By adaptive - October 16th, 2012

The Reactive Business: Social Media as the Customer Interface Social media powers big data and puts customer attitudes into the public domain, but finding out what customers are saying calls for ...

The Reactive Business: Social Media as the Customer Interface

Social media powers big data and puts customer attitudes into the public domain, but finding out what customers are saying calls for investment, intelligence and open-mindedness. For businesses that take the trouble to find out – and react accordingly – the rewards can be rich and long lasting.

The Internet has made us rather blasé about what should be jaw-dropping statistics. Take this nugget from IBM: “Every day, we create 2.5 quintillion bytes of data” And, to save you looking it up, a quintillion is 1 with 18 zeros - a billion billion. What’s more, these numbers are going up all the time: by the end of this year, we’ll be creating massively more bytes of data, adding to a store of information that is inconceivably vast.

This is “big data” - information we all create every day through online transactions, purchases and searches on retail sites, digital pictures and videos posted on Flickr, YouTube and the rest, tweets, Facebook posts, LinkedIn updates, smartphone data exchanges, and so on … and that is just data from individual Internet users.

For some people, the phrase “TMI - Too Much Information” might come to mind, and to some extent there has been a tendency to talk about an “info-glut” – or what Charles Ping of data management specialists Fuel brilliantly terms “data obesity”. But for all that, serious-minded businesses know that knowledge really is power, and according to Fuel’s Stefano Matteoli “research in the US indicates those who have invested in big data have benefited from a 20% increase in revenue”.

Use data intelligently to improve products and customer service

What’s important – essential even - is to harness that knowledge and use it intelligently to improve products and to deliver better customer service. And this is where the fun starts, because this mass of information is almost impossible to manage and process within traditional database systems.

On the other hand, making best use of big data still requires the deployment of conventional business practices, notably goal setting and planning. As part of this process, businesses need to consider so-called “time to value”: in other words, is it going to be worth all the time, effort and costs to find out what the data is worth.

And having decided that it is, it’s important to get input from all key stakeholders to establish what kind of data management is needed, and what are the proposed outcomes: it’s no use just shoving information in a data warehouse – there needs to be a reason, and that has to be related to business effectiveness and profitability.

Katrina Lamb, analyst and researcher at scientific marketing innovators Sentrana explains that one of the hallmarks of big data is “multiple data streams from multiple sources in multiple formats.” To render this data into a form relevant to a user’s specific marketing needs calls for a step-by-step approach, and she cautions that several of these steps can be quite challenging:

“For example, there needs to be the processing infrastructure in place, as well as the capability to do the transformation and translation of multiple streams and formats,” Lamb continued. Not every business has the necessary capabilities and attendant skill sets, and successful enterprises will be those who know how to find and deploy the relevant specialists and technologies: it probably won’t be cheap, but it will certainly be effective.

The challenge of analysing social data

For many businesses, it’s the data acquired through social media that is perhaps the most challenging to analyse, in part because it comes in so many different forms, from a re-tweet to a Facebook “like” to a post on a brand forum and so on – and it’s happening all the time. No wonder social media is often described as “word-of-mouth on steroids”. Analysis of this data is vital because, as Fuel’s Stefano Matteoli notes, “we should be able … to track the real behavioural change in humans and identify when a new trend is about to come.”

The methodology is, however, a subject of some discussion among different industry specialists. Darron Gregory of data and CRM specialists Celerity Information Services suggests: “For most businesses this data needs to be used customer by customer – rather than trying to create an IT infrastructure to manage it. Therefore the cost is the personal time to react to customers and the effort to make social interactions part of the customer management landscape.”

On the other hand, Charles Ping of Fuel says that handling masses of social data “is where software applications can sit as ‘middleware’ and help to translate raw data into actionable chunks of information.” He points to applications such as Brandwatch, Radian 6 and Sysomos that can help brands to decipher social media data although, as he also observes, it is up to individual companies to decide how to use this information: “Whether through data integration with existing databases, direct action through dialogue or merely observe the social media ecosystem”.

Dr Charles Randall of business analytics provider SAS notes that businesses also have the option of outsourcing to a third party, “which can provide them with access to the computing environment, analytical tools such as SAS Social Media Analytics, and the skilled analysts they need to take advantage of big data.”

She does, however, caution that in addition to the costs of the software, there’s also the need for skilled people to both create the visualizations and to analyze them. And Fuel’s Stefano Matteoli says that this could be an issue in the future, noting that it is “very hard to find qualified data scientists and people who are able to implement those systems. It is thought that by 2018 in the US there will be a shortage of data scientists, with only 190,000 available against a demand for 490,000.”

This is one of the most interesting – and, frankly, challenging – aspects of the big-data revolution: the increasing need to merge the business roles of marketing and technology. Time was when interpreting and using customer data was the sole preserve of the marketing department. However the scale, complexity and versatility of big data means that technology specialists are increasingly integrated into the customer-relationship paradigm.