Performance Marketing

Putting Big Data to Work

What is Big Data?

Like many buzzwords of the moment, Big Data appears equal parts intimidating and confusing. However, the reality is quite straight forward. Big Data refers to the collection, storage and management of large pools of data. This data can be analysed and interpreted to build a fuller picture of users interacting with your brand and to identify trends.

Big Data continues to be a focus in 2014 and so it should be, never has it been more important for advertisers to monitor and manage their first party data. The collection and analysis of data allows greater integration, increased differentiation capability and to be more personalised and therefore relevant advertising to specific user pools. Big data doesn’t only allow you to get more efficient for your online activity but allows for more efficient cross channel marketing and greater transparency into offline conversions as a result of online activity.

Data Prevents Wastage

The more you know about users of your site, the better you can optimise your digital campaigns.

It’s important to remember that the usefulness of data doesn’t expire once a user has completed the purchase process and nor should it. First party data such as transaction data can be used to feed and inform all future activity.

Take the Example of Transaction Data

If you’re an online retailer you can use transactional data to build loyalty programs for your existing customers and drive positive sentiment amongst your consumers online by offering bespoke offers to them, for example a 10% discount.

Data shouldn’t be about short term tracking, advertisers should be taking the long term view. For example, if you’re a service provider, you can use transactional data to drive future contract renewal activity. For example, targeting specific pools of users, depending on which month a contract was taken out.

It’s not just post sale data that informs optimisations, advertisers should increasingly be looking at how they can activate their data pools in real time, help personalise the purchase funnel for the user and inform their sale at point of purchase both online and offline.

Increasingly, advertisers should be using data analysis to build models to predict consumer actions based on past online behaviour. In 2014 these robust models will drive look-a-like targeting strategies that drive similar users into the purchase funnel and deliver better performance results.