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Improve the quality of your customer data today.
Data quality is a vital element to any business foundation, customer management and achieving the best possible outcomes. A typical database will go stale at 2% per month and up to 24% per year due to people moving, changing contact details, divorcing, dying and MORE. Melissa is proud to offer a comprehensive way to clean and maintain your customer data – a core component to any data management strategy.
Verify, standardise, transliterate and correct addresses for 240+ countries and territories to ensure a clean and up to date address database.
Uncover, merge, & purge duplicate records for a single customer view.
Identify individuals with MPS and TPS preferences to ensure you maintain the preferred contact methods for your database.
Check and verify emails to improve deliverability, maintain spam compliance, reduce fraud, and ensure emails exist.
Ensure phone numbers (domestic & international) are valid and callable. Verify country code, national prefixes, carrier data and more.
Enrich your data with B2C demographic data to gain additional insight and identify prospects like your best customers.
Enrich your database with firmographic data, ranging from corporate to sole traders in the UK.
Convert addresses to latitude and longitude coordinates for better mapping and analytics.
Data cleansing also known as data cleaning or data scrubbing, is a comprehensive process to clean, maintain and enhance your database by identifying incomplete, incorrect, inaccurate, or irrelevant parts of your data. It can be done by data quality tools that instantly verify incoming data or by batch cleansing through various data segments and reference datasets. Data cleansing is a core component of any data management strategy and should be performed often to stay on top of your customer data.
1 Upload
Send us your file through a secure FTP or upload via our listware portal.
2 Data Audit
Our data quality experts will audit your data to understand the current health of your prospect data.
3 Data Selection
If you know already what data quality service you want, you can select a service via listware or just let our data quality experts know.
4 Verify
Uses authoritative, in-country reference datasets to check the validity & deliverability of a physical address.
5 Transliterate
Transforms foreign languages into Latin characters so an address can easily be validated.
6 Output
A clean, deliverable address ready for mailing, order fulfilment, or analytics.
Stop bad data in its tracks with Listware Online or for Excel. It’s the all-in-one SaaS data quality tool that cleans, verifies, dedupes and enriches all of your contact data wherever and whenever you need it, on demand!
View ListwareData Cleansing is an essential step in data management and analysis, and provides the following benefits:
Overall, data cleansing is important because it improves the reliability, accuracy, and usefulness of data. It enables organisations to make informed decisions, gain insights, and maintain a competitive edge in today's data-driven world.
While the specific steps may vary depending on the context and the nature of the data, here are five general steps involved in data cleansing:
It's important to note that data cleansing is an iterative process, and these steps may be repeated multiple times until the data is sufficiently cleaned and ready for analysis or further processing.
Data cleansing is typically performed by our data experts, who are responsible for ensuring that the data used in an organisation is accurate, consistent, and reliable. They perform various tasks to cleanse the data, such as:
It's important to note that data cleansing is a collaborative effort involving various stakeholders, including domain experts and IT professionals, to ensure accurate and reliable data for analysis and decision-making.
The time required for data cleansing can vary widely depending on several factors, including the size and complexity of the dataset, the quality of the initial data, the specific data cleansing tasks involved, and the tools and resources available. Here are some factors that can influence the duration of the data cleansing process:
It's challenging to provide an exact time frame for data cleansing as it varies significantly depending on the factors mentioned above. It is recommended to perform a thorough analysis of the dataset and consider the complexity of the required cleansing tasks to accurately estimate the time needed.
Data cleansing, or data cleaning, offers several benefits for organisations that rely on data for decision-making, analysis, and operations. Here are some key benefits of data cleansing:
Overall, data cleansing plays a crucial role in improving data quality, accuracy, and reliability, leading to more informed decision-making, improved operational efficiency, and enhanced business performance.
The frequency of data cleansing depends on several factors, including the nature of the data, the rate of data change, the importance of data accuracy, and the specific requirements of the organisation. While there is no one-size-fits-all answer, here are some considerations for determining how often data cleansing should be performed:
It is recommended to establish a data cleansing schedule based on a combination of the factors mentioned above. Regular monitoring of data quality and conducting periodic data audits can help identify patterns, trends, or issues that inform the frequency of data cleansing. Adjust the frequency as needed to ensure that the data remains accurate, reliable, and aligned with your business requirements.
When undertaking data cleansing, businesses should consider several factors to ensure a successful and effective process. Here are some key considerations:
By considering these factors, businesses can approach data cleansing in a structured and comprehensive manner, leading to improved data quality, accuracy, and reliability.
Data cleansing is suitable for a wide range of organisations and industries that work with data. Here are some examples of who can benefit from data cleansing:
In summary, data cleansing is suitable for any organisation that values data accuracy, reliability, and the ability to make informed decisions based on high-quality data. It is particularly beneficial for businesses that heavily rely on data, deal with complex data structures, operate in compliance-driven industries, or aim to enhance customer experiences.
Improve the quality of your customer data today.
Discover Melissa APIs, sample code & documentation.
Full-service data cleansing to clean, dedupe and enrich.
A free trial of our standout verification services.