Transcript

Okay. Camela thank you so much for joining us, uh, to do our favorite thing, the no bullshit demo. And in this case, you’re going to be talking about CaliberMind I’ve obviously been talking to you and the team for a while. I love what you all are working on. Um, yeah, and I. Uh, really excited that you took the time to go through, uh, all the questions and sort of prepare ahead of time that actually helps streamline the effort.

And that’s exactly what this whole thing’s about. So I’m looking forward to learning more about what CaliberMind can do, and I’m looking forward for you to go through the deck and take us through it.

Wonderful. Thank you. And thanks so much for having me. I’m Camela Thompson. I’m the director of growth at CaliberMind, but my background is actually in revenue operations.

It was revenue operations before it was a thing spanning sales, marketing, and customer success, managing tech, stacks, and analytics. Right. I love it. I love it. You know, the, you know, the audience. Well then yes, I have felt the pains very personally without a doubt. Well, cool. So let’s jump in. Um, why don’t you tell us a little bit about the product and you know, like what it does, why it exists and all that.

Perfect. Yeah. So CaliberMind really came out to be a thing because a bunch of operations professionals and at heart, and most of us in the company, we either came from operations or still are in operations. We thought 11 years ago, when people started talking about attribution, it’s a really great compelling concept because we know marketers and sales and everybody has to touch an account several, several times in order to close this.

The problem though. And why attribution has fallen short for so many people? Is that those legacy legacy platforms, they just bolt right onto your CRM and assume your data’s. Okay. They also tend to just look at campaign members as it exists in Salesforce and not integrate with a lot of other systems.

What we were really seeing is that executives understand and hear from all of their employees about the lack of quality of data is particularly in their CRM. Even Salesforce estimates that about 91% of CRM data is stale or missing information, which is scary, terrifying. I know. So. 54% of executive marketers report, the marketing analytics.

Hasn’t had the impact that everybody expected and 34% of CMOs don’t trust their own data. And I’ve seen in organizations where people have oversold what their attribution tool should be doing or can do, because it’s just looking at marketing touches and doing some simple math and it really dings their credibility with the rest of the executive team.

So a lot of marketers have recognized this huge gap. We’re missing data connections. We’re not looking at the whole picture, so they’ve tried to do it themselves. So what we’re seeing a lot of companies doing is they’re building their own data warehouse. Uh, they’re connecting to all their sources and they’ve got a bunch of logic in place.

We feel this is the right approach, kind of the struggle is it’s really expensive. It takes a long time to implement and marketers change tools all the time, because what works and doesn’t. That changes. And when you’re working with an it team, that’s managing your data strategy, your data warehouse, it could take weeks to months to get a new tool connected.

And then you have to layer in more logic that allows it to stitch all that data together. Because as we know. Your website may identify people through IP addresses, your marketing automation relies primarily on email. All these tools are speaking a different language and each time you add one into your ecosystem, you have to do a lot of groundwork to get it to all talk together.

Yeah. I’ve seen a bit of that and, you know, frankly, I have not seen very many. Let’s just say whether or not I’ve seen it. I have not spoken to anyone that has said, oh, Are, you know, warehouse situation, be it, uh, I don’t even know any of them. Right. Is, is spot on. Oh. And that was, that was, uh, well worth the effort.

Uh, the last two years. I not, not heard that yet. Oh. And it’s so sad. I I’ve seen a lot of data. Scientists get really excited about building these marketing models too. But the problem is they lack a lot of the business context. They don’t always know where to focus and what, what is noise? What they should be focusing on.

And the models proved to be really disappointing and ineffective. For the most part. I’ve, I’ve heard a lot of organizations that have built them out, and now they’re looking for a tool because it just didn’t pay. Which is why we exist. Right. So CaliberMind fits. Okay. There it is. That’s the, that’s the visual right there.

