The marketing industry is beginning to understand the importance of big data, although a recent report from IDC highlighted the fact that 80% of customer data is being wasted as a result of poor data practices, suggesting that businesses are still not making the most of the data which is available to them.
Many marketing professionals are already using structured data from CRM systems to gain insight into current and future customer behaviour, but are missing a trick when it comes to analysing unstructured machine data generated from websites and apps. Subsequently, companies are missing out on valuable data insights that could help shape and improve their marketing strategy.
This machine data, traditionally used by IT departments to provide operational intelligence into the performance of IT infrastructure and detect security threats, can also deliver huge value to marketing departments. Marketers can leverage analytics to gain insight into what their customers are doing in real time, and make the most of key 'business moments' like a customer's failed transaction, an abandoned shopping basket, flash sales or a personalised promotion based on previous buying patterns combined with what they are looking at now.
Machine data is one of the fastest growing and most pervasive segments of big data. Generated by 'machines' including websites, applications, servers, networks, mobile devices, virtualised servers and sensors, it provides a more in-depth view of how a business' sales and marketing channels are operating.
By monitoring and analysing the key steps in a customer's journey from clickstreams and transactions to network activity and call records, new technologies can turn machine data into valuable insights and operational intelligence.
Unlocking the power of machine data for marketing purposes requires collaboration with the IT department. However, this doesn't mean that marketing should rely on the IT team to provide all the answers. Analytics tools are much more accessible and user friendly today and what marketing teams really need is direct access to these platforms, and the data itself, so they can spend time asking the right questions of the data that is being harvested and drive the most value for their own purposes.
In combining this previously untapped resource with traditional, structured data sets (for example past purchasing patterns), marketing can access a gold mine of new intelligence and generate insight into emerging trends. With analytics tools now being easier to use than ever before, marketing teams should take the opportunity to play around and answer previously unknown questions, rather than relying on data scientists or IT professionals to deliver the answers to specific questions.
Domino's goes coupon crazy
In the US, Domino's Pizza started using machine data analytics to resolve IT issues by collecting, indexing and monitoring the machine data generated by its IT infrastructure. As time went on, the company realised that there was potential for machine data analysis outside of the IT department. Domino's began using Splunk to visualise business sales trends across geographical locations such as orders per minute, numbers of transactions per store, what types of pizzas and other food items customers order and what coupons they may be using to do so.
As a result, the Domino's marketing team has been able to analyse the success of promotional campaigns as well as one-off promotions in real time. For instance, the team can now compare the effectiveness of various percent-off coupons. If one is more effective than the other, Domino's can quickly make the appropriate online adjustments.