Why Wall Street Should Be Paying Attention to Hyperlocal Analytics | Street Fight

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Why Wall Street Should Be Paying Attention to Hyperlocal Analytics

0 Comments 28 September 2012 by

I have many friends who are or were Wall Street analysts. They all want the same thing: data that can reliably predict key business trends but does not violate SEC rules on insider information.

Such data sources are fiendishly hard to find for most publicly traded companies. How can one predict iPhone 5 sales without insights into what is happening at the Apple stores? Retail tracker NPD provides some sales numbers on this topic, for example. But it does so a month or more after the fact. Apple fans have crowdsourced this project by counting serial numbers on phones sold — an effort that has actually yielded surprising success. But predicting spending at chain of restaurants or at a clothing store in a mall, which NPD may not actually track, is far more difficult.

Which is why I was so intrigued by Asif Khan’s column about integrating analytics tools into social media marketing and coverage on how restaurants can listen to location-based services. He referred to a MomentFeed infographic detailing how check-ins translate into sales trends. Obviously, this will do a poor job of predicting precise sales figures. But the correlation between directional trends and sales trends appears to be quite strong, based on what MomentFeed is showing. That’s great for marketers — but could be pure gold for Wall Street or for just about anyone trying to analyze how a company is doing on a month-by-month or week-by-week basis (think private equity firms and business brokers).

Let’s take a quick example. A publicly traded chain of retail stores may run some holiday promos during November, the biggest shopping month (and one that often accounts for as much as 25% of total annual sales volume). Social media is heavily involved in these promos. Users check in and retweet and otherwise engage. A savvy analyst would know, roughly, how much each customer is likely to spend per store visit — or to have a decent idea of this. After a few quarters of watching social media trends and mapping this back to actually quarterly sales, the analyst should be able to piece together decent correlations that would allow him or her to predict the direction of sales momentum and the percentage change.

This information alone should provide key insights when combined with baseline sales numbers, and here is where it gets really interesting; unlike extremely expensive services like Bloomberg or expert networks or survey firms that typically sell deep insights to Wall Street, social media listening around location and company is going to get very cheap because it is driven by economics of the Internet. So in the near future everyone will be able to set a screen tracking check-ins and tweets for a wide swatch of public companies they may happen to be following or own as stocks. Overall, too, this will collapse the gap that has persisted between Main Street and Wall Street with regard to access to truly actionable information about company performance. In the past, this information was whispered or collected through less Democratic means. In the future of LBS and listening tools — leveraging powerful analytics tools to make sense of it all —  hyperlocal becomes not just a way to understand customers but a way to invest smarter and way to level the information playing field.

Alex Salkever is an executive at a cloud computing company and a former technology editor of BusinessWeek.com. The views expressed in his column are his own and not those of his employer. His Personal Fight column appears every Wednesday on Street Fight.

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