Menu
Go back to DataExchange

Meet the vendor:

DemandMatrix

Engaging in meaningful conversations and successful account-based marketing strategies begins with the right data. In Episode 1 of Talk Data to Me – The DataExchange Experience, Asher Mathew, VP, Revenue and Operations at DemandMatrix, takes us through the differences between front-end and back-end technographics, and the all-too-often missed buying signals that back-end technographics provide.

Ep01: DemandMatrix[Full Episode]

With more than 14,000 technologies being tracked, DemandMatrix offers comprehensive front- and back-end technographics, giving businesses a complete picture of what hardware and software products are used within organizations, and what purchases are next in line.

View the Transcript

John Kosturos:
All right, Asher, well, welcome to the talk data series, um, with RingLead. We’re excited to have you here today and to get the chance to interview you and just kind of educate the market and the, the RingLead family on, on what you guys really do well and who you serve. And so really when I want to start out with is a little background on yourself and then, uh, we’ll start out with some background on the company demand matrix as well.

Asher Mathews:
Terrific. Thanks John. And thanks for having me on. Hi everybody. This is Asher and uh, I’ve been in the tech space now for over 15 years and the last, uh, three and a half, uh, I’ve been in sales and MarTech, loved the space, loves, uh, helping sales and marketing folks, uh, get, do better in their roles. Uh, you don’t hit their numbers, get all those trophies, go on those really expensive trips, uh, love all of that. And so, uh, what I enjoyed the mountain Beatrix, uh, because demand mind matrix is a data company and what we are doing is we are on emission define the highest propensity to buy accounts. And so that’s our banner. That’s our flag. That’s, that’s the world that we want to live in. And so, uh, so, so what we’ve done over the last four years, the company has been in existence is just to get an under a deep understanding of what data is really beneficial for technology companies or technology sellers and marketers.

Asher Mathews:

Could you describe the limitations of front-end technographics, and describe the additional value of backend technographics to drive target account strategies?

And what we found that technographic data, uh, specifically the front end, the backend tech stack, the other signals that that data can bring to you is really important information. Because ultimately today everybody wants to have a meaningful conversation. But how do you have that meaningful conversation? Well, you need to have some information and a, and then anybody and everybody can find the revenue, uh, size data, the employee size data, the industry, you know, like the list goes on and on and on. So there’s two cases of data now that are helping sales folks and marketing folks. It’s technographic data and uh, and actually the advanced signals and the technographic data. Because I believe today you can get front end technology data anywhere. And so the couple of things that we’ve done is really honed in in the advanced signals when it comes to technographic data.

Asher Mathews:
And those are skillsets we can find and uh, and tell you exactly how the skill sets of a given company are trending, whether they’re increasing capacity for a certain skill set or decreasing capacity for a certain skillset. Uh, we have information about projects, we have information about certifications, we have information about their cloud maturity. So again, all of the data that, all of the information that can be derived from this dataset that is focused on the technology infrastructure, why would we do that is because as a data company, we want to know why companies will buy it. [inaudible] so all of the intended the marketplace today, and what it does is it tells you when they would buy it because it’s all predicated on somebody searched for a keyword, somebody went and landed on a landing page, somebody subscribed to an email, a newsletter. The big piece of this where we believe things are going is the why.

Asher Mathews:
And we drive the why from a capabilities perspective. And so when you look at technographic data and you really understand the tech stack, the skillsets, the projects, the certifications, the ISV or SSI landscape, you know, you now are thinking about a prospect’s business almost by being in their shoes. And that amount of context allows you to say, will this company be successful when they buy my product? And if they are your renewals talk to be a problem. And so hence we derive the why would you buy from us versus the winter you would buy it from us. And so that is also one of the signals that we have. Um, today that’s a very unique, I think it’s a really cool idea. You know, I’ve got my mind kind of already thinking about how, how we could utilize some data like that, you know, to, to better target accounts that have no, I think it sounds like front end technographics would be, they use a certain set of technologies and backend technographics would be more about now how many certified experts do they have, what size are they using, what projects are they working on?

