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How to drive more revenue without all the repetitive work

How to drive more revenue without all the manual and repetitive work | Gil Allouche - Metadata

About Metadata

Gil: Metadata is the operating system for B2B marketers. Our platform automates all the technical, repetitive, mundane tasks that B2B marketers have to do in order to build a pipeline for their sales team. And it does it by executing campaigns creating target audiences, automatically monitoring those campaigns, and changing them based on pipeline results that show up in sales. It also personalizes the experience for its end customer by changing its website based on who the customer is and where they came from. All of these operations are being automated by AI, and even some of the content and the creative are automatically being generated by our generative AI component.

What is the biggest problem that you’re solving for companies?

Gil: The biggest problem that we’re solving for a company is, first and foremost, creating a profit. For the marketing organization in B2B companies by applying economical methods and experimentation on their campaigns. Make sure that for every dollar that you put in, you get more than a dollar out in revenue, and by doing constant experimentation, it’s like trading stocks at high velocity, you have a lot more optionality. And so you can fine-tune out of 10,000 experiments to the 500 that generate the most pipeline for the lowest cost. The second thing that we solve for is making because making marketers happy again by moving them away from technical, repetitive, mundane tasks to creative ones.

What are the products you offer?

Gil: The full platform that we offer includes all the modules, but if you want, as a marketer, to start small, you can use MetaMatch. If your advertising is not in the hundreds of thousands and you are going to run everything natively by using MetaMatch. It’s our audience creation product. You can guarantee that every dollar that you spend, you spend on the right companies, and within those companies, you spend them on the right personas.

The Metadata platform is the full platform with execution and experimentation, which also includes generative AI, so an ability to automatically create content, create text variations, and so on and so forth. And then finally, we have Reactful, which is by an acquisition that we made last year, and that is our personalization product that allows for a marketer without changing their website.

They can apply experiments on their website and use all kinds of data that are otherwise unavailable because Reactful can tell you which company is visiting your website, even if they didn’t sign up. Who is the buyer? What campaign did they come from? Did they come from Google? What keywords did they click on? So all that information is available for you, and you can use it on the spot in real-time to optimize and dynamically change your campaigns.

Why did you acquire Reactful?

Gil: We acquired Reactful because we identified that in B2B, the experience of buying is so out of date. It doesn’t matter if you are a prospect or a customer, it doesn’t matter if you come from Microsoft or from a five people startup. You’re going to get the same experience on the website. While if you’re a consumer and you’re buying products like Amazon, imagine Amazon and Netflix, they know everything about you. And so the Netflix website or the Amazon website is completely customizable to you, particularly to who you are or to who I am. And so what we’re doing is we’re trying to apply the same kind of intelligence to the B2B buying world and changing the buying experience to be more sophisticated and personal.

What is the Marketing OS?

Gil: The marketing operating system is our vision of having a place for every B2B marketer to log in in the morning and log out at night. A place in which all of their operations are stored. They can see all of their total address in the market, they can see all of the campaigns that are running. They can see all the playbooks and all the best practices from their industry. People can see all the results, money in, money out in all the customer journeys, and what every customer, whether they signed up or still anonymous, is doing on their website. There are a lot of components to the B2B marketing world, and we’re trying to create a home for them, or they can have a center of execution.

Best Metadata features

Gil: Historically, experimentation is our biggest feature because no one has built that in the B2B world. If you want to run experiments, and as a marketer, you better run experiments because you’re gonna find out a lot of golden nuggets. You’re going to find out channels that are generating a lot of pipeline or campaign types or audiences, and so on and so forth. And so, experimentation is something that is unique to Metadata. And by offering it in such a simple methodology, we get marketers who never did experiments before to now experiment at scale. That’s one of the things I’m mostly historically excited about.

Currently, if you ask me, what I’m most excited about that we’re releasing is the playbooks. If you’re a new marketer, or even you have a few years other than you under your belt when you use metadata, now you get all the best practices and playbooks that were written by the best marketers. These are not the only playbooks that we came up with. These are playbooks that people like Dave Gearhardt came up with or other marketers who are very successful, and they put their tactics in a full playbook in a template.

And now we’re coding that template inside our platform so that you start essentially 80% of the companies already built for you based on best practices that are proven, and you just have to fill in the blanks for your particular situation. By doing that, you’re not just getting a technology, but you’re also getting into the industry’s best practices. To me, that’s going to be one of the major innovations in the B2B marketing world. People don’t start from scratch.

Metadata costs

Gil: We’re actually changing the pricing as we speak. We’re still a very dynamic startup, and we’re trying to cater to this tougher economy, but with Metadata, I would say the average price to work with us is about $50K give or take, 50 or so depending on how sophisticated you want the platform to be. And how complex attribution how much spend you’re putting in there? Are you applying personalization? Are you going to use the buyer in data?

