There are many steps that a company should take when performing data cleansing. Data cleansing should be done on an on-going basis either quarterly for large amounts of data or annually for smaller data sets. There are also many steps that typically companies perform during their data cleaning initiatives. Steps include:
Data Deduplication – This is when you look at your database and identify duplicate records between leads and contacts, duplicate accounts and other data deduplication that can be found in your CRM. Once duplicates are identified a hierarchy of merging is established. Keep in mind that the merging should minimize any data loss.
Data Normalization/standardization – The second step is to identify fields or records which need their data standardized. Example of standardized fields includes: phone numbers, websites, states and country normalization and titles.
Identifying bogus records – The third step is to identify bogus or test records that were created. Depending on your data set this can be used by setting up filters to catch them or by using machine learning techniques similar to those used in Spam Filters.
Identifying records with missing data – The fourth step is to identify records which missing information which is needed in order to assign sales reps, perform segmentations and for analytical purposes. This is where data enhancement will come in handy. An example of this is filling in address information, filling in email information and so on…
Data Verification/Validation – There are many tools out there that can help you validate email and physical addresses. They can also be pricey, especially for large-number of records. The advice here is to only run verification, validation and data appending on records which are unusable because they bounced, unsubscribed or out-dated records.
Typically data cleaning process can take anywhere from a week to a few weeks especially when dealing with third party data suppliers. Due to the large investment that the company requires, it can be cheaper and more time efficient to hire an experienced data cleaning company such as StrategicDB.