John:
Um, and I think that’s wildly important for when you’re putting together a always changing set of target accounts for, you know, an ABM or, or just a general campaign. Mmm.

I want to ask you a question about that. Do you recommend for new customers that they map the tech stack and the front and the backend of the techno graphics for customers first? Or do you typically see this being like a targeting for net new buyers? Because I’m thinking how I’d like to get a better understanding of my customers. Right. And this could be a really great way to do that. Yeah.

—-
Should I purchase technographic data on my customers, before investing in the whitespace — buying targeted account list with

So, um, believe it or not, in really large companies who we serve really well, there is all kinds of data available. And uh, and I was at a pretty good company as well before,
but the problem was like, how do I get all of this data to make, to stitch together so that I can make use of it?

Right? So, I mean, if you look at data as internal data and external data, and a lot of times the, our customers are asking us for external data, which validates their internal data. So, so this is also another pain point of companies were getting access to the right information is really, really hard. And when you’re in a time crunch, it’s good to validate externally how the internal account data is working. And so we do find a lot of customers asking us for data on their own customers just so that they can validate that the software, even though it exists, is it actually been used because you can always say, Hey, my subscription is active, so great. Like this person’s sort of be there. And there’s sometimes you started there and, and uh, and uh, and, and we can okay content as an active customer, but is it actually being used? Right. And so, so the only way you can find that information is, will, is it used in projects? Is it used in sort of, are people certified on it? Right. Those are the signals that allow you to learn if it’s an actively used technology or worse that if it’s about to be churned because if the skill set for that specific technology is being moved out of a company, chances are gotcha. Technology is not going to be there.

John Kostouros:
[inaudible] all right. Um,

Asher Mathews:
so

John Kostouros:
yeah, I get some pretty generic questions. I want to ask you and we’ll probably cut this moment out, but um, this next question is what are the main problems that you help your customers solve?

John Kostouros:
Yeah. So, uh, there are the age old problems that is just a better way of solving them, right? Like, Oh, the big thing is account discovery. Like even though you may have a million accounts in your database, like which ones are actually relevant. And so, um, so we can help with like account prioritization, right? Or even though you have a million accounts in your database, your who you serve make me change. So you need to go find out who are the right, the accounts that you want to go serve. So account discovery, account prioritization. Uh, in some cases we help with Tam analysis and stuff. But from a pure day to day perspective, we have the common discovery account. Prioritization are the two big ones. And then there’s some advanced signals in that, right? Like, because I kind of privatization affiliates, it’s like a bucket that’s like intent, right?

Asher Mathews:
And a, and then there’s like different types of account prioritization that is happening. It’s, it’s a, can I go, uh, are our people up for renewal our people up for our people, uh, people’s cloud maturity high enough so we can go sell them new solutions, right? So those buckets are the projects that we sign up for. And uh, and that’s how we like optimize our data. So the one thing to remember about demand matrix, cause we’re all about quality. We not do quantity and we also do not go, uh, by data from other companies and, uh, and produce our technographic data. And, uh, and, and we own that into our pipeline. And what that helps us to do is focus on quantity. And then that quantity allows us to further optimize the data for specific themes. So cloud would be a theme. IOT could be a theme, storage could be a theme. Gaming could be a theme. High performance computing could be a theme. You know, like all of these teams matter and uh, and they matter because marketers are using themes for their campaigns as well. And so those teams, whether people want to move the from one cloud provider to another cloud provider, right? Um, hello marketers further, uh, they’re uh, campaign goals and that’s how they make their number.

John Kostouros:
Sounds great. I, you know, again, it’s for me it’s very relevant. Um, you know, I, again, I, my mind keeps going back to, I would love to know all of these things you’re talking about about my existing customers so that I could then create profiles for my best customers that maybe have signals in the, you know, the what projects they have or, or how many certified experts or when their Marketo renewal is or you know, there’s so many different variables that could help me kind of zero in on where now, what is the cause? Cause it’s always easy to widdle down to like a thousand or 5,000 target accounts. Um, but if you want to get that down to a hundred or 200, you know, what are the, we know the techno graphics and we know that business size and verticals. Now what are the, the, the buying signals, right? That we can derive from a third party data provider from like yourself. So, um, that’s a pretty powerful functionality. I want to ask you, are there specific verticals that you guys are focused on serving?

