FullStory’s summer releases turn up the volume
Some dissatisfied customers complain to your support team. Others leave negative reviews. But 65% simply leave. These “quiet critics” abandon your site after one bad experience–and you never hear a thing.
In fact, 55% of dissatisfied customers report they will not only leave–they’ll never come back.
How can you improve experiences when users simply disappear? This is where advanced analytics and real-time response become critical.
By leveraging DXI, teams can use quantitative analytics and contextual session replay to detect subtle signals from even the most introverted users. Their rage clicks, error clicks, thrashed cursors, and pinch-to-zoom all tell a story–stories you’re already hopefully reading if you’re a FullStory customer. Despite these users staying quiet, their actions show they want better experiences.
Metric Alerts: Stay ahead of shifts
When key metrics hit certain thresholds or adverse trends emerge, automatically notify your whole team. Catch the problems your quiet critics may be facing based on triggers like absolute value thresholds, percentage change relative to previous periods, or absolute numerical change.
For example, an e-commerce site could set up real-time alerts for drops in conversion rates, revenue targets, or traffic from key marketing channels. Product managers might create alerts for drops in key engagement metrics or usage of new features.
Once configured, alerts are delivered via in-app notifications, email or any Slack channel you choose. Plus you can access the history of when alerts were triggered from within the metric definition.
Alerts empower teams to:
Get notified proactively when metrics reach concerning levels or experience abnormal shifts that could relate to quiet critic struggles
Respond swiftly to investigate issues or opportunities uncovered by alerts
Continuously monitor KPIs even after taking actions, with alerts informing teams if trends improve or persist with quiet critic groups
Share alerts with stakeholders across teams to drive visibility and coordination on potential quiet critic impacts
Track alert history to identify patterns and chronic issues over time with quiet critic cohorts
With timely notifications triggered by alerts, teams can rapidly validate hypotheses, troubleshoot problems, and optimize experiences–taking action before small issues with quiet critics escalate or result in lost business. But merely responding to alerts isn't enough. Teams must understand the implications of these alerts, and for this, FullStory brings you metric insights.
Metric Insights: Automate interpretation for faster storytelling
Metric Insights leverage statistical analysis and machine learning to generate automated plain language descriptions of changes and anomalies in key trends over time, including data related to quiet critic actions. That means any one at your company of any skill level can clearly understand the data.
Now, metric insights will appear directly on metric cards without any additional clicks. For instance, an insight could reveal:
"Your daily website visitors from social media have decreased 52% compared to the previous 2 weeks. Additionally, the gap between direct traffic and social referrals has grown 67%."
With data patterns quantified and explained, teams spend less time interpreting charts and more time creating empathy and driving action for improvements to quiet critic experiences.
One-click quantification from session replay: Instantly connect qualitative to quantitative data
Within session replay, product managers and other users can now instantly pull up tailored metrics on specific user events like errors, taps, or abandoned carts, including data related to quiet critic behaviors. Just click the event icon to see the metric.
For example, while watching session replay, a PM noticed an uptick in errors during checkout, particularly among quiet critic user segments. With one click on the error icon, they pull up a graph showing the error occurred 89 times over the past week, spiking on Monday. When they segment by user IDs, they realize the impacted customers fit the quiet critic definition.
This instant quantitative view enables rapid validation of the PM’s hypothesis: that a recent code push introduced a bug affecting loyalty members matching quiet critic criteria. Without switching contexts, a PM, engineer, or CSM can obtain key insights to prioritize a fix, uncover an optimization, or remove a dead end for quiet critics.
The following events currently include one-click metrics from session replay:
With one-click metrics, FullStory users can quickly quantify and validate their hypotheses, empowering lightning-fast root cause analysis and optimization for this important customer segment.
Together, these capabilities create real-time user empathy at the speed of curiosity for both vocal critics and quiet critics alike. Just as critics won’t wait to abandon sites, teams can’t wait for weekly reviews to uncover issues. They must foster an environment focused on immediate understanding and optimization. With the right tools, teams can detect every user struggle in the moment–even for those quiet critics who never speak up.
This summer we released nine more features to help you create deeper connections with your customers. Read about them here.