Time For Science to Be Part of Your Customer Journey

We've been talking about "Customer Journeys" now for over five years and I see the influence it has had in executive suites across sectors and markets.  Over that time, it has evolved from a framework for how to think about developing one's marketing strategy, to the vector by which many companies have begun aligning their organizations and investing resources.

Despite the progress, the science of analyzing journeys has been lagging, mainly because of challenges in capturing the broad breadth of data involved and then in making sense of it so that business leaders can make better decisions. That is now changing. The tools and approaches are coming together so that we can analyze, manage, and shape customer journeys quantitatively, as we discussed in our Competing on Customer Journeys article in Harvard Business Review.

A company we work with closely, Clickfox, calls this "Journey Science."  It is the study, analysis, and classification of complex interactions between a customer or potential customer and the brand that has to a specific purpose.  It starts by building a flexible database which aggregates and sequences individual customer interactions (both online and offline), classifies journeys by their business purpose (learn, buy, get, fix, advocate, etc.), and uses a clear journey taxonomy across all channels. The data is automatically and collected on at least a daily basis so you can get rapid feedback on how changes in the design of an interaction affect the performance of a journey.  With powerful visual analysis tools, you can literally see the dominant paths leading to different outcomes as well as identify barriers and leakage, based on connected time-stamped interactions and their sequences.  This is the fact base that supports a relentless process for implementing and measuring changes in the design of specific interactions or entire journeys, bringing together skills in data management, data analysis, data science, agile execution, UI/UX, IT, marketing, sales, and customer service.

How does it work in practice? A case example

A large US bank has wholly embraced the a journey science approach as a means to improve their customer satisfaction levels, while also reducing operational cost and identifying revenue generating opportunities. With many ways to now interact with the bank, 55% of a customer's experiences include touching multiple channels to complete a journey.  The journey science approach de-mystified where the bank should start in establishing a journey-centric practice for continuous analysis, change and measurement.

Organize…

Most organizations are aligned in a business silos focused on marketing, customer service, operations, IT, etc.  This bank realized that organizational changes were needed across the enterprise to truly take advantage of journey analytics. They appreciated that in order to drive change they needed to appoint a journey strategist and journey owners that have the authority to prioritize system or process changes that touch any channel of the journey, whether that’s in the digital, contact center, or marketing channels. Moving to a customer journey-centric approach is difficult – it requires new KPIs, reporting structures, incentives, talent – but it’s necessary in today’s omnichannel world.

Define, Construct, & Manage…

With a journey-centered team in place, they identified first the core enterprise journeys their customers take.  By building a platform containing all relevant connected data, the bank was able to identify and classify the exact steps customers took throughout their key journeys. The process of explicitly defining each enterprise journey gave them a common language across the entire enterprise, as well as a way to align on journey definitions (for example, how each organization defines how a customer makes a payment, whether it’s from the Digital Channel, an IVR, an Agent – or a one-time payment vs. a payment arrangement).

Analyze, Monitor, Change…

With an organization and a platform in place, the bank began executing an agile approach to driving performance based on journey science.  In this process, the journey strategist prioritizes changes with the appropriate operational teams based on findings that come from the journey analysis.  The journey science team works from a prioritized backlog in an iterative manner not unlike the software development agile methodology.

The first area the bank wanted to improve was satisfaction, and rolled out a series of tests and new initiatives to see what would work. With never-before-seen visibility into the customer journeys affecting satisfaction scores, they were able to create and monitor journey-specific metrics that allowed any change they made to be measured immediately instead of the several weeks it took to gather that data previously.

The bank has improved its satisfaction scores by 25 points since beginning the program, while cutting over 20% of its call center expenses.  We've now seen similar impact in telecom, B2B, insurance, and travel businesses.

The beauty of this approach is that once configured, all journey variations, as well as the defined enterprise journeys, can be analyzed and measured continuously.  This allows for a test and measure approach to prove how changes in operational systems are impacting customer journeys.

In his blog, Clickfox’s Tim Friebel lays out a good structure for how to think about unique attributes of Journey Science.

I think this is going to be an important vector of analytic thinking, and look forward to hearing more stories of breakthroughs.  How are you finding and profiting from insights on ways to improve customer journeys?

Learn more this and other topics on our McKinsey on Marketing & Sales site. Follow us on Twitter @McK_MktgSales and @McKinseyDigital. And please follow me @davidedelman.