Most businesses have realized that it is time to start journey analytics. But it isn’t easy. Analytics is an expensive direction for businesses to pursue if those efforts don’t deliver a return on their investment. Gartner rightfully points out that right now, across almost every industry, analytics resources are misaligned with business goals. With massive differences in how different marketing and CX teams use analytics and data science in the first place, clear results can be difficult to find despite a wealth of data. Enter journey analytics. As a practice, journey analytics uses many of the same techniques that traditional marketing analytics has developed, but by shifting the perspective, data is no longer a problem to be wrangled, but rather an asset to be leveraged in delivering a great experience.
There is no one place to include journey analytics when it comes to the journey management process because journey analytics is necessarily an integrated part of that process. Despite this, you do need to start somewhere. Below are three places that the journey analytics process can start.
Start Journey Analytics At The Beginning of the Journey (A Very Good Place To Start)
Customer journey management is a process that continually evolves, but often the best place to begin is with a proper analytics project. Because journey analytics gives you insight into the entire lifecycle of your customers, using it as a starting point for better journey management can give you the tools to understand how each transition point and action impacts the customer experience. Starting with a journey analytics project means taking your current-state journey and working out to see where there are issues, and what journey paths exist in the first place. This gives you the building blocks to build a better customer journey in the future.
Whichever stage of the customer journey you apply analytics to, some of the most value comes from discovering which journey paths exist and how customers traverse them. Especially at the beginning of a project, identifying these paths allows you to use your time most efficiently going forward. It’s a powerful way to start journey analytics.
Determine The Right Metrics
Understanding what you need to measure is just as important as being able to measure it in the first place.
By starting your customer journey management project with analytics, you can determine which metrics you will track over the lifetime of the project. These metrics often look similar to campaign or program metrics, but taken over a more holistic and long-term scale.
Many find journey analytics critical to getting started, but what if you already have a basic customer journey orchestration framework in place?
These Are A Few Of My Favorite Things: Start Journey Analytics To Steer Journeys and Personalization
If you’ve completed an initial pilot or built a simple decisioning process, then you’re already ahead of how most marketers and cx teams are using data to add value. If you haven’t already, it’s a great time to add journey analytics as a new layer on top of your existing projects. Journey analytics works best when it’s integrated seamlessly into the larger journey management process, and while it’s often easier to begin by performing a journey analytics project, it’s entirely possible to add enhanced analytics into existing journey efforts.
One of the most powerful features of modern customer journey hubs is the ability to listen across all channels in real time and digest that information. This means that the same capabilities that you’ve built out for orchestration can feed into a journey analytics process. By capturing data about the channels being orchestrated, a journey analytics tool can understand impacts on the customer experience and changes to journey flows in real time.
Another exciting option for teams who want to close the time to value on their customer journey investments is integrating customer journey analytics into the real-time decisioning processes that are already being built. By building feedback loops within your journey, customer data can feed into making individual and collective customer experiences even better. Some of this automation can be difficult, but with advanced AI and machine learning tools like Kitewheel can help.
So Long, Farewell, Auf Wiedersehen, Adieu: Post Mortem Journey Analytics
One place to start journey analytics that we have not yet discussed is in looking at lost business or customers that fail to convert. Rather than exploring future paths or impacting present journeys, businesses can look at what has worked historically to plan future projects.
This approach does come with its own challenges.
Journey analytics data is most powerful when it’s collected in real time. Historic data is extremely useful, but often lacks the granularity to explore how customers have travelled each journey path.
While there are uses to doing journey analytics to do post-mortem analysis after the fact, this is generally an extra area of benefit, rather than the primary goal of a successful journey analytics project.
Conclusions: Journey Analytics Impacts Every Stage of Journey Management
Customer journey analytics isn’t a once-and-done project that businesses can complete and then make decisions from. It’s about building process and systems to look at how the journey is happening in real time and to forecast future results based on present activity. Wherever you begin with journey analytics, to find the most success you must integrate as part of delivering great experiences for your customers.
If you’re interested in learning more about what separates leading customer journey analytics solutions in a confusing market, read the Forrester Wave™: Customer Journey Orchestration Analytics. It’s a powerful report, from one of the most trusted names in the business that highlights key metrics, capabilities, and design benefits of leading customer journey orchestration tools. Download it free for more information.