Asher Mathews:
Yeah, so today we are doing Telekom, uh, technology. Of course we’re, the media were doing security. So a lot of the, I would say most popular, uh, uh, verticals that are in the marketplace. Uh, those are the ones we are, are serving, serving. But we are also seeing that as we expand out of just serving the coasts and move a little bit into the country, there are traditional like manufacturers who are starting to think about themselves as being a technology company. So we’re, we’re serving them in the similar manner that we’re actually serving the technology companies. Right? Our core vertical is really our technology, media, tech, um, uh, security. And then, uh, and then the likes of there.

John Kostouros:
Yeah. Um,

Asher Mathews:
okay. Yeah, we can cut after that. That was good.

Asher Mathews:
Okay. Mmm. Asher, are there specific geographic locations that you guys really serve well in? Yeah, just like any other startup, like our core is the Americas, right? So we have done a lot of work on figuring out the best data set for the Americans, but now just like everybody else, we’re also going deep with our customers and trying to serve them in other markets. And one of the big initiatives that’s going on at metrics currently is we have expanded into the APAC market and, uh, and we have live customers there today who we’re working with. And uh, and then those, those customers are then asking us to stretch to LATAM and EMEA as well. So the key thing that we found is, is as long as it’s an English speaking country, we can serve, uh, customers anywhere when it’s a specialized country or I would say when the language is not English, then we have a little bit of work to do, but that work can be, uh, can be done, uh, efficiently with our market research team. And so, so we can totally serve geographies that don’t speak English. It just, we just have to narrow it down that there are technology companies that we serve them first or media companies or telecom companies, you know, like anybody that has a digital footprint that we can work with them first and then we can, we can work with the other companies after that. That’s great.

John Kostouros :
Alright, so the next one, yeah, as, sorry, I’m, I’m, I’m going in between two sheets right now because I’ve got new questions that I want to ask you based on your answers at the end too. Um, and then I know you guys categorize yourself as B2B, but you made it a B to C as well. So I’m going to ask you this question because it’s also something that, you know, it’s a common question if it could be like an FAQ or something. So yeah. All right. Um, how would you categorize your data, Asher? Is it B2B, B to C? Could you B to B to C is, you know, it could be all of the above, but where do you guys really focus?

Yeah, and so we actually think about this as the data stack and a, and just like companies have like the tech stack, they have the sales tax, they have the marketing MarTech stack, they have like the uh, uh, I do security stack, you know, they have the developer stack, you know, like we actually start up starting to thinking about things as the data stack and companies need to think about this in a very framework oriented manner.

Does DemandMatrix categorize their data as B2B or B2C?

Asher Mathews:
And so we think of account data has firmographic data. It has contact data as a technographic data and is intent data. Now you can always move these around to like fit underneath one each, each other as well. If you wanted to like condense or consolidate that data stack. But those are the pieces of the data stack. Now in that data stack, uh, our view is that, uh, uh, or ours are our market that we wanted to serve is primarily B2B. And so we have not delved into B2C today because our customers are highly concentrated into B to B. And our belief being a customer first company is when those customers take us into B2C or if the requirement comes up, we will absolutely consider that and uh, and serve them. But majority of our requests today are, are very B to B. And in some cases it could be, you could call it B to B to C to, because when you start looking at SIS and, and, and uh, and took the teacher to distributors, those companies, um, information we have, we have as well.

John Kostouros:
Absolutely. All right. Do you guys consider yourself an enrichment provider, a list provider or both?

Asher Mathews:
No. Yeah. So, so this is an interesting one because, uh, uh, and, uh, and, and as we are evolving as a company, you know, like startups are, are, are, are interesting because they’re originated from all kinds of different places. Right? And so our backgrounds, I would say a demand matrix is backward. At one point in time we used to do lead development where we had callers and dialers and you know, we were working on all of this. We was trying to figure out what is our path. And so I would say we are a data provider, right. And, uh, and uh, and the data can then be used for as a list. It can be consumed by as a list. It can be consumed directly via an API, which is what we working on with you guys. Uh, it is, it can be used for enrichment.

