Host (NachoTuesday): Cool, sounds like it started as a real MVP! So, what are some key features that Revlytics offers, especially for marketers?

Madu (Revlytics): There are many features, but I’ll highlight two critical ones. First, from a visibility standpoint, is our reporting. Everyone says "reporting is common," but it’s actually very limited in most tools, especially native CRMs. For example, you can connect Google Ads to Salesforce and instantly build a report, but you can’t measure the influence of your campaigns or tie that performance directly to revenue. Revlytics can do all of that, connecting multiple data sources to give very specific metrics tailored to your business. Marketers can use this to understand campaign ROI, and sales teams can track the performance of their teams. So, advanced, custom, and tailored reporting is one of our key features.

The second key feature is predictability and auditing. We allow you to set up DIY alerts, so if something happens, you’ll be notified. Our models can predict whether you’ll hit your MQL goal or your sales quota. If you’re off track, we can explain why and what areas need focus. It’s a combination of optimization, auditing, and recommendations integrated within our reporting engine.

Host (NachoTuesday): A lot of marketers keep everything in silos, right? They might have Google Ads, email marketing, and other campaigns, but they don’t have visibility into how all these channels tie together, especially when attributing MQLs from different campaigns.

Madu (Revlytics): Yes, that’s exactly it! In addition to reporting, we also help you build influence and attribution reports, as well as cross-channel reports. For example, we connect finance data directly to your marketing spend, making sure everything is aligned. This can really help marketers and, ultimately, the CEO, who wants to see measurable ROI from marketing efforts.

Host (NachoTuesday): I agree! Marketers are often seen as just spending money without being able to demonstrate ROI, but I would argue that marketers do want to show ROI; it’s just that reporting is complicated, and they often lack the resources to do it effectively.

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**(06:03)** For them to do all these things manually, that’s where a tool like ours can help—everything is completely automated. Every marketer, CEO, CRO, and VP of Sales we’ve spoken to who uses Revlytics wants to know the answers to these questions. The problem is that they don’t have access to the right tools, resources, or time to actually gather this information.

Yeah, I was just being self-deprecating as a marketer myself. But you're right—most marketing professionals are in the business of getting ROI. However, as you mentioned, they’re often stretched thin, lacking the time or visibility they need. That’s where you come in. Revlytics provides 360-degree visibility into their GTM (Go-To-Market) efforts, right?

Exactly. And it’s not just marketing. We primarily serve three types of customers: marketers, revenue operations (RevOps) teams, and sales teams. Marketers want to understand campaign influence, performance, and reporting. RevOps teams, on the other hand, are responsible for sales and revenue visibility. For example, sales teams using our platform might rely on our famous scorecard reports or our pipeline funnel, which provides full funnel forecasting. This gives high-level insights, such as the input metrics needed to achieve output goals.

You can't just say, “I want to 3x my pipeline.” To do that, you need to know specifics: how many demos are required, the expected conversion rate, the number of emails to send, and how many calls a rep needs to make to achieve quality connects. All of these are the input metrics required to reach that 3x pipeline goal. These metrics can vary based on channel, territory, persona, industry, and geography. We break down these variables and provide a highly detailed view of what’s needed, based on your own data and industry benchmarks. We combine CRM intelligence with other tools like Gong and Outreach to deliver specific insights in an actionable way.

Data silos are a major challenge for many companies, especially when they have data spread across different departments. Essentially, you aim to help companies break down these silos and bring all their data together, correct?

Absolutely! Revlytics is the easiest, fastest, and most efficient way to do this, offering the most bang for your buck. That said, we’ve seen some companies try a DIY approach, and we fully support that. If you can build it yourself, go for it. I did the same thing in a previous organization, building it from scratch with software tools.

If you're going the DIY route, you need to understand that data silos aren’t just about business intelligence (BI) tools. BI is merely the visualization aspect. A lot happens before you can visualize your data. You first need to normalize it, filter out garbage (because “garbage in, garbage out” is a real issue), and define the key performance indicators (KPIs) relevant to your organization. This involves creating custom metrics and dimensions specific to your business. All of this happens in the data orchestration layer. The problem is, many people skip this part and jump straight into BI, which leads to messy data and inaccurate reports that are often ignored.

At Revlytics, we combine both BI and the data orchestration layer, ensuring everything is properly managed. If someone wants to build this themselves, they’ll need to purchase a data warehouse and create connectors to import cross-channel data from all sources—ads, email campaigns, sales data, etc. Then, they'll need to write scripts to normalize and stitch the data together. Once the data is ready, they can visualize it using BI tools, but that doesn't solve all the problems. BI tools alone can't predict future outcomes, forecast trends, or generate AI-driven recommendations. These are capabilities we’ve built natively into Revlytics.

There’s no easy shortcut, but that’s the basic process: a data orchestration layer, a data warehouse, AI for analysis, and then BI for visualization. Even with this setup, though, it doesn’t solve the predictive or forecasting aspects, which are critical for long-term planning and decision-making.

