Can you use big data to make money?
ARE you using big data to make money?
Over the last decade or so, marketing changed to something VERY data-driven. No longer do CMOs make decisions based on intuition and experience alone. Increasingly, every decision.
Famously, John Wanamaker (the department store giant) said:
Half the money I spend on advertising is wasted. The problem is I don’t know which half.
Well, today’s CMOs would lose their jobs for making such a statement. Not only are they expected to know the ROI of everything they do, but they’re also supposed to use data to INCREASE the ROI by informing better decisions.
And, the potential for increasing ROI using data is enormous — 241% greater ROI results from using data to make better decisions. And, most businesses use big data to make money. Yet, online use of the wealth of data coming from your various social media platforms — Google Analytics, Facebook Insights, YouTube, and soon, Twitter analytics — is low. According to HBR, only 12% of companies are effective with their social media marketing and nearly 1/3 feel supporting the ROI of social media marketing is their biggest challenge and nearly half find it difficult to see how social media marketing can make a difference in their firm’s performance.
The Guardian echo’s findings from the HBR study, showing too few firms using data to support their social media marketing ROI or extracting business intelligence from their social media network.
Compare these numbers to data in the infographic to the right and you see a huge disconnect.
91% of firms use big data to make money, yet MOST don’t employ similar tactics to extract ROI from their social media marketing.
Using big data to make money
So, how ARE firms using big data to make money:
- improving efficiency on their shop floors to reduce waste
- identifying problems BEFORE they cause loss
- tracing CAUSES of defects and failures to the underlying condition
- finding new sources of raw materials — like oil
- making real-time decisions based on data unavailable before — such as GPS tracking
Likely, a variety of reasons explain why social media marketing lags in using big data to make money.
Social media marketing isn’t really that old. I read an RFP yesterday asking for 5 years of social media experience. Well, that was the infancy of Facebook and other social platforms were unheard of 5 years ago. It’s no wonder social media marketing hasn’t developed the tools of more mature fields, such as POM (production and operations management).
2. too few skilled workers
Many folks working in social media marketing come from either marketing (or related fields like advertising and PR) or the web. Neither fields teach specific analytics skills inherently important for gleaning insights from social media metrics.
3. emphasis on vanity metrics
Social media marketers don’t really know WHAT to measure and too often default to what we can “vanity metrics” — things like # Fans. While these metrics likely say SOMETHING about the effectiveness of your social media marketing campaign, translating these vanity metrics into sound decisions is problematic.
4. prevalence and ambiguity of existing tools
Google social media analytics and you’ll get a plethora of tools — too many, in fact, to evaluate effectively. And, more tools enter this space every day. I’m writing a social media analytics book and I’ve given up trying to evaluate all the tools as part of the book.
Plus, the available tools are ambiguous. Some say they’re social media analytics, when, in fact, their analytics capabilities are minimal and their main usage is in social media automation. For instance, I love SproutSocial but calling it a social media analytics tool is REALLY a stretch. In fact, since they’ve made integration with Google Analytics an upgrade, the analytics are pretty worthless. Its value lies in other uses of the software.
5. lack of planning
Maybe this related back to some of the other 4 aspects of why social media lags in using big data to make money. But, firms run social media marketing using a “seat of the pants” approach too often — without careful strategy development. Thus, it’s unclear what firms SHOULD measure. Plus, an over-emphasis on micro-conversions (sales) overlooks all the necessary steps LEADING to sales, which you must also measure.
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