What’s the value of social media analytics? Two general use cases get talked about the most. The first is ‘engaging with customers’ and the second ‘measuring sentiment’. Brian Solis at HBR is circumspect about businesses’ prospects of meaningfully and sustainably engaging their ‘customers’ via social media:

As part of its research, IBM asked business leaders what they thought consumers were seeking in a social relationship. The results identified a dramatic gap between presumption and actual demand.  The top two reasons consumers gave as to why they interact with companies in social networks were:

1. Receive discounts (61%)

2. Make purchases (55%)

In contrast, businesses believe that the top two reasons consumers follow them in social networks are…

1. Learn about new products (73%)

2. To receive general information (71%)

While consumers expressed the desire to receive discounts or make purchases as the top reasons for engagement in social media, businesses view these actions as the lowest two motives for connecting in the social web.

But there are deeper problems than this misalignment. As Solis notes:

Brands are furiously creating profiles in social networks such as Facebook and Twitter in the hopes of building engaging communities with customers and giving people what the brands think they want. The main activity in this effort is to spur consumers to “like” and “follow” a brand’s Facebook and Twitter streams.

Most traditional data mining done by businesses is on data which captures revealed preferences, or, in the case of surveys, carefully framed stated preferences. A sales transaction records an identifiable customer choosing to hand over money for goods and services. Even an ‘anonymous’ point of sale cash transaction is still a sale, attributable to a product at a store at a point in time for a price.

Social media, on the other hand, is free to use and useable by anyone. It demands small measures of time but none of money. Accordingly, its strength and reliability as a measure of revealed preferences is limited. Eyeballs, tweets, likes and mentions, though they may be plentiful, are not dollars spent. Nor are those who generate them necessarily customers. Any social media user can say something positive or negative about your brand online. They don’t need to be customers—or even prospective customers—to do so. Neither does their audience. The dollar impact of such sentiment is therefore unclear. Nor are people offline necessarily who they say they are when they’re online. Social media user accounts are personas. Without a reliable and substantive signal in place—such as money changing hands—the relationship between an online persona’s social sentiment and an offline person’s commercial value is weak.

Furthermore, as John Barnes recently argued in his excellent post on unrepresentative sampling, even the “best, subtlest, and smartest analysis cannot overcome the problem of analyzing the wrong population”. The representativeness of the subset of customers ‘engaged’ via social media should be open to question.

These are all reasons to suggest that, for the vast majority of businesses, analytical resources are probably better deployed almost anywhere other than on social media analytics. Online, for most businesses, is just another sales channel and should be prioritised accordingly (pure e-commerce companies being the obvious exception). There are, as always, more perverse hype-centric reasons for the focus on social media, as we’ve commented on before.

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