Yeah. Yeah. So, uh, we’ve been there and done that. So you don’t have to, we’ve already worked with all the platforms out there. We even, um, if we don’t, we have over 150 connectors. If we don’t have a connector. And your tool allows API. We can actually build it for you, or you can go old school and do SFTP.

Like we have a lot of options, but our real intellectual property calling us an attribution tool is really underselling us really it’s that customer unification and that stitching together of all that data where our value is because out of that can come engagement and lead scoring attribution return on ad spend and further down the funnel.

Turn analytics, uh, predictive modeling around churn. That’s hugely powerful. And while we provide data visualization, standard dashboards, reports, that sort of thing, we do allow you to connect your data warehouse or visualization. Directly to CaliberMind. So we’re the brains underneath the operation. So if you have a really passionate data team who wants more control over the visible visualizations, you have a really specific way of looking things in your, in your business.

We allow for all of that. That’s awesome. So, all right, so that sort of answers, you know, one of, one of the core questions of like, why MO Pros use your product? Um, I don’t know if you have any more to address, address that, but, you know, we do ask a lot about, you know, the sort of the integrations and the capabilities and all those things.

And so looking at like, what is sort of the, the examples of where your product really shines? Okay. Although you gave us one already, right. Data visualization and letting your data team. Yeah. So that’s pretty cool. Well, obviously I love this question. Um, encourage everybody to go to G2 and look at our reviews.

We’re really proud of what people have to say. There, we work really hard to keep our customers happy. Um, The three main reasons why MO Pros love us is we fix the unspoken problem, which is exactly what we just ran through. We don’t plug into your CRM and assume everything’s okay. We don’t assume you have all of your best practices in place, which is where number two comes in, which is our support team.

They’re all. Really seasoned operations veterans who have made the mistakes, uh, they’ve seen what best practices can do for an organization. And they can really come in and help you put things in place like proper UTM parameters, proper structure for your campaigns. Um, they can make recommendations around data cleanup, like whether or not you should be automatically converting.

Leads into contacts and having that entire story on your. So that’s kind of number two. I think we’re really well known for our service and our understanding of what marketers go through day to day. And then of course, the third point is we continuously innovate. So, um, I think we’ve started in the attribution space.

We’ve, we’ve kind of branched out into ABM engagement scoring, um, and, and now we’re looking at the rest of the funnel. So I think we also are in. Of making a major change to our UI and moderate modernizing our look and feel. Um, I think we were formed with the belief that just because people do things a certain way doesn’t mean it should be the way that things are done.

And we really embody that within our organization. Mm. I love that. And I love the use of the G2 literal. I assume these are G2 reviews that you pulled into align to each one of these points, which is spot on. I, you know, really. Creative in it. Uh, clearly your customers are enjoying the product. That’s very cool.

Yeah. I think that’s so central to like, don’t take our word for it. You can take their word for it. Yeah. Definitely goes a long way, right? Yeah, I think so. Um, okay, cool. So, so tell us a little bit about the. You know, some of the examples of like the core integrations that are kind of really common. Um, you know, what would you say are kind of the most frequently used scenarios that can have.

So, um, so traditionally the legacy platforms really only plugged into your CRM. There are a few out there that do that. Plus maybe some ad platforms and a web site tracker we offer, uh, like I said, over 150 connectors, here’s just a small subset. We work with a technology partner. To enable API connections.

If they don’t have the connection in their list is always growing. And the tool does allow for an API connector. We can build it in house. Um, we really wanted to move away from building all of our connectors and partnering with a technology partner because we really believe that. The core of what we do.

And what’s most important for us to focus on is really cleaning up the data and understanding the data issues that organizations are running into as opposed to creating connectors. Right. Right. That makes sense. So like put, like staying focused on your products, core mission and value, and allowing the sort of like expert in the connector kind of API world, manage that and leverage their expertise for, for that.

Exactly. So within the admin screen, you can see that we also allow for SFTP setup. Uh, we also have what we call, uh, flows and an object manager. So flows are kind of it’s Wiziwig point and click set up for things like lead to account matching, where we populate the ID and even lead to contact convert. We can enable that within our platform.