Asher Mathews:
Uh, but we provide data only. We do not provide anything after, after that. We do not provide any type of portal today or anything like that. Uh, we provide the data, we want to make sure that it’s high quality data and that that high quality data can be consumed in a flat file. It can be consumed by an API. Uh, it can be in multiple different ways, but we are not going to okay into other, I put some assistance today because we want to take all of that time and resources and energy and make sure that the data that we do provide is like the highest quality data that’s out there.

John Kostouros:
I think that’s a really important point. Um, you know, you find that companies try to do too much, and I always say this, it’s like they’re really great technology companies are amazing data companies and I think the data

Asher Mathews:
yes or the belongs to the companies that spend all the time on it, right? It’s like you gotta maintain that list lives in breeds, it changes. And if you don’t have a hundred percent of your focus on maintaining it and evolving with it, um, [inaudible] okay. And that’s always a terrible thing. So. Mmm. Do you guys have, um, Oh no, no, no. Here we go. How many business and person records are in your database. Okay. Before you answer that, actually ask her, do you guys offer company, uh, lists and in Richmond only or do you do any contact enrichment or list providing? Yeah, so we are only sure we provide data that’s at the account level or the company level. We do not provide beta at the contact level. Although when we deal with marketers, they always ask us about contacts. And so we have a couple of partners that are trusted partners and the way we partner with them and the reason why we partnered with them because they were already in our customer accounts.

Asher Mathews:
And so it was natural for us to probe partner because they were already invented. And uh, and as you know, John and dealing with large companies, it’s really hard to become a vetted like a vendor. And so when you find somebody that has gone through all of that due diligence, it makes it easy to partner with them because they’re already there. The customer has a confidence in them and they have a level of maturity. So we’ve then worked with them. And so hence what we’ve started doing now is if we have marketers who really want contact data, we will source the data for them, but we will forward it to one of our trusted partners who, like I said, we’ve been working for a year over a year. Okay. So then my next question is how many companies do you have in the database? Yeah.

Asher Mathews:
So this is again, the quality versus quantity problem that companies like to solve. Right. And, and I’ve never known before I answer that question, like I was in the, uh, in a cycle with, uh, with another really large, uh, company that’s global, who basically was super proud that they had a million records in their database that they could go after, right. A company’s basically right. And, uh, and I said, okay, this is great. But like, like how many of those really matter? Right? Like how many of those are engaging with you? Like is there, like, can we talk about like with how many of them are actually in your audience? And there was like maybe a hundred thousand of them, right? Yeah. Okay. So you have like 90% of your database is just like, like sitting there and you may or may not go after them, right?

Asher Mathews:
Because you clearly have not made a strategy to go after them. And so what are you going to do with it? And so two weeks later they were like, well, we just took the 9,000 accounts. We just like, right, cleaned our database because things are downright, but things are slow. So we figured it was a good time to do cleanup. So I said, this is great because that’s our philosophy as well, being as we focus highly, highly, highly on quality. And so even though in our database today, we have I think like 71 million companies, you know, like, like you can, you can go and uh, and, and uh, uh, you can just go on and on and on and on and on in terms of the data that you collect. Right. But actively, there’s about 15 million or so, but even in time, John, like the time that we’ve spent in this B2B sales marketing space. Right. Okay. I don’t know about you, but I find it really hard for a company to say I’m going to efficiently target half a million accounts. Yeah. I think the best ad targeting half of minnow and all those half a minute guys know there are companies out there that are very, I would say SMB in nature, but this is not for SMB. This is for, this is target account. Right. So,

