Data hygiene in marketing
Learn how to cleanse your data and better target your customers
Data is a marketer’s bread and butter. It guides the formation of everything from customer personas to entire marketing strategies. McKinsey released a report in 2020 that organizations using data to make decisions are 23 times more likely to earn new customers, six times more likely to retain them, and 19 times more profitable. However, data in its raw and unprocessed form is largely unhelpful to businesses until it has been audited and organized via data hygiene procedures.
Data hygiene involves cleansing consumer data by removing duplicates, verifying and correcting inaccuracies, and other errors. In this blog post, we’ll discuss what data hygiene is, what causes dirty data, how to cleanse it, where you can start, and how Experian can be your partner in the process, empowering you to reach your customers with greater confidence.
Data hygiene, also called “data cleansing” or “database hygiene,” keeps data healthy, accurate, and encompasses any steps taken to clean and maintain it. Your data should be easy to understand, error-free, and organized. This helps marketers make more informed decisions based on the most accurate and up-to-date data available.
Poor data quality can have significant consequences for a marketer’s business. For example, if your consumer data is outdated or inaccurate, you will waste time and other valuable resources on campaigns that target the wrong audience. You might also miss opportunities to engage with customers or prospects, leading to lost revenue.
IBM has reported that bad data quality costs U.S. businesses $3.1 trillion per year.
Data hygiene services can help businesses like yours avoid these situations and experience the following benefits:
Data can naturally fall out of date with recency. Outdated data may include an old address, phone number, or preferences that change as the customer ages. File corruption may also occur over time, which compromises customer data integrity.
Different formats across platforms are bound to cause inconsistent data, such as when different abbreviations or date formats are used. If records are different, you can’t merge data from various data sources.
Whether intentional or unintentional, incorrect data input is to be expected. When an individual enters a fake name or invalid email address or leaves a field blank, this can cause data inaccuracies.
This is among the most common causes of dirty data. Customer information may be incorrectly input into a platform by a salesperson, or an analyst might misinterpret data because they don’t have enough context. It’s common for these errors to occur during data entry, processing, or analysis.
Customer data hygiene involves identifying and correcting inaccuracies, inconsistencies, and redundancies in customer information. Here are some ways you can clean up your data to use it to make better marketing decisions.
Outdated data can include contact information that has changed, customer preferences that have evolved, or outdated purchase histories. Your business should establish a regular schedule for reviewing and updating customer data in which you verify contact information and confirm customer preferences — and remove old data afterward.
Customers that are on a do not call/mail list
If a customer has opted out of your calling or mailing list or has added their phone number or mailing address to the National Do Not Call Registry or National Do Not Mail List, you must honor that request. Failure to do so can result in regulatory violations, legal or regulatory penalties, and damage to your brand reputation.
Customers that have moved or are deceased
By regularly conducting address verification, you can find out when specific customers move or pass away. You can contact customers directly, utilize external data sources, or change-of-address services to do this. When you know that a customer has moved or died, you can remove their data from your database, avoid wasting marketing efforts on that person, and prevent legal problems for your company.
Duplicate data usually arises due to data entry errors, system issues, or data merging. For businesses, duplicate data can contribute to wasted resources, inconsistent data, and incorrect analysis, and it needs to be consolidated. The consolidation process involves identifying and merging duplicate records into a single, accurate record, improving data accuracy, reducing redundancy, and enhancing customer relationships.
Duplicates with slight variations
Duplicate data can occur with slight variations when the same customer information is entered multiple times with minor spelling, punctuation, or formatting differences. This can lead to inaccurate reporting and frustrated customers, which is why businesses need to identify and merge duplicates to maintain the most accurate and up-to-date information.
Duplicates from multiple databases
To consolidate duplicate data from numerous databases, businesses should start by identifying the sources of data duplication. This may require a data audit to identify databases that contain similar or identical data. Once you know the origins of duplication, you can start merging duplicates.
Incomplete customer data, which ranges from missing contact information to incomplete profiles and outdated records, can be challenging for businesses that use data for marketing and decision-making. Companies should delete irreconcilable data, seek out matching data points, and reach out to customers to get their missing details and append their data.
By appending data, you can supplement existing data points with additional helpful details like demographics, psychographics, email address, phone number, purchase history, and more. This will give you a more comprehensive consumer view that lends itself to effective marketing messaging.
When you’ve discovered dirty data in your databases, it can be overwhelming to know the best method of approach. Here are some intuitive places to start.
To improve your data hygiene, start by auditing your existing databases, which entails a review of all data sources used for marketing, including customer databases, email lists, and social media accounts. By auditing these, you can identify any inconsistencies, inaccuracies, or missing information and take steps to address them.
It would be valuable to partner with a trusted data solution partner like Experian to help you with a database audit.
Ensure all data is properly segmented and organized, remove duplicate records, update contact information, and verify data accuracy as needed. Then, analyze the data quality and identify gaps or discrepancies, comparing data across different sources or validating data against external sources.
To improve your marketing with data hygiene practices, you can also start by creating standards for data entry accuracy and consistency. Standardized practices for data entry ensure all data is entered consistently and accurately, making it easier to analyze and utilize for marketing purposes.
One of the first steps in this process is to define essential data points, including customer contact information, demographic data, and purchase history. Knowing these, you can establish clear guidelines for collecting, entering, and maintaining this data. These guidelines should develop standardized formats for names, addresses, and phone numbers and include instructions for handling common data entry errors, such as typos or missing information.
Businesses should have a data management system for all employees who come into contact with data, from data entry staff to marketing executives, to ensure everyone who handles data knows the expectations for quality and consistency. You’ll need to establish clear data management policies and procedures, which may involve defining data quality standards, creating data entry and processing guidelines, and establishing customer data validation protocols.
There may also need to be training on data hygiene best practices, covering topics such as data entry, data processing, and data analysis and emphasizing the importance of maintaining data accuracy and completeness.
Data hygiene provides businesses with a foundation for all of their marketing initiatives. With clean and accurate data, companies can gain insights into customer behavior and preferences, such as their purchasing patterns or the channels they prefer to use for communication. Here are a few additional ways your marketing can benefit from proper data hygiene.
Segmentation is the process of grouping customers or prospects into smaller, more specific segments based on shared characteristics, such as age, location, or behavior. By segmenting data, you can improve your targeting and create campaigns with a greater chance of resonating with audiences and driving better results. However, data segmentation relies heavily on accurate data. If data is incomplete, outdated, or inaccurate, it can result in improper segmentation, leading to marketing campaigns that miss the mark.
With direct marketing, you need current customer data to reach the right audiences. Dirty data, like inaccurate or incomplete contact information, can result in wasted marketing efforts and lost opportunities. For direct mail campaigns, incorrect or outdated addresses can lead to undelivered mail and increased mailing costs.
Similarly, for email campaigns, dirty data can result in bounced emails or trigger spam filters, hurting email deliverability rates and reducing the campaign’s effectiveness.
At Experian, we know the importance of data hygiene and offer a range of services to help you improve your data-driven marketing. From data append to data cleansing and enrichment, our solutions are designed to help you get the most from your customer data and create effective marketing campaigns that drive results. Contact us today to get started.
We can help you create marketing strategies catered to the specific preferences and behaviors of your current and prospective customers. We specialize in helping brands discover data-driven insights to make an everlasting impact on consumers.
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