written by
Yves Delongie

Customer journey analytics: why you should care.

Analytics & Attribution 3 min read

Marketers today are challenged to deliver ever more personalised, differentiated messages to customers and yet deliver higher than ever ROIs on their marketing investments. Achieving this herculean task requires bringing together all the different pieces of customer data available to a company in a unified way, in the moment, to create a unique, compelling message delivered to the customer in a contextual manner.

A 2017 Dun & Bradstreet survey reveals that, despite the growth in consumption and use of data, there is surprisingly little sophistication in how data is analysed. Twenty-three percent of those surveyed are still using spreadsheets as their primary means for data work! Seventeen percent are solely using dashboards that go little beyond spreadsheets. While only 41% use predictive models and/or advanced analytical and forecasting techniques, even more astonishing, 19% of respondents use no analytical tools more complicated than basic data models and regressions.

Traditional analytics: inflexible static data.

Traditional systems such as google analytics, even when combined to other data sources through Data Studio, makes gathering important customer information a complex and static process. It's easy to see how online information can be inserted in customer touch points, but how about offline information or information residing on 3rd party data warehouses? And dashboards vendors (such as klipfolio) are outperforming themselves to get a full 360 holistic view on customer data, but fail massively in bringing meaningful marketing-specific insights to the table.

Customer Journey Analytics to the rescue.

Journey analytics tools are designed to quickly integrate data across a variety of systems and channels to create a unified customer view. Customer journey analytics allows marketers to analyse millions of data points in real-time and produce actionable analytics in a timeframe when it is still relevant and actionable. Journey analytics tools also allows for changing models along the way, without needing to re-format tracked data.

Journey analytics tools are designed to quickly integrate data across a variety of systems

Journey analytics provides real-Time, behaviour-based analytics.

To provide each customer with a personalised experience based on their own unique preferences and personal journey, marketers need to connect millions of data points and analyse customer journeys as they happen.

Customer journey analytics platforms are designed to make this possible. They enable marketers to identify opportunities for real-time engagement based on a deep analysis of customer behaviour. They give you the power to identify at-risk customers before you lose their business.

They let you connect the dots between customer interactions and business outcomes in seconds, rather than weeks and months.

Journey analytics triggers engagement in real time.

In addition to providing a means for monitoring customer behaviour in real time, customer journey analytics platforms enable customer experience and marketing teams to automatically engage with each customer at the best time, through their preferred channel and in a relevant, personalised way.

By embedding event triggers at any point in a journey, you can engage with each customer via their preferred channel (e.g. email, SMS, in-app message) in real time. And journey-based triggers are a lot easier to manage and more effective than rule-based systems of the past.\

Journey analytics capture multi-channel journeys.

Most analytics tools work independently on data within a single channel and do not capture complex, multi-channel journeys.

For instance, a digital analyst in a marketing team, would use a web analytics platform (such as Google Analytics) to measure traffic to a website or app, acquisition sources, behavioural flow and content engagement. A social media analyst in the same team may be using a dedicated social analytics tool to measure reach, engagement, sentiment, sharing and other social metrics.

While useful, this traditional approach only helps to understand channels in isolation and gives an aggregate group view, instead of the individual, unique customer journeys across channels that are needed to build a complete understanding of customers for delivering real-time, personalised engagement at scale.

In Conclusion

In a world where customers are one click away from abandoning their journeys, marketers need processes and use platforms that are powerful, elastic and automated, while at the same time require fewer technical resources.

Marketers need to deliver measurably faster campaign results, with easily accessible technology at a significantly reduced cost. Given the limitations of traditional marketing analytics tools, marketers need to urgently rethink their model and the tools they are using so they can deliver effective marketing programs.

Customer journey analytics platforms make this an achievable scenario. Modern customer journey analytics platforms are built to aggregate and present data in an easy, practical and efficient way to facilitate engagement with your customers at the optimal time via the best channel. These platforms will enable marketers to truly harness the promise of big data and position them to stay in step with customer needs while delivering enhanced ROI.