Brewco uses AI to tell you exactly which factors matter for better SEO.
The company's system scores your site and competitor sites using neural networks, then helps you make SEO moves that improve rankings.
You can even predict how website changes will impact SEO using the company's AI-powered simulation of how Google works.
We spoke with Brewco's CEO, Jonathan Epstein, to learn more about this AI-powered solution.
In a single sentence or statement, describe your company.
Brewco accelerates the results from search engine optimization, and makes SEO impacts predictable, using AI
How does your company use artificial intelligence in its products?
Market Brew, our platform, uses AI in two primary ways.
The first is the use of particle swarm optimization—a multivariate optimization branch of genetic algorithms—to adjust the weights of the hidden layers of its built-in search engine neural network until its search engine results page (SERP) matches the Google SERP, thereby creating a simulation of how Google works.
The system crawls the target site and other competitors sites and scores them across a variety of factors, using various neural networks and other techniques for the semantic analysis components.
What are the primary marketing use cases for your AI-powered solutions?
You can use it to:
- Accelerate the results from SEO.
- Test site redesigns and other changes for SEO impact before launching.
- Identify key SEO gaps between the company's site and those of competitors.
What makes your AI-powered solution smarter than traditional approaches and products?
Because Market Brew builds a model that identifies which factors influence search rankings and by how much, it helps SEO teams to work efficiently, only on those factors that matter, versus a slower checklist or "best practices" approach.
The weights of the factors (semantic, internal linking, algorithmic penalties, domain rank, site and page performance) which influence rankings differ greatly from keyword to keyword, and country to country, and also change over time, which is impossible to model without using AI.
When you have a search engine model for your searches, you can also test changes before you launch them to determine their impact on SEO, which is key for risk mitigation, particularly on larger redesigns.
Are there any minimum requirements for marketers to get value out of your AI-powered technology? (e.g. data, list size, etc.)
The solution isn't suitable for startups which have little domain rank.
Who are your ideal customers in terms of company size and industries?
Given the nature of our products, they are best used by advanced SEO practitioners, at either the company or its agency.
While Market Brew works for any size company, we focus on enterprises doing $10 million or more in revenue, whether that's from sales, lead generation, or advertising.
SEO is important for all industries where searches are a key entry point, so almost every field is a good fit.
What do you see as the limitations of AI as it exists today?
It depends on the family of algorithms used.
Genetic/evolutionary algorithms are vulnerable to getting stuck in local maxima, and are only as good as the fitness function they are working to optimize.
Neural networks provide statistical insights but many users fail to understand that they are just that—predictions—and not 100% accurate.
And, for marketing (and our solution falls into this category), the AI solutions for one area (like SEO) may not be the ideal solutions for another area (CRO) since there is not enough integration of the various optimization systems (yet).
What do you see as the future potential of AI in marketing?
AI will continue to provide more optimal paths for marketers, across all marketing disciplines (including creative!) to reach their audiences, influence their audiences, and achieve the desired result (a sale, a lead, a donation, a pageview, etc.).
I expect to see greater synthesis of various AI optimization techniques across the full funnel, with reduction in the siloing of marketing departments as a partial result.
Any other thoughts on AI in marketing, or advice for marketers who are just getting started with AI?
- Don't be afraid to try AI solutions.
- Temper the recommendations of the AI against you and your team's experience. It's not perfect.
- Remember AI predictions are statistical in nature and as such will not always deliver. We're right 85-90% of the time. But not always. Manage expectations.
- Learn about AI and its uses or you risk becoming less relevant in your career.
- Break down the traditional silos of marketing—not the skill sets, but the silos.
Paul Roetzer is founder and CEO of Marketing AI Institute. He is the author of Marketing Artificial Intelligence (Matt Holt Books, 2022) The Marketing Performance Blueprint (Wiley, 2014) and The Marketing Agency Blueprint (Wiley, 2012); and creator of the Marketing AI Conference (MAICON).