A few years back, I attended a three-hour “vendor shoot out” between two CRM vendors hosted by an IT services firm. The consultants ran through a series of standard CRM processes including lead management, dashboards, record customization by the site admin, and Outlook integration. Anybody who was assessing CRMs would have been impressed by the flexibility of the systems, the professionalism of the analysts, and the breadth of the Q&A discussions.
Yet, at no point did I hear a discussion of data quality, data hygiene, contact verification, field standardization, or company and contact enrichment. Neither the analysts nor any of the attendees broached these topics. Except for a short discussion on de-duplication of records, you would think that data was miraculously keyed into CRMs perfectly and wasn’t subject to decay.
So, while data quality went unremarked, it is a critical variable in ensuring strong ROI for your CRM investment.
The math behind data decay
Let’s assume that today your B2B contact database is 90% accurate. We know that most databases aren’t close to this level, but stick with me. It is generally accepted that contacts age at 2% per month due to job changes, new titles, company name changes, office relocations, and companies going belly up. So, after one year, absent any data quality initiatives, your 90% accurate contacts have decayed to 71% accuracy (.9 * (1 – .02)12). After two years, your contacts have declined to 55% accuracy (.9 * (1 – .02)24). That is four out of every nine records being bad after only 24 months!
Even if you run an annual batch update, your records will still average an 80% quality level over the year. Such accuracy should not be acceptable to your sales and marketing teams.
The high cost of bad data
Bad data shows up in a series of tangible and expensive process failures.
How much time is wasted by sales reps leaving messages for contacts no longer at a firm? Whether voice mails or quick emails, this activity has zero ROI. Improving your data quality allows them to focus on actual prospects – folks they can sell to.
Poor data quality also impacts your marketing department’s targeting. Weak firmographics, technographics, and contact data result in ineffective audience selection. How much money is wasted on direct mail programs for collateral that is immediately dumped in the trash?
How about your email programs? Many marketers simply rely on email bounces and unsubscribes to verify their emails. But moderate to high email bounce rates can cause your marketing campaigns to end up in SPAM folders. Likewise, poorly targeted messaging will drive up your unsubscribe rate. ESPs may even choose not to deliver your messages or throttle email delivery.
Another gap occurs in lead scoring. Weak data results in inaccurate fitness scores, generating poor prospect nurture decisions. If sales reps fail to act on marketing qualified leads, one reason is poor data quality.
It’s time to improve data quality
By associating accounts, contacts, and leads with third-party verified reference files, marketing and sales processes operate more effectively. Marketing and Sales Operations enjoy fuller and more accurate segmentation reports, prospect decisioning improves, and leads are routed to the proper sales rep.
So, if you haven’t recently cleansed your CRM or Marketing Automation Platform, you will find decreasing returns on your marketing campaigns and sales rep outbound calling. What’s more, vendors now offer automated batch and on-demand data enrichment, making it more efficient and faster to validate and enrich your enterprise platform records. You can even request human-verified contacts to replace departed executives or fill in gaps at your ABM accounts.
Hopefully, Marketing and Sales Operations are giving more thought to data quality. The term Garbage In, Garbage Out comes from the early days of IT, but becomes ever more relevant as our applications and processes become more sophisticated.