3 Social Analytics Mistakes: Don't Be Fooled - InformationWeek

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Software // Social
09:06 AM

3 Social Analytics Mistakes: Don't Be Fooled

Are you rocking your brand's social presence -- or kidding yourself? Make sure you don't fall into these common traps.

10 Worst Social Media Meltdowns Of 2013
10 Worst Social Media Meltdowns Of 2013
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Your company is raking in social capital: Likes, followers, retweets, mentions, and so forth. You're flat-out killing it, as the kids are fond of saying these days. But what's all that data really worth?

If the value of your brand's social presence seems to fluctuate like a Bitcoin on a bad day, it might be that you're making some major mistakes.

We asked Ben Cockerell, director of marketing at uberVU, which was recently acquired by Hootsuite, to help identify the most common errors brands make when sizing up their social analytics. Here's what he had to say.

1. You're not measuring against industry benchmarks.
All those highfalutin' social metrics you've been bragging about around the office don't mean anything without the proper perspective. For starters: How do your numbers compare with your closest competitors'?

[What do you hate about Facebook? Read Facebook: What We Love To Loathe.] 

"Brands may have great impression and engagement metrics, but without the context of measuring them against the rest of the industry, you're only seeing half the story," Cockerell said via email. "For instance, say you have millions of monthly mentions -- that's impressive. But if that's par for the industry, you're really not gaining any share or traction."

Cockerell shared an example from the auto industry. Chevrolet generates 15 million impressions a day on social media, according to Cockerell's numbers. That's a figure many marketers would love to take into their boss's office. The problem? When stacked against Ford, Toyota, and Honda, Chevrolet is barely keeping pace. On some days, Chevy's getting lapped. Ford, for instance, has been hitting -- and sometimes blowing past -- 50 million impressions per day of late.

2. You're searching wrong.
Cockerell lives by the phrase "you get what you measure." If you're not listening to the right signals, what you hear on the other end could be a chorus of nonsense.

"The only way to do social analytics right is to measure the right things," Cockerell said. "That inevitably begins with optimizing the search expression you're using."

Photo: Wikipedia.
Photo: Wikipedia.

He offered a straightforward example: If you're tracking social sentiment around Apple, your search expression better not be: "Apple." That's at best an incomplete picture, and more likely will generate a bunch of noise that drowns out the valuable data.

"Instead, you'd need to filter your search to focus on the keywords used in social when talking about Apple the brand -- not apple the healthy fruit snack," Cockerell said.

A more optimal search expression might look something like "apple corporation OR company OR store OR stores OR phones OR smartphone OR tablet OR ipod OR iphone OR ipad OR mac" -- you get the idea. Likewise, an optimized search would exclude terms such as "eat" and "fruit."

3. You're only measuring marketing metrics.
This one's a gaping pitfall for businesses of all sizes: Social analytics is all about marketing, all of the time, without much consideration for what all that data means for the rest of the organization.

"Social analytics were born in the marketing department, but they don't have to stay there," Cockerell told us. They "can be utilized throughout the organization to improve business results."

Here are three measurements uberVU has seen clients use to positive effect outside of the marketing department:

  • Tracking response time to social posts (customer service)
  • Attributing leads to specific social channels (sales)
  • Establishing market size by measuring a specific industry's volume of social mentions (product/business development)

Got your own social analytics success stories (or whopping failures)? Don't be stingy, social mavens; share them with us in the comments section below.

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Kevin Casey is a writer based in North Carolina who writes about technology for small and mid-size businesses. View Full Bio

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User Rank: Apprentice
2/14/2014 | 1:34:19 PM
Re: Helpful, Actionable Insight
D. Henschen--thanks for thoughts and the insightful question.

Automated sentiment analysis is most definitely a hot topic now and I suspect will continue to be so. While incredibly useful, I never view automated sentiment analysis in a vacuum; rather, it is one metric among many (key words associated with brand or product and sharing are two key others) to best determine an accurate assessment of how social is reacting in regards to your search term.

Additionally, if you are seeing a strong disconnect or lack of correlation between these other metrics and the automated sentiment analysis, you'll know it's time to further investigate its accuracy and make changes to scoring where necessary. Great question--hope this helps!

D. Henschen
D. Henschen,
User Rank: Author
2/13/2014 | 9:28:06 AM
Helpful, Actionable Insight
This is great, practical information that you can put to use. Particularly relevant is the pointe to look beyond marketing metrics. Any tips on ensuring that automated analysis of sentiment is on target? Or whether "positive" and "negative" are truly helpful measures? These remain hard questions for those mining social data.
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