Monetising the big data deluge
A few years back I remember reading an amazing story about how the American store chain Target, keen to corner the ‘new mother and baby’ market, had analysed its data to discover which products pregnant women bought – with the aim of winning customer loyalty before the birth rather than targeting after the birth as its competitors did. It discovered there were 25 products that expectant mothers typically bought and by combining the timing and volume of these purchases they could accurately predict when the birth would be and send out vouchers and catalogues accordingly. Its approach was so successful that it actually resulted in one teenager in Minneapolis receiving a catalogue of baby products before she had got round to telling her father she was pregnant!
Now Target isn’t alone in cleverly analysing its data: last year Tesco collected over 1.5bn pieces of information a month via its Clubcard system which it uses to tweak promotions, inventories and price (I’m sure most of us have received the ‘50 extra Clubcard points’ token to buy the slightly more expensive washing up liquid than we’d normally purchase) while Amazon claims that 30% of its sales are now generated by its recommendation engine - “Customers like you also bought / you may also like...”)
Since Target started its analytics work back in 2002 two things have changed – scale and availability. Astonishingly it is predicted that every 22 hours this year humanity will create as much information as we did from the dawn of civilisation up until 2003 while data is being collected by (or being given to) a wider and wider range of organisations - social media, apps and search engines just to name a few.
The insight from analysing data collected is not just limited to what your customers like, dislike and purchase – we can also look inside an organisation to identify which salespeople are the most efficient, what the optimum number of meetings per client is, sweet spots for margins and the like. For the sake of simplicity, I’ve broadly categorised the gains that can be made into three areas:
- Improved decision making: the improved availability and frequency of data allows more informed and improved decisions to be made by managers and sales people.
- Spotting of trends: analysis of large data sets can allow trends to be spotted – for example consumer purchases vs the weather or the probability of winning a sales pitch by margin for a specific product.
- Narrower segmentation and tailoring of customer services: detailed information on consumer preferences allows customers to be segmented into very small groups allowing services to be targeted specifically (as per the example of Target above).
While the above examples of Target, Tesco and Amazon pay tribute to the game-changing effect of harnessing big data properly, the majority of companies are far behind the curve in this area. It is estimated the average British business only has insight into only one-fifth of its data. As such, it’s clear that huge opportunities exist for companies to monetise the value of the data they may already hold. Navigating how to do this, is the challenge.
There are still obstacles to overcome to capture the full potential of big data and the changes that businesses will be required to make in order to maximise it will be significant. However, it is clear that the rewards are there for those who pioneer in this field.
David is a Consultant in the Customer practice specialising in the use of technology to improve sales force effectiveness. He is currently working with a multinational security firm on the design and global rollout of Salesforce.com CRM to help improve its account and opportunity management.Twitter | LinkedIn