By adaptive - October 17th, 2012

Big data tells us more than we ever knew about customers: their attitudes, their preferences, their dislikes, their hopes and aspirations. But is that too much, when all we want to do is make a ...

Big data tells us more than we ever knew about customers: their attitudes, their preferences, their dislikes, their hopes and aspirations. But is that too much, when all we want to do is make a product that customers will buy? Can we (should we) talk to individual customers and design products accordingly? It’s not without its dangers – or its opportunities.

Unwrap the Information and Find the Opportunities Within

Big data tells us more than we ever knew about customers: their attitudes, their preferences, their dislikes, their hopes and aspirations. But is that too much, when all we want to do is make a product that customers will buy? Can we (should we) talk to individual customers and design products accordingly? It’s not without its dangers – or its opportunities.

In the time it takes you to read this blog post, billions of bytes of social data will have been created, through thousands of tweets, Facebook Likes, LinkedIn updates, blog comments, forum responses, posts on Foursquare, Pinterest and Instagram – and those are just the more obvious places. It’s seriously big data, and it’s getting bigger.

If your brand or business has an active Twitter feed or Facebook page, watch it for a while and see how social-media chatter reflects and frames opinions - about your business, your brands, what you sell and don’t sell, and about the level of customer services your business delivers.

What can you do about it? Well, firstly, you can’t just ignore it and pretend it will go away – that is not going to happen. You can try and use it, but because social-media data is largely unstructured, that’s not going to be easy. There’s no point in even trying to monitor and analyse it manually: the days when you could take on a marketing trainee to monitor and respond to social posts were over almost as soon as they began. So, once again, what are you going to do about it? It’s a question that has to be addressed – and quickly.

Research shows data has a balance-sheet asset value

Dr Charles Randall of business analytics provider SAS says that businesses are increasingly aware of the value that big data offers, pointing to research conducted by SAS which showed one in five businesses assigning a value to the data they hold. He notes that big data has three characteristics: volume, variety and velocity, and says that “Our customers have found that coming to grips with the velocity at which data arrives offers the greatest potential for companies to change the way they do business. Online retailers can offer an adaptive customer experience which changes in real-time in response to a particular customer’s past and present browsing and purchasing behaviour.”

It’s clear that successful businesses will be those which actively use the data they acquire, or which is readily available in the public domain. But how much data will simply be warehoused – because that is relatively simply – and not used?

Katrina Lamb of scientific marketing innovators Sentrana makes the point that: “Data – even big data - is of little use in its raw form”, and goes on to note that raw data must be translated “into the customary business language that expresses how you measure performance – financial performance, operational performance, return on marketing investment – and how you gain predictive insights that let you make data-informed decisions.”

There’s no getting away from the fact that this will require investment: and the larger the brand, the more the social media traffic, the bigger the investment is likely to be. And, on the other side of the equation, the greater the potential rewards to be reaped. Cara Rogers of McKee Wallwork Cleveland makes the point that some analysis can be relatively inexpensive as “most of the social media platforms offer access to metrics associated with company profile pages; this can be quite useful in analyzing the effectiveness of a company’s social presence.” She also emphasizes the importance of “having a solid means of collecting and analyzing the data to help guide marketing strategies,” because, as digital channels evolve, the average company will have access to more and more data.

Big data leverage

Darron Gregory of Celerity Information Services says that: “As a data practitioner, I’m excited about the possibilities that big data brings,” and while cautioning against its misuse notes that if big data is used properly it “will provide a brighter CRM future where we finally realise the promise of contextual marketing.” And this is, of course, the Holy Grail of customer marketing: addressing individual consumers who interact with brands on a social level, analysing their needs and preferences as demonstrated through social media, and linking this information in to all the other touch points that consumers have with the brand.

The point was made in the previous post in this series that to achieve this requires a melding of the skills of technologists and marketing specialists. Database specialists and statisticians need to work alongside behavioural scientists and marketing analysts. This is going to take investment in personnel, software and equipment, some or all of which can be outsourced.

As Stefano Matteoli of Fuel explains, “many software vendors have developed platforms that support the hosting and storage of big data. Online businesses have started to invest in those technologies since they have seen the value in it.” He does caution that it’s going to take a while before CRM can be fully personalised and suggests that: “it would be more beneficial to try to derive insights from big data and use that to identify trends and make major improvements to the product.”

Cara Rogers of McKee Wallwork Cleveland agrees that data should be used to identify trends within a marketplace, but also suggests that it is possible to compile databases with individual customer information: ”Through data collection and intercept studies at each point in the customer lifecycle, a company can learn quite a lot about each individual prospect or customer.”

She goes on to point out that this very much depends on company goals and its overarching strategy, because tailoring messages to individuals rather than groups of consumers can be both expensive and time-consuming. The cost of targeting individual customers is something we’ll come back to in the final post of this series.

It’s undoubtedly the case that the data from social media can help businesses make a connection with customers that’s far deeper and more intense than any other contact apart from sitting with them in their own homes or offices. But the bottom line is that the investment in analysing and using that data has to have a positive impact on the bottom line: unless there are profitable sales as a result, social media chatter is, well, just chatter.

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