It is a truth universally acknowledged that digital experiences rarely break in one obvious place. Friction happens when a customer gets an outdated answer or an automated journey makes getting help harder than it should be. When looked at in isolation these can seem like separate operational problems. Together, they shape how much confidence customers have in the brand behind the experience.
Digital authenticity gives you a way to look across those moments by looking at the gap between what customers expect and what they actually experience. That’s the approach we took when building the Digital Authenticity Index. In partnership with Ipsos we measured nine signals across credibility, relevance, and responsibility, comparing how important each one is to consumers with how well they think brands generally deliver it.
The nine signals give you a practical framework for reviewing your own customer experiences but you probably already have most of the evidence you need. Use them to decide what to investigate and then draw on customer feedback, journey data, content reviews, and service data to understand where attention is needed.
What tools help track digital authenticity?
Tracking digital authenticity means bringing together evidence from different parts of the customer experience. Analytics, customer research, content reviews, experimentation, and service data can each help you understand different signals.
| What you're looking for | Where to look |
|---|---|
| Conflicting or unreliable information | Content audits, search behavior, support queries |
| Friction or lost context in a journey | Journey analytics, experimentation, behavioral data |
| Personalization that misses the mark | Preference data, testing, customer feedback |
| Confusion around data or automated experiences | Customer research, usability testing, privacy feedback |
| Difficulty reaching human help | Service data, escalation patterns, customer feedback |
Different pieces of the puzzle will highlight different solutions. An abandonment rate, for example, tells you where people left while customer feedback could explain what got in their way. A content review might uncover conflicting answers that are confusing the journey; service data might show customers repeatedly asking for help after an automated interaction.
Use the sources that fit the problem you're investigating. As the picture becomes clearer, you can focus your effort on the part of the experience that needs it.
Start with a customer journey that matters
The Digital Authenticity Index gives you useful clues about where to pay attention, but you need a starting point I'd recommend choosing a journey connected to a goal your team already cares about. Go through it as a customer would and make notes when you encounter unnecessary friction.
By doing that, you're already taking a big step toward digital authenticity. The three largest gaps in the Index sit in the "responsibility" category.
Personal data makes transparency particularly important while automated service puts more weight on human accountability and research, and purchase journeys can expose credibility problems when information changes between touch-points.
Your own priorities will depend on what you uncover, so use the relevant signals to guide your review and then bring in the evidence.
When customers abandon a step, look at what happened before they left. A rise in support requests after an automated interaction deserves a closer look at the handoff; conflicting answers across channels probably lead back to the source content. You need enough evidence to understand the problem and make a useful change.
Build digital authenticity across channels
When it comes to omnichannel experience design, digital authenticity means giving customers a coherent experience as they move between touchpoints. Information should remain dependable, and useful context should travel with them.
The Digital Authenticity Index calls this experience coherence.
90%
of consumers expect interactions to connect logically across the journey.
77%
think brands generally deliver it well.
Customers are very good at finding the seams.
Someone might discover your brand through an AI answer, continue on your website, then return through search, and eventually speak to a person. Changes in the answer become obvious across that many touchpoints, and customers will absolutely notice a journey that suddenly forgets everything they’ve already done.
Review the handoffs as carefully as you craft the individual channels. Different teams may be working from different information. Useful customer context might stop at a system boundary. A channel may work perfectly well on its own and still create friction in the wider journey. When something breaks, follow it back to the source.
Build digital authenticity into content planning
Content strategists can build digital authenticity into their plans by making accuracy and clear ownership part of how content is created and maintained.
Start with your source material. Keep important information current and make it obvious who owns it. That matters when the same information can feed a webpage today and an AI answer somewhere else tomorrow.
Content audits are useful for more than deciding what to delete. Check whether a page still answers a real customer need. Look at whether its information agrees with what customers will find elsewhere and whether teams are still working from the same facts.
Content personalization brings another layer of context. The information may be presented differently based on what you know about the customer. It still needs to be dependable.
Know what improvement looks like
Define progress around the problem you've found.
Conflicting information may lead you back to the source. A broken handoff may show up as repeated steps or abandonment.
Watch what happens after you reconnect the experience; monitor whether the same discrepancies continue appearing in search, support, or other parts of the journey. And remember that transparency often needs direct customer input. Research can help you understand whether people have a clearer view of how an experience works after you've changed it.
Keep in mind that the review doesn't need to run constantly. Come back when the experience changes, customer feedback raises a question, or the data tells you something deserves another look. And keep the business measures that already matter to the journey in view. Conversion, engagement, completion, repeat use, or retention may move after an experience changes. Treat that movement as evidence rather than proof that digital authenticity caused it.
Keep reviewing the experience
Digital experiences rarely stay still for long. New content appears, journeys change, and new technology creates different ways for customers to interact with your brand. Over time, the framework gives teams a shared way to understand where customer expectations and the experience may be drifting apart.
Use the nine signals when those changes give you a reason to look again. Follow the evidence back to what customers are experiencing and make the change where it will have the biggest impact.