How to Measure and Improve Content Quality Using AI
Time to evaluate your content marketing efforts. Which topics outperform the rest in terms of traffic to your website? Is content marketing actually moving the needle on thought leadership? And are there gaps in competitive content you can leverage?
Remove the guesswork (or deep dive into analytics), and answer these questions and more in a matter of moments. That’s the goal of MarketMuse (@MarketMuseCo), a platform powered by artificial intelligence that gives your content strategy an upgrade. We learned how by talking to Aki Balogh (@akibalogh), MarketMuse’s cofounder and CEO.
In a single sentence or statement, describe MarketMuse.
MarketMuse transforms how you research, plan and craft your content.
How does the company use artificial intelligence (i.e. machine learning, natural language generation, natural language processing, deep learning, etc.)?
We analyze web data to build knowledge graphs, similar to the Google knowledge graph. Knowledge graphs enable marketers to determine what relevant topics to write about and how to write about each topic comprehensively.
Then, by comparing the knowledge graphs (the ideal set of topics) against their site's content inventory, we build prioritized content plans that help marketers make better decisions on where to spend their time and resources. As a result, marketers are empowered to build engaging content consistently and at scale.
What do you see as the limitations of artificial intelligence as it exists today?
Artificial narrow intelligence (AGI) such as ours is excellent at pattern recognition and provides excellent intel. But it still needs a user to guide it and make decisions. To get great results, there's always a trained human in the machine.
What do you see as the future potential of artificial intelligence in marketing?
A few years ago I was a VC at OpenView Venture Partners, looking at big data investments. It became clear that there's an overabundance of information but a shortage of attention. AI in marketing helps better target messages so that the right information reaches the right person at the right time. It's a necessity because we're all drowning in noise.
What makes MarketMuse different than competing or traditional solutions?
Although other vendors have tried to provide this type of intel in the past, we're the only company that can provide high-quality and predictive intel on how to write about a topic comprehensively.
MarketMuse analyzes all web content, samples it, and builds pre-processed models that are called “high-dimensional vector spaces." Then, we analyze millions of articles on a given topic by understanding related topics and following links until we build sets of millions of content items.
Our algorithmic platform is a combination of:
- Bayesian statistical methods (a collection of algorithms that measure, for example, co-occurrence). Our methods are generally patterned from Latent Dirichlet Allocation which analyzes the connections between words in a vast corpus of documents.
- Natural language processing that measures, for example, the relationships between concepts in the English language and their specificity. For example – “dog” can be a pet, is a type of animal, has legs, etc.
- Graph analysis that looks at content as a collection of edges and vertices, in one document and across a collection of documents.
- Deep learning / neural networks that look to learn and to understand documents similar to how the human brain processes them.
Who are the prototype customers in terms of company size and industries?
We primarily work with B2B software companies, digital agencies, financial services and healthcare companies, as well as midsize and enterprise companies that have a strong culture of content.
What are the primary use cases of your product(s) for marketers?
One, craft a comprehensive article, and better understand its performance through content scoring.
Two, build depth of coverage on a topic across your site. Examine your content inventory in a topical manner and identify high-priority content gaps.
Three, compare your content quality to your competitors and identify strengths, weaknesses and areas of opportunity.
Finally, prioritize your topical gaps and construct a content plan with directed insights on what to write about next.
Any other thoughts on AI in marketing, or advice for marketers who are just starting to explore the possibilities of AI?
Don't shy away from AI. It sounds complicated, but it's simpler than you think. Experiment with new AI solutions. Every AI solution is just another way for marketers to become more productive. Read up on what's out there and try it out for yourself!
About Paul Roetzer
Paul Roetzer (@paulroetzer) is founder and CEO of PR 20/20, author of The Marketing Performance Blueprint and The Marketing Agency Blueprint, and creator of The Marketing Artificial Intelligence Institute and Marketing Score. Full bio.