The biggest mistake companies make is not factoring in the cost of bad data. Only 17% of companies factor in the cost of bad data when calculating return on investments, according to findings from a report by Radius and Harvard Business Review.
The findings also show that companies with advanced data strategies are twice as likely to report more than 30% annual revenue growth.
Radius and Harvard Business Review (HBR) released a study on the connection between data strategies and B2B growth, but the data also relates to marketers reaching out to consumers. The study found 55% of marketers believe data silos are the biggest challenges to creating data-driven strategies, 33% cite a lack of the right data analytics tools, and 32% cite incomplete data.
HBR Analytic Services surveyed its readers and social media channel, with 189 business executives completing the questionnaire. About half of the respondents were very familiar with their organization’s B2B marketing strategy and use of data, and the other half were somewhat familiar. Those who were not familiar were screened out before completing the survey.
Only 31% of companies say they have "somewhat' advanced data strategies, but companies with advanced data strategies do a better job of attracting and retaining customers, earn a bigger share of customer wallet and generate more revenue than companies still struggling with data analytics.
About 34% of the companies participating in the survey think of their data strategy as "average," with 21% calling their strategy "below average" and 8% citing it as "poor." Only 6% call their data strategy "highly advanced."
Of those who have a data strategy, two out of three marketers say an advanced data strategy gives them a better position in the market compared with competitors.
Some 60% of executives say their companies are focused on investing in data and data analytics. Some 53% say data and analytics will help the company target new customer groups, 47% say they will invest in new marketing technologies, 45% are ready to revamp pricing strategies and models, and 42% will expend or refine distribution strategies.
As the findings suggest, having "a lot of data" isn't always good if it's poor quality. As the saying goes, data-driven marketing is only as successful as the quality of the data that underpins it, even for paid-search ads and when optimizing content for text and voice search. Take, for example, Google Shopping data feeds. Garbage in, garbage out, in the advertisements marketers hope will move consumers to sales.
Some of the biggest gains and greatest potential from accurate data and analytics resides in improved customer service, increased customer loyalty, and a bigger share of the wallet with a higher customer lifetime value, according to the findings.
Very interesting, Laurie. In my consulting experience and before that as an agency guy, I've found that very few advertisers have a handle on how to define ROI, let alone the tools or data that permit a more refined analysis. The study seems to indicate that this is still the case---if one reads between the lines. Blaming it on bad data or missing data is the usual lame excuse for a faliure to study all of the available facts, especially those that show trends, and define exactly what elements that relate to ROI are applicable in each advertiser's particular situation. Just looking at a sales chart isn't enough.
I'd also add the reliance on 'soft metrics' (e.g. brand recall), and lack of forensic interrogation of the 'hard' metrics they use.