Sunday, August 10, 2014

How “Big” is Big Data and how “Micro” should Segmentation Be?

“Big data” and “micro” are buzz words infiltrating nearly every marketer’s vocabulary. But how relevant right now are these trends, really, for most companies?





Image Source: from C570 Marketing lecture PowerPoint.


First, Micro segmentation:

While I agree that market segments are becoming increasingly smaller and that some companies are able to effectively “micro” segment I would argue that for the majority of companies, “micro” segmentation is a future (rather than present) reality.

First, I’d like to highlight some of the companies who are currently micro-segmenting, and doing it well. For example, Amazon actually has a customer segment of “one” because it customizes the user interface based on the user’s specific search history. Based on the user’s specific search history, the page will show different sponsored or recommended items. Another great example is Pandora, an online music service which customizes each individual’s play list based on past preferences of the user’s likes and dislikes.

While micro segmentation has been very effective for these companies, all companies should not conclude that micro segmentation will necessarily be a golden ticket for them. Amazon and Pandora have some things in common which make micro segmentation an ideal strategy for them, but it may not hold for all companies. For instance, both are heavily digitized; however, companies with large physical infrastructure will find micro segmentation much more difficult. For example, according to the “Long Tail” podcast, Barnes & Noble holds ~10,000 books compared to Amazon’s 5 million. Imagine a physical store that tried to keep Amazon’s entire inventory on hand!

If micro segmentation is not automatically a great fit for every company, what should a company consider before jumping on the bandwagon? First, a company should consider if micro segmentation will help with the company’s competitive advantage now or in the future. Second, while “micro” segmentation might not be possible for a company yet—how can their segmentation strategy be moved closer along the spectrum to “micro”?

The bottom line is that although the trend is definitely moving towards micro segmentation, some companies will need to take some steps to get there.

Second, Big Data

“Big Data” has to be one of the biggest buzz words in marketing today (pun intended). While the idea is simply fascinating, I have to question just how useful “big data” is right now for the majority of companies.
In January this year I attended a guest lecture by John Lucker, a principal from Deloitte Consulting on Business Analytics, in which he talked a lot about Big Data. His opinion was that Big Data was powerful but also over-hyped. I was glad to hear I was not the only one feeling this way! Big Data is similar to Micro Segmentation in the sense that if it is harnessed properly it can be extremely powerful; however, most companies have no clue how to deal with it, or the capacity to do so.

One company which has begun to harness Big Data is GE, which is monitoring large equipment in order to predict when breaks will occur to prevent downtime.  However, for most companies the barriers to Big Data are simply too large (pun intended again). First, there is a contextual problem with Big Data. As Lucker pointed out, even something as seemingly simple as Facebook “likes” can be difficult to derive value from. For example, if someone posts about a relative passing away, and someone else “likes” it—what does this mean and how does that compare to other likes? In order to make Big Data useful, you need to have the appropriate context, which is not always easy to do. Another barrier is that due to its complexity, proper Big Data processes require a large team with diverse skill sets—something most companies simply don’t have the time or resources to invest in.


Therefore while the potential power of Big Data is huge, it is important for companies to be wary of what Luker calls the “hoarder mentality.” There can be a temptation to store away Big Data for the future, hoping at some point the company can use it effectively. While this strategy might be warranted in certain cases, before they start “hoarding” companies should ask themselves the hard questions of “How much does it cost to store?” and “What value do you expect to derive from it?”. If the value equation doesn’t add up yet, hoarding too much “Big Data” could be a big mistake.

Readings:
  • HBR Social Media
  • IBM's CEO on the Death of Segmentation
  • The New Influencers
  • Seth Godin TED Talk: How to get your Ideas Spread
  • Chapter 1: The Long Tail (and podcast)
  • The Point of Twitter NPR podcast


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