Data Matching: Definition, Process and Benefits
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Many organizations collect large amounts of electronic data about consumers, products, vendors and competitors. One way an organization can refine its data and identify trends is by using a data matching software tool. If you work in an administration, marketing or leadership role, learning about data matching can help you develop procedures to enhance the way in which you use information. In this article, we define data matching, explain how different industries use this process, describe how it works and list several key benefits of using these tools.
What is data matching?
Data matching is a technological process that compares different sets of data to find matches. Organizations that process large amounts of data might have a data matching tool built into their server, database or another system. They might also use a separate data matching program, which may include analytics and business intelligence features. For example, a government agency might have a data matching tool that analyzes individual entries in their database and matches entries that have the same social security number or driver's license. This process reduces the number of duplicate accounts in the database.
What industries use data matching?
Data matching can be a valuable tool in a wide range of industries, including:
Retail: Companies with customer databases might use data matching to decrease duplicate customer accounts and identify purchasing trends across different groups of consumers.
Government agencies: For government agencies, data matching tools can ensure that residents using public services have a single online account for census and registration purposes.
Professional services: Companies that offer professional services might use a data matching tool to identify spam accounts in their client database and detect user trends.
Education: School districts might use data matching tools to merge student accounts across schools and identify demographic trends in test scores and graduation rates.
Health care: Data matching is common in medical systems, where administrators merge patient accounts at different hospitals to centralize information about a patient's medical history and drug allergies.
How does data matching work?
There's a wide range of data matching software programs, which can analyze information in a database and flag duplicate or similar entries. Here are common steps in a data matching process:
1. User defines the matching policy
Databases and servers have access to vast amounts of data, so the first step in the data matching process is to define the parameters you want to analyze. If a user wants to run a matching process to merge duplicate entries, they might choose a data point that is unique to each person, like a user ID or social security number. Matching policies for analytics or data mining might focus on parameters that multiple entries have in common, like location or timestamp.
For example, in a customer database, the administrator might choose the client's phone number as the key parameter for the match process. As customers typically use the same phone number when they contact a company, the tool can use that number to identify accounts that might belong to the same person, even if they use different names or email addresses. Identifying these duplicate accounts can allow the database administrator to merge them into a single account that lists all activity relating to that customer.
2. Data matching tool identifies matches
Next, the data matching tool analyzes all the information in the database to find matches. Depending on the type of data tool and the customized settings the user applies, a data matching tool might rank potential matches by percentages. For example, if two entries in a government database have the same name and social security numbers that differ by one digit, the tool might find they have a 50% chance of being the same person, with a typo in the social security number on one entry.
Often, data matching tools create reports for the database administrator or other professional using the program. They might also feature interactive dashboards with built-in merging controls. For databases that feature location data, the matching tool might suggest corrected addresses by referencing postal data, which can be useful for customer databases.
3. User analyzes the results
You might use a data matching tool's reports to merge duplicates or create analytics resources, depending on your department and role. If a database administrator runs a program to identify potential duplicate accounts, they might open the flagged accounts and merge them if they're clearly the same person. Some data matching tools have auto-merging capabilities, which allow the program to combine accounts with the same information. Some companies use data matching for marketing analytics. In those cases, a marketing coordinator or other professional might use the information from a data match report to segment emails.
Benefits of data matching
Here are some ways that using a data matching tool can improve an organization's performance:
Regularly using a data matching tool to identify and merge duplicate accounts or entries can keep your database running smoothly. It can also ensure that employees have access to a single place for information about a client, vendor or product. Because many companies have multiple sources of information, merging duplicates can improve client relationships and streamline the sales process.
For example, three different employees from a small retail company might contact a tech firm to get information about financial services software. If they speak to different sales representatives, they might have three unique accounts, even though they're all within the same company. A data matching tool can identify similar email addresses, company names and phone numbers and provide a report for the database administrator, who can link the accounts together. That way, sales and customer service teams can easily access all the information about the potential deal.
Provides analytics and business intelligence
A data matching tool can convert data entries into the same format, which can help in the data analytics process. Analytics software is a powerful tool for finding trends in large amounts of data, but many programs require that the user standardizes the data before performing any analytics tasks. In companies where multiple employees manually input data into a CRM or other database, the data might use different formats for dates, names and locations. A data matching tool can allow a database administrator or other clerical professional to reformat data in hundreds or thousands of database entries automatically.
Improves sales tactics
You can use data matching tools to enhance your understanding of a target audience, which can help you refine your marketing techniques. By comparing a company's CRM (customer relationship management) data to a third-party collection of information, data matching tools can connect user profiles to demographic information, which creates a more complete profile of a current or potential customer. When a potential customer calls a company, the sales representative might collect the caller's contact information and interests. Third-party data collection applications can provide more information, including the caller's address, age and profession.
For example, a tutoring company's sales representatives might communicate with a parent who's interested in tutoring services for their teenager. The representative might put the parent's phone number and zip code in the company's CRM platform. By comparing this data to the information the company purchases from a data collection agency, the data matching tool can provide information about the student's school district and local competing firms. This information can help the sales representative create a targeted pitch to the potential customer.
Many organizations use their databases to store compliance information, like approval forms and contracts with vendors and clients. Data matching programs can help companies maintain their databases and ensure that they've met compliance regulations for different accounts. By identifying duplicate accounts and accounts with similar parameters, these programs can streamline compliance tasks, which can help administrative staff work more efficiently.
For example, school districts might require special approval for outside vendors before allowing them to operate within system schools. A school system's database might contain information on hundreds of potential vendors who have asked about offering services or selling products in their schools. Using a program, the database administrator can identify duplicate accounts for companies and merge them. That way, they know exactly which vendors have a valid approval form on file.
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