Depending on how many premium features you are going to use, it is around $50,000.if you are a smaller company, you can actually start with our free trial of Metadata. You get one month of free trial, and you get to experiment with the product to see if it works for you and if it generates a positive return on investment for you. And if you want, you can even start using the product and pay with a credit card without even talking to sales. And so we have that entry point to the, into the product if you’re a smaller company and have a smaller usage.

How one customer generates over $7M a month using Metadata

Gil: When we were going through our pricing, we did some analysis to see how much value customers get from the platform, meaning how much sourced pipeline they generate using Metadata pipeline that otherwise wouldn’t be available. And we learned that some customers, I can’t mention the name, but we have one customer who is generating $7 million of sourced pipeline every month from the platform.

This is crazy because they don’t pay anything close to even 10% of that or 5% of that a year, you know? And so I thought that was wonderful because that’s proof that experimentation is a scientific approach to guarantee gains. We’re applying that scientific approach to marketing, and that makes marketing scientific and numbers based. The use case to me is if you’re a marketer and you’re a performance marketer, you are a revenue marketer, at the end of the day, nothing else matters. You need to generate pipeline in a profitable manner. And that is the biggest value that marketers and their CFOs and their CEOs get from using the.

How the use of AI makes Metadata different

Gil: The MarTech space is one of the most competitive spaces out there. I think there is something like 9,000 different marketing technologies available out there. When I started the company when I saw this vision of all the companies that are in the. I was like, this is not gonna be easy. This is a very, very busy space. But you’re asking about differentiation. In the B2B marketing space, there is no single company that built its technology with experimentation as the basis. S

With Metadata, there are millions of actions being taken every day without you flipping a finger because artificial intelligence goes through all the possible scenarios and executes them. They don’t recommend you, they don’t give you data. They’ll give you the insight, and if you really want to, they’ll ask for your permission before it. But most of the time, our customers, because the confidence rate is so high, the AI will just go and execute for you.

And because there is a full feedback loop with Salesforce, the CRM, knows what’s successful and what’s not. It doesn’t have to ask you, was that a good idea? Was this good? Was this bad? It can see in Salesforce, did we generate pipeline this, this pipeline created revenue or not. If you did, we now mark this one as a success, and we create more derivatives. And if not, even if there are impressions and clicks, and leads, who cares? If there is no pipeline and there is no revenue, the experiment is done. And so that’s one of the main differentiated rates that we have. We have many patents on this particular innovation. And that’s just one of the things that we’ve done.

Why they chose email-based targeting, and why cookies are going away.

Gil: One other differentiation that we have is that our entire targeting is based on corporate and personal email. That means that while other companies are using cookies, which are going away from the world to target individuals and companies, we’re actually using people’s personal and corporate emails, and that’s how we match them on different platforms. Whether I find you on LinkedIn, AdWords, Facebook, TikTok, or Twitter. I know that you are X. I know that it’s particularly you, and so I can serve you whatever campaign I have without having to worry that I may be spending and wasting my advertising and marketing dollars.

What is the future you see with AI in marketing?

Gil: I think AI is gonna take over a lot. I think the immediate things that are going to be taken over by AI, and you’re going actually to see them in the platform even this year, is automatically creating. Not just text variation for your ads but also automatically creating visual creatives. Instead of having to design your ad, the system is automatically going to generate the visuals for you because it already knows what kind of message and who is going to see that message.

And then the next level is it’s going to automatically start generating content. I mean, ChatGPT already knows how to generate really good content. It’s more of a template today. I think as time goes by, it’ll automatically generate very, very SEO-friendly, high-quality content. And I think as the AI is going to evolve, humans and marketers are going to really spend all of their time on fun, creative, strategic tasks, and they’re not gonna worry about attribution and UTM tags and executing campaigns and AB testing and this and that.

Why did you choose to start Metadata?

Gil: I started the company seven years ago, and we spent the first three and a half years or so just building intellectual property, just building the technology. It’s a little monster of technology. And then we started selling. In the last few years, we hit a nice growth curve. We chose this niche mostly because of my background. I’m a robotics engineer in my background. I’m a software engineer with a robotics background. I worked post my graduate school, I worked as a VP of marketing in a few B2B companies, and I realized that the technology is available to automate the vast majority of tasks.

I use my software engineering and technical skills to automate a lot of my work and apply a lot of the methodologies that we have in the software. As a marketer, I was very successful as a marketer, and at some point, I decided that I could make myself a commodity so that no one had to hire me again. They can just buy these pieces of software, and they can focus on the creative tasks, and the software will focus on the technical tasks, and that’s basically how it came to it. Right now, we’re about a hundred people across about 20 different countries, and in our latest funding round, Series B, we raised around $40 million.

Have you found a strong product-market fit?

Gil: I think we found a very strong product market fit, and I think the market is slow, I think it’s just the beginning because the vast majority of the customers that we have are still early adopters. There are power users who see, you know, we have more than 20 customers, former customers who are actually employees of the company, and former customers who are investors in the company. And that tells me that we are still in the very early adopter stage. We are starting to see that more and more marketers understand that AI and experimentation are the waves of the future, and they’re using Metadata to start doing their work. I suspect that in the next few years, we’re going to see a crazy amount of AI and experimentation in B2B marketing. I think we’re just kind of at the beginning of that curve.

