USA Local Search Local & Multi-Lingual Search Engine Network Development

Solution

How DOYJO improved the path.

You may remember, back in 2003, Google was the biggest search engine but Google's local search favored and returned results from the local Yellow Pages sites and other directories. The results were pretty much useless if you were trying to find the actual website of an actual local business.

Local search was going to be the next big thing and Google had not mastered how to organically crawl and rank actual local business websites, so Brian Bateman as SEO LLC accepted the challenge to build the best local search engine.

As you might imagine, it is no small task and it was very expensive for a web designer to take on such a project out of pocket, but the resulting search engine network changed local search forever.

Within 6 months, Brian had developed the USA Local Search search engine network and over the course of the next 6 months wrote crawling rules and ranking rules (Google calls them algorithms) to favor actual local business websites and for a time, USA Local Search returned far superior local search results.

When Google realized that they had a contender for the local search market, they used their investor's money to buy billions of dollars work of data collected by the mailing list company, Info USA rather than create their own crawling & search algorithms to compete organically in the local search engine market.

The hidden benefit to Brian Bateman personally was that having had the opportunity to actually build search engines and writing the algorithms to crawl and rank local business websites is that he became the only SEO in the world to have actually engineered search engines and written crawling & ranking rules for search results. That education in true organic search engine optimization was certainly worth the money invested in engineering search engines because Brian is able to see things from a search engine perspective with deep insights into what is going on under the hood of search engine algorithms.

Challenges:

Create the Best Local Search Engine

Return Only Results from Actual Local Businesses and Organizations

Create Algorithms to Prevent Crawling Black-Hole Websites Like Yellow Pages

Write Algorithmic SPAM Rules to Immediately Downgrade SPAM Websites

Build Data-Center from Ground Up

Key Services:

Network & Configure 54 Front-End Servers & Database Servers

Install Full Fiber Optic ISP

Leverage SQL Server Enterprise & SharePoint Portal Server Enterprise

Install Intelligent Battery & Gas Generator Power Backups

Re-Write SharePoint Portal Server Enterprise to be Internet Facing

Develop Search Engine Per State

Develop Search Engine for Non-Profit Organizations

Develop Search Engine for Government Agencies

Develop National Search Engine Drawing Data from Each Local, Organization & Government Entity

Write Crawl Rules & Ranking Algorithms

Outcomes:

Created the Most Accurate Local Search Engine in 2004

Superior Local Search Results to Google's Local Search

Created Local Search Database by US State

Created Additional Search Databases for Non-Profit & Government Agencies

Local, Non-Profit & Government Search Databases Fed the National Search Engine

Created a Similar Multi-Lingual Search Engine Network for the Liberian Government which Included All Countries of Africa in their Native Languages

Forced Google to Buy Data for Their Local Search Results

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