10 Nov Why Should I Care about Dirty Data?

DataQuality is not new news; however, traditionally Marketing was primarily charged with driving the number of leads – the more, the better. Today’s business needs shifted these priorities a bit – more nimble organizations and modern technology architecture require a more thoughtful approach.

More specifically, in the world of marketing automation, systems are “tied” together and “speak” to each other constantly – many data updates occur in real time. Sales teams depend on these processes to provide timely and relevant response to prospects that show interest and might be closer in making a purchasing decision. Marketing relies on this connection to work seamlessly to ensure scoring, new lead creation, and lead attribution work properly.

According to a SiriusDecisions study, on average, “25 percent of the B2B marketer’s database contains critical data errors”. And in my experience, in B2C companies even a larger percentage (as high as 50%) may be bad, especially, if e-commerce is the primary revenue channel. Bad data is undoubtedly costing companies money in lost lead generation budget and additional infrastructure overhead; but the cost extends beyond that to additional working hours spent performing activities that don’t result in revenue.

Consider taking a methodical approach to identify data quality opportunities, institute sustainable processes to remove issues and ensure closed loop feedback and verification.

To learn more, listen to the replay of the Marketo Summit session.