Continuous Decision Intelligence for GTM

Julia Nimchinski:
Thanks, and welcome to the show, Tuba de Raz. Hi, long time no see.

Tooba Durraze:
I know, right? Yes.

Julia Nimchinski:
What’s the latest and greatest? What’s neurogentico ass? I need to know.

Tooba Durraze:
Myogantic OS is, like I said, all robots from our panel earlier. Our job is to bridge humans and robots in the best way possible. I will actually try to get through the conversation today without mentioning things like the neural net or agents, but just know, for people, it’s happening in the background.

Julia Nimchinski:
That’s a new one. Let’s do it.

Tooba Durraze:
That’s a new one, yeah. Well, thanks, thanks for having me again. I think before I jump in, a quick introduction. So again, my name’s Tuba, founder and CEO of Amoeba AI.
I’ll give a little bit of context to folks about what Amoeba AI is before we jump into the product, and… As always, you know, visuals are the way to do that, so I’ll quickly turn to our fabulous website, where we can talk about, you know, what Amoeba actually is.
So, again, last 20 years, we talked about this in the panel earlier today, companies are investing a ton in system of records and system of actions. But we’ve invested a lot in the system of record, which includes your CRMs, data warehouses, dashboards. all with this idea of, like, we want to answer the question of, like, what is happening? There’s, like, this intrinsic curiosity about that.
And I would say as humans, we’ve gotten really good at that, frankly. My theory is knowing what happened is not the same thing as knowing what to do next, basically what would happen in a system of action. And that’s what Amoeba tries to solve for you. Every team that you look at has their own version of a dashboard, every function has their own version of a truth.
And yet, decisions are taking longer and longer as time goes on, because our fields are becoming more and more complex, both in terms of data and the consumer behavior. Amoeba basically sits on top of your data, so between your system of record and your system of action. We’re called the system of intelligence platform, and we do something fundamentally different.
Our job is not to report on your metrics, but to understand how your signals are interacting across your different business sanctions, and then identifying what’s actually driving those outcomes. And it’s telling you what to do next with evidence, where a bunch of scientists and geeks have kind of created this. The idea is science is core to our methodology, so everything is very evidence-driven.
Today, I’m going to show you an example of how that looks like in our platform, with a very simple example taking a marketing organization, at the helm. So bear with me here. We’re gonna start with the only thing that leadership cares about, which are outcomes, essentially, which are our goals.
I’m going to talk about 3 very easy metrics that most marketers Most leaders in the business who have a marketing org would look at, one of them being, traffic growth over here, as you can see. We’re about at 342,000 visitors, which is trending above average.
Traditionally, you would see that number in the dashboard, you’d say, hey, I’m almost there, and start patting yourself on the back and saying, I’m doing a great job. Creating demand in the market. So top of funnel is looking strong to me.
But I look to the next of it, and I see my MQL volume, and I know we say MQLs are dead, but I don’t think they’re dead, because we see them day in, day out with our customers. We’re seeing our MQL volume is about, 3600, which is trending below target. So we see we’re driving more traffic, but then fewer qualified leads.
And then we look to the next of it, and we see our marketing sourced revenue, which is ultimately what we care about, which is how much revenue is marketing bringing in, all those efforts bringing in, are about $5 million, and also kind of below expectations. So if I look at these three. As a layman kind of sitting here, I look at these three and I say, something is not adding up.
Your traffic is going up, your pipeline and revenue are both going down. In the words of Gen Z folks, math is not mathing here. What is actually happening is naturally where we would go.

