I had the fortunate opportunity to attend the largest SaaS conference on the planet last month, SaaStr Annual 2018. I ran into Aki Balogh, CEO of an up and coming SaaS startup called MarketMuse.
While I visited nearly all of the booths at the massive SaaS conference, the MarketMuse booth stood out, as it was nothing I had seen before. They are SaaS-based platform powered by artificial intelligence (AI) that serves as a “highly relevant research assistant”. Their platform helps digital marketing firms and companies with large copywriting teams scale their research and copywriting efforts so they can produce stronger, more relevant content at a much faster rate.https://www.bayleafdigital.com/b2b-digital-marketing-tips-seo
AB: Oh yeah it was fantastic, the best conferences for us are the more content-focused conferences.
SaaStr was like an experiment for us, we wanted to get some West Coast exposure, see who you meet out there, but that said it was great. I mean we were completely busy almost all the time. People were coming by every few minutes and the whole week.
We have over 100 customers and we’re growing fast. We just secured funding about a month ago and stay laser focused on making meaningful connections, so we have to pick and choose who we spend our time with.
We try to spend time with people who are familiar with content, have a background in SEO, those who are really the customers and type of partners that we can make the most successful.
The conference was a really good showing in terms of fit. And people were really excited about what we were doing.
AB: So MarketMuse is an AI powered research assistant for content creation.
It takes the heavy legwork out of researching how you are going to write about a topic. Of course, the goal of content marketers is to write high quality, comprehensive, deep, rich content covering topics that are relevant to the products and services that we provide.
I come from a software engineering background and used to design decision support systems for the Fortune 500. Then, I went to a venture fund where I worked with big data, machine learning, and marketing automation. I sourced an $18 million investment into a social media platform called Spredfast, but I was very interested in big data and the AI side of things.
From there, I went to a startup where I was writing content on analytics and I ran into this challenge on how to write great content on complex topics like databases and how to do a good job.
I realized there are a lot of tools out there that can help you with keyword research, it can show you the competition behind the keyword research. And you have enterprise SEO dashboards that can show you what keywords you have on what content and what’s performing kind of historically, but you don’t have anything that actually helps your write the content.
So, then you have to piece it all together, so you end up using your existing domain expertise, so whatever you happen to know about that topic. Of course, people aren’t perfect, so even if you have been doing something for years it’s still incomplete.
Secondly, people just Google them out. They read the front page, they read competitor’s pages in the top 10 top 20 and they try to piece it together. I realize the Web has trillions of content items, if not more, and we should just mine that.
Even for a topic we can just go to the web download tens of thousands or even hundreds of thousands of content items on that topic crunch it and build this blueprint we call a Content Brief but it’s actually a blueprint that shows the writer exactly how to write the covered topic.
AB: It’s actually a branch of science called “topic modeling” that goes with given a set of documents, what are the main topics and the most important topics in that content, we have to do those kind of prominence what topic comes up often, co-occurrence of what topics come up together, you know just like natural language processing, so how common are particular topics in the English language.
For example, how generic or how specific the topics are. We built a topic model system that chooses a variety of approaches, I think we have about seven different variety of approaches at the moment and we really just calculate relevance.
So what we do in our engine is something Google does in theirs internally in their systems as well. A few years ago Google bought a company called Freebase for over a billion dollars. Freebase has the same kind of semantic knowledge base of how everything relates to everything and they snapped that into search and now they call it the Google Knowledge Graph.
They can map how close to the related topic search it is and they use that to evaluate the quality of your content and your style of fresh topics, etc. And the engine we built is very similar to that, diving deep on individual topics for marketers.
AB: We came to market about a little over 2 years ago, so October, 2015 was when we first started getting out there.
Since then, we have built a suite of products. The first product that we built was Content Analyzer which lets the marketer measure and improve the quality of one content item.
“Given a topic and a content item, we provide a numerical score, called the content score that tells you how well that content reflects that chosen focus topic.”
So, we can say, “This is two points…” and then we look at the competition on the top 20 Google searches and say, “OK, this one is 60 points”, and then you can really drill down and see on a detailed level why.
So this competitive content talks about ABC-related topic that you don’t cover… or perhaps you talk about it but make it very tactical. So now you can better understand your content as a collection of related topics.
For example, say I’m writing about SaaS content strategy, we will also possibly talk about anything like copywriting, lead generation, or SaaS social media marketing or you know Content Marketing Institute or similar related concepts.
That was a general example but you can put anything in the system and it will build this high fidelity content knowledge graph about it.
So that was our first SaaS product that is still available today.
We have a second product called MMX where we look at your entire site, measure the quality of all your content, identify all the blind spots and the low quality content you have, prioritize it against the search SEO impact framework and then list out the next twenty things you should do.
And in terms of priority, we build a content plan that shows you exactly how the writer should create the new content or optimize the existing content.
