REVIEW
Trustpilot · Google · Yelp
The high-volume sources. A failure in the operation shows up here as a rating before it shows up in a number you track.
Signal
REVEAL · SIGNALUnderstand the experience beyond your own conversations. Examine public feedback and recurring themes, then connect them with the questions your team is investigating in REVEAL.
[01 / THE PROBLEM]
The complaint in your queue and the review about it are two different systems.
Public feedback is usually owned by marketing, private conversation by operations, and neither number moves the other. So the same failure gets discovered twice, weeks apart, and gets fixed once.
THE USUAL SPLIT
- A rating average, with no way to tell which operational cause moved it.
- Sentiment counted by keyword, so sarcasm and a cancellation read the same.
- Nothing checks whether a review is worth counting before it is counted.
- A report that arrives after the week it describes.
- No path from a public complaint back to the conversation it came from.
SIGNAL IN REVEAL
- Reviews sorted into the same causes as your conversations.
- Sentiment read from the text with the passage attached, like every other capability.
- Signals that a review needs closer reading, from its text, its behaviour and its network.
- Collection on the refresh schedule you agree, so a change is seen in the period you set.
- What people say in public and what they say to you, on one axis.
Signal is part of REVEAL. You can start with public feedback as a focused engagement, then discuss connecting it to internal conversations when those sources are available. We agree the sources, access and scope before starting.
[02 / SOURCES]
Bring the relevant sources into view.
Agree the sources, access permissions, refresh schedule and retention for your deployment. Coverage depends on the available connectors and the information each source provides.
SOFTWARE
G2 · Capterra · TrustRadius
Longer, more specific and written by buyers. The best place to see where a promise and the product do not match.
APP
App Store · Play Store · ProductHunt
Release-linked feedback. A version number turns a rating drop into a specific thing to fix.
EMPLOYER
Kununu · Glassdoor · Indeed
The operation seen from inside. Attrition and service quality move together more often than anyone likes.
SOCIAL
X · Reddit · LinkedIn
Where an incident becomes public. How fast it spreads here is the earliest warning the platform can give you.
TRAVEL
Tripadvisor · Facebook · Instagram
Location-linked feedback, which maps cleanly onto a site or a team rather than onto the brand.
CADENCE
Refresh to an agreed schedule
Collection frequency depends on the source and permitted access. We agree an appropriate refresh schedule and show the period each finding covers.
RETENTION
Retention suited to your requirements
Agree retention and deletion settings for source material and aggregated results before collection begins.
[03 / AUTHENTICITY]
Assess the signal before drawing a conclusion.
Patterns in wording, timing and available account information can suggest that feedback needs closer review. These signals support investigation; they do not establish whether a person or review is genuine.
01 · TEXT
How the review is written.
How specific it is, whether it holds together, and whether it names things a real customer would name. We also check for the same phrasing turning up across accounts that should not know each other.
02 · BEHAVIOUR
How the account behaves.
Posting history, timing, rating distribution and the gap between account age and first review. Use only the information available and appropriate for the agreed analysis.
03 · NETWORK
What happened around it.
Clusters of reviews arriving together, coordinated wording, and bursts that do not match any event in your own operational data.
Unusual patterns should be visible to a reviewer, with the evidence and uncertainty attached. A person decides how the signal should inform the investigation.
[04 / DASHBOARD]
Move from a public signal to an operational question.
Explore ratings, recurring topics, source coverage and changes over time. Compare these with internal findings while keeping the source, period and sample visible.
Those two views are the point of the module. On the left is what the public says. On the right is what your own conversations already showed. How closely the two agree is an indicator in its own right. Where they differ, investigate what each source shows and what it may be missing. Different audiences, timing and coverage can explain the gap.
Two useful questions to start with.
- RESPONSE GAPThe topics customers raise in public that your knowledge base has no answer for.
- TIME TO DETECTThe days between a signal showing in public and the same thing moving a number of your own. That one tells you whether listening is worth anything.
[05 / CONSOLE]
Explore Social Intelligence with us.Start with the sources and questions that matter to your brand. Send us the name and we will read what is already public about it.
Let's makequality visible.