For many companies, data becomes a dump of information, which doesn’t help anyone if it’s not structured or useful. What advice would you give companies to make better sense of the data they already have and extract value from it?

The first thing companies need to do is start identifying key metrics that matter to their business. You need to filter out the noise and focus on the data that directly impacts your goals. It’s all about data orchestration—ensuring that you collect, clean, and normalize the data before analyzing it. Only then can you generate meaningful insights that will guide strategic decisions.

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For an output, you can use that data to visualize it and create specific charts. However, the issue with most BI tools is that they don’t always allow you to build the specific types of charts you need. This is why many people resort to using Google Sheets, where they can easily input a number into a cell and it works. The entire process needs to be automated and predictive because you need to know in advance whether you will meet your targets. There's no point in realizing after the fact that you've missed your numbers. Therefore, it must be automated, predictive, and easy to build and operate, especially as new data sources are constantly being introduced.

If someone wants to build a similar system themselves, it's not a quick fix. They would need to establish a data orchestration layer. This would involve a data warehouse connecting various data sources, integrating with AI to finalize the data, and then using BI or equivalent tools to visualize the results. This approach solves the visibility aspect, but it doesn’t address predictability, forecasting, or generative AI use cases like identifying recommendations and summarizing data for board presentations. These are capabilities we already have built into our platform. But for those who want to build it themselves, that’s the general approach.

A lot of companies collect data, but they don’t know how to make sense of it. It often ends up just being a data dump. You can have all the data in the world, but if you’re not extracting value or identifying trends, it doesn’t really matter. To extract value, you need to start identifying patterns in your data. The insights won’t appear on their own; you need to dissect the data first. This means figuring out the right segments, combinations of data, and the time frames to analyze.

Typically, insights are identified through time series patterns. You look at whether something happened last year, the year before, or a month ago. You need to plot the data in different ways to find patterns. For example, you could identify seasonality or business trends. However, every business has its own unique patterns, so there’s no one-size-fits-all approach. To speed this process up, you can leverage AI, which can analyze millions of data points quickly, identify trends, and figure out what has worked consistently in the past.

To dissect data effectively, consider the time frames you’re analyzing, the segments you’re focusing on, and the channels involved. It's a lot of trial and error, and for manual work, it’s very time-consuming. However, with the right tools, like Revex, this process can be automated in hours.

We have a data science team that has developed an algorithm to identify patterns. Our model works with a "master and child" concept. The master model is generic and works for everyone, while the child model is specific to each customer. This unique combination ensures that insights are tailored to each customer, based on their data as well as industry data.

Our platform offers visibility into the data, but it goes beyond that. It provides predictive insights, forecasting, and even generative AI capabilities that recommend actions based on data. It’s all integrated into a single platform to eliminate the need for spreadsheets.

Regarding security, we anonymize all data. We don’t share any customer data with others, but we can use industry-wide patterns to provide insights. Customers can choose whether to allow us to use their data for this purpose. If they opt in, we can offer insights based on trends observed in similar businesses, such as identifying potential issues early or recommending specific actions.

For early-stage companies, most rely on CRM-native reporting or reporting from platforms like Google Ads, Gong, or Outreach. As they grow, they need a better understanding of how all their data connects. In the beginning, using Google Sheets or Excel is fine for basic reporting, but as they scale, it becomes harder to manage. Learning Google Apps Script can help integrate all their data into a single Google Sheet for more specific reporting. However, it’s not scalable in the long term because of limitations in Google Sheets.

For agencies, we offer a white-label option, allowing them to customize our product and use it with their clients. This gives them full control over the branding and the ability to manage client access without worrying about data storage.

In terms of missed opportunities, many companies don’t realize that there could be valuable insights in the data they already have. Once we work with them, they often discover blind spots and areas they could improve, but initially, they didn’t even know those opportunities existed.

(22:16) Nowadays, everyone has access to a lot of data. The issue isn't the availability of data but the time it takes to connect it all. Most companies, whether they become our customers or not, when we first sit down for a demo, we primarily want to understand their current processes. The biggest issue we see is that no one truly understands data orchestration. People tend to think they just need dashboards.

(22:44) While dashboards are important, the real focus should be on understanding the underlying data. We’ve worked with companies ranging from early-stage startups to those approaching a billion dollars in revenue, and the common thread is that no one has clean data. If you think this problem disappears as you grow, it doesn’t – it only gets worse. So, for any company, figuring out the data hygiene layer and what we call the data orchestration layer is essential. This is often the biggest blind spot.

(23:12) You could use a product like ours, or you could have someone internally who understands the different data schemas and how they interact to make the necessary connections. However, this crucial step is the one that almost every company skips, and that’s where mistakes happen.