John Kostouros:
well I think there’s a bit of a, it was a bit of a loaded question because there it’s, it’s, it’s really not about, it’s about who the customer is targeting. So in my past I’ve had so many different types of customers clean, let’s shake duplicates and they’re all so different. And when they would ask me, Hey, who’s the best data provider? You know, it was right for one was right for the, wasn’t right for the next, it wasn’t right for the next. And so yeah, that’s why I kind of started on this journey. Um, but what I see is 15 million companies, it’s not small by any means. And also you, it sounds like you guys have an amazing market research team where makes you flexible. So if it’s like you get, you know, some healthcare company from Canada that needs you to track some proprietary, okay. You know, a type of technology that’s being used by hospitals or something that you guys could be flexible and start to build that same process around really any vertical or any type of technology. So I think that’s like what you mentioned, 15 million companies, very targeted, very good data. Well, we got to a system where we can scale that out really for customer requests as well.

Asher Mathews:
Yeah. Yeah. They’ll know that market research team is worth their weight in gold or whatever. Metal is even better than gold. But, but yeah, it does allow us that flexibility to not only look for new technologies, uh, if there are a customer requests, but even for the optimize the data, right? Because somebody will come and say, I want cloud data. What cloud is huge, right? Like, do you want the DNR optimize for like Alibaba cloud or do you want to do it too? You optimize for any of the other large cloud providers. And so the, uh, the question is always about like, like what will you do with the data when I give it to you and how fast can you use it? And most companies are not set up to even take let’s say half a million accounts a quarter and go utilize it.

Asher Mathews:
No, that’s effective. Right? You’d have to have a huge sales team. Exactly. Exactly. So, so then, then the question then becomes like, okay, so what is a good number of, of data? And I always, I used to think like more is better, but uh, but actually having worked with a lot of these companies and trying to get, go deeper into these accounts and really give, um, people like advanced signals about why a customer or prospect would buy or why a customer churn like this is specialized data. So we have decided that we’re going to be okay, very focused on quality because we want to work with customers who want to then have a long relationship with their customers. And so, or at least the customer segment that they’re going after. And so, Mmm. So that’s, that’s basically another thing that was dry from our current customers.

Asher Mathews:
It’s not, we were thinking about it, but then we said, let’s go talk to our customers and figure out like what’s really valuable and if we give you like 50 minute accounts, what are you going to do with it? Right. I don’t know. Right. And the market is like, we want contacts and then, and then you go to this contact game and then the game just never ends. Right? So, so we ultimately came back to and said, less is more, let’s focus on they, Mmm. A small number of, or more manageable number of companies. And then let’s go deeper into them. But let’s provide like insight, not just data that people just put in. And then there’s like a lead score, an account score that’s happening. But let’s provide insight. And so, um, on that note, I also want to add that even though we do provide, uh, data and we only provide data only, uh, um, we do offer a visualization services too.

Asher Mathews:
So we will create dashboards so that sales teams can consume that information. Because sales teams aren’t going to go and, uh, and do a bunch of like, uh, configuration of data to get to what data they want, right? They want like readily available information so they can then go and have that meaningful conversation because they’re spending a lot of time preparing for that conversation. So, so we’re saying saying, uh, we’ll provide a dashboard and then the dashboard can have all the signals on it and then, uh, and then those signals can be interpreted depending on what the, a person that’s trying to do, whether they’re trying to win in a conversation with the company.

John Kostouros:
That’s great. So, um, are there any specific types of technologies that you guys would be like, Oh, perfect. You know, like perfect strike right down the middle. I have CRM and marketing on it. I need CRM marketing automation, or is it ERP or EHR or, you know, like what’s, what’s the perfect mix of technologies that a customer could ask from you?

How many technologies does DemandMatrix track?