Uh, we have several other flows that are out of the box, like website, domain fixes, and, uh, data standardization. Our object managers, a Wiziwig point and click for like, uh, data substitutions industry is a great one. So as we know, most of us have at least one data enrichment platform and they can all spit out different values.

This is our newer UI when it comes to reporting. So people who may have had a demo with us in the past, probably remember a different look and feel. Um, I haven’t loaded it yet today, so it’s going to take a second. Okay. So, um, a few things I wanted to touch on before we get to the data normalization and where that really plays off.

So first of all, Mine believes it’s your data. You own it. So of course you can connect your own visualization tools to it. This is our visualization tool and you can choose whether or not you want to go with ours or somebody else’s. Our dashboards are really meant to work like an analyst work. So we started a very high Somerly summary level and then click through to additional detail to dig in and answer questions.

I also want to point out that you can toggle really easily between different attribution models. So if I want to switch to a different multitouch or even single touch model, um, Stoli possible. And the reason why we believe in doing that and having multiple models is because they answer different questions.

So. I want to know what’s driving initial engagement or what’s tipping people over into creating an opportunity. I would probably go with the single touch model in those cases, if I want to understand which tactics and this is where attribution really comes into play, and it really brings value. Those touches like.

Direct mail webinar, user group, the kinds of things that are engaging deals that are already in flight or existing customers. We really can’t measure the impact and argue with finance, why we should be doing those tactics. If we aren’t looking at what happens after the deal opens until it closes. So that’s why I think this piece right here is really powerful.

Out of the box. We also allow you to aggregate aggregate either by the open date or when your pipeline. Is generated when it’s considered pipelines, whatever definition you have, it’s totally flexible. I find this really useful as a marketer because I can’t wait the three to six months. It takes to close a deal to decide where I’m spending, what I need to dial up, dial back on.

And what’s working today. We also have the ability to aggregate by the close date and filter down to one opportunities or lost opportunities. So you can do some pretty powerful closed. Won or lost analysis and use that in your QPRs again, I think it takes a little bit too long to get to that point, to be using it, to make day-to-day tactical decisions about your campaigns, but I still absolutely believe and it’s useful.

Yeah. Yeah. I would agree with that statement for sure. Is there any sense of like having other kind of date fields or like stage stage dates, like stage gates dates? Um, no, that’s a great question. So, um, not when it comes to attribution, we do have some pipeline reports in place where we look at, you know, uh, deal conversion points.

What I will say though, is our engagement scoring is kind of, so we have. The early medium and late view into what’s working and what isn’t, I think engagement score, which is think traditional lead scoring, but a little bit more sophisticated. And account-based, that is super helpful really early on when my campaigns are first running and that’s, you know, other than being in the tools like we’re big fans of using multi.

Data points to judge the effectiveness of a campaign and not really relying too heavily on any one thing along with looking in tools for really, really early, uh, effectiveness engagement is kind of the first point where I can tell who’s engaging with my content, whether or not it’s the right people, the right company.

So I do spend quite a bit of time in there. That was a really great question. Cool. Thank you for. Course. So I’m going to drill into campaign type. Like I said, these reports are really intended to work. Like an analyst works, dig into the details and then this is where it starts to get really interesting.

So one of the most common use cases that I hear about are marketers come to me. They say, you know, demo signups are. Pretty core to our business and generating opportunities initially. But I don’t know where they’re coming from. I use a chat bot. I can’t capture the UTM parameters. It don’t know where they’re coming from.

Well, with our web tracker, we can actually take a look at where those events are coming from, stitch together, the data. And then if I click on any of these blue fields, it’s a drill down. I’m going to go and look at demo signup details.

a minute, but it’s really cool. I’m like, I’m like God eagerly, awaiting that examples. A great example, right? Chatbots. Don’t exactly. Point to. Point of entry necessarily. Right? Well, and the thing is like with drift, I can’t dump more money into, well, I could dump more money into the tool, but really what I need to understand is which tactics are driving people there to engage with it.

