As a company focused solely on data, Untitled has become well-versed in best practices for storing data cleanly. The practice of data hygiene is crucial for any company that wants to successfully leverage their data. It’s frequently one of the first improvements we look at when dealing with clients. From address normalization to data cleansing, Untitled ensures companies have the most accurate data possible.

Companies normally possess a wealth of useful first-party data within their own systems. However, if the right systems aren’t in place, that data can become dirty and hard to capitalize on. When this happens, it affects every aspect of your business. From marketing campaigns to hiring, a lack of data hygiene is a detriment to any company.

data hygiene

Data hygiene starts with ensuring the right file structure is in place for any data coming into your systems. This normally means establishing the column organization in any data table that information is fed into. Depending on the data coming in, the columns could include: address, phone number, email address, sales, demographic information and date of purchase to name a few. Correctly classifying all available information is the start to ensuring good data hygiene.

After that structure is established, you need to ensure that you minimize inaccurate or bad data as much as possible. This can be conducted in a variety of ways depending on the information coming in and database architecture a company has in place. Something as simple as address normalization can be the start of ensuring an accurate view of your consumers. Maintaining a customer record of 600 1st Street and 600 First St for the same consumer will result in an inaccurate file.

data hygiene

This may not seem like a major problem at a small scale, but when conducting data analytics over thousands or millions of records the issue becomes highly impactful. Key insights will be missed if an identifier is incorrectly registered as multiple different records as opposed to one unified point. In the case of a retailer, this could cause marketers or analysts to miss important consumers that have a higher value then the inaccurate data shows.

Not only will this impact marketing campaigns for each individual record missed, but it is very detrimental to overall analytics. The more of these cases that come up across an address, email, product ID, city, state, product category and missing information, the greater impact it will have overall on the company. In the case of product ID, bad information will affect something as simple as measuring cross-sell performance across consumers and products. Data hygiene is necessary to identify improper records, and at times purge missing, duplicated or unrecoverable records.

When conducted effectively, data hygiene is an integral part to any business. Establishing this is crucial for a company no matter what stage they are in. With the entire business world migrating towards a data-centric approach, the longer it is put off the more harmful it will be. Untitled specializes in helping companies improve their data hygiene and establish the needed data infrastructure for the future. Interested in learning more? Contact us today.

Connor Gaffney

Author Connor Gaffney

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