Big Data – The Austerity Buster

There’s one thing that practically everyone agrees on when it comes to the economy. To get it moving again, people have to be willing to spend money.

When times are bad, convincing people to part with hard-earned cash isn’t easy. The threat of redundancy looms over large swathes of society while businesses face ever-lengthening lead times to get their invoices paid and ever-narrowing access to credit. The net result is that spending – whether on the high street, between businesses, in the housing market or anywhere else – dries up. Businesses don’t make money, investments stop and the Treasury takes a hit to its tax revenues.

Many ideas and tools have been developed to help the situation. VAT went down, VAT went up. We had the automotive scrappage scheme. The banks have been implored to open up overdrafts and credit lines for small businesses. Companies have been asked to commit to paying invoices no later than within 30 days.

Out of those measures which had any effect at all, nothing has become the silver bullet. Perhaps it’s time to consider big data?

Essentially, big data enables you to give people what they want. This occurs in two ways, both of which we will explore now. One – you can find out what people are looking to purchase and serve it up to them instantly. The other – you can find out what aspects of your products people use and enjoy, and where they think improvements should be made to increase their engagement.

This is particularly prevalent in a tiered use and payment service environment. The more features people use, the more they pay for. A mobile phone contract is a perfect example.

Understanding our customers

Big data enables targeted marketing in a number of ways. In the simplest scenario, Joe Bloggs ‘likes’ a product – say Wellington boots, for example – on Facebook or expresses a desire to buy a set of everybody’s favourite rubber footwear on Twitter. We can then buy advertising space on the next website he visits and advertise a fetching set of the farmer-friendly waders directly to him.

Alternatively, we can go one step further and locate him via the GPS on his mobile phone and send him an advertisement the next time he physically comes within a walking distance from the boot shop.

In terms of the complexity of the intelligence, we can go as deep as our data and our ability to process it allows us to. For the average person, that is pretty deep. Perhaps Bloggs mentions on Twitter that he has just won tickets to a music festival on the upcoming weekend. As well as the Wellington boots, we can assume that he’ll be needing a tent, a rain coat, some sunglasses and probably some hangover tablets too – we can then advertise accordingly.

Moreover, our intelligence doesn’t need to be so explicit. We can spot patterns in transaction data which show that if you are interested in the first three products, you’ll probably be interested in a certain fourth, even if it has nothing to do with the first three.

We can see subcultures you belong to which you might not even necessarily recognise yourself. We can then identify which platform (Internet, mobile, print, voice etc) you are most responsive to for advertising and which aesthetics (text colour, background colour, accent) you react to most often. Far removed from spam emails promising to extend certain parts of your anatomy, big data gives the right information to the right people – it allows for occasionally quite eerily accurate advertising and marketing campaigns.

These are all things we have tried to do before, in many cases with great success. But big data takes it away from analysis of the masses or even small niche groups where lots of people are grouped together and are tarred with a single brush. Increasingly, it’s all about the individual.

Reporting back

Moving on, product improvement has been greatly aided by big data and the ‘Internet of things’. This latter term of course refers to the fact that everyday items from kettles to cars now come laden with RFID and telemetric chips constantly reporting back on their performance.

This means that we can see which areas of a product or service are being utilised, and to what effect. We can take this intelligence to improve future iterations of a product – for instance, install more durable components in a car – which will improve the performance and, thus, our reputation as a company.

In the manufacturing industry, many suppliers include telemetric devices within their equipment, which report back on the frequency and noise levels of the machinery. The issuing company can then manage maintenance schedules or supply consumables more efficiently, while the host company can receive data on employees’ working habits which can be used to find inefficiencies.

These are all ways (and there are infinitely more) of adding to the value proposition of our offerings and giving people the right marketing messages when they want them. The extra revenues we earn will result in the growth of our company, paying more taxes, employing more people that then buy more products themselves, and the wheel keeps turning.

Ergo, big data is the best tool the economy has to call upon.

Concerns

Of course, this theory relies on the assumption that people will spend money if they are presented with the right opportunities. It could be argued that since the doom and gloom warnings have forecast that it will take decades for the economy to be restored, people would rather sit on the reserves than spend them, no matter what they are offered.

The downturn of the economy was the result of a complicated web of factors and knock-on effects. Any potential upturn would need to follow a similar route, but we maintain that big data could grease the wheels.

Some might say that some of the tactics of big data are underhand, such as leveraging the colours and fonts that most appeal to the consumers. The argument would be that no value has been added to the product, only the marketing material. However, this is nothing new; big data merely accentuates it, as it does anything else. And the end game is the same – people spend more money.

Others have expressed concerns about the intelligence of big data systems in predicting what we want – does this not prevent us from getting a rounded view? It’s a valid argument for another day; all we’ll say now that any nun searching the Internet for ‘the second coming’, as in our cartoon, will probably be glad if the system adopts to her.

Value proposition

Big data allows you to take basic frameworks and then adapt them creatively to fit your business needs. If you’re not in a position to gather your own data (which most should be able to do in one form or another), you’re not excluded. In the start-up industry alone, there are thousands of companies that are gathering all kinds of voluminous information which could be useful. They’ll offer it up to you as a service; you just need to identify the partnerships that can support you.

In the end, just like we can now find the buttons to push for each individual, your path to big data value creation will be unique to you. Take inspiration, sure – there’s every merit in recognising a good idea when you see one – but don’t feel bound by what others are doing. Big data takes us into the realm of unique solutions; to get the full benefits you need a strategy that is yours and yours alone.

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