The big deal about big data

Big data is becoming a marketing catchphrase. No longer the sole preserve of IT directors, big data matters to marketers because it’s largely created by consumers’ interest in their business via the ever-growing number of touchpoints.

If you’ve yet to come across the term “big data”, you may have been on holiday for months. Big data incorporates every route that data feeds into a business: be that via customer service, transactions, online orders, or third-party data the company has bought in to contact people. Another way of looking at it is the “3Vs” approach: Volume, Velocity and Variability.

Volume is the most obvious of the “three Vs” but also the most deceptive. There is exponential growth caused by emailing, surfing, tweeting, blogging, but how much of it is real and interesting? Volume alone is not changing the world-rather volume combined with the other two Vs.

Velocity is a key driver of change in marketing and sales strategy brought about by big data; the essence of this is that the more interesting behavioural data (think product search) has a limited shelf-life and must be acted upon quickly.

Variability of data is unprecedented and a real game-changer. Some is transient, some structured and an enormous amount now unstructured (such as social-network data) yet incredibly powerful. There is a great challenge in taking raw data from the huge variety of possible sources, integrating these into systems and producing actionable insights that feed operational systems.

As the amount of information consumers produce grows, brand guardians need to ensure they’re taking it seriously. Getting to grips with the amount of information available is, however, easier said than done.

Brands need to find a way of structuring the collection and analysis of data; not just offline but online, too. The volume and complexity of the task necessitates 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 leaf around us, but when we sense movement our eyes immediately swivel to the source and respond to the threat or opportunity. Marketers need to create the ability to manage signals but continuously be aware of new ones within the noise and react appropriately.

The starting point isn’t always clear, but the following five-step plan may bring some quick wins:

1) Put the consumer first For a brand to be successful, it needs a compelling offer delivered to consumers via the right channel at the right time. Big data does not change this, but creates new opportunities. Data can be used to enhance the product, improve the price and make the promotion far more relevant to the place. Firstly, align your efforts to your business objectives. For marketing and insight teams this means focusing on initiatives that benefit your consumers. And in most cases, that includes the unstructured territory of social media.

2) Define the starting line Approach the task in hand by conducting a consumer-centric data audit. This will create a register of what data you’ve got-and what’s missing. Outside marketing, involve IT, data analysts-familiar with combining and using disparate structured and unstructured data sources-and the privacy or legal team.

3) Create “Plan A”: a proportionate response Now you must build a strategy to make big data actionable. The challenge here is the volumes and variety of data involved: 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 that 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 A significant investment may be required to establish a big data environment; demonstrating ROI is therefore crucial to securing sponsorship from the business. Activities at this stage include statistical analysis (mining), searching for predictive patterns then turning these into processes that can be tested in real-world scenarios. You should now possess a solid body of evidence to support the business case and understand the resources and processes required.

5) Create a roadmap This is where you can begin to achieve both focused and peripheral vision: the ability to focus on the data that matters most while being aware of other data, and be constantly on the lookout for new or previously unavailable data.

Priority consideration should be given to what big data can most quickly be operationalised. For example, compare the investment in the capability to turn unstructured data into large volumes of structured insight against that needed to capture more modest volumes of structured data. The yield of each option must be identified and the answer may be to do both.

Thanks to digital media, big data has been evolving for some time. It’s time for marketers to take on the challenge.

Matt Hollingsworth is managing account director at multichannel marketing services and technology firm Acxiom.

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