Datarati :: Will Scully-Power :: Data, Analytics & Optimisation in the World of Advertising!

A new SiriusDecisions study reveals that best-practice organisations could actually realise nearly 70 percent more revenue purely based on data quality.

SiriusDecisions reveals that despite its importance to the business, the databases of b-to-b organisations are akin to an attic filled with contents that over time have not been properly labeled, managed and maintained. However, unlike that long forgotten “stuff” in your attic, prospect and customer marketing data can actually make or break your bottom line.

“Most b-to-b marketing executives lament the status of their databases, but have difficulty convincing senior management of the gravity of the problem,” notes Jonathan Block, SiriusDecisions senior director of research. “The amount of data in the average b-to-b organisation typically doubles every 12 to 18 months, so even if data is relatively clean today, it’s usually only a matter of time before things break down.”

Mr. Block continues, “The longer incorrect records remain in a database, the greater the financial impact. This point is illustrated by the 1-10-100 rule: It takes $1 to verify a record as it’s entered, $10 to cleanse and de-dupe it and $100 if nothing is done, as the ramifications of the mistakes are felt over and over again.”

Focusing on b-to-b sales and marketing best practices, the firm has found that from 10 to 25 percent of b-to-b marketing database contacts contain critical errors — ranging from incorrect demographic data to lack of information concerning current status in the buying cycle. Not updating records after every sales interaction will lessen the impact marketing can have during later stages of SiriusDecisions’ “demand creation waterfall,” which visually depicts the roadmap to conversion-rate success.

“Organisations must shift their focus from one-time data cleansing to ongoing data maintenance to turn the tide,” says Mr. Block. “The good news is that we’re seeing a strategic shift in approach in strong organisations, from one of data cleansing (a project with a set completion date) to data maintenance (ongoing policies and procedures to maintain data quality). The fundamental trouble with one-time data cleansing is that the day the project ends, the data is the cleanest it will be until the next round of contacts is added to the database.”

Mr. Block concludes, “The major impact of bad data on conversion rates really becomes clear when we roll these stages up and look at the difference between an average and strong organisation. Using an example of a prospect database of 100,000 names at the outset and a constant campaign response rate of two percent, a strong organisation will realise nearly 70 percent more revenue than an average organisation purely based on data quality. For those marketing executives having problems convincing senior management that a permanent process upgrade rather than ‘quick fix’ will pay big dividends in the long run, this is the kind of eye-opening statistic that should prove invaluable.”

Better quality data means you’ll have better:

• persona and profile information
• segmentation capabilities for personalisation
• higher engagement due to content relevance (based on actionable insights)
• more accurate sales forecasts
• better delivery for email campaigns
• a more accurate gauge of interest levels
• higher credibility
• valuable conversations