Asher Mathews:
Yeah, so, uh, this is another one of those, uh, quality versus quantity, uh, questions, but we track 14,000 different technologies now as we have worked with customers. And looked at like what are the actively requested or use technologies. It’s probably like two to 3000 of them, right? But again, we have a 14,000 of them that we track and we’ve got data on even more if needed. Right. Uh, but, but again, like I was sharing as part of the previous question that, uh, the ones that like what we’re seeing and where we’re headed and as this target account approach becomes even, even further in green by companies of all sizes, by the way, right? Like there are companies today that do not know what ABM means and they will, they’ll say that they, they know what ABM was that they’re doing, but they don’t actually know what that little band is or account based selling or our good accounts. Like they don’t know that they, they, they talk about it in their slide decks, but when you dive down or did, they don’t do it right. And, and it’s interesting, uh, uh, and surprising at the same time. But, uh, but yeah, to answer your question, there’s about 14 or so thousand, uh, technologies that we track. And then, uh, but you know, to share some information for as value for our listeners. Uh, there’s about 3000 of them that are actively requested.

John Kostouros:
And what would you say the most popular requests are for technology information? Like what’s this you like? Is it Salesforce? Is it Google? Like

What are the most popular technographics that DemandMatrix customers are looking for?

Asher Mathews:
even further, basically that it’s, uh, it’s, it’s both at the, uh, it’s at the platform level. You know, like, like people are saying like, how much cloud is consumption? Uh, how much, uh, like, call it AWS versus Azure versus Google cloud versus all the other flower. Do you know, like, how much of that is, what’s happening? What are people spending on it? Uh, where are, uh, what type of workloads do they have on those, uh, platform, uh, um, solutions, the, uh, the other, the other thing would be like, things like IOT, things like security, things like, uh, like high performance computing, you know, like, like again, like tech heavy. Uh, it’s interesting, like we’ve got a lot of people that just say, Hey, uh, tell me how many people use like Salesforce. Right? Or at least I would say in my entire time here at van matrix, I think I’ve had that maybe once or twice. It could be because of the type of customers that we work with today. Um, but, uh, but yeah, I mean if somebody asked me for a list of, uh, uh, Salesforce customers, uh, what’s easy for to pull? But again, like I said, we’re like super specialized even further, right? So we’re talking about, um, what are the next few things that a cloud, uh, a company that consumes cloud heavily going to do and, uh, and that, and that’s where our customers are finding value.

John Kostouros:
All right, so we have gotten to the end of the interview and I think you’ve dropped some amazing insights for the audience. And, um, now we’re going to kind of switch gears and, and go through a presentation that Asher and I put together. And it will be a short presentation, but I’m gonna share my screen now.

John Kostouros:
So let’s talk about the RingLead demand matrix partnership. And, um, you know, I think the first slide is yours. Um, uh, Asher, but for those of you listening, um, demand matrix is a valued partner on our data exchange. Um, we have connections with the database and, uh, we are very excited to, you know, have Asher on today to discuss to our user base and you know, our community, uh, what they’re really good at. And um, I think you got a lot of that in the initial questions, but those are kind of my scripted questions. So now we’ll give Asher the chance to go through, you know, his presentation here and then we’ll, we’ll, we’ll move on.

Asher Mathews:
Perfect. Okay. I think was talking about the material that I was speaking to my presentation about it already, but the number one question I had taught, I get the minute I introduced a matrix and what we do is where are you getting the data from? So, so I just like before I, even before somebody even asked me that question, I’d right away like bring this slide up and tell them that we are looking at over 70 different data sources and you can think of demand matrix as a vacuum. And we have these really powerful, like, like Dyson level data vacuums that, uh, that go and, uh, and grab, uh, data from all kinds of publicly available, uh, uh, places and our data sources. And then the magic that we have is in taking all of that data and converting it into information. And how, the way we do that is we apply machine learning.

Asher Mathews:
And in specifically in machine learning, we applied natural language processing. And, uh, and, and the example for the viewers is when you come across something that says Salesforce, is that Salesforce as a sales team or is that Salesforce as in the CRM technology provider, right. It’s, it’s, it’s at that level where our machine learning algorithms are, are, uh, are tuned cause it does take time to tune them and to make them smart. Right, right. And we’ve been at this for over four years. And so we then take that all that vacuum data and we push it through this machine learning algorithm process. We call this the data pipeline. And then we, we look for signals. And then, uh, and then, and then after that, all of this stuff, we leverage our, our market research team and our quality control team. And then that team makes sure that, that there is a quality checklist so that we can guarantee a high quantity data. And so that’s how the data pipeline takes all of the 70 plus different publicly available sources, grabs this information from them and then creates it into, into information so that it’s then usable by either sales teams or marketing teams or data teams or ops teams or, or, uh, or strategy teams.