(23:37) The second obvious thing – which doesn’t even require fancy tools – is setting up simple alerts on Slack or via email. There’s no need to log into a dashboard or check a report to find out something is wrong. It might not always be about direct numbers; it could be about trends, like something dropping unexpectedly. You can set up simple scripts for free – you can even use ChatGPT for this – without needing coding skills.

(24:04) For example, you could set an alert for when your 7-day or 30-day average for MQLs (Marketing Qualified Leads) drops below a certain threshold, say 5% or 10%. It’s a simple example, but it applies across various metrics like ad spend, Google Ads quality score, and more. The problem is that people get buried in so many reports and dashboards that they don’t even know what to focus on.

(24:33) When things go wrong, companies might discover they overspent by 30%, only to realize they actually got fewer conversions. After digging into the issue, they might find that the report told them exactly what happened, but they didn’t look at it properly. Setting up these basic alerts will notify you when things are off, so you don’t have to dig through reports to find the problem.

(25:00) You don’t have time to be checking reports 24/7; you should be executing. The reports are there to analyze performance, so when something goes wrong, you should get an alert right away. It’s a much faster and more efficient way to stay on top of things.

(25:29) I agree with you – setting up key alerts has been incredibly helpful for us too. For example, if a campaign goes live and you realize you’re overspending, you can shut it down immediately before it becomes a bigger issue. If you wait too long, you might end up wasting a lot of money and failing to acquire new customers.

(25:53) Absolutely, this is the easiest thing to do, and you don’t need any specialized tools for it. In fact, I’d recommend you don’t buy a tool just for this. We have free resources available that you can use, and if anyone wants help setting it up, feel free to reach out to me on LinkedIn. I can guide you through it. Whether you’re a startup, mid-market, or enterprise company, you can implement this with existing tools and simple scripts. Just by doing this, you could see a 30% lift in your performance.

(26:21) It’s not just about tracking KPIs. It’s also about setting up simple rules to catch things like missing fields when opportunities are created. For instance, if the opportunity amount or forecast is missing, you can set up an alert. These small fixes in your process can result in immediate improvements, and they don’t cost anything. You’ll see a noticeable lift in performance across the board.

(26:49) You can learn more about these features and integrations on our website. I can also drop a link for you or share it directly via LinkedIn if that’s easier.

(27:15) If a company wants to take their go-to-market (GTM) strategy from good to great, where should they start? It really depends on the stage of the company. For early-stage companies, the approach will differ compared to those further along in their journey.

(27:44) The first thing to do is identify what’s working and what’s not. It’s often much easier to spot what’s not working. A simple exercise is to open a Google Sheet or any document and list everything you're doing from a GTM perspective, noting how much you’ve spent and how much you’ve earned. It doesn’t need to be perfect – just basic math. By doing this, you’ll quickly see what’s not working and can stop those activities right away.

(28:10) For things that might be working, but you're unsure, you can tweak them to see if they improve. The key is to stop what’s not working and focus on the things that do work. Eventually, you’ll have a much clearer view of what’s effective. From there, you can scale up what’s working and minimize or eliminate what’s not.

(29:01) Once you understand what’s working, the next step is to figure out how to scale it. When you double down on successful campaigns, you'll realize that certain segments or programs are driving most of your conversions. You can then allocate more spend to those high-performing areas.

(29:29) On the flip side, when something’s not working, repeat the process to identify the root cause and shut down those initiatives. This framework can be applied to sales processes, marketing campaigns, revenue operations, pipeline forecasting, and more. It gives you five key focus points to assess how to improve or cut out activities that are impacting your top and bottom line.

(29:53) This framework is essential because it gives you a starting point. From a philosophical standpoint, everything branches out from there.

(30:20) As for what’s next for RevLitics, we’re excited about our upcoming product launch. We’re introducing our own intelligence agent. One challenge we’ve heard from customers is that they don’t want to upload their data to tools like ChatGPT because of privacy concerns. Additionally, most tools just summarize data without providing true analysis or recommendations. Our solution addresses these two issues.

(30:53) Our intelligence agent, launching in mid-to-late February, allows you to ask specific questions like “Which Google Ads campaign drove the most revenue?” It will integrate with your CRM to show you the revenue directly influenced by that campaign. It goes deeper than just summarizing data – it provides analysis and recommendations, helping you understand what to do next. It’ll also protect your data by keeping it secure, using SOC 2-type security protocols.

(32:23) This is one of the biggest things we’re launching, and we can’t wait to share it with the world!

(32:47) Yes, we are really focused on providing tools that people need today, and that are directly relevant. It’s not just about nice-to-haves but practical, applicable features.

(33:20) You can learn more about RevLitics by visiting our website at revlitics.com. If you'd like to connect or have questions, feel free to reach out to me on LinkedIn. I’m happy to chat with anyone and help out.

(33:49) We’re also available on the Nacho Nacho B2B SaaS Marketplace, where you can find the best products. We’re excited to continue growing with you and working together. Thanks for having me, Andy. Take care!