The State of Social Media Analytics: Listening is Not Analyzing
As I mentioned in a previous post, we are working on a vertical solution for Social Media Analytics. I chatted with a few folks yesterday over lunch who posited that the recent acquisition of Radian6 (R6) by Salesforce.com (a good post on the acquisition by Susan Etlinger can be found here) meant that opportunities for a social media analytics product had passed. I thought this discussion was interesting enough for a post. But before I begin, my congratulations to the folks at R6 on a great exit and on being acquired by such a great company.
I think the best way to think about the current state of Social Media Analytics is to look at the history of brick and mortar retail. In any industry, it is initially very difficult to communicate with, and learn from, important external entities, be they suppliers or customers. The communication typically starts as a manual process and as the relationship becomes better understood, you then move on to automation, storing key interactions in some sort of digital system (such as a database, data store, or data warehouse). Over time, as the ecosystem gets more sophisticated, the signals (red cell phones are selling, inventory is continually low in the Southeast, Retailer X always pays late) become richer, more varied, and frequent. Automation then speeds up the pace of business and those important or missing parts of the signal become visible. For example, in traditional retail, we went from manual PO’s, to faxes, to fully automated Supply Chain Management with EDI, and continue to enrich the signal between retailers and consumers with technologies like near field communication (NFC) that enables things like mobile payments, mobile ticketing, and smart posters.
It is interesting to note that the technology to automate and store all this transactional data existed for years before automated systems really started to use it effectively (such as Price Optimization, Demand Management, etc., etc.). In fact, large retailers’ analytics systems are still primarily made up of expensive, home grown systems, like RetailLink at Wal-Mart, or by a combination of SAS and Excel which is then powered by a room full of PhDs.
The point is this: you have to get to good at capturing the signals before you can analyze them. Social media as an industry has just entered this stage. While there are some great tools you can use to publish a social media campaign, to monitor/listen to conversations about the things you care about, and perhaps, to gauge sentiment (IMHO there is some real snake oil feel to a lot of sentiment analysis—people claiming to do it with lexical analysis have got to be kidding—however, that is another post), there are still no true analytics packages. This is why Altimeter Group’s study by Jeremiah Owyang The Social Business Stack for 2011 cites ROI as the number one concern for corporate social media groups and includes analytics in three of their four viable remaining targets for venture investments in social media. (I highly recommend viewing the whole slide deck as it is a great read.)
We have had many discussions with some very smart social media folks throughout the design phase of our solution and were shocked at the problems they were having justifying their budgets because they could not directly tie their social media campaigns to hard numbers. Today, buying a great listening tool like R6 and then exporting data into Excel is considered state of the art for social media analytics. Where are the multivariate market impact models that even medium sized brick and mortar retailers routinely use today?
Rather than being closed, we believe that the market for social media analytics is just beginning and we are looking forward to getting our product out there. We are not going to try and reinvent social monitoring/listening tools, but are building on the foundation of these platforms and great web tracking systems like Google Analytics to bring social media analytics into parity with other customer focused marketing tools. This is the beginning, not the end for social media analytics.