Asher Mathews:
And so we’ve talked a little bit about this already, but the result of all of that vacuum plus cleaning, right? Uh, and understanding is this technographic data and the, we specialize in backend technographic data, which is behind the firewall because we believe that front end, uh, technographic data is super easily available, but back data, graphic data, things that are paying the firewall are harder to find. And so, so we are like a certain, like, you know, we now have close to 14,000 different technologies that we do. We deal with, uh, or we, uh, have in our database. But what we do more is focus on the top 3000 or the top 4,000, you know, like depending on like what our customer is asking for, we just make sure that those technology signals are the richest and the best available as possible. And then we give this high quality data to our customers.

Asher Mathews:
And so as we were going through this technographic, uh, scanning, if you want to call it right, and, uh, we found that that companies actually buy technologies in a very specific pattern. So we started looking at this trend and then we realized that there is a correlation between tech stack projects, certifications, skillsets, and when you take all of that data and then you look at it and macroscopically and under the lens of a theme, maybe like the theme is cloud or it’s IOT, then you can actually tell that this particular customer or this particular account is now ready to buy and consume just next technology. And so it’s, it’s an interesting concept because it actually answers the question of why somebody would buy a technology versus the when or the walk or the how. Right. And so, so we believe this is the next frontier in data. And so we are working very, very closely with our existing customers already to uh, share this data with them and then they’re using this in their territory planning.

John Kostouros:
That’s cool. I’m thinking of one specific, uh, you know, like I’ve seen, you know, every once in a while you see your logo on somebody’s recommendation for a tech stack. And so I wonder if like you sent some of those high, highly popular like blog posts, infographics to demand matrix and say, Hey, see how many companies like have a similar, uh, set of technologies to this and then which ones don’t have us yet, where we could go and sell it to them.

Asher Mathews:
Um, absolutely. And, and, and this is interesting because like, even as tech, I would say at least almost all of the folks that are in sales team soil’s roles in the sales and marketing tech world, right. In our own space are always trying to figure out tech stack information, but they’re like, what’s some of your tech stacks from your tech stack, right? And especially when you’re dealing with ops ops is always like, okay, I have this tech stack, where does all this stuff fit into? Right? And uh, and uh, and, and, and when you leverage technographic data, you can actually get that tech stack pretty quickly, but it’s get to the tech stack is one piece of it, right? Like trying to figure out why this customer would buy and in what type of a conversation I’m going to have with this customer is actually a lot more about resources because the minute you buy a new technology, you have to figure out whether who’s going to own this, right?

Asher Mathews:
Uh, the minute you buy a technology, you have to say, well, which projects or which strategic initiatives is this going to support? Right? All of that data I think is a, uh, or at least I think, but I believe should be, is available today, but it needs to be consumed by sales teams. And the onus is on companies like ourselves to make it very easily actionable in whatever system that companies are using. So whether it’s Salesforce or Zoho CRM or HubSpot CRM, doesn’t matter whether it’s MarketoEloqua or not, it doesn’t really matter, right? Wherever the S the, the targeting activities are happening, reship, push those data. And that’s the reason why we’re specialized on providing very, very high quantity data. And then we will work with companies on the infrastructure that they already have to orchestrate

John Kostouros:
or act to this data, which by the way, in a lot of companies it was homegrown solutions. All right. Um, well, you know, again, just kind of transitioning to how are we better together? I think, you know, I’m seeing just the way that some of our joint customers have utilized the solutions together. I think, you know, just that account planning has been a huge part of it, right? Understanding any insights, like you said, it’s not just the technographic, you know, static information, but what insights can you pull from that to develop a target account strategy or an ABM strategy? Um, but then that once you understand that, um, you really have to plan around it. So anything from territory planning, uh, and, uh, building out assignment rules for inbound leads or, or list purchases or trade shows, right. Um, and being able to target contacts within those companies were built or get that data into the Salesforce or the Marketo or the elk or whatever marketing automation system it’s required.

