5 Ways That Marketers Are Mishandling Data | Adweek 5 Ways That Marketers Are Mishandling Data | Adweek
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5 Ways Marketers Are Mishandling Data

A skills gap
  • March 24, 2014, 8:00 AM EDT
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Your organization might embrace data-driven marketing, but are you putting analytical skills into practice? Producing actionable results poses considerable challenges for inexperienced teams. These five missteps are among the most common causes of a business failing to fully utilize the information at its fingertips.

1. Not taking advantage of deeper demographic information
For the marketer of yesteryear, the available information on consumers and audiences was limited at best: gender, age, household income. Today, the information is nearly limitless, but many marketers linger at the shallow end of the data pool. According to The Neustar Global Media Intelligence Report for 2013, retail marketers that targeted campaigns according to things like home value and brand of car resulted in a 500 percent performance lift over non-targeted campaigns. When combined with other data like a consumer’s credit and interests, these demographics can produce dramatic increases in conversions, as the computer maker Lenovo recently discovered by personalizing the banners on its site for different groups of visitors.

2. Focusing on the wrong metrics
Numbers need context, but context doesn’t always fit on a PowerPoint slide. Cherry-picked vanity metrics—Facebook fans, app downloads, etc.—create an illusion of data analysis, or even an illusion of success. But these measurements pale in comparison to deeper behavioral data, like navigation paths and brand preferences, directly linked to conversions. According to a Forrester Consulting study commissioned by Silverpop, B2B marketers utilizing behavioral data are contributing 34 percent of leads in their sales pipelines, compared to 26 percent for non-behavioral marketing. Even if the primary campaign goal is to raise brand awareness, retention and engagement metrics will provide more lasting value than, say, pageviews.

3. Ignoring offline activity
The traditional prospect-lead-customer sales funnel no longer applies to the way consumers make purchase decisions. Marketing campaigns stretch across an ever-increasing number of channels, and as a result, businesses are collecting data that they aren’t accustomed to tracking or analyzing. With so much attention being paid to new digital metrics, it’s easy to ignore or misjudge offline activity, such as purchases in brick-and-mortar stores attributed to online advertising. Per a Twitter study, consumers who engage with brands online are more likely to make in-store purchases (12 percent sales lift on average). Without a proper data analysis tool such as Neustar AK Closed Loop, the cause of those offline conversions will likely be chalked up as a great mystery.

4. Conducting analysis that doesn’t lead to action
Data analysis must inform every phase of the campaign, starting with planning and strategy, even when the numbers challenge gut assumptions and anecdotal evidence. Old-fashioned marketing teams work backward, belatedly gathering data to support the decisions they already made. By contrast, forward-thinking marketers harness data not just to critique the past, but also to predict the future. American Express uses predictive analysis and behavioral data to identify at-risk customers and reduce churn; since implementing analytical software, they’ve reported a 740 percent increase in attrition-combating efficacy. Predictive analysis will make the case for the ROI of a given campaign before it's launched, with mid-campaign adjustments helping maximize efficiency in real-time.

5. Assigning ownership of data to untrained staff
Ideally, data can spark a cultural shift, becoming infused not just in every stage of marketing campaigns but in all facets of the business as a whole. In the meantime, though, many businesses will encounter a big data skills gap. Surveying 500 U.S. business and IT executives, CompTIA found that 60 percent of respondents acknowledged a need to improve data management and analysis skill levels. A serious approach to data requires the commitment of resources, whether training existing staff, hiring in-house experts, wrangling outside analysts or purchasing new technology. Don’t count on the social media intern to separate causation and correlation.

Read Neustar’s Global Media Intelligence Report for 2013 and other useful materials for the data-driven marketer:

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