Data Quality in Marketing: Trends and Directions for 2017
Asking whether data quality is important to your marketing efforts is a little like asking if apple pie and motherhood are important – of course, the answer will always be “yes.” Recently, however, some interesting quantitative research was published that shed light on just *how* important it has become.
Marketing research firm Ascend2 performed a survey of 250 mostly senior people in marketing, to see what they thought about data quality. Over 80% of the respondents were in management roles, with more than a quarter of the sample holding C-level positions. Fully half were associated with large companies with over 500 employees, and more that 85% had over 50 employees. Respondents were also equally split between short versus complex sales cycles.
The results showed very clearly that data quality has risen to become a critical consideration in marketing success nowadays. Here are some of their key findings:
Improving data quality is their most important strategic objective. With 62% of respondents rating this as their top objective, data quality now ranks far above more traditional marketing objectives such as improving marketing data analytics (45%), improving user experience (43%), optimizing the lead funnel (26%), and even acquiring an adequate budget (20%).
Data quality is also their biggest challenge. Respondents also ranked data quality as currently being their most critical challenge, in smaller numbers (46%) but in similar proportions to the other factors such as those mentioned above.
But things are getting better. Fully 83% of respondents feel that their marketing data strategy is at least somewhat successful at achieving objectives, with over one-third (34%) rating their own efforts as “very successful (best-in-class).” Similar numbers also feel that their tactical effectiveness is improving as well. While 14% feel that they have been unsuccessful in achieving objectives to some degree, only 3% consider themselves to be very unsuccessful.
Data quality is a downstream process. Respondents clearly favored cleaning up contact data versus constraining how it is collected. Nearly half (49%) felt that validating contact data was the most important tactic for improving marketing data quality, while less than a quarter (24%) felt that standardizing lead capture forms were important. Other upstream measures such standardizing the data upload process (34%) and developing segmentation criteria (33%) were also in the minority.
Call in the experts. An overwhelming majority of respondents (82%) outsource either some or all of the resources they use to improve marketing data quality, with over a quarter (26%) using no in-house resources at all.
The results of the survey clearly show that data quality is one of the largest challenges that marketers are currently dealing with. Whether you are frustrated with incomplete or inaccurate sales lead data, tired of bad contact data causing customer service issues, or wasting money on marketing campaigns with results negatively impacted by poor contact data, understanding the quality of your data is the first step in identifying the true costs that poor data quality is having on your organization.