In customer experience, the most difficult challenge is the gap between desire and execution. We all want to deliver a better experience. So why can’t we?
At the root of this problem are information systems that are not configured to deliver the ideal experience. Since the digital experience is entirely comprised of information, flows of data are part of what goes wrong. Here’s an example: my bank recently sent me an offer to refinance my house. It was a great deal. But I was already in the process of refinancing with the same bank, a process I’d spent a month on so far. Why didn’t the bank’s marketing department recognize that messaging me was not only futile but likely to damage a crucial service in process with a high-value customer? Because the marketing department did not have the data from the mortgage operations department. Why does that sort of thing happen in many organizations?
One source of these sorts of disconnects is the traditional approach to customer journey maps. Your organization has doubtless developed customer journey maps at some level of detail based on customer research, testing, focus groups, and working sessions with executives and others. Such a journey map probably isn’t overly complex. As the customer service experts at your company may be saying, “We don’t want to overcomplicate things.” They are likely attempting to create journey maps that are comprehensible to the average executive.
But the challenge is that by insisting that journey maps are easily comprehensible to the executives, you miss important details about the systems that power them. These simplified journey maps fail to represent customer stages and objectives in ways that computers can understand and act on. And that representation is crucial for improving the customer’s actual experience.
A system-focused method is necessary because systems are the wellspring from which the consumer interactions emerge. After all, how many systems do customers interact with at your company? You may be amazed as you research this.
For example, at one financial services company, we discovered more than 50 platforms used to manage customers and their investments. Some processes required transferring from front-line representatives to specialized experts, some of whom needed to check with additional back-office experts to solve other problems. Each system, step, and process had a purpose that, at least ostensibly, was designed to serve customers, but the end result was often so filled with bumps and detours that it left valued customers feeling abused and disrespected.
Artificial intelligence, often applied with the objective of making these processes more efficient, can add to the complexity. AI applied to a complex system without understanding makes it opaque and unpredictable. And that makes the customer experience even worse.
Creating a High-Fidelity Journey Map
There is a solution to this conundrum. It requires effort, but it pays off in creating an architecture for future improvements, including AI. I call it the high-fidelity journey map.
A high-fidelity journey map addresses how customers interact with all of the company’s systems throughout their journeys – the relationships between their journey and your stack of technologies. How do you create such a journey map? Systematically, in six steps:
1. Map the customer lifecycle.
This establishes a high-level perspective on the journeys as customers discover your products or services, evaluate them, purchase them, use them, interact with your support staff, and if all goes well, tell others about your products.
2. Define the customer engagement strategy at each step in the lifecycle.
Your company differentiates itself by these strategies. How do you do marketing, with which messages, in which channels? Where do people buy – online, or through a distributor, retailer, or partner? How do they get support?
As you investigate this, you will learn more about how your company models what goes on the mind of the customer. This mental model has elements in all the systems that you’ll investigate in the remaining steps described here – and it provides clues about the descriptors within those systems that predict the customer’s state of mind.
3. Survey and assess existing tools and approaches.
Learn more about the descriptors and systems that, together, create the customer experience. Such systems may include CRM systems, customer support systems, knowledge bases, product information systems, e-commerce systems, and so on – as well as AI add-ons to those systems.
This sort of investigation can reveal how system interactions contribute to or impair the customer experience – as my company found when investigating the 50 systems at the financial services firm. This step would identify the missing data flow between the marketing and loan operations groups at my bank.
4. Assess the maturity of supporting processes.
You may be familiar with the concept of a maturity model – a rubric for evaluating how advanced and flexible a company’s systems are. At this stage, you apply the appropriate maturity model to each process the company uses (marketing, sales, e-commerce, and support, for example).
This information is pivotal because applying advanced improvements to systems at a low level of maturity is futile. The objective is not to make rigid and outdated systems more efficient, but to identify whether their architecture is getting in the way of making any future customer experience improvements.
5. Assess how tools, technologies, and processes relate to the engagement strategy at each stage.
Now take the tools you reviewed in step 3 and relate them to the strategy from step 2. You need to evaluate each tool according to how inherently important that class of tool is in a particular stage of the customer journey.
The question is how to most effectively serve the customer at each stage and what tools to deploy to do so in a manner most closely aligned with your value, type of relationship, and customer preferences. For example, if the business emphasizes product selection and ease of online purchase, then the e-commerce catalog and product data must be highly optimized and aligned with the things that the user finds most important and appealing.
6. Develop a roadmap for implementing improvements based on the maturity assessment and areas of opportunity.
In this step, score every technology area based on how important it is as well as how mature it is. Combine those and you can see exactly where improvements are both possible and impactful.
This may sound like an imposing exercise. But without it, you have no real idea what parts of your organization are causing customer experience problems – and what parts have the greatest opportunity for improvement. Traditional journey maps can’t get you close to that knowledge.
And because of that, you may find yourself hitting barrier after barrier as you mount futile assaults on poorly understood technology systems. The high-fidelity journey map identifies those disconnects, like the one I experienced with my bank, because the roles of technology at each stage are defined along with the data that makes up the customer experience.
Once you’ve completed the high-fidelity journey map, you’ll be far better positioned, not just to know what’s going wrong, but exactly how to make it better.