The process of tracking the customer journey has developed significantly since the early days when marketers measured behaviours, such as visits and clicks, in order to increase conversion rates and improve websites. Far richer and more granular data is now available which enables marketers to develop deeper customer insight and improve their marketing effectiveness. Companies are using that highly granular data in numerous ways to improve their marketing effectiveness through a number of specific activities.
Highly granular online customer behavioural data collected from visitors to a website, can be used to optimise an organisation’s marketing spend through the introduction of predictive campaign optimisation. This process ensures that marketing budget investment is focused on activities which drive the most profitable online leads. The very same data can also be used alongside real-time personalisation software to maximise the conversion rates of those leads.
Online customer insight technology extracts, records, and delivers data on individual online customers, enabling digital analysts to build dynamic, historic and real-time profiles on visitors. With this insight, digital marketers can determine the behaviour of online customers and their progress to and through the purchasing process.
Using the online behavioural data from different marketing campaigns, data models can be constructed in order to establish which campaigns drive the highest value visits. Predictive models can then be developed which have the capability to predict, with high accuracy, whether a visitor is likely to convert on their visit.
Typically, organisations have to wait for up to three weeks before they can accurately determine the success of a campaign. By applying a predictive campaign optimisation model, however, organisations will have the capability to predict campaign success within just 48 hours of its launch.
As a result, marketing departments will have access to insight enabling them to dynamically allocate resources and budget to the most productive campaigns much earlier than previously – preventing wasted time and investment. This both optimises their campaign spend and drives higher value leads.
Using the proven Awareness, Interest, Desire and Action model (AIDA) as a construct around which to shape marketing messages, and real-time personalisation software to drive the personalisation, businesses can now display the relevant messages to each individual on the website in real-time based on where they are in the sales cycle.
Optimising new customer acquisition efforts, discovering more about the online customer journey and visitor reaction to particular online campaigns enables organisations to provide a personalised experience for existing customers and enhance cross-selling opportunities. Through an appreciation of the products a customer has already purchased and the offers that have failed to drive a conversion, digital marketers can optimise the advertising of more suitable offers or cross-sell other products to increase further conversion and therefore increased revenue.
To read a Case Study which examines the use of predictive campaign optimisation in detail, please click here
