6 Reasons Why Marketers Fail to Use Data Properly

Posted on Posted in Research & Analytics

It seems to me that the growing chorus of experts highlighting the value of data has resulted in leadership teams getting increasingly twitchy about what they do and don’t know. 

Round the clock engagement with online communities and MI systems generating reports by the hour mean that most organisations are waist deep a pool of their own stats. Large volumes of data can be a hugely important to marketing communications, proposition development and campaign tracking. Indeed, data – behavioral, attitudinal and transactional – can play a pivotal role in the growth of an organization’s fortunes. Timely insights can help to improve customer service, provide near real-time assessment of corporate performance and be a very low cost source of intelligence to inform planning. However, if crunching numbers is not central to an organization’s core operations, big data can be a source of big headaches. Consequently, there’s a clear gulf between those businesses that have data at the heart of their corporate DNA, such as native online retailers, and those ‘traditional’ businesses’ for whom serious number crunching has historically been limited to financial reporting.

I’ve been hose organisations that experience problems with their use of data in marketing typically do so for two or more of the following reasons:

6. The Dreaded Silos

Customer data, market intelligence, management information and social media analyses are collected and analyzed separately by disparate teams . In effect, the pieces of the ‘insight jigsaw’ are scattered and no-one can see the bigger picture. Moreover, those who are closest to the data or who have the best opportunity to undertake analyses (often back office specialists) are rarely aware of wider commercial considerations that might inform their assessment methodologies.

5. Bad Timing

Data about customer preferences and opinions are often collected in waves or discrete surveys, not on an ongoing basis. These typically include the board reports, the post campaign analysis, the annual review. In the real world, threats and opportunities occur in real time. Waiting weeks for a snap shot of the market or your customers will mean your intelligence is too late in delivery or too narrow in scope to be useful.

 4. Poor Visibility

This challenge is a variation on the issue of silos. Results of analyses are frequently not distributed to or interpreted by the people who need the insights most. Boffins in the research department or web team are often blessed with data rich in value that they simply can’t appreciate or exploit. Most people don’t relish the prospect of wrestling with data and the most experienced, senior staff sometimes don’t have the time or the inclination to get stuck in.

 3. Fear & Ignorance

People fear breaching legislative and regulatory constraints and so avoid anything other than rudimentary use of available information. Ignorance of Data Protection and Privacy laws makes people cautious to the point of being ineffectual.  Perhaps more alarmingly, some businesses – particularly in highly regulated sectors such as pharmaceuticals or financial services –  are almost phobic about sifting through data. If they don’t know about a problem, their liability is perceived to be reduced.

 2. Misplaced Optimism

Data is eagerly analysed in the hope that it will magically reveal wisdom, rather than being scrutinized to test a prior, specific hypotheses. I once worked with a very intelligent and experienced executive who had an impressive background in research. They were absolutely adamant that exploration, if it is dogged and meticulous, will usually yield some revelatory results.  “Let the data speak!” was their mantra. I disagree more now than I did at the time. Collecting and crunching data without clear strategic objectives is like stamping on tubes of paint in the hope that a Cezanne or Turner will appear on the wall.

1. Corporate Momentum

This problem is as much a function of the psychology of social groups as it is an organisational or managerial shortcoming. Picture the scenario: A large study of truck loads of data has been undertaken at great expense in terms of time and money. The much heralded results are presented to the leadership team in a huge, beautifully presented Powerpoint that confidently sets out some apparently unequivocal truths. Who’s going to raise their hand and question the insights, let alone question the assumptions and methodologies?  The best case scenario is that deck is quietly ignored. The worst is that it is embraced as an unequivocal account and consequently influences important decision-making.