Top data matching tools and techniques your business won't survive without

Top data matching tools and techniques your business won't survive without

Data matching techniques have been around since 1946, in some form or shape, but with the generation of large amounts of data on a regular basis nowadays, data matching and cleaning software has become a necessity for various businesses across the globe.

Data matching is the task of matching identical entries and merging them into a master database, and so on. It essentially compares two sets of data, looking for copies and consolidates them into a single record that contains all the details of that particular entry.

Data matching tools help businesses save money, time and resources. It shortens and combines lists of addresses and contact details, making the sales and marketing operations streamlined and systematic, where minimal time is wasted in making duplicate calls and sending emails to the same customer segment.

Speaking monetarily, a consolidated list of clients free from duplicates can save thousands of dollars for businesses annually, by cutting logistics and operational costs.

Integrating data in data matching software:

In a data matching tool, data is integrated into a single database from various sources. Some of the methods of data integration are:

1. Matching data: It catches and merges fields which are matching and belong to the same entry in reality. It eliminates duplicates and creates a single database of collected information.
2. Schema matching: It finds the structures and patterns in data pointing to the same chunk of knowledge that that data represents.
3. Data fusion: Forming single entries by merging two or more entries containing the same information

Why do you need data matching tools?

The world is constantly changing. From changing jobs to changing marital status to changing homes, the details and demographics of a person are constantly in a state of variation. When a number of these people become customers of a business, the business needs to have complete details on how to reach them for marketing, sales and customer relations. A business invests a considerable amount on these activities and expects a positive ROI. But if the data is polluted due to naturally occurring changes in the personal lives of the customers, leading to multiple entries for the same person, and these lists become a mess, rife with outdated details and duplicates. This is where a data matching tool comes in. These tools help save customer relations and save the business from the trouble of sending the same fliers to a single entity multiple times, which adds in cost, time and customer annoyance.

Challenges of data matching:

Cleaning and matching data comes with its fair share of challenges. While handling personal customer information, privacy is of utmost importance, especially in sensitive fields such as healthcare and banking. As the patient or the customer gives out his personal details to corporations or healthcare providers, these details are not always comprehensive or accurate, which can result in a delayed diagnosis or a late delivery of an important mail. Data matching software enables corporations to keep their collected data in check; it ensures that the data is complete, comprehensible and updated, without risking the privacy of the customers. With the help of fuzzy matching techniques, it overcomes the issues of unavailable unique identifiers and recognizes the same person twice in a database and records it as one.

Fuzzy matching, a data matching technique:

Fuzzy matching is a popular and widely utilized data matching technique. It works on the probability of the match and does not rely on exact copies in order to match and consolidate data. It can work with abbreviations, misspellings, similar words or typing errors, all fine-tuned by the user by tweaking the algorithm to find matches according to their requirements. Each business need may require a certain level of probability to make a match. For instance, the probability required to match customer names across various forms could require a higher probability than collecting sales data.

Data Ladder utilizes advanced fuzzy matching algorithms to clean and deduplicate data efficiently and quickly. Variations in spellings, address formats, typing errors and multiple records for single entities can be handled with ease with a data matching software of high caliber. It can perform data cleaning tasks with such speed and accuracy that getting them done manually by a data science team would be considered a terrible idea.

Benefits of employing data matching software:

Some benefits of using a data matching tool for your company are:

• It helps you look clearly at the bigger picture. Your data tells a story, and a data matching tool helps you listen clearly to that story by cleaning up the mess hidden between details.

• The business can get a realistic perspective at the customer base by looking at the clean numbers achieved by data cleaning software. This helps the business make better decisions in terms of marketing and pricing.

• Helps the business devise better strategies, cut costs associated with printing and posting marketing material, and improve overall relations with the clients by using a deduplicated record of customers.

• Saves time and resources: the entire business operations are made more efficient by organizing the processes according to the newly cleaned data.

• Highly sophisticated data matching tools lets you successfully migrate the data to a storage device of your choice, and readies it for your data lake so that it can be utilized for further analysis and prediction. Clean data is an excellent source of making future predictions and looking out for your competitors. From comparing marketing content to email lists, businesses can track their competitors’ advances and prepare beforehand.

I’m Javeria, an experienced web developer and B2B/SaaS writer specializing in writing for the data management industry.