How AI transforms digital customer journey mapping
For one top global airline, post-booking upgrades—like purchases of early boarding passes, extra checked baggage or class upgrades—are critical, bringing in about 10% of its total annual revenue. When the airline’s artificial intelligence (AI)-powered digital customer journey map alerted it to an increasing abandonment rate on its seat upgrade page, the company took a closer look and discovered a failed AJAX call affecting Microsoft Edge users. This sizable issue caused these users to see a HTTP 500 error message that made them abandon the site, costing an estimated $80,000 per day in lost revenue. Without AI to flag this change in customer behavior, the failure may not have been rapidly identified and the airline could have spent weeks uncovering the source of the problem.
As the airline found, AI can be a powerful tool for improving customer experience (CX) when used in combination with digital journey mapping. It saves substantial time that product owners and DevOps would otherwise spend on error reproduction, error identification, root cause analysis and understanding monetary impact. AI delivers intelligent understanding that often can’t be uncovered with traditional analytics or manual assessment. According to Gartner, “The use of AI technologies…can help analyze customer sentiment and customer feedback at scale, precision and speed not achievable through humans.”
When applied to digital customer journey mapping, AI unlocks new opportunities to close the gap between the real-world experience customers have and the one that they want. Take a look at AI’s impact and ability to help you:
Understand the reason for abandoned digital journeys
There are multiple customer journey mapping tools, including Google Analytics and Adobe Analytics, that show how consumers move through digital experiences like websites and native mobile apps. Digital journey maps powered with AI and machine learning capabilities complement traditional web analytics tools by analyzing every interaction and event that occurs during a digital pathway—and why. You can determine exactly what is causing customers to abandon forward progress.
AI first develops an understanding of the daily, weekly, yearly and seasonal changes happening in customer behavior. It can then distinguish what behavior is normal or abnormal at a granular level and send alerts for further examination when behavior changes. These threshold alerts are only triggered when a certain number of users are experiencing an issue. AI uncovers issues that an organization didn’t know existed and eliminates the time associated with unearthing a problem’s source.
Quickly pinpoint what’s causing user struggles
journey-mapping/Product owners and digital analysts who commonly work with traditional digital customer journey maps would benefit from seeing a Struggle Score, or a rating of the difficulties customers have with a specific page. AI takes these scores a step further by correlating massive quantities of data (like rage clicks, erratic mouse movements, device rotation, etc.) with specific journeys and flagging exactly which pages and events are causing struggles.
With AI, product owners and digital analysts can rapidly move from a macro-level view of what’s happening with their digital products to zoom in on specific struggles. It makes associated session replays immediately visible for each struggle, empowering CX stakeholders to watch what their users are experiencing in real time without hypothesizing about the cause.
Automatically quantify the impact of anomalies and errors
Think about the sheer volume of events that happen in a typical journey—API calls, AJAX requests, clicks and taps, entering information into forms and more. When you break down a journey into what needs to successfully happen in order to deliver great CX, there are typically more than 1,000 individual events that take place. Answering the question of “Where are customers experiencing issues?” doesn’t truly get to the heart of the information that DevOps, product owners, digital analysts and other groups tasked with improving CX need to know. To make improvements and rapidly resolve errors, they need to know which specific events are causing problems, since there can be hundreds of events on an individual page.
AI-powered digital journey maps can automatically surface the elements causing customers to leave a website or native mobile app. Plus, by calculating the impact an error is having on revenues, engineering teams can prioritize their resources. Capturing all events—both seen and unseen by users—also saves money by eliminating the days or weeks of time it traditionally takes to recreate errors.
Revenue-driving CX improvements that close the gap between actual and desired experiences, like those experienced by the airline, are easily achievable with AI-powered digital customer journey mapping. To learn more about how intelligent digital customer journey mapping can transform the way your organization delivers CX, read our white paper, Digital Customer Journey Mapping in Today’s World.
