I'd like to hear more about the journey and what led you to start Humanic.

My background in the last few decades has been in product and engineering, mainly in the Bay Area. I worked in many large and small companies – Yahoo, Adobe, and a couple of different startups in the networking space.

At Adobe, I was head of product for personalization for Creative Cloud. Most people probably don’t recognize that Adobe was a PLG product before PLG was called PLG about ten years ago. My mandate was to look at product usage data, how people are using Photoshop, Illustrator, and InDesign, and be able to nudge them to discover the rich set of apps and things in the Adobe ecosystem.

That was the idea's genesis to say product usage is a precursor of revenue. And that's what Humanic is about – understanding product usage and helping you generate revenue. And we can talk about different ways people are going around in this space, and I can talk more about it.

I want to stop for a little bit on your experience with Adobe. Can you elaborate on Adobe’s PLG strategy during the massive shift to the cloud?

Yeah. 2012 Adobe shifted from box software to a 100% cloud subscription. Adobe used to sell Photoshop in the whole suite for $2,500 for perpetuity. And in 2012, they made a complete switch. They were the first box software company that completely switched to a cloud model.

So for the last ten years, you can only get something on your device by creating an Adobe ID, having an email, and having something to do with the cloud.

Adobe has the data of who had logged in, when they logged in, what they used, and what features they used. All of that data for several years before it became mainstream only to have those kinds of products. Very few B2B companies had similar numbers – only Salesforce and Google with Gmail and Google Docs come to mind. But people don't consider Google a PLG motion, even though they are sure they are the largest PLG company.

When I was at Adobe, we knew everything about Photoshop because Photoshop is a hundred percent instrumented. So as Illustrator, InDesign, After Effects, and Adobe Premier, are all the top four five products, and the Adobe suite of 20-30 products.

Can you share more about the particular personalization tactics in both marketing and sales teams?

Yeah, it was the beginning of that state where the marketing team had decided they had reached a level of not being heuristic-driven and wanted to be entirely data-driven. The idea was that we have all this data for all these users for several years, and we utilize that data to understand both things.

So one is marketing automation, like onboarding and nudging people along based on what part of the journey they were that they use X product and Y product and this feature. As a result, they should get an in-app notification on an email and AB test.

The second part utilized this data to identify specific individuals who were champions or evangelists using the product quite a bit, which could then be funneled into the sales team. So both motions of marketing automation and what is now called product-led sales. So you take product usage data and give it to the salespeople.

For how long have you been building Humanic?

I've been building Humanic for a couple of years to utilize this data and build a product many PLG companies could use. And we did a lot of exploration before starting Humanic around the entire tech stack regarding machine learning and stuff like that.

Now Humanic aims to automate the product-led growth (PLG) go-to-market strategy by integrating the capabilities of product analytics and CRM. In the past, different teams used separate tools for product analytics, marketing automation, and CRM. However, with the rise of data warehouses and the need for a unified approach, Humanic seeks to streamline the process.

We enable data collection from various sources like product analytics tools, Stripe, and data warehouses. This data is then funneled into the CRM, facilitating product-led sales. The current approach involves manual tracking and moving prospects through different stages, which can be time-consuming for sales teams and primarily focuses on larger, high-value accounts.

Overall, the way that we see it is that product analytics and the CRM worlds are colliding. Amplitude and Mixpanel help you understand the cohorts, analyze all these people manually, then utilize that analysis to run marketing automation and pipe some of that data into your CRM.  That is coming together to say, If I know the people who are activated and habitually using the product, all I need to do is orchestrate the outreach for them. And that can be automated, low-touch through marketing automation tools, or a salesperson. But the rules that define who gets what kind of outreach needs to be configured today and analyzed. And that will ultimately be the AI; the generative AI will do a better job of what humans can do to do that piece together.

So for the guru market teams, there isn't going to be that need for visibility and analytics as long as the analysis and the outreach are optimized. The VP of marketing and VP of Growth want to automate outreach; People want product-led growth so that they can reduce CAC. And which is the cost of cost acquisition. But they are using existing tool sets already in their systems, which weren't built for a PLG motion.

Can you talk better about the current state of Humanic?

With Humanic, you can define stages based on user behavior and engagement, allowing for more targeted and personalized marketing efforts. The platform connects directly to your existing tools, simplifying data integration and making it easy to create meaningful stages without needing a data warehouse. You can leverage ML-generated rules or create your own to segment users and create personas. Humanic also enables the orchestration of marketing journeys from a single interface, allowing for efficient management of marketing automation tools and CRM systems. We combine tools like Mailchimp, Customer.io, and HubSpot, allowing us to set up campaigns and effortlessly replicate filters and segments across different platforms.

