Big data is definitely more than a trend.

With a reported 90% of the world’s current data created in the last two years alone, thanks to the internet, the potential for businesses to use large amounts of data to focus their decision making is immense.

Big data refers to a collection of data sets so large and complex that it becomes difficult to process using on-hand database management tools or traditional data processing applications. According to Wikipedia, the challenges for businesses include capture, curation, storage, search, sharing, transfer, analysis and visualization.

Businesses that can get round these issues, and have the resources to match, can make their decisions and create marketing campaigns using the might of big data. For them, gone are the days of working on gut instinct and historical knowledge alone.

Those running smaller businesses are likely to become increasingly aware of the risk of a divide from bigger businesses, if they don’t have the resources to access, interpret and use big data. According to Christina Donnelly in Harvard Business Review: ‘Big data threatens to create a deep divide between the have-datas and the have-no-datas, with big corporations gaining advantage by crunching the numbers and small firms left to stumble in the dark.’

For SMEs that want to grasp the opportunity in a meaningful and affordable way, the opportunity may be best realised for now through social media and their CRM system, to ensure that available resources are allocated to a manageable data set.

Just 3 ways business product resellers can benefit from big data are:

  1. Affinity analysis: this means analysing the purchasing habits of customers to find products that are often bought in one transaction. Amazon uses affinity analysis to cross sell when it makes recommendations based on customers’ purchase histories and the purchasing patterns of other customers who’ve bought the same product. Rather than assuming there is an affinity between products such as laptop risers, back supports and wrist rests, for example, data might highlight some new and unexpected links to any of these products and suggest a whole new approach.
  1. Customer segmentation: this means dividing customers into groups based on their buying behaviour and designing marketing campaigns specific to each group. This helps you to plan for the future, attract new, profitable customers, tailor your messages and increase customer value among other things.
  2. Google Trends. By typing in your keywords here you can see related search terms and maximise your online marketing activities accordingly.