Tooba Durraze:
So Amoeba’s way of showing you, kind of, what’s happening behind the scenes is actually what we call Pulse. This is where most teams would normally get stuck.
So now you would look at that as a dashboard, and you would say, oh, I need to investigate, I’m gonna create reports, I’m gonna create You know, a ton of different investigation parts to understand what’s happening, and then the team will come back and debate, is your answer correct, or is my answer on the diagnosis correct?
Pulse for us is, instead of you going to the data, Amoeba is bringing those signals to you. So right away, a few things are flagged. So as you can see, Amoeba is flagging that the traffic growth is decoupled from pipeline generation. Amoeba is also flagging that your cost per lead is rising due to inefficient spend allocation. It’s also looking at… there are a lot of risks here in this scenario.
It’s also looking at your programmatic contribution to MQLs is declining, despite your higher spend.
And then it’s bringing up one interesting insight, which is Email is your highest converting channel, so even though email is your highest converting channel, despite lower traffic volume, which means you might not be putting as much effort towards it, it is still underutilized for you, but you should be utilizing it more.
I’ll pause here for one second, and I’ll talk about something that we get asked a lot, which is, hey, Tuba, couldn’t I just do this with an LLM? Could I just apply Claude or ChatGPT, toss it on my data, and basically try to have it understand what’s happening in my data? Here’s my theory.
An LLM, any LLM, can summarize data, obviously with the right guardrails in place, because hallucinations are something you should be aware of, but yeah, sure, it can do a decent enough job of summarizing data. The moment you ask something more complex, like, why is pipeline down even though traffic is up? It’s not a single query anymore.
So you’re looking at a system-level problem and a system-level reasoning problem. You need to be able to connect signals across channels, definitions, and funnel stages to generate those answers, essentially. So an LLM can generate answers, but Amoeba is actually looking at the relationships behind the answers, which is more important to understanding how your business is operating or being run.
So instead of just answering things like. This might be why something is happening, you’re getting… this is what’s driving it, and here is the evidence, because again, everything should be grounded in evidence of, like, why we’re saying something is happening. Naturally, our instinct is when we look at numbers, we want to explore.
We want a way to be able to pull on threads to understand what better is happening around your business, and Amoeba allows you to do that in the form of natural language as well. We don’t have a fancy avatar yet, although now I have FOMO after watching the one before that, but we allow you to interact with the avatar via any kind of voice or any natural language interaction.
So, over here, you can see I’m exploring channel efficiency. Traffic growth is, again, being driven up by paid channels, which are especially programmatic, but those channels are converting MQLs at a much lower volume rate. Now, when you look at, kind of, where the issues are coming from, the first thing that you look at is what’s happening with conversions, right?
So you’re looking at your conversion rate drifts. So overall, visitor to MQL conversion is dropping significantly, system is becoming less efficient. One other thing you’ll notice here, our average output count is quite a bit higher than the kind of answers that you would get if you were to ask an LLM a simple question.
That’s intentional, that’s by design, because we focus on longer-form, research-based answers. Our job is to try to have you understand how your business is operating, less answer you A plus B equals C. Now, let’s say we look at the conversion rate drift. The next step for us is probably to look at where the audience composition is changing.
Basically, okay, now that I’m diagnosing the problem, it’s more so my traffic. What is actually happening with my traffic? And I come here and I see our high intent traffic is down. mid and low intent traffic are increasing. So, this is my aha moment.
Because I’m understanding now I let Amoeba tell me it, but I was able to investigate it myself, and understand very clearly that your high intent traffic is down, and the mid and low intent traffic are increasing. Because we want… we don’t want you to just believe Amoeba’s word for something.
We always want to give you the ability to be able to pull on an answer, and really explore further on, like, how something is changing. Now that we have this idea, we’re… normally, we would take a step back and say, is this happening just now? Has it happened over a period of time? And that’s what Amoeba does automatically.
So behind the scenes, Amoeba is already looking at those trends that are happening without you having to ask it to do that. So, as you can see, instead of those isolated insights that we kind of showed you in explorations, Amoeba’s already pointing to a recurring pattern, where your traffic growth is increasingly driven by lower intent.
Acquisition sources, again, growth is real, but it’s coming from less qualified sources. It’s a trend Amoeba had been picking up on for the last 30-plus days instead of just today, as you witnessed. An escalating pattern, which means conversion efficiency is declining, so even after this traffic holds or increases, output per visitor is dropping.
You’re starting to realize it’s not just noise, it’s basically a systemic degradation. And then the last emerging pattern, where high-efficiency channels are underutilized, is basically an opportunity for you to be able to take something and be able to introduce more towards it. When you connect these patterns, you’re getting a very clear story. We’re scaling low-intent channels.
While under-investing in high-performing ones, which is, from what I understand, every marketer’s worst nightmare, essentially. It’s driving lower conversions, and it’s reducing pipeline. Ultimately, the outcomes that we looked at are not getting achieved.

