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Big Data for Marketing – Five Top Ways of Harnessing it for Business Advantage

Marketers were among the first groups to see the value of big data as a tool for business advantage. They were quick to understand the benefit of getting instant insight into customers so as to influence behaviour at the point of sale. They rapidly saw the potential of analysing vast volumes of data to drive analysis and segmentation of different groups and achieve more accurate targeting of customers and prospects.

However, the theoretical benefits of big data are one thing but translating the theory into real commercial benefit is another. Here, we outline five top tips to help marketing departments achieve this shift and deliver successful big data projects.

1. Don’t get hung up on volume - Remember big data is diverse in origin, style, consistency and quality – and, paradoxically, size is not always important! Some organisations have to handle massive quantities of data. Others have smaller data sets to manage but more sources and formats to deal with. The key is to ensure you are focusing on the ‘right’ data. Whether you are looking at sales performance, CRM records or social media feeds: identify every relevant source, and don’t worry if you don’t need to immediately expand your processes to manage vast quantities of data.

2. Don’t neglect data - Some of the data you need for big data projects, such as transactional data used or generated by CRM or performance measurement tools, is clearly identified. However, much more is hidden on servers; log files or desktops. Much of this is neglected. Some even goes to waste in the ‘exhaust fumes’ of IT. Typical examples of this are activity or sensor data that are only processed when errors or exceptions occur, but can provide tremendous insight even in normal operating conditions. All of this kind of data is potentially relevant. Don’t limit your project to the first group. Record all of it and deploy collection mechanisms for it so that it adds business value.

3. Don’t move everything - Too many marketing departments are focused on breaking down data silos and bringing all the data together in one central location. Remember - it’s not always necessary to duplicate and replicate everything. Businesses need to think about making distribution as easy as possible beyond the data processing phase.  You don’t need all the data physically in the same place in order to get a single view of the data - as long as a logical layer exists that enables this data to be accessed transparently.

4. Don’t focus on storage alone - The latest and greatest software frameworks should not just be repositories for big data, they also need to give marketers the opportunity to extract meaningful information from that data. Unfortunately, businesses at the moment are not making full use of the processing tools and capabilities that are available to them on the market. In order to draw out the intelligence they need, they should be applying the latest technology to harness that data, through data processing and ultimately data analytics.

5. Don’t treat big data in isolation - Sandboxes for testing technologies work well for proof-of-concepts but when big data projects for marketing go live, they need to be dealt with as an integral part of the business architecture rather than an isolated project.  Your business will need to integrate big data applications with other systems, both upstream and downstream, and at the same time ensure big data is part of the business’s overall IT and information governance policy. Of course, marketers are only one constituent in this overall strategy - but it will have a big impact on them. 

Looking to the Future

Interest in big data for marketing is growing and this is being reflected by more companies rolling out strategies that address this core business need.

Leading-edge technologies lower the adoption barrier, making it easier for marketing departments to get started. Yet, moving pilot projects into mainstream IT requires more than just technology. If marketers take note and follow the five tips above, they should ensure their big data projects get off the ground and help drive success for the business as a whole.