Challenges faced since starting the company

Gil: At the beginning of the company, survival was the biggest challenge. You build a piece of technology that is very early to the market, and your biggest job is just to stay alive, just to make sure that you still have money, to pay your employees’ payroll, and keep the lights on. Once you hit product market fit, you have to constantly balance between growth and efficiency. Growth and efficiency.

If you ask me, personally, what’s the biggest challenge, is just managing my own psychology. Being okay with difficult decisions and difficult conversations, and believing in yourself and your intuition. Not making decisions out of fear. YManaging people effectively from a good place, from a place of love. Not creating a toxic culture but creating a collaborative, open, transparent, non-political culture. All of those elements are elements are things that I invested a lot in, and they didn’t come naturally. I didn’t know what to do, I had to learn, I had to read books. I had to talk to a lot of CEOs and founders and my investors, and my board members to really learn how to do that. And slowly, over time, I got better.

The 3 growth tactics Metadata used to get new customers

Gil: I would say the first one is using conversational ads, which is a combination between InMail and chat. Going to particular people within particular companies and hitting them up with offers. That’s one very particular tactic. The second one is content, we create really good, valuable, honest content on our website, and it attracts the right buyers. Actually, we find that those leads, those demo requests, are the most qualified. And they convert the most to sales.

And then, finally, we realized that once we opened up the floodgate. With the MetaMatch free trial, you can start with $300-400 per month. You can start using a piece of the platform. And once we opened that up, so many new prospects and customers came into the product. And so that is becoming one of our biggest legions as well. The tactic is that we are offering a cheaper product, you don’t have to talk to sales, you just run your credit card, and boom, you get access to the platform.

What’s your future vision?

Gil: I want to keep growing metadata, I want to keep growing myself as CEO and grow the people who have been working with me. We have lots of people who have been working together for four or five years in the company, which I think is unique. I think we have at least several more years to go before heating the inflection point before we get to the 1 billion valuations or so, and then we can choose our destiny.

We can go the IPO way, we can go the strategic acquisition way, or we can become a profitable private company that gives dividends, so we can really choose our way. Right now, we’re laser-focused on optimizing every KPI in the company to make sure we have sustainability and high growth over the next few years.

What is your story, Gil?

Gil: I started coding software when I was really young, probably around eight years old or so, when I wrote my first line of code. I studied game development, and as a hobbyist, I used to build games and game creators. Back then, I had a small business when I was younger in which I fixed computers for a living. That brought me a lot of nice revenue, that was my first touch in entrepreneurship. When I was really young, about eight or nine years old, I was selling fact records that I imported from France. But my first legal business was when I was fixing computers.

And that was my first kind of experiment with being my own boss. And I really liked it. After my military service, I worked in robotics, and then I worked in financial services as a software engineer for a couple of years. I really liked it. I was good at it. But I realized. I had to get into the business side because I was clueless. I just knew how to build products, and I had no idea about the business side, marketing, sales, or product. So I decided to go to the US, I went to Boston, to a place called Babson College, which is an engineer entrepreneurship school to learn how to start companies, and yeah, then I had two failed attempts to start a company, and the third one was Metadata.

You moved to the US for college – was it worth it?

Gil: That’s a difficult one. I do think the college helped me because it was my ticket to the US, and it taught me some things. Some professors were immensely helpful. They gave us a really good experience. A teacher in marketing was like – you guys either do the homework, or you start a company, and you close a deal. If you close a deal, you get an A, or you have to do all the homework. And I never liked to do homework, so I ended up starting a business and selling you the product. And I was like, this is awesome. I had classes like this that were really helpful, and they did get me somewhere. Did I need to pay a hundred grand? And go to two years of school to do my MBA to start a company. No. I could have probably done it without it, but it was a nice springboard.

What’s your best piece of advice for a starting founder?

Gil: I would say my biggest piece of advice for starting a founder is to get started. Don’t wait. If you’re ready to start a company, start it today. You’ll figure out everything you have to figure out on the way. Well, you are building a company, so don’t wait. You don’t have to go through anything before starting a company. And the second thing is to surround yourself with a support system of advisors, investors, consultants, board members, or whoever you need friends, to make sure you have someone to go to when things are good, but most importantly, when things are not good so that you can ask them for advice and they can keep you honest. That’s my biggest advice.

I’m also an advisor. Not too many companies. There are a few companies that I pick and choose every year, usually no more than three that I advise the CEO. And I’m also an investor in a few startups selected startups, usually in my space, where I can be the most helpful.

What’s your favorite SaaS product?

Gil: HubSpot is one of my favorite products. I think it was really well-built, and it’s been the best marketing automation software in the past 15 years.