1. Why traditional monitoring is no longer enough for Product Owners

Most teams already have APM, logs and infrastructure metrics in place. These are essential, but they were designed for IT, not for Product.

As a result, they don’t really answer questions like:

• “How many users drop out of the payment journey, and at which step?”
• “Did the new onboarding version actually improve activation, or not?”
• “Which features generate the most frustration or support contacts?”

Traditional monitoring answers “Is the app up?”, DEM answers “What are our users really experiencing, and what does it mean for the business?”.

2. DEM: seeing your product through your users’ eyes

Digital Experience Monitoring combines several data sources to reconstruct real experience:

• Real User Monitoring (RUM): measurements in browsers and apps for real users.
• Synthetic monitoring: automated scenarios replaying your critical journeys 24/7.
• Session replay & behavioral analysis: replays, heatmaps, funnels, segments.
• UX & Core Web Vitals metrics: LCP, INP/FID, CLS, p95 latencies, user-visible errors.

The key difference vs. traditional supervision is that these data are organized by business journeys (sign-up, payment, selfcare, support…) and connected to your product indicators.

3. What DEM changes in product steering

3.1. Near real-time visibility on experience

With DEM, you can continuously follow the performance of your critical journeys:

• success rate for the journey (sign-up, payment, project creation…);
• drop-off rate per step and per segment;
• completion time, p95 latencies, user-side errors.

3.2. Backlog prioritization based on facts

Instead of arbitrating based on opinions, you can quantify:

• how many users are impacted by a bug or slow journey;
• the estimated impact on revenue, leads or retention;
• the volume of support tickets tied to a journey or feature.

This makes your backlog decisions much easier to defend to tech teams and leadership.

3.3. A deep understanding of UX journeys

Replays and funnels let you go beyond the numbers:

• do users go back a step before finishing?
• do they get lost in navigation or a complex form?
• are some error messages confusing or invisible?

3.4. An objective measure of release impact

Every production release can be measured on the journeys it touches:

• changes in journey completion times;
• variation in conversion, activation, retention;
• detection of regressions missed in pre-production.

3.5. A common language for Product, UX, IT and support

By showing shared data (journeys, KPIs, replays), DEM reduces friction:

• the Product Owner talks about user and business impact with numbers;
• IT sees the concrete effect of an incident or architecture change;
• support can illustrate trends with data, not only with verbatim.

4. Embedding DEM in the Product Owner’s practice

4.1. Start from product journeys, not screens

Begin with a short list of critical journeys:

• onboarding / sign-up / activation;
• transaction journeys (purchase, subscription, payment);
• recurring usage journeys (core action of your product);
• selfcare journeys (login, password reset, profile edits, document download);
• any regulatory or highly sensitive journeys.

4.2. Define a few truly actionable metrics

For each journey, pick a small set of metrics:

• Performance: LCP, INP/FID, CLS, p95 latencies.
• Reliability: success rate, user-visible errors, critical error codes.
• Experience: rage clicks, drop-offs, completion time.
• Business: conversion, revenue, activation, retention, related tickets.

4.3. Plug DEM into your agile rituals

• Sprint Planning: use DEM insights to prioritize the highest-impact items.
• Daily: keep an eye on critical alerts (sudden drop in success rate, error spikes).
• Sprint Review: show before/after impact of a release on 1–2 key journeys.
• Retrospective: review how experience issues were detected and handled.

4.4. Example of a 90-day DEM roadmap

• Day 0–30: identify key journeys, enable RUM, build a first “product view” dashboard.
• Day 30–60: add synthetic scenarios, define alert thresholds, use DEM in Reviews.
• Day 60–90: extend to more journeys, refine metrics, use DEM to arbitrate the backlog.

5. Use cases: DEM in a Product Owner’s daily life

5.1. Reducing drop-off in a payment funnel

Context: an e-commerce site sees high drop-off on the payment page, with no major errors reported in classic tools.

• Replays show repeated clicks on “Confirm payment” with no visible feedback.
• DEM highlights a 5–8 second response time from the payment provider.
• Roughly 15% of drop-offs correlate with this slowness.

Product decision: add a clear loader + optimize the PSP call. Result: –12% drop-off in two weeks, immediate revenue uplift.

5.2. Improving retention on a SaaS application

Context: a B2B project management app shows flat 30-day retention.

• RUM: search is slow (> 3 seconds) on mobile in some countries.
• DEM: front-end JavaScript errors when creating projects, invisible in backend logs.
• Onboarding funnels: 40% of new users drop at the 3rd step.

Product decision: optimize search, fix front-end errors, simplify onboarding. Result: +25% 30-day retention.

5.3. De-risking a UX redesign

Context: before rolling out a new interface, the team exposes 10% of traffic to the new version.

• Comparing task times on key journeys between old and new UX.
• Tracking success and drop-off rates per version.
• Detecting browser/device compatibility issues.

Result: three critical issues are fixed before full rollout, avoiding a temporary hit on satisfaction and conversions.

6. Pitfalls to avoid with DEM

6.1. “Analysis paralysis”

DEM generates a lot of data. Without framing, you can end up spending more time analyzing than deciding.

• Define 1–3 North Star metrics per product or journey.
• Set thresholds with clear action rules (“if X, then Y”).
• Accept that not every fluctuation requires immediate action.

6.2. Over-optimizing tech at the expense of value

Cutting a screen from 1.1s to 0.8s doesn’t always have business impact, while a bug in onboarding can block hundreds of new users.

Key question: “What is the business gain if we fix this?”

6.3. Forgetting the user behind the numbers

DEM doesn’t replace interviews, UX tests or qualitative research. The best decisions combine:

• quantitative data (DEM, analytics),
• qualitative feedback (tests, verbatim, support),
• product and business expertise.

7. Choosing a DEM solution that fits your product

The DEM market is broad: some platforms come from the infra/APM world, others from analytics/UX. For a Product Owner, key criteria include:

• Business readability: dashboards understandable without IT expertise.
• UX capabilities: replays, funnels, segmentation, frustration signals.
• Integrations: Jira, Azure DevOps, Slack, ITSM, analytics tools.
• Performance impact: lightweight script, good collection practices.
• Cost model: predictable, aligned with your traffic volume and goals.

8. DEM checklist for Product Owners

8.1. Check that the fundamentals are in place

8.2. Tracking table: DEM plan per journey

Once these items are checked for a few key journeys, you will have laid the foundations for product steering truly driven by digital experience.