Tooba Durraze:
Now, insights without action fall flat, because at the end of the day, if we’re telling you what’s wrong, we also need the system to be able to tell you what to do against it. And that’s where Amoeba’s recommended actions come in. They’re grounded in the historical trends that you’re seeing, as well as emerging trends, sort of, that are in the market. So we’re moving from understanding to action.
Reallocate spend away from low-performing programmatic channels. Again, in this case, nothing that we’re asking you to do will be at the expense of one of the goals that you had set up. You’ll never be in a position where marketing is meeting its goals and say, sales down funnel is kind of not meeting its goals, right? Refocus paid search or solution-ready keywords instead of exploratory terms.
And then expand email capture and re-engagement. So again, not just diagnosing the problem, we’re telling you what to do next. There’s one last piece, because finding the answer is only half the job, I’d say. At some point, you have to take this to your leadership team, and be able to show them, hey, this is what I found, and this is what I think we should be doing against it.
This is where most organizations, oddly enough, break. You’re exporting charts, you’re tossing them into Claude, you’re building a bunch of slides, you’re trying to explain, hey, this is what I found, and this is what it really means, and when you get in that room with your leadership team, sometimes you end up debating the data all over again.
Instead, Amoeba has this feature called our Intelligence Briefs, so it’s taking everything we just saw. You saw goals, you saw pulse signals, you saw explorations, you saw patterns, you saw recommendations. It’s taking all of that, and it’s basically pulling that into one brief that is telling you what’s driving it, what’s happening, what it means for the business, and what to do next.
So instead of analysis, you get a decision-ready story backed by a neutral source, which is Amoeba. Your leadership team can align on immediately, because it’s not one person’s perspective, rather the system diagnosing what’s actually happening. So if you zoom out of all of this, for your goals that we had in here, Amoeba did three things. It’s telling you what happened.
Now, again, if you had a dashboard, that’s the only thing… about the only thing it would tell you to do. It tells you why it’s happening, it’s telling you systemically why it’s happening, and it’s also giving you the ability to also pull the thread and try to understand why it’s happening. And then lastly, it’s telling you what to do next. And then making sure that it’s actionable.
Your team can actually act on it and do something about it. So again, end of the story, Julie. I made it to the end without talking about AI or agents or neural nets. This is a first for everyone. Dashboards are telling you what happened. Amoeba is telling you what to do next. And then we would love to show everyone how this can… what this can mean for your business as well.

Julia Nimchinski:
I was super impressed by you. I’m saying this every session, every summit here. A lot of, you know, super experienced CMOs in B2B and CEOs are just evangelizing this category of decision intelligence. But very few can actually build this product, and it’s incredible to see it in the work. And and yeah, how can our community best support you?
What’s the best place to go to learn more and to test this?

Tooba Durraze:
I think the best way to learn, find me on LinkedIn, connect with me, connect with my team on LinkedIn.
Come, come talk to us, and we can show you what Amoeba can do for your data, not just data you kind of have in store, but we obviously bring in a ton of marketing intelligence data that you may or may not have access to, and then Let us show you what the magic looks like in your organization, and I think that’s the best way to understand all that Amoeba can do for you.
And then if you ever want to geek out over neural nets, I will never deny anyone over a geeky conversation, so I’m always here for that.

Julia Nimchinski:
Thank you so much.

Tooba Durraze:
Great. Thanks so much, Juvia.