In today’s modern B2B organizations we collect data on all areas of the business from your website’s form submits to customer service calls. Regardless of how well you have established data governance rules in your organization, data still manages to get dirty. Dirty data can come in all forms, from a bogus form submission to a test record created by your IT department to an error in data entry by a rep. The good news is that with a simple data quality reporting you can identify and pinpoint when data cleaning is needed using five simple signs.
- An Increase in Unreachable Contacts – A simple test is to see if your reachability has decreased over time. This can be done by monitoring these three things:
- Bounce rate for any marketing or sales campaigns that go out.
- Call Connects–if you do track calls, you should track the number of calls that get a number that is no longer in service.
- “No Longer There”–With employees switching jobs every couple of years, it is not uncommon to uncover that a contact or lead is no longer at the company.
- Incomplete Records – Incomplete records can decrease your team’s productivity without being measured. For example, if you pass a lead to your sales rep that has a missing extension number this can cost the rep an extra five minutes of his time to get to the right person at an Enterprise level organization. Think about the cost of a missing phone number all together! To measure if a record has incomplete data first identify all fields that are required for your business. Typically, at a minimum, this will include First Name, Last Name, E-mail, Phone #, Organization’s name. However, you may want to also include additional information such as title, industry, size of the organization and so on. Once you have identified fields that are mandatory you can add a data completeness score to each record to see if they have 100% completeness, 75% and so on. Keeping track of your average level of completeness in your CRM can be a great indicator when that average starts to decrease. Keep in mind that if your mandatory fields are marked as such this can create bogus information added to your system and you may need to use secondary fields to measure levels of completeness.
- Inability to segment or target but the data is there – You may uncover that you have information inside your CRM that is not structured in a usable way. For example, you want to send a marketing campaign to everyone that is in the financial industry, but when you look at the industry field you uncover that you have “banking”, “investment firm”, “financial services” and the list just goes on. This makes it impossible to do any segmentation, target marketing, or analysis on this field until it is standardized into one category. A good way to avoid having such a problem is to have a drop down instead of free text fields. However, do not despair if there is data in that field a good data cleaning company will be able to help.
- Decreased Productivity – If you are starting to notice that productivity is decreasing for one or more departments it is time to understand the root cause. Data plays a big part in today’s B2B organizations. Sales rely on good data to make their calls and close deals, marketing needs leads to be able to market, and even accounting has to have proper information passed to them in order to bill accordingly. Since data touches so many departments, it is not uncommon to have data be the prime cause of productivity loss. How you measure productivity differs by the department, however, general KPI’s (Key Performance Indicators) per department can pinpoint when there is an issue.
- Outdated Records – If you have been in business for longer than a couple of years you probably have records that are outdated. Keep track of the date records are created, the last date of communication and whether they are a customer or not. This information is not only important for the management of your business but may also be required by law. While there is nothing wrong with an established database, it can get in the way of your day-to-day if you do not keep an eye on it. You want to make sure you are, at the very minimum, replacing your outdated records with new records. If the balance is broken, you may need to clean your records.
In conclusion, you do need to make sure that you keep track of unreachable contacts, incomplete and outdated records, monitor your ability to segment and keep track of each department’s KPIs. While these indicators should be monitored on an ongoing basis, there are other circumstances where you may need to clean your data. These may include new legal requirements such as GDPR, a systems migrations, uncovering of bogus/fake records, and high duplicate rates. Keep in mind that a good data cleaning will help improve all areas of business and should be done periodically.