Big data analytics is the new buzz phrase - but it’s not all about 'big'. Intelligent ‘small data’ may be just what you need.
It seems impossible these days to mention ‘data’ without feeling the need to put the word ‘big’ before it. The rise of the ‘big data’ phenomenon has sparked a lot of hype and conversation amongst both the Marketing and IT professions – but just how much value and insight is the business achieving from these big data analytics? Is anyone actually analysing all this information and using it to make sensible, informed business decisions? Or is it more likely that the company is now collecting so much data, from so many different sources, that it has become impossible to leverage anything useful?
As with most projects, the key to success lies in the planning stages. Before anyone jumps into big data analytics, the business has to have a clear vision and strategy in place that defines:
- What the business is trying to achieve from big data
- The business objectives of the project
- How these objectives will translate into realistic action plans
In a world where you can pretty much collect data on anything, it’s imperative to have a clear understanding of what the business is looking to achieve and what data is needed in order to influence the decision making process and reach these goals. Data analysis, be it for big or small volumes, provides evidence and answers. Therefore, in order to know what analysis needs to take place and what data needs to be collected, the business has to know what questions it wants answering and how these answers will help to achieve the common goal. This can include getting more customers, increasing profits, up-selling & cross-selling opportunities, accurate forecasting of what customers are most likely to purchase next and many others.
Armed with a clear understanding of what is needed from an information perspective, the IT department is also able to make an informed decision with regards to what hardware is required and which, of the many software tools available, is most suitable. On any project, clear communication and the sharing of common goals between IT and Marketing is important – but when dealing with something as complex as big data, it is critical. If there is no central framework on which Marketing and IT are working together, it will be impossible to attain the business objective of a 360 degree view of all customer interactions.
Once the marketing/business questions are clearly understood, then your data can be structured and segmented to provide value and meaning. It may also be the case that it’s not actually ‘big data’ that the company needs, but rather intelligent data - information and metrics that are fit for the purpose.
But it’s not too late. If you’re running a big data solution and not receiving the insight or results that you were hoping for at the outset, try taking a step back and reassessing the overall objectives of the project. Define the analytical objective needed to support your marketing campaigns and bring your IT team fully into the loop regarding the key goals. Armed with the right information and accurate data, marketers have the confidence to alter campaigns and test new ideas with conviction – based on informed decisions.
For more information, help and guidance on how to get the most out of your big data projects, download our eBook: Big Con/Big Data – how long can you afford to wait?