Every marketer, sales rep and analyst has probably complained at least once a week if not a day or even hour about the state of data. Data quality can vary depending on the company but we can all agree that even the best data governance strategies fail at keeping data accurate 100%. We have analyzed the multiple ways on how despite the best data cleaning tools, data governance best practices and a dedicated team that cares about data, uncleaned data still exists in their data sets. Here are the most common ways bad data makes it to your CRMs:

  1. Form Submits – even with spam filters, dupe stopper installed on your forms and with marketing automation capabilities you still end up with:
    • Duplicates – As people use multiple email addresses. And if you de-dupe based on email only, you will have records with someone’s personal email address and corporate one.
    • Bogus Data – While there are tools that will help identify xxx, Micky Mouse, xyz records, it will not catch someone calling themselves John Smith (After all they do exist), wrong phone # being put (think back to dating world when you got the wrong number) and simply made up names for emails and company number.
    • In-accurate Data – this one is probably the hardest one to spot, but with drop-downs for revenue or industry, people will not always select the correct answer. Sometimes they simply did not pay attention or they just do not know and the form requires you to input something so they guess.
  2. 3rd Party Sources – No data source is perfect and while some come close to having high data quality they still fail on certain instances. Here are just some of ways that their data maybe wrong:
    • Outdated – Some data was accurate in 2004 but now its 2014 and no one has updated it and well a company may no longer be in business or that consumer has long moved to a different state.
    • Miss-matched data – when trying to match your records to third party especially for when enriching your data you may match based on website and company name or just last name and state that could lead to bad data coming in.
    • Inaccurate Data – As no solution is perfect third parties often have the same data integrity issues that you face as well therefore, while they can improve yours they are not 100%.
  3. Human Input – Human error is inevitable. Here are some common ways that people have messed up their own data, ironically they are often the ones to complain about it to their systems admins:
    • “Not Sure” or “N/A” – When certain fields are mandatory, sales reps will often put “Not sure” or “N/A” into the system to be able to save the record.
    • Focused on everything BUT data accuracy – When you are trying to convince someone to donate money or buy your latest technology, data is the last thing on your mind. Who can blame them after all the company’s bottom line depends on that sale! Therefore, they often forget to ask what state are you located in? or How many employees work for your company.
    • Mis-communication – Without anyone’s fault people may mis-understand what should be filled in or the format it need to go in. A common example is the date field if not automatically assigned by the system, some may input it as 10/24/2017 while others 24/10/2017.
    • Duplicates – No time to check if the record is already in the system.
  4. System Implementation – When setting up your Salesforce or Marketing Automation Tool, Admins are often focused on making sure all workflows are working, all fields are in the right tables that they miss the use-case for that specific field, issues include:
    • Not adding standardization – It is much quicker to set up a field to be text or number, as oppose to having it a lock down drop down field, and some may not know what values are going to be inputted to make that call. Therefore, you are left with thousands of records for the same industry or country name.
    • Mandatory Fields – Mandatory fields is a lifesaver for analysts and marketers as they allow for an easy way to analyze results and send marketing campaigns. However, in certain instances they can also be your biggest downfall with bogus data coming in or worst less form submits as people do not have time to fill in 10 questions.
    • No Option for “Other” – While 90% of your fields will fall in your list, there is always the 10% or 1% that will not. In order to decrease errors on these you should always have an “other” option preferably with a text field that follows for them to input what “other” means.

As you can see you may not always be able to stop bad data, but you are not alone. All businesses no matter how small or large have data integrity issues, especially since our systems evolve over time, employees change and type of data we need also differs year over year. That is why data cleaning companies exist, to help you solve your biggest data cleaning issues from record duplicates to incomplete or outdated data. StrategicDB can help, we are full service data cleansing company that helps business identify their data issues and provide solutions not just for the short term but for long term! Contact Us Today!