A Transparent
Search Engine Model
With a strongly correlated model, you can predict what will happen next. Search engine models allow users to define, create, and deploy statistical replicas of any search engine environment.
With a strongly correlated model, you can predict what will happen next. Search engine models allow users to define, create, and deploy statistical replicas of any search engine environment.
Market Brew search engine modeling technology allows users to define, create, and deploy statistical replicas of any search engine environment. It does this by starting with a "generic" search engine model, complete with all the modern families of algorithms, representing everything from on-page to off-page ranking factors. Each part of the search engine model's biases/weights are then finely tuned by an artificial intelligence process called Particle Swarm Optimization.
Think of it as a search engine that can calibrate its own settings using machine learning to behave like any search engine you want.
Users can test their website changes in the model and can immediately predict how their actual ranking results will be affected, months before those changes show up in their rank trackers.
There are some key technical innovations that enable Market Brew to accurately and efficiently predict search rankings for the major search engines:
Market Brew includes the most advanced search engine algorithms, that are accurately calibrated against whatever target search engine you choose.
When search engines adjust their algorithms, your Market Brew search engine models are too. Even track algorithm bias/weight settings across time.
By having your own search engine model, you can command it to do almost anything you need. On-demand re-crawl, re-calculate, and even re-calibrate whenever you want.
Market Brew includes one of the most advanced crawlers ever built. The first line of code was written in 2006, it has since pushed the boundaries of modern crawling techniques with a number of patents to prove it.
It utilizes Chromium and the Blink rendering engine - allowing our crawlers to see exactly what the Chrome browser can see (and more). JavaScript rendering / modeling is no longer an issue. Prerender.io is no longer necessary.
The Market Brew crawler is a self-learning crawler. Because of this, it is lightning fast compared to brute-force crawling tools: typically able to re-calculate a 10 million page site in a few hours.
Our patented technology exposes the key values and ratios that drive all search engine algorithms.
These algorithms have been adjusted so their bias/weight settings are similar to the target search engine environment that was selected.
Simulate any desktop or mobile device, or even specific geographic locations, user agents, and more.
See what the search results will look like when you make an optimization to your target page. Did you get closer to your competitor? By how much?
Your search engine models use accurately modeled environments to calculate the statistical gaps in each part of the model between your target page and its competitor outperformers.
Every search engine environment can be a different mixture of algorithmic factors and weightings. What works in one environment may not work in another.
And because you can track these Boost Factor changes over time, your models give your team insight into how the target search engine is changing over time.
It then runs millions of predictions that identify the highest ROI opportunities, and auto-generates a task list for your team. Tasks are sorted by the biggest effect on ranking position.
Whether the team is seasoned SEO professionals, or new to SEO, every part of the search engine model is easily accessible. Users can fix, test, and immediately verify what those changes did to the model.
One of the hardest parts of SEO today is understanding how algorithmic updates affect your specific search results.
Market Brew automatically detects when the models diverge from the target search engine environment. When this happens, Market Brew re-calibrates itself, and because the search engine models store their bias/weight settings, users are able to compare the settings before vs. after to determine which parts of the search engine model are now more or less emphasized.
The search engine model forms a basis for a real-time environment that can analyze ranking depth or distance, utilize statistical gap analysis to determine exactly which part of the model your target page is weak in, and even give you automatic optimization tasks based on your team's capabilities. This gives you a positive expected value on every optimization you make.
Is fully customizable, allowing each user to mimic ANY target search engine environment (TSEE), like the US version of Google. They can upload their own metrics like revenue, conversions, and more to make the simulations as locally accurate as possible.
Is automatically self-calibrating. When the user first creates their search engine model, the algorithmic weights are run through a genetic program called "Particle Swarm Optimization". In it, each algorithmic weight becomes a particle in a swarm of other particles. This Particle Swarm Optimization process allows your search engine model to dynamically respond to the targeted search engine environment.
When Google changes, your search engine model changes.
For one client, within 3 weeks, we were able to get them from position 80 to position 1 on Google, and that honestly blew us all away.
We saw a huge spike in traffic...highly recommend it, one of the best marketing investments I've made.
Everyone who's doing Enterprise SEO should look at Market Brew. I've really fallen in love with their adaptive model approach.
I've used it for several years in client sites and in-house...couldn't give Market Brew a higher recommendation.
Market Brew is like if Google Search Engineers had built a platform to show us exactly what Google wants to see.
