By adaptive - October 17th, 2012
It is theoretically possible to know precisely what individual customers think about products or types of products. Are they fans of Macs or PCs; Galaxy or iPhone users; Kindle or paperback read...
Are you Ready for One-to-One Customer Communication?
It is theoretically possible to know precisely what individual customers think about products or types of products. Are they fans of Macs or PCs; Galaxy or iPhone users; Kindle or paperback readers; Tesco or Waitrose shoppers; and so on. But what internal systems and procedures are needed to act on this granular data? And is it worth the effort?
Anyone who has ever purchased – or even looked at – products on the Amazon website will be familiar with the subsequent stream of emails suggesting related goods in which you might also be interested.
Depending on your perspective, it’s somewhere between being a gross intrusion on your privacy and a helpful source of information. One thing is certain: opportunities for this kind of individualised customer interaction are going to increase.
We publish more information about ourselves than ever before, not only through tweets, likes, forum posts, video uploads and views, but also as a result of web surfing, online searches, smart phone data streams and the rest. Another of those amazing statistics from IBM: “90% of the data in the world today has been created in the last two years alone.”
Understand the customer to meet their precise needs
This mass of data clearly represents opportunities for businesses: the better you understand what a customer likes, enjoys, desires or prefers, the better able you are to meet their precise needs. And conversely, the sooner you know what a customer doesn’t like, or what irritates the hell out of them, the quicker you can stop yourself doing it.
Steve McKee, president of McKee Wallwork Cleveland, writing in Businessweek said: “For any size business to stay competitive, it’s imperative to get a handle on its data because its counterparts are already doing the same with theirs. The glut of data available today is of no use if it’s not in a form that can be easily accessed and understood.”
And all businesses have access to this data: the question is how best to use it. Darron Gregory of Celerity Information Services advises: “Organisations often have to go through cultural changes that are more profound than system ones. What the data means, how can it be used, what it tells us about our customers – these are some of the questions that need to be grappled with.”
He goes on to explain that making both data and insight actionable: “requires businesses to think of big data strategies from the outside in AND from the inside out.” Dr Charles Randall of SAS agrees: “the biggest change a company needs to be ready for one-to-one customer communication is cultural. All the successful companies that have made this shift have first gone through a significant and profound change in their internal culture, with a shift from being product centric to being customer centric. Changes to internal systems and processes then naturally fall out of this change.”
One of the strategies that needs to be considered in dealing with big data is simply its storage. Data warehousing technology has developed at speed, alongside the explosive growth in data acquisition, and the latest architectures provide a wide range of opportunities for both the management and structuring of data.
This is particularly important given that data is increasingly acquired from different sources and in different formats. Some is structured, a lot is unstructured, and to make it suitable for product development and customer relationships, it needs to be integrated, restructured and re-presented so that complex queries can be understood and answered quickly and effectively.
Refining data warehousing and making it more effective
Programming technologies have also been developed to refine data warehousing and make it more effective. One of the most important is Apache Hadoop, an open-source software framework that is designed to run applications across a large number of computers – which is typically how a data warehouse operates. With its origins in Google’s search processes, Hadoop is used by a wide range of software developers to create programs, which enable warehoused data to be mined, interrogated and summarised – users include the aforementioned Amazon.
Fortunately, most businesses don’t need the complex programs that Amazon uses, and have no need to get to grips directly with technology such as Hadoop. Specialist providers – including several of those that have contributed to this series of posts – have developed applications that will enable businesses to make genuinely customer-centric decisions, based on defined and stated preferences.
Cloud-based applications – many based on the Hadoop platform – and more powerful, low-cost hardware allow massive amounts of data to be analysed at incredibly high speed, presenting results that enable complex judgements to be made on-the-fly. Charles Ping of Fuel points out that the days of holding data simply because you can are coming to an end: “Data that can’t drive a different decision or action is of little value. What’s important is the design of systems that can aggregate data rolled-up into specific views for example by brand, time period or individual.”
The implications of this are considerable, because it will enable businesses to entirely change their approach both to customer interactions, and to the way in which they structure their offering. Steve McKee of McKee Wallwork Cleveland says: “Perhaps the most exciting application of big data is in helping organizations anticipate the future…using customers’ online behavioural data to project how new products will perform. For marketeers, social media’s initial promise was brands’ ability to interact with their fans in real time. Now its bigger value may lie in analyzing those conversations to determine customer sentiment, identify product improvements, head off nascent public relations crises, and understand evolving needs and perceptions.”
Katrina Lamb of Sentrana says that with so much data in the public realm: “one of the potentially transformative aspects of big data is in forcing a greater level of collaboration among industry partners in value chains. Enterprises will need to find better platforms for collaboration where they can improve performance up and down the chain, not just within their own concerns.”
It’s clear that the impacts of big data, particularly data derived from social media interactions, are going to be considerable. It will provide more information about markets, customers, trends and attitudes than any other form of business intelligence in history. Moreover it will provide it more quickly than ever before. For those agile businesses that react efficiently, it could offer a potentially deadly advantage in the marketplace.
June 2014, New York
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