The platform provides valuable insights on free-to-pay conversion rates and allows you to run targeted promotions and personalized campaigns to drive engagement and conversion. Connecting with feature flag systems like LaunchDarkly lets you quickly offer incentives and promotions to high-value users. With Humanic, you can connect these targeted users to specific campaigns or push them into a CRM. This allows your sales team to quickly identify and prioritize the users generating the most revenue for your company.

Imagine a scenario where a salesperson can simply go into the CRM, see the list of users who meet specific criteria, and give them a call. The beauty of Humanic is that it keeps the list up to date. The ML model runs daily, so if users drop off from the 90th percentile, they will be removed from the CRM or untagged. This ensures that your salespeople always have an accurate and current list of users who meet certain Product Qualified Lead (PQL) criteria. This is where the worlds of analytics and CRM collide. Most companies have pricing tiers based on various usage factors, such as storage, number of users, or activity levels. Knowing who falls within the 90th percentile of usage in the free tier. In the past, this data would need to be processed in a data warehouse and analyzed in tools like Amplitude. But with Humanic, it's all in one place. With a simple click, you can see which users are in the 98th percentile, who sends the most emails, hosts the most chats or video meetings, and then seamlessly push them into your HubSpot CRM daily.

Humanic empowers your sales team with real-time, actionable insights, enabling them to focus on high-value users and make informed decisions based on the most current data.

Who are your Ideal Customer Profiles (ICPs) at the moment?

Our current Ideal Customer Profiles (ICPs) are typically companies with annual recurring revenue (ARR) of around $10 million. We primarily target Vice Presidents (VPs) of growth and marketing, CEOs, and other C-suite executives. These individuals typically oversee companies with 30,000 to 50,000 monthly active users, sometimes with 100,000 signups. They seek a solution that provides effortless organization and enables them to quickly identify insights from their data without relying on data scientists or analysts.

Most VPs of Growth and marketing today have a solid technical background and a good understanding of data. They want to leverage our platform as building blocks, allowing them to gain real-time insights and make informed decisions daily rather than waiting for weekly reports that a data scientist would typically provide.

Let's discuss reverse ETL products like Census and Hightouch. It seems that in Humanic, you're addressing the same problem but without relying on a data warehouse with direct integration. Could you elaborate on this?

Absolutely. Data warehouses and tools like Hightouch and Census have their place, but they come with their own challenges. Firstly, they can be costly, not just in terms of the tool itself, but also the resources required to manage data warehousing and reverse ETL processes. You often need a team of people with specific skills to handle these tasks.

However, a more significant challenge arises when you're a revenue leader who understands the importance of data but may not possess the technical expertise to operate a data warehouse and write SQL queries. In such cases, you become dependent on the data warehouse and reverse ETL teams, leading to bottlenecks. Each time you need something, you must go through a sprint or backlog process to request and configure the desired outcome. At Humanic, we aim to overcome this obstacle.

Our primary goal is to drive higher conversion rates and better engagement as revenue follows from these metrics. Whether you have free users that you want to convert or paid users that you want to engage, the key metric to improve is engagement. Defining engagement can vary depending on your specific business goals and user behavior. With Humanic, you can define engagement based on various actions and combinations of actions. For example, engagement could be defined as users who act X or who perform X, Y, and Z. Our platform lets you see immediately how many users belong to each defined group, enabling you to personalize marketing efforts accordingly.

We are currently working on integrating generative AI into our platform. This addition will provide recommendations for personas and their corresponding context. For example, if you use Intercom and have multiple campaigns, our platform will recommend using a specific campaign (e.g., Campaign X) for a particular persona. This simplifies decision-making by removing the need to overthink which campaign is appropriate for a specific group of users. Additionally, the platform will make it easier to identify users who should be sent to a CRM for further follow-up.

We aim to make analytics usage super simple and effective, eliminating the need for a data warehouse, reverse ETL, and creating filters and rules across tools like MailChimp, Intercom, and HubSpot. Each tool excels in specific areas, such as MailChimp for transactional purposes, HubSpot for marketing, and Customer.io for onboarding. Today, businesses must create filters and rules separately in each tool. At Humanic, we are the central nervous system that brings everything together, providing a seamless and unified analytics experience.

I can identify the individuals who would be a good match for our pricing plans with basic heuristics. How do you perceive the personalization of the product experience?

