Surveillance capitalism has become the world as we know it – a place where the value and ethics of big data are still being thrashed out.
I’ve always had a bit of love-hate relationship with fashionable ‘megatrends‘. Working for technology companies that invent terms and trends designed to boost sales has trained my sceptic-antennae to wiggle whenever a new ‘revolutionary’ term was handed to the marketing desk for treatment. big data was no exception.
The ‘big’ in data, in fact, made the concept so vague that nobody could really tell what it looked like, where it lived or what it meant. Convoluted corporate speak didn’t exactly help matters.
It took a few years of to-ing and fro-ing until we all accepted that ‘big’ was referring to the amount of raw user information that exists in various digital containers and ‘data’ was about making sense of that information – preferably in real-time. Kind of like a factory line of information that goes through a processor and comes out at the other end all nicely packaged, and with a price tag. Perfumed with the allure of ‘megatrend’, we mustn’t miss out on how it’s going to change our lives – with or without our permission.
The moment I digested the actual simplicity of it, I started having wild arguments with my Eastern European friends, who cried that the whole concept reminded them of a Russian visa-application process. This particular task apparently requires you to divulge the kind of information about your mother, father, partner, high-school teacher, childhood pet, current and former boss, and any secret lovers – thank you very much – that you might have trouble providing if any of the mentioned are no longer among the living.
Your memory might simply (or conveniently) fail you. And fail to deliver you to St Petersburg where No 56 on your bucket list – visit the Hermitage – is to be crossed off. Am I exaggerating? Just a little. But Eastern Europeans don’t like surveillance and Russian visas and big data reminds them of it. Big Time.
It wasn’t the Europeans who invented the term ‘surveillance capitalism’, though. The term was coined in the intellectual cradle of capitalism – at Harvard Business School – to describe the process of data extraction and commodification of personal information in order to ‘produce new markets of behavioural prediction and modification’.
American computer security and privacy specialist, Bruce Schneier, puts it less politely:
“The primary business model of the internet is built on mass surveillance,” he says.
This surveillance might be incidental and obscure, but it nevertheless produces massive amounts of ‘meta-data‘ that can be turned into intelligence or – as marketers call it – insights.
These insights are mostly used by corporations to sell products and services through personalised advertising (governments, as Schneier observes, only piggy-back on the surveillance trends). That’s the price of technology proliferation and democratisation, and the excitement of it – if you’re in the marketing game.
Ethical insights into consumer behaviour can indeed help companies spark innovation, uncover new sources of growth, and successfully develop new products, services and brands. By digging into customer discovery, purchase decision journeys and customer feedback, insights allow marketers to make informed decisions about their marketing strategies, product design, pricing, customer experiences and brands.
Want more? Try this: Why there’s no denying disruption
Aside from establishing and implementing appropriate privacy and ethics boundaries, the biggest hurdle to unlocking value from all this data (big, big sets of it!) is analysing and acting on it.
This process has given rise to yet another trendy consulting term – technology-driven marketing transformation. In plain terms, if you spend enough money getting the right software and systems in place – you will be able to get into the customer’s mind deeply enough to predict and prepare for their purchasing behaviours, cycles and needs. And if you follow the stuff advertisers serve to you online – you know that some of these systems allow you to react to your customer’s behaviour in near real-time.
Avis Budget, a car rental company operating two brands that serve more than 40 million customers around the world, recently used big data to get better insights into their customers’ purchasing habits and intentions, according to a case study by CSC.
Standing out is difficult in any industry these days, but rental companies have even less scope to differentiate through fleets, locations and rates. Hence, differentiation is built on customer service and experience – both of which are largely technology-driven, according to Tim Doolittle, Vice President of CRM and Marketing Science of Avis Budget.
Doolittle and CSC built a 360 view of the customer, enabling millions of customer records and data sets to work together to analyse and predict customer behaviour through a single customer dashboard.
“Technology is used to forecast regional demand for fleet placement and pricing. Data is analysed to better understand customers’ needs, preferences and intent to rent. From the service side, technology helps us offer a more cohesive customer experience across each of our customer channels,” Doolittle says.
Doolittle said the transformation allowed Avis to “yield three-to-five-year projections” of customer behaviour, analyse their profile and profitability and develop differentiated customer service solutions in line with those predictions.
Insights about Avis’s marketing outreach are equally useful – they reveal where campaigns, communication and surveys fail to reach or engage the customer. “That approach has increased the effectiveness of our contact strategy, in many cases above 30 per cent,” Doolittle said.
Avis’s experience illustrates most of the key lessons on how to use big data to derive useful marketing insights and strategies.
1. Big data gives you more information about the customer than ever before
As Doolittle explained, analysing data to learn more about your customers gives you not only a better ability to target them with matching products, services and experiences, it also gives you the ability to accurately forecast and plan your sales ahead of time. Integrated customer behaviour data, analysed and presented in a single dashboard enables up-to-date customer insights to be accessed in real-time.
2. Real-time personalisation is a digital marketing must
Marketers need to send the right message at the right time in the right way in order to engage. Big data provides timely insights into who is interested or engaging with our product, service or content – in real-time. Integrating digital behaviour and insights into CRM and marketing automation software will allow you to track what your customers are interested in and send them relevant content, product or service offerings at the right time via the right channels.
3. Moving customers down the sales funnel is no longer a guessing game
Some content engages, some doesn’t. Before big data and analytics, it was hard to tell how our content was engaging the customer or generating revenue. Today, integrated tools like content scoring allow marketers to develop content strategies that assist buyers and compel them to purchase.
Millions and millions of data points derived from online content interaction enable real-time visibility of content performance, helping marketers to target and adjust their strategies in time to move their customers along the sales funnel.
4. Predictive analytics generates 50% more qualified leads at lower cost
Predictive analytics is one of the most effective big data strategies marketers can employ to impact their sales funnel. Predictive lead scoring – such as Avis’ analysis of future buyer behaviour – integrates and analyses a company’s CRM and third party internet data to successfully predict future customer behaviours. Historical data around successful leads (i.e. closed and won deals) give marketers clear insights about digital behaviours that should be weighed more heavily in lead scoring.
But that’s only the beginning. Marketers around the world are finding hundreds of ways to harness big data and inform their strategies.
Share yours in the comment section below.