John Kostouros:
And so, um, RingLead basically is a data orchestration platform. Uh, as many of you know, it that now connects to, uh, the world’s top data providers and demand matrix, uh, is made available through, um, different inputs like, uh, manual submissions from sales reps can automatically be upended, uh, by demand matrix. Or if you’re a head of, you know, demand gen is importing a list from your most recent trade show, uh, you can push technographics right into that list while it’s going into your end destination. And not just push them in, but utilize them within, you know, the assignment rules, uh, with the territories and, and, and the, the different, uh, round Robins that you want to assign those, those new leads to. So you know, Ringley can take that information, uh, structure it in a way that matches your systems, pipe it in through any end point like web submission list, import, manual entry, it, we even have triggers right inside of this year.

John Kostouros:
I’m in the marketing system for anything that can flow through from a third party application that may be sinking with your system. We also have a batch processing mechanism that can do batch of pen directly into this year. I’m remarketing system across any section of accounts or leads because this information is important on leads as well because it pertains to the company. Um, so, uh, there’s a lot of synergy between the two companies where demand matrix helps to provide strategy around who to target, um, and helps build the database. And RingLead helps become the piping and the delivery and orchestrate orchestrated orchestration mechanism that, uh, powers functionality like duplicate prevention or, um, you know, uh, assignment rules, uh, account assignment, et cetera.

John Kostouros:
Um, you know, here’s, um, sorry, here’s some information on, you know, just basically why you should care about all of this stuff. Right. Um, you know, there’s some really great studies that we’ll share with you in a presentation that, uh, after the, the session here. But these are from Gardner and from other, uh, highly credible sources. Talk about, you know, the cost of dirty data, its impact is never been greater. Uh, theater has never grown faster and as you can see with everything everyone’s going through now, it’s becoming more and more important, uh, for our society. And so, you know, just the stats as of today, uh, 12% of revenue, uh, from companies is lost on average as a result of inaccurate data. Um, 20%, uh, stalled productivity, which is one day per week is caused by poor data quality and 40% of all business initiatives, uh, fail to achieve their targeted benefits because of poor data quality.

John Kostouros:
Um, so I’m sure, Asher, I’m speaking for you and myself, we’d love to help you along the journey of not only finding the best data, learning how to utilize it, uh, build scoring around it, build target plans, and really orchestrate processes. Like, how’s that information gonna make it into your CRM, um, in your marketing system. How’s it going to power other, uh, processes like routing and targeting and, um, you know, all that stuff. So we want to thank you and Asher, I want to give you a chance to, um, you know, say anything we can rerecord anything. Um, we’re going to edit the heck out of this thing. So all my mistakes I just made, they’re gonna get cut out.

Asher Mathews:
No, this was great. Thank you so much for everybody and uh, and John and during the theme, we’ve will look forward to supporting your customers and, uh, and helping people achieve the data dreams.

John Kostouros:
Awesome. Well, we got it done. I think we got some really good content out of that.

Asher Mathews:
I was talking and truly shit about, uh, about data. Right? And then, and let’s see, I get really true. Like if, if I told somebody that said, Hey, I’ll give you a million accounts, but he got to action them in two weeks.

John Kostouros:
Not many companies can do that. Yeah, no, not at all. Or do that. Well, I mean, they can all send people an email. Yeah, that’s, but even if you do that, you ended up on spam lists and you blacklist your IP and you go whack, you know, so there’s just really no way to do it properly. I guess you could give it out to like a Mailgun or something and let them, the third party like tech target, blast your list. But yeah. Anyway, good stuff. Cool man. Right. Thank you so much. We’ll let you know. I’m not sure how long that’ll take for him to edit. You know, probably take a couple of weeks

Asher Mathews:
stolen. Can do it over the weekend, so

John Kostouros:
that’d be awesome. I’m sure he could pull something together. Exactly. Our brother. I have a good day. Bye bye.

Clips

Top