So if I can understand if a particular ad or webinar or some kind of event that’s happening, that’s kicking people over into that event. And so much more powerful than just seeing that demo signups are the thing that usually happened before an opportunity. Yeah, definitely. Uh, a couple of things I want to point out is everything I filtered carries down automatically.

The further I drill down. So I clicked on demo, sign up. That’s the only data we’re looking at. We’re still looking at an even weighted model and we’re organizing it by the pipeline open date. So whenever I moved to a lower, late or lower level, I’m looking at a subset of the data that I was just looking at.

So right off the bat is opened up with job level. This really speaks to that, uh, substitution, logic, or normalization that we put in place. Typically your titles are massive mess and it’s much more useful to be able to identify the level and department. We also have that industry logic and instead of having 500, 1,015 hundred different values, we have a really concisely.

And it organizes my attribution data. So. Now, here’s why I’m really here. And I think this is super powerful. So like I mentioned, uh, when you have a demo request and let’s say you’re using a chat bot that chatbot doesn’t capture the UTM parameters very well. Well, this does, because we use a web tracker and we stitch all the data together for you.

So I can actually see what people were doing before they landed. On our demo request and which tactics are working really well. So, um, this tells me whether or not search display and a few other areas like paid social are effective in driving demo requests. If I do see some hopeful signs there, I can dig in and see the actual campaigns that drove people there and start replicating those and scaling them.

So instead of kind of feeling powerless and not really know what. Where things came from and being frustrated that you see this really big category, you can actually dig into it and see why it’s working, how it’s working and what kind of people are engaged. That’s really cool. Are the channels, um, standardized the same way that Google kind of standardizes them.

And then you set up rules to map to those, or how are those pulled together? That’s a great question. So it’s totally customizable. Again. We have those configuration screens so we can change the logic, but what we generally tend to see is that, um, the source field is. Fairly standard across marketing departments.

Um, and, and that’s what we’re really looking for. When we look at the UTM parameters. Um, we also recommend that if people haven’t already started putting their campaign IDs in the UTM parameters string, that they start doing it today, before they get an attribution tool or an analytics tool to make mapping easier than having to do some fuzzy logic on the names.

This is a really good, best price. Love it. Okay. So I’m going to pop out of the demo. Um, and we can continue the Q and a if you’d like. Yeah, I would love it. So, yeah. So next question. Uh, thank you for the demo. Obviously we love looking at the tool and you gave us some pretty cool, uh, Layers that we’ve got to look out there.

So we appreciate that, but yeah. Um, next, next question is what’s the average size of your customer. So who’s your, you know, kind of ICP, uh, Uh, great questions. So we tend to work with companies that are 200 employees and bigger. However, we found that where companies are on the marketing analytics, maturity curve as far more important for a good match, then how large they are.

So we have giant corporations that don’t really have a solid data strategy. And, uh, don’t value analytics as much that aren’t going to be a good match. And we have teeny tiny startups that absolutely believe in putting a firm data foundation in place before they scale anything else up. So it just depends on the data mindset in the marketing organization.

Hmm. I love that. I’m all for the. Data layer, foundational stuff. Uh, as you go to scale, you don’t want to slow down progress by not having the pipeline laid, but you definitely should like start with the end in mind, I think is what I like to say. Yeah. I mean, it’s really important. You have a leadership team that sees the value in using data to make decisions.

Now, there are some. That we’re really transparent about that attribution. Doesn’t do a great job of tracking like podcast influence, sometimes organic social, those sorts of things. I think. It’s really important to point out that we still suggest doing those tactics and that multiple data points are necessary for a reason.

You still need the qualitative information. You still need, um, more context to be able to make decisions for your program. I think multi-touch is super powerful and unnecessary thing, particularly improving value with in-flight deals and customers, but it’s not the only thing you should be looking at.