AB: Yes, we actually have a content grader, but retired it for some cleanups and will be relaunching it shortly. But essentially we have the same kind of capability – we look at what content score is and show you how to improve it and through that you have sort of a free calculator and then the full platform kind of goes from there.
AB: Yes – that’s essentially what we do. We have got a very wide range of interests at the same time, so it makes sense for us to focus on companies that have a greater degree of sophistication.
What happens in that market which I’m sure you appreciate because you have seen this a lot, everyone would like more traffic, more relevant MQLs, SQLs, leading to more customers.
Everybody wants it but not everybody has the capability to generate that content focused strategy.
“So we have to prioritize our time on the people who are more sophisticated content planners and content strategists.”
Say for example, two or more content writers are creating long form content like ebooks, articles, whitepapers, etc.
We can accelerate a lot more than we have to piece among the basics, they are not really equipped for that.
We have been spending most of our time with large content publishers with writing teams in the hundreds and thousands where their team has a hundred content writers in one business unit.
That model is very compelling which makes sense for us to make that relationship extremely successful.
We have been getting a little pickier on that front and we are also launching an agency partnership program so we are looking at hard working agencies and arm them with sophisticated collateral so they can use MarketMuse internally as well as with their client because it really accelerates the agency’s business.
Those are some of the things we are trying to stay closer to people who are the content mavens already.
AB: Yes absolutely, there are two main classes of benefits:
The Content Analyzer SaaS tool is a do-it-yourself tool that sounds kind of expensive but requires some manual hacking and hashing to put together the brief.
We have been told that with our delivered Content Brief, it saves copywriters six hours a day from having to do that research. And the results are of such high quality, you have that peace of mind that you have covered everything. You are not really missing anything important in covering that topic. So the first big benefit of saving several hours per brief for several hours a day really adds up. And the second side of it is the search impact which is huge.
For example, we have a case study that talks about 400 content items wrote the brief for each one, we had 10 people who made the changes for a two month period and as a result it tripled in ranking, so he went from 42,000 ranking keywords to 120,000 to be exact.
AB: You said it the right way, we are Neil Patel’s secret weapon. He hasn’t quite said anything about it as he doesn’t want to give it away. The case study really does show the difference between prior to MarketMuse the page look like X post MarketMuse it looks like Y.
As a result the ranking has significantly increased in a very short time.
AB: We grew over 5x last year.
BLD: Congratulations that’s great!
AB: Thank you. It really took off. My cofounder Jeff, prior to joining MarketMuse he consulted for a major private equity company. He was an advisor for the portfolio company and before that he built and ran a 30 person content optimization team at a company called Tech Target.
When Jeff joined in October, 2015 he started to improve our product and started building the content analyzer and then also started doing the content filing side the more sophisticated enterprise technology.
So in 2016 we were mostly in product development and adding customers to help the product weapon. And last year we brought in a sales team and really started going after the market opportunities and we found that there is tremendous demand in seven different markets actually.
We sell B2B, in-house marketers, enterprise software companies, financial services, life sciences and healthcare but really it can also be B2C, in-house marketing teams.
We sell to ecommerce, it’s its own separate vertical with product descriptions, category descriptions. We sell to large corporations, we have API integrations so we sell software tools as well as content quality tools. So it really is for anyone who really cares about content whether it’s for search or for thought leadership.
AB: Oh yeah, my life is nothing but hurdles.
One of the challenges we face is how do we articulate what we do because we have two problems we are looking to overcome:
“People are just not aware, they just don’t know that it is possible to mechanize content creation.”
That is a concept that people are not familiar with, it’s kind of like you know about self-driving cars…perhaps they have heard about it and think that’s interesting but think to themselves, “That’s never going to work.”
People often question whether this is really going to work. We look at it and then they wonder if this is going to eliminate jobs, which it doesn’t. My view is that it can double and triple the amount and quality of content produced.
But we never see any of our software eliminating jobs, that’s just another thing people can think. Since we are a marketing technology company, and there are over a thousand SaaS and marketing companies, a lot of them are basically rehashing the same business model.
But because we are in SEO and lead gen, we are on that side of the spectrum where it is easier to pitch ourselves as an SEO tool, which is perceived as a little bit of a snake oil.
So it’s important for us to be able to punch through that noise and tell people what we do and articulate that message clearly and tell that brand we’re your trusted research assistant for content.
There is just way too much noise. CMOs are getting pinged about 10 different tools a day there is a lot of confusion and it’s getting complicated to punch through that noise.
AB: Luckily, we are content nerds and can write it down. We write case studies.
Case studies like the Neil Patel one I mentioned earlier really describe concrete examples of what we do.
We have ventures participating and then we have two more that are looking to jump in. Educating the market teaching people about content quality is actually an easy thing to prove.
Because if you write content that people love reading about, they learn a lot and they really want to search. Content quality is an obvious answer and the implementation is hard. We can tell that story, align it, and just show people how to write great content.
