Click to learn more about author Mark Hensley.
Organizations increasingly understand the importance of Data Governance, or the method of control that ensures data entered into a system meets a precise standard. In fact, the topic has been addressed extensively here at DATAVERSITY®, with articles on how to get buy-in from executives and set up a Data Governance policy with teeth and on data policies’ affect on Data Curation, to give just two examples.
Unfortunately, what sometimes gets forgotten as we think about how Data Governance policies affect our business is the impact of a policy, or lack thereof, on customers and prospects. In an attempt to rectify this, I’ve highlighted five common pitfalls made by organizations managing customer data so that you can hopefully avoid them.
1. Wrong Place, Wrong Time: Poor (or nonexistent) processes to manage information result in disparate systems not effectively sharing information. For example, your CRM not feeding updated information into your marketing automation tool and vice versa. The result is that prospects and customers get incorrectly classified. Someone who started off as a prospect has become a customer but their status only gets updated in your CRM and not in your marketing automation platform. As a result, your customer is sent irrelevant nurture messages extolling the virtues of your product, getting frustrated and losing faith in your brand as a result.
2. Losing Friends and Alienating People: Related to the first point, when information is not stored appropriately or passed into enterprise CRM systems bad things happen. Say that a customer or prospect visits your site and selects Spanish as their preferred language. Your site should be smart enough to remember their preference so that they’re not forced to reselect it each time they return (at least until they clear their cache). This is easy to fix by using a tool like Google Tag Manager to record visitor preferences.
3. Dude, Where’s My Privacy?: Customer relationships are just that, relationships and they won’t last if you abuse the trust customers place in you when they share information. Sometimes this can be unintentional. For example, a customer shares their email address with you but chooses to opt out of certain communications. Unfortunately, due to a lack of appropriate Data Governance policies, that information is not communicated across the organization and the customer receives unwanted messages, poisoning the relationship.
A host of new regulations, such as the EU’s General Data Protection Regulation (GDPR) have brought privacy to the fore and threaten to impose penalties on companies that fail to comply. Having unified Data Governance policies in place is the only way to comply with GDPR’s stipulation that individuals be able to access all of the data your organization has on them and request that it be wiped.
4. Regulation is an Opportunity, not a Hurdle: When HIPAA first came into practice in the late 1990s it was widely greeted with groans by healthcare providers. Too many saw it as another “hoop” to jump through. Yet HIPAA wasn’t a hurdle so much as an opportunity to better serve customers. Per my point above, good Data Governance respects user privacy. If privacy safeguards weren’t in place than it wasn’t a good policy to begin with, with or without HIPAA.
This pattern is playing out again today as IT and marketing departments view the rollout of GDPR with suspicion and fear. Ultimately, we shouldn’t look at regulation like HIPAA or GDPR as a burden but as an opportunity to examine our policies and find ways to do better by our customers. In most cases, these regulations are simply pushing us to do the things that we should already have been doing.
5. Data Governance isn’t a One Night Stand: In addition to my day job at Liferay, I serve as an Adjunct Professor at University of Redlands and I always try to impress on my students the importance of the 1-10-100 rule; what costs one dollar to prevent, costs ten dollars to fix and a hundred dollars to clean up once it becomes a mess. Yet many organizations still haven’t figured out that Data Governance is a way of life, not a one-time event.
Consider the following scenario: a company sends out 1,000 emails as the first step in a drip campaign, of which 900 come back as undeliverable. One company might focus solely on how to fix that particular email list or ignore it altogether and move on to another list. That would be a mistake. Instead, the company would be wiser to look at their entire process – how did those emails get collected, what process is there to verify their validity, how can the data collection process be improved in the future, etc. By doing so they’re much more likely to avoid having the same issue come up again and spending even more time and resources having to fix it.
What are some of the worst Data Governance mistakes you’ve seen organizations make? How have they affected customers? Let me know in the comments below!