Yeah. Yeah, absolutely not to get too meta here, but you know, this, this video recording may not be trackable for you all at CaliberMind. I still think it’s worth doing so we’re here. Yes, that’s right. Um, okay. So we talked about average size of your customer. Let’s get into time to complete an implementation.

What does that typically mean? So great question. Um, typically we’d like to say eight weeks to be safe, but really want to point out that we have your CRM and marketing automation platform plugged in with the, uh, within the first couple of days and that data all mapped within the first two weeks. So you, we have one-to-one functionality with our legacy attribution competitors within week two and a half to week three.

So you’re not waiting the entire period to get your value. Um, It’s it’s a process because we’re going through all of that normalization and mapping and, uh, one of the harder parts to get correct is a return on ad spent and how we’re moving. Yeah. Yeah. Sorry. Many people mess with that either to be honest.

And it’s largely due to how complex it is. Well, yeah, and a lot of companies work with proprietary or vendors that use proprietary solutions to deploy their ads. We actually still work with those tools and we’ll take it on, but it is important to have best practices in place and can consistently be using UTMs.

Yeah. Yeah. Without a doubt. Okay, great. And then, uh, what is your pricing model? Um, you know, are there set up costs and those kinds of things? I forgot to point out one thing. Do you mind if. I just want to call out that these are eight weeks where my operations professional is spending their entire week cleaning data and doing things we’re looking for three to four hours a week to get some guidance around the data standards you guys want to focus on and what your normalization should look like.

And if you have any strange values that we should be considering. So it’s really three to four hours per week. Not that entire time. Okay. Yeah, that makes sense. And that’s not bad at all. Right. That’s less than an hour a day. Yeah. I remember every time my marketing department would want to bring in a new tool and like, Ugh, how much time is that going to?

Yeah, absolutely. Well, cool. Let’s talk pricing. Um, what would, what is the pricing model? Um, are there any setup fees or anything like that or. Right. So there aren’t set up fees. It’s a monthly fee. And you’re going to notice that we are more expensive than a lot of the legacy competitors that’s because of all the data orchestration and stitching together that’s going on underneath.

So the very, very base level is just connecting to your CRM. So your reports are going to have that one-to-one parody with the legacy solutions. All of the data management and transformation underneath that’s deduplication, merging normalization, all of that good stuff. Most of our clients land in about the 5,000 per month range.

And that’s connecting to a CRM marketing automation platform and implementing a website tracker and then a.

RO as connectors. So return on ad spent LinkedIn Facebook, Instagram, like all of, all of your advertising, social and search and retargeting platforms, plus the data management and transformation and advanced marketing analytics. So I will point out all of our solutions come with full onboarding. It’s a CaliberMind led implementation, which allows you to only spend those three to four hours a week and we do full training.

So. Um, some of our competitors really rely on the knowledge base or knowledge of the people within your organization to do the implementation themselves and walk through each of those steps. We really don’t believe that’s the right approach because, um, why not benefit from our best practices and then custom.

Uh, we work with some organizations that have multiple CRMs. They have multiple marketing automation platforms. They actually want to have a dedicated senior data analyst or data scientist to build models for them, analyze their data and spoonfeed them everything. So there’s really a range. I love that. I mean, it’s nice to, I’m glad that you called it out just to know that it’s available for some of those large, larger organizations out there.

Right. So. Um, okay. So as we get into it, yeah. You know, we talk a little bit about pricing model. We like to ask about, um, you know, who else sorta needs to be involved. Um, and, and that’s both sort of like internally and externally, like what does success look like from a teams and involvement perspective?

Yes. So that’s a great question. Before I move to the next slide. So typically we’re primarily working with marketing operations and now we’re seeing more and more revenue operations involvement, which I think is wonderful. Um, we also do, if we’re connecting to any system, we meet. The admin or the person with the rights to that system to be available.

