Big Data – Big Deal?

Thanks to the proliferation of new media channels and rapid changes in consumer technology, data has been getting exponentially bigger for many years. But ‘big data’ has emerged as an industry term only in the last few years.

The IT department is no longer the sole natural home of big data. The explosion of consumer information has been provoked by changes in consumer behaviour and consumption - the way people shop, work and relax has evolved so much - therefore it’s impossible to ignore the influence of the marketing department in dealing with these vast volumes. Media fragmentation and the advent of Smartphones, Apps and social networking means massive amounts of data is available in real-time; in other words, big data is here. And as it has been largely created by consumers, marketers must care about it – this is their space.

Marketers are indeed recognising they have a chance to make the most of the opportunities for growth that big data represents. But the volume and complexity of the job in hand means they need a cast iron plan for dealing with it.

Consider this analogy: human vision features both focused and peripheral abilities. We walk down the forest track looking at the path ahead, not seeing every movement of every leaf around us, but when we do sense that movement our eyes immediately swivel to the source and allow our brains and bodies to respond to the threat or opportunity presented. In the context of big data, marketers need to develop the ability to manage the signals but continuously be aware of new ones within the noise, and react appropriately.

The starting point for dealing with big data isn’t always clear. However, I believe the following five-step road map can generate quick wins for any organisation which holds or has access to massive volumes of customer information:

1) Put the consumer first
The first step is quite straightforward. Every marketer knows that for a brand to be successful, it has to have a compelling offer delivered to consumers via the right channel at the right time. Big data does not change this, but creates new opportunities that are there for the taking. Thinking about the traditional 4 P’s of marketing, data can be used to enhance the product, improve the price and make the promotion far more relevant to the place.
One of the major challenges at this stage is deciding where to begin. The initial part of a journey into the fast-moving world of big data should be to ensure that you are aligning your efforts to your business objectives. For marketing and insight teams this typically means focusing on initiatives that benefit your consumers.

2) Define the starting line
Once you have a more customer-centric mindset, it’s necessary to have a good overview of what big data your organisation has. The way to approach this task is by conducting a data audit.

A big decision is to determine who within the business should be involved in the process. Outside marketing, IT should definitely play a part as the department is likely to be most at home with data, and may be able to help uncover silos of data unknown to the rest of the team. Data analysts should also be involved as they are already familiar with combining and using disparate data sources and will ask the right questions of the data owners when compiling the data audit. The privacy or legal team should also be engaged to ensure the boundaries of data usage are properly respected.
The specific deliverable from this second step of the journey is production of a comprehensive list of the raw materials you have available for any big data initiatives and identification of the gaps where the data is unavailable.

3) Create ‘Plan A’ – a proportionate response
Once you have understood the objectives and your organisation’s landscape in steps one and two you must then build a strategy for managing and making big data actionable – a ‘Plan A’. The challenge here is the volumes and variety of data involved. Furthermore, unless the data gets processed and actioned rapidly then it quickly becomes stale. Your organisation must:
• analyse raw data to determine when and how it can be used
• make data operational quickly and efficiently
• identify, and if necessary discard, junk data which will clog the system
• automate decisioning to accommodate the variety and velocity of Big Data
• carry out all work in a way that is compliant with current data laws.

4) Run a big data proof of concept test
The fourth part of the road map is essentially a reality check. There may be a significant investment required to establish a big data environment, not just in terms of hardware but also skills. Can your organisation afford to do this? Demonstrating return on investment to the board is crucial to securing sponsorship from the business.

A paradox here is that many of the use cases do not actually require big data. The volumes are so large that the decisioning necessarily becomes simplified. There is nothing fundamentally new about big data, it just requires a new mindset. It should be perfectly possible to execute big data use cases without building a new, full-blown environment for doing so.

Typically, the activities at this stage will include statistical analysis (mining), searching for predictive patterns within the data and then attempting to turn these into processes which can be tested in real-world scenarios.

Moving forward from this step you should be in possession of a solid body of evidence to support the business case, and a clear understanding of the resources and processes required to underpin these, possibly including outsourcing to third-party experts.

5) Create a roadmap
Finally, you are ready to build on the results of the proof of concept. This is where you can begin to achieve both focused and peripheral vision within your organisation: the ability to focus on the data that matters most whilst being aware of other data, and be constantly on the lookout for new or previously unavailable data.

The road map should outline how any proof of concept tests can be operationalised and how they will help the organisation move forward, with future tests already defined. It will also implement your peripheral vision. Priority consideration should be given to what big data can most quickly be captured and translated into these existing environments. You need to conduct a value analysis and prioritise.

The road map should be a strategic and tactical plan that puts big data trials into practice, generates results, enables learnings and identifies potential opportunities so that marketing, your brand and its customers continuously benefit.

Given the fact that consumers create big data and brands need to engage, serve and delight them at all touchpoints in order to be successful, it follows that marketers are best-placed to plot the course towards digging for the golden nuggets of information that will ultimately improve revenue generation and customer relationships. Big data has been evolving and growing in the background for some time. Now it’s time for marketers to take it on and use it to be more successful.