Whenever you read an article aboutor analytics, the focus of the article is generally geared towards size and the terabytes of data being produced by businesses every day. If you took these articles at face value, then you’d be forgiven for thinking that we are drowning in data and unable to cope with the massive amounts of information we continue to amass. But is this really the case? Are we producing so much data that we can no longer cope? More to the point, is size really the most important factor in ?
The fact is most organisations do not produce enormous amounts of data, unless of course those organisations are the size of Amazon or Google. The majority of companies are producing levels of data that they can comfortably cope with. What’s important for these companies is not how much data they can generate, but how they can derive advantage from that data and use it to gain insight. It’s a question of deciding which data metrics matter most. What’s important is bringing together all the different types of data, and using this amalgamated information to track the customer journey: in other words, joining up web traffic, advertising and promotional codes with sales or referral statistics. Using this joined-up information will give businesses an insight about what customers were doing before they made their purchase. This approach allows companies to join up the dots, and gives them information they can act on and measure.
But increasingly many companies are taking this broader analysis one stage further: the focus isn’t now so much on the customer journey, but using big data analytics to influence customers before they begin their journeys. The reason for this is simple: by the time a customer visits an online store, they’ve probably already made their mind up about their purchase. They’ll have talked to friends, looked for recommendations on social networks, read online reviews, and completed all the research they believe is necessary to inform their purchase.
The trick for businesses now is to get in on the ground level and to start to influence these purchasing decisions. They can achieve this by overlaying web traffic, search analysis, social media insights and competitor analysis on top of sales data, leads, referrals and other internal statistics. This combined information will help them to better understand the type of thinking that underpins customer choice, and give them all the information they’ll need to start to influence customer choice.
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