Our connectors are a matter of a few clicks, but you do need to have the proper permissions to be able to, uh, get that data streaming properly. The only other person I think we would involved would involve would be your web operations person to install the JavaScript necessary for the web tracker. If you’re not already using one.

So if you are, then we can use that data. Got it. Got it. Okay. Manage services. Yes. So we have a lot of companies that contract with us to once they’re established customers to clean up their database and do a one-time push. So we do a lot of statement of work, which is of course, variable. Managed services start at 1500 a month.

And while that seems like a lot, it’s a tiny, tiny fraction of what a really talented data analyst would cost on your team. So that gives you named support twice monthly strategy calls, a dedicated slack channel, rapid responses, and they do a tremendous amount of work on the backend. Around data, normalization, deduplication, like all of those pieces.

And they’re continually working with your department as you add new systems, change how you do things and need to modify your models. And then the kitchen sink is really for that giant organization that has multiple marketing automation platforms or multiple CRMs, and really needs a ton of handholding and wants to be spoonfed insights and told where they should be spending and not.

I love that. I wish I had the monies for that.

Not that I don’t love digging into the data myself. Yeah. I mean, I do too. And I think what I ended up doing is I inevitably just sort of go down too many rabbit. It’s easy to do my friend. It is so easy without a doubt. Okay. So, um, you obviously have managed services. I imagine that, you know, outside of your team, we don’t need to engage with any other external agencies or consultants because you have the team within the.

In-house so that’s great. Yep. Um, and then support options. Um, we started talked a little bit about that in terms of your onboarding, but sort of the ongoing, is this sort of the way that support is managed and like in terms of managed services or is that sort of a different bucket? Um, so onboarding is kind of a different, um, beast in itself.

Uh it’s where a lot of. Like work happens, but the managed services, those are the twice monthly strategy calls, the dedicated slack channel and people are monitoring it all the time, asking questions, getting answers and managed services is really intended to help organizations when. Um, they add a new tool or they changed their process or they add a new product line or, you know, the changes businesses just go through.

I will say that a lot of our customers that go through the onboarding and implementation process and see the value that our team can bring in terms of pivoting and adapting to those different use cases and needs, uh, they tend to go with the managed services. Okay. Um, so we’ve talked about support and, uh, I think the last question, and we sort of, we sorta touched on this, you said in about two and a half weeks, you start to see some, some value out of the solution.

Um, but you know, at the end of eight weeks, you’re sort of fully ramped up and, and, you know, uh, leveraging the product, but what would you say. Time to see success. Is that really at the eight week mark or, you know, somewhere in the middle or even longer. So, because we do so many things, it depends on how you define sex.

So we had a large enterprise client that went from an attribution tool that was saying they influenced 20% of the deals to 80% because we could install the web tracker and look at a much broader audience. So it depends on your current level of sophistication and what your goals are. Um, and, and that happens within the first two to three weeks.

So it just depends on. Companies pain points are what you’re looking to solve. Um, I would say Roe as, uh, some of the workflows that we recommend putting in place for engagement that’s that’s later in the onboarding. Um, so again, just totally depends on the organization’s goals and what they define as success.

Wonderful. Well, I think that sums up all the questions that we like to ask. Camela thank you very much for taking the time to do a no-bullshit demo and, uh, we really appreciate it. And hopefully we’ll have you, uh, as a guest on the podcast, again, I know your team joined us. Uh, fun fact, the number one all-time most downloaded episode of the podcast is all about attribution.

There’s a reason we call them the. Marketing operations without a doubt. And he is one of the co-founders so, well, thank you again, Camela. I really appreciate it. Thank you. I appreciate you having me on.

CaliberMind

Born from Operations Professionals, CaliberMind is built for and by Marketing Ops, Sales Ops and RevOps pros. It doesn't assume your data is "okay" so it'll help you fix your attribution, the right way.

  • Company

    CaliberMind
  • Recorded Date

    January 2022
  • Length

    33 min