Big data strategy – realising the big potential
We all know that data is valuable and all digital businesses are essentially making money from how they process, store or interpret it. So why do so many businesses fail to find success with their big data strategy?
Even relatively new businesses can be collecting and processing vast amounts of information. In my opinion there are three main types of data that can contribute to a ‘big data’ strategy:
Types of big data
- Direct collection. This is where a company collects the information themselves. A web form for example, or historical sales information.
- Acquired data. This is where a company acquires data through a purchase or as a by-product of another process. An example would be a consumer data file purchased for the purposes of marketing.
- Extrapolated data. This where two or more pieces of information are combined to create new information. We can use Geopify as an example for this. At Geopify we know the size of each land title in the UK, and we also know the size of each property. A simple sum is used to determine the size of the outside space. There is also some factoring in of flats and other property characteristics, so it is a far more complicated and scientific than this, but hopefully you get the idea. This new piece information has been extrapolated and it appears in our property attribute database.
What’s the value of big data?
Big Data is based on the idea that large data sets can be combined in a meaningful way so it can be commercialised or used to inform key decisions. For example, Geopify does this by aggregating UK property attribute data, home mover data and local area information. We then provide this to companies to improve key understanding of their customers so that they can provide targeted, meaningful and successful marketing and communications.
Other commercialisation opportunities created by big data can include strategic support, analysis, creating persona led marketing strategies and for PR purposes – to name but a few.
Big data equals big value – but it can be a challenge to realise its full potential.
What can you do to make your big data strategy a success?
There are a few steps you can take to make a big data strategy a success:
Conduct market research and make sure there is actually a need for the product or service! A ‘lack of a need’ of a product is the number one reason new businesses fail. So do some homework to give yourself the best chance of success.
Your big data team
Set up a big data team and ensure that it includes a mix of: analytical, technical, marketing, operational and commercial experts. Too many businesses believe big data is just a technical challenge and it is therefore an IT project. However, co-operation with other departments will help to ensure that all areas of your business are involved. This process also makes sure that nothing is missed. The commercial element in particular will help you to establish priorities, so that you can focus on the parts of the projects that will yield the quickest financial return.
A big data strategy is about far more than crunching information, it is also about collecting it. Ensure your big data project and strategy provides answers to how you can collect more customer data, and considers what information you are trying to collect. It is especially important to consider GDPR*, as you should only be collecting information that is relevant to the services you provide.
Big data technology choice
Consider various technologies for your big data project. NO-SQL is great for large quantities of data as the querying is slicker, however it is not so good at tracking changes. Whatever technical solution you decide on, make sure that it scalable.
It is vital to get several opinions. Also whomever is leading the technical aspect of this project should be able to explain the choices to you in a simple way that you can understand.
If you can’t explain it simply, you don’t know it well enough – Albert Einstein
Don’t let anyone bamboozle you!
Realising the big data potential
Lastly, stay the course. A big data effort is more than just creating a database you can query. It is a strategy and like all strategies it can take time to produce results.
*This blog item mentions GDPR. For more information seek professional advice and visit the ICO website for more details.