Fuzzy Match Algorithm

When it comes to matching incoming marketing leads against CRM accounts a simple string match may be sufficient for some people, but is that enough? What if you were told a thorough operation has to include taking out common legal company suffixes, handling special characters, and being able to identify acronyms and nicknames common in the business world. It also has to be able to recognize popular stock quotes, identify what entities have undergone mergers or acquisitions, and take into geographical sensitivity into account when matching leads. Wouldn’t that be much better?

Over the years, Lead Angel has developed a state-of-the-art fuzzy match algorithm that is not only fast and accurate but also flexible to fit different needs. It’s not a final formula; behind the scenes Machine Learning also allows Lead Angel to be able to improve that algorithm over time. Fuzzy Matching accuracy is achieved by hundreds of matching rules and thousands of data points. The following are the key areas where rules have been implemented :

Legal Suffixes

Not all companies have the same names or backgrounds. However, company suffixes such as Inc., Corp., LLC, and Ltd., etc. don’t serve much purpose when it comes to matching searches. Lead Angel’s algorithm makes sure these suffixes are ignored.

Special Characters

Special characters like “&” and “AND”, “AT” and “@” are practically the same. LeadAngel’s algorithm is designed to ignore these as well as other special characters like commas, periods, etc. Since company names can come in other languages you should expect to encounter accented characters like “é”, “ê”, “ç”, “ñ” and “à”. With LeadAngel’s system, items like these are controlled in such a way to produce desired results.


Are IBM, I.B.M., and International Business Machines the same? In LeadAngel’s search algorithm they will be. It is able to identify popular acronyms with or without spaces, with or without dots, etc. Are you looking for Ingvar Kamprad Elmtaryd Agunnaryd? That is actually shortened as IKEA. Dalsey, Hillblom and Lynn is more popularly known as DHL, just to name a few.

Popular Names

Not all big companies or businesses were previously known as they are called now. For example Quantum Computer Services is now called AOL, AuctionWeb is now called eBay, and the Marafuku Company is now called Nintendo. LeadAngel’s algorithm will be able to recognize popular names and previous names companies went by.

Web Domain

Over the course of its operations, a business may put up new websites and abandon old ones several times. It may even set up a domain to help direct customers to the right website. A record with a missing company name but valid business domain presents no problem to LeadAngel’s match algorithm.

Geographical Sensitivity

LeadAngel’s match algorithm searches all over the world, but priority is given to geographically closer company location. So in case of multiple matches you don’t have to worry about looking at results that are actually inaccessible to you, or located halfway around the world.

Mergers And Acquisitions 

Here’s what happened earlier in 2017: Extreme recently bought Avaya’s Networking Business Unit, Xerox recently bought MT Technologies, and Palo Alto Networks recently bought LightCyber. Are other algorithm systems familiar with business mergers that took place recently? LeadAngel’s search algorithm will know what companies already merged with what, like Youtube with Google, and Taleo with Oracle, etc.

Customization And Performance

LeadAngel’s fuzzy match algorithm is designed to be flexible to fit your needs. You can turn on or off some of the rule to adjust the match confidence level. Stricter rules means fewer results, but these results will be more closely matched to what you are looking for; relaxed rules means there will be more results to choose from, but only loosely matched to your criteria.

Also, if there are certain companies that always go together for your business (due to existing relationships), or never go together, these can be defined in custom “Always Match” or “Never Match” rules.
How fast does LeadAngel algorithm and architecture work? It is designed to match more than 7 million records per hour. This will come in very handy when running a segment based on a company name match.

As you already know, lead generation is important for making sure your sales pipeline is constantly filled with potential customers. The issue is that many leads are not ready to immediately make a purchase. Some of these leads will be ready down the road, while others may never be ready to pull the trigger. For those that just need more time, you need a lead management strategy that nurtures leads until they are ready to make a purchase. You need software that digs deep and has the ability to filter through and analyze every piece of data against Customer Relationship Management (CRM) accounts.

The Fuzzy Match algorithm uses cutting-edge AI technology to determine the relationships between different data points, going far beyond a simple string match. It is able to determine even the smallest connection and interpret the relevance against the rules you have defined using the intuitive interface. Marketing and lead generation are constantly changing. For this reason, the Fuzzy Match algorithm is constantly improving behind the scenes to help you stay ahead of the game and to ensure the desired results with a high level of accuracy.

Fuzzy Match offers fast, reliable, secure, and customizable features to meet your organization’s needs and goals. Rules and data dictionaries are applied to match company names based on the client’s fault tolerance settings which can be set at:
  • Add content - use ENTER key for new LI line.Strict match
  • Moderate match
  • Lenient match

There are 14 basic rules that are the cornerstone of the Fuzzy Matching algorithm.

  1. Email and web domain match – Fuzzy Match is able to detect relationships between email domains and web domains that ultimately link to the business. This is even true of companies that have more than one email domain.
  2. Company name match – This algorithm has the ability to use exact string matching.
  3. Suffixes – Fuzzy match recognizes that company suffixes are not a distinguishing feature between businesses and therefore understands they are insignificant.
  4. Geographical Spellings – Geographical abbreviations are recognized as being the same as their spelled out counterparts. For instance, the U.S. is the same as the United States.
  5. Whitespace – There are instances in which one company name will at times be spelled with a space and other times not. This algorithm is able to ignore the space and realize it is the same company with or without the space.
  6. Nicknames – Fuzzy Match recognizes popular, shorter names of a company as being the same as that company. For instance, Kentucky Fried Chicken is more popularly known as KFC.
  7. Names Change – It is not uncommon for company names to change over time due to rebranding efforts. Both old names and the current name are recognized as being the same company.
  8. Acronyms – As with company names, acronyms are recognized as well. Did you know that AOL used to be called Quantum Computer Services? Fuzzy Match identifies both as being the same company.
  9. Mergers – Mergers and acquisitions can cause confusion, but this algorithm is robust enough to understand when these occurrences have taken place between companies. For instance, in early 2019, Disney acquired 20th Century Fox. The algorithm is able to recognize and understand that this merger took place.
  10. Inferred Industry – An inferred industry is assigned to the records during matching such as the healthcare or high tech industry based on words such as “pharma” or “technology” that have a high association with their respective industries.
  11. Stock Codes – The software is able to identify stock tickers and match against master records for that company.
  12. Common words – Settings can be adjusted to ignore common words that may be part of the company name, yet not a distinguishing factor such as “group”. For example, John Doe’s Real Estate Group.
  13. Geographical match – When there are multiple locations of one company, the closest geographical location is the one chosen.
  14. Special characters – Matches will be detected even when special characters are used versus the whole-word counterpart. It is recognized that @ and “at” have the same meaning and act accordingly.

This smart and intuitive platform even allows for tiebreaker rules to be set when potential duplicates are found. By default, the account with the most leads, contacts, and opportunities is chosen. However, custom tiebreaker rules can be created to fit your company’s needs.

Lead generation and management are not one-size-fits-all. Fuzzy Match allows you to define rules that work for your business and decide on how strict the rules are. It is important to note that the stricter the rules, the fewer matches you will produce. The future of your company depends on your ability to generate leads and nurture these leads until your company is able to close the deal. Using a reputable vendor will help you reach your goals faster. LeadAngel today and schedule your half-hour consultation session!