Best practices in Data Cleaning
Many researchers take a shortcut from data extraction to data analysis while skipping the step of data cleaning in between. But this mistake ruins their analysis as clumsy data throw more challenges in data analysis.
- Quality Plan: Planning is the work required in every field. Know where most data quality errors occur. Identify incorrect data. Understand the root cause of the data health problem. Develop a plan for ensuring the health of your data.
- Standardize Contact Data at the Point of Entry: Before data cleaning can happen, check important data at the point of entry. This ensures that all information is standardized when it enters your database and will make it easier to catch duplicates. Talk with your team about creating a standard operating procedure (SOP). Following the SOP will ensure that your team is only allowing quality data in your CRM at the point of entry.
- Accuracy of data: There are some great tools for cleaning data such as list imports. Find data hygiene tools that offer email verification. Effective marketing occurs when high-quality data and tools are used to seamlessly merge various data sets. You can still validate the accuracy of your data online without the appropriate tools, however, it will require a lot of manual work which most marketers don’t have the bandwidth for.
- Identify duplicates: Duplicate records in your CRM waste your efforts. Dupes also cost you too much in campaign spending and general maintenance. They prevent you from having the essential Single Customer View. Duplicate contacts damage your brand reputation and guarantee a bad experience for your customer. They cause inaccurate reporting.
- Append Data: If you don’t abide by the law, you may have compliance issues. To avoid being in violation of GDPR or CASL, you need to understand not only the business location of the company but also of each contact at the company. Not having complete and comprehensive data for each record in your database is called “white space.” Some software companies out there can capture information directly from first-party sites. One example is LinkedIn.