Email is like a starting point for us; this is the least effective of all the channels, especially for engaged people. Intercom does an excellent job of providing ten different modalities. You can put a banner, you can put a chat, you can do SMS and all of these different things, and it's out of the box. Furthermore, using feature flagging tools like LaunchDarkly in conjunction with Humanic can create powerful user incentives. For example, suppose you have identified the right type of user based on their engagement. In that case, you can offer them premium features for a limited period, say two weeks or 30 days. Instead of giving some bogus marketing email tips and tricks, I'm giving you the product. Humanic allows you to automatically identify the right user segments and leverage feature flags to enable specific features.

We are currently collaborating with design partners to refine this functionality. The goal is to create a mini content management system (CMS) where the marketing team can define rules for personalized offerings. However, no available CMS solutions cater to this specific need. Therefore, we are developing a general-purpose system that allows platforms like spatial chat to implement this personalization and test its effectiveness. With the aid of generative AI, analyzing these personalized initiatives becomes more straightforward, as it can provide insights and recommendations based on collected data.

It's a general-purpose system that allows SpatialChat or anybody like that to do that and test its efficacy. However, with generative AI, we can provide precise recommendations and optimize the effectiveness of marketing initiatives based on user preferences, channels, and modalities. This is an ongoing focus for us at Humanic.

I see how you differentiate from other B2B PLG products. As a bootstrapped company, can you share how you found and worked with your first customers?

Acquiring the first customers was undoubtedly challenging, as many entrepreneurs can relate. It involved extensive conversations, email outreach, active participation in Slack communities, and a relentless pursuit of connecting with potential customers who could truly understand the problem we aimed to solve.

There is no one-size-fits-all approach or secret formula for acquiring those initial customers. It requires a combination of persistence and a "hustle" mentality. It's about putting in the effort and continuously pushing forward. It's essential not to get discouraged by setbacks and to keep seeking individuals who genuinely feel the pain and are willing to collaborate with us to address it.

One significant factor that has contributed to our progress is our dedicated team. Our team shares the same vision and passion for our mission. With a motivated and united team, it is possible to achieve something meaningful. Even if you have numerous interested customers, progress would be challenging without a team committed to solving the problem, especially when the outcome is uncertain. The exceptional individuals on our engineering and go-to-market teams have played a vital role in our journey. They all believe in the significance of the problem we're tackling and continue to drive our efforts forward.

Our engineering team has eight members, while our go-to-market team has four individuals. We strongly focus on product development, blending engineering and product expertise. We define a "full stack" mindset not solely based on backend and frontend skills but also by deeply understanding the product we are building. This approach ensures that everyone comprehends the purpose and context behind their work. It's a crucial aspect of how we have structured our team.

Having the right team has been the most significant factor in our ability to build a product. While there is still a long way to go, this collective dedication has brought us to where we are today.

How do you structure your relationship with the first customer? Are you more focused on finding a design partner to collaborate on product design and gather feedback, or do you prioritize validating the monetization potential and their ability to pay for the product?

Our primary focus with the first customers is on data. We prioritize connecting their data to our platform because that forms the foundation for everything we do. Monetization and financial considerations are not our immediate concerns, especially in the initial stages. We believe in simplifying the data connection process and building customer trust. It's essential for them to feel confident in sharing their data with us. Once the data is connected, it opens up numerous possibilities for us to explore and enhance the product.

We encourage everyone to start using our platform. Users can sign up, create an account, and access the demo mode to explore its functionalities. They can also connect their data to see how the platform works with their specific information. Once the data synchronization is complete, a team member will reach out to provide support and assistance in setting up stages, personas and connecting marketing automation.

Our objective is to make it easy for users to connect their data and discover the insights they can gain from it. We aim to establish connections with all users who can benefit from our platform. As long as users are not experiencing significant issues, we proactively engage with them. At this stage, someone from our team, typically myself or another team member, will reach out to offer assistance. It's important to note that our platform is free to use, and users are only charged once they derive value from the product.

How do you monetize the product now?

We charge based on monthly active users. So we charge 299 for the first 5,000 monthly active users and then a hundred dollars for every set of 5,000 active users. And that will change if your monthly active users change. So we grow as you grow. If we stall or plateau, then we grow less. We identify users by at least one activity in the last 30 days, any activity in the last 30 days—so not dormant users but active users.

What's your suggested suggestion for B2B companies, how to utilize the behavioral events, and how to maximize the efficiency of these events for B2B business?

One of the first things is instrumentation. That's a starting point. So you need to spend some resources instrumenting the application correctly with Amplitude, Segment, Mixpanel, or whatever it is. And then you need either homegrown tools, Humanic, or a data warehouse where you need to put this data to build from there. But focus on instrumentation. Most people fall there.

Thank you. Thank you for the conversation, It’s pretty exciting, and we’ll look forward to seeing how things go.