Your Customer Journey Program: From Beginner’s Luck to Scalable Process

By April 13, 2018 No Comments

Get started, even a chaotic start

For most enterprises, Customer Journey Analytics usually starts like the Wild West.  An acute pain is presented from the executive team – unexpected drops in CSAT, spikes in servicing costs, or an angry guest at the CEO’s weekend bar-b-que complaining about your company (those are the most fun).  So, you grab data from wherever you can find it, throw out anything that isn’t “normal” and slap tables together with whatever fields look like they might match. You run some quick queries, and… 

You’ve got your first customer journey insight! Share this with some colleagues – “Hey, did you know… but what does it mean??” – ask some favors, and next thing you know, you’ve made your first change to improve customer journeys.

Now that you’ve had that first – almost accidental – success, you’re tasked with building a full-scale Customer Journey Analytics Program.

Extend the team skill-sets

Many of these accidental starts begin with a small group: A business analyst frustrated with status quo and a data engineer to sling code. Together, these two roles can identify key data, discuss meanings, and comfortably move between SQL, spreadsheets and charts. While effective for the initial project, these two people simply aren’t scalable. 

When growing the team, think of what this highly-functional team should accomplish:

  • Identify and collect data from systems across the enterprise
  • Conduct cross-department discussions of business processes
  • Merge multiple data sources to map complex business processes
  • Analyze and measure those processes
  • Brainstorm actionable recommendations
  • Present engaging stories to executive sponsors

As you look for additional team members, look internally first. The most critical skill in Journey Analytics is understanding your own business and customers, which only comes from resources with experience within your own business and customers. Only after considering the skills already around you, should you look to outside candidates.

Build a process – repeatable and predictable

If truly being honest with themselves, most beginners will admit to cutting some corners in the first journey project. Maybe some educated guesses were made when connecting some dots, or some business processes weren’t fully understood.

A functional Customer Journey Analytics solution must be both repeatable and predictable. One-off or custom analytics efforts are often slow and always expensive. Achieve repeatable analytics by defining processes and guidelines for the team to follow. Guidelines should be myopically aligned to the company’s core goals. No science projects people! By controlling scope and setting obtainable and valuable goals, targets and deadlines, your team’s analytic throughput will become predictable. But it’s equally important for these processes to grow and adapt as your understanding does. Many teams incorporate aspects of Agile frameworks and iterative feedback loops.

Validate inputs and outputs

Next, you’ll want to make sure that your findings, insights and recommendations are accurate and meaningful.

Start by quantifying and qualifying your data repositories. The team should know what sources exist, what elements they contain, and from where the data originates. By building reference dictionaries and defining quality requirements, you can select better data sources and define rules for cleaning sources that don’t meet quality demands. The journey analytics team – and more broadly, the whole organization – can confidently agree on higher-level meanings and logic for joining data sources. Having target data architectures and schemas will allow the use of tools to automate data collection and manipulation, to test and validate results, and to alert when automation fails.

Then, your analytic processes must be accurate. The broad fields of data analytics advertise many creative solutions, but these must be tempered with best practices. Review and understand standard statistical methods – both basic and advanced. Remember, too, to assess the evolving regulatory, security and privacy demands on your organization. You should explore the latest methods while also adhering to – and occasionally challenging – company guidelines and standard processes.

Measure daily

Like most things, customer journeys must be measured to improve. This includes defining new performance indexes, identifying what matters to other departments and organizations, then prioritizing what those organizations can change and react to. With BI dashboards and automated daily updates, you can put these new measures in front of decision makers regularly and make them a part of the daily business. Ideally, this will allow you to run your business centered around the concept of journeys.

As your reports are accessed by audiences outside your team, you’ll be able to hear and respond to new feedback. Other departments will ask you to share, seeking your assistance and proactively suggesting new measurements. But they will also challenge your results with their own experiences and perspectives. Embrace both the praise and the criticism as opportunities to further improve.

Streamline and scale

With the right processes and constructive feedback, you can comfortably add new members to the team – bringing in new skills and adding bandwidth on existing high-demand skills. Iterative feedback on processes will be more critical with every addition. Each new skill and each new voice may require your processes to evolve. Together, new people and new processes allow the team to move faster without sacrificing quality or accuracy.

With growth, you may divide into several distinct teams. Many Agile frameworks suggest teams of 5-9 people. You’ll want each team to be independently functional, with all the skills to accomplish their goals. And while each team will likely be focused on separate problem statements – one department, one customer journey, etc. – it’s equally important for the teams to share ideas, successes, failures, and process suggestions.

With the right care and attention, you can build an analytic program from the ground up. That first, accidental bit of insight can spark a cultural revolution and set your path toward a company driven by customer journey improvement.