS, all those positive things that come in, being able to even just drop that in an email uh or you know, uh getting on a call with them, being like, hey, by the way, we've been actually getting really good feedback from the analyst. Are you hearing the same? Um, and then it further validates like, okay, like there's value here. I need to make sure, you know, that I keep um this company in mind.

SPEAKER_02 44:58

That MPS scoring, how are you surfacing that to them? Are you just sending them an email with a link to to respond? Is there a pop-up in uh in the desktop app?

SPEAKER_03 45:08

Yeah, it's in platform. Uh so it's done on certain cadences. Uh, can't remember when, uh, but it's like key trigger points based on the customer lifecycle. Uh, and that's a really, you know, uh I never used to think how important MPS was as a consumer. You know, I just got off a flight yesterday and I immediately got an MPS survey from Delta Airlines, right? Like you don't think about it, but then what you can surface from that in terms of like advocates or detractors, it influences product, it influences you know your data strategy, but then also validates is my team doing the best that they can be doing, right? Are they actually staying top of mind? And having that higher MPS score or validation also helps in terms of our differentiation.

SPEAKER_02 45:55

So And how does that so that obviously make sense if they're using a UI, but if they're just pulling in the data through an API or S3 or another mechanism, how are you surfacing that?

SPEAKER_03 46:05

Email, yeah. It would be like doing email communication.

SPEAKER_02 46:09

Awesome. Understood. Um, questions of time, maybe one question to to end it. Um you've now been at a couple of vendors and sort of built out this function quite successfully. So where do you find vendors are going really wrong with customer success that they should really think about changing?

SPEAKER_03 46:25

Um, I think where where they could be going wrong is not treating it as this um support function, right? Which we tend to be seen as uh in in a lot of cases because of sometimes there's a reactive nature, right? Client has questions, they reach out, we answer question, and and then we kind of just carry on with our days, right? And I think where we could be really improving is actually almost like having a seat at the table and being more proactive, like surfacing things to them before they're thinking about it. Um, so for example, like I had mentioned, like pre-earnings, what could we be doing to surface insights to them leading up to it? Because they're already thinking about this and they're probably more receptive. Uh, and then what's the communication channels we should be using? Like, I was with a client uh this week and he's like, I have so many things in my inbox. Like if you email me, I'm not gonna, I'm gonna miss it. And so luckily I was in person with him. I said, okay, can we just set up a quarterly call, 30 minutes? Let's talk about product, let's talk about roadmap, let's talk about cool things we're doing, but also I want to hear what's going on with you. And his immediate answer was yes. You know, that'd be much easier. Right. And I I think sometimes we're afraid to ask for things like a phone call, an in-person meeting, uh, you know, a recurring invite. And I think we tend to just like be reactive. So I think we could, as an industry, just do a lot better with that.

SPEAKER_02 47:54

Yeah, I agree. I we we um we interviewed uh Florence, who's a CRO at General Index earlier today. Um, and she was talking about the idea of roles becoming more proactive towards the revenue function. So even like RevOps getting much, much closer to the SDR function as we think about automation of outbound and um creating intent signals for for sales reps. But I think that's exactly right. There's more sort of what you would historically think on SAT as a supporting role in data, becoming very, very proactive. Um, even product getting much, much closer to customers and understanding the usage uh of data and being quite sophisticated. But yeah, I think that's uh a great answer. Awesome. I I think we're at time. I really appreciate you uh joining us. Um it's been great having you.

SPEAKER_01 48:42

Yeah, thank you so much, Shiraz. It's been great having you on. Yeah. Thank you.