Turning passive feedback into a national client insight system built to scale

At a glance

Role: Client experience, communication strategy, programme design and measurement

Timeframe: 2022 to August 2026

Scale: Annual feedback requests grew from 209 to 2,916; responses from 65 to 1,436

Key collaborators: Technology team, adviser managers, board and communications stakeholders

Outcome: A CRM-connected feedback system, journey-level insight and a Trustpilot programme reaching 175 reviews and a 4.9 TrustScore

The challenge: feedback existed, insight did not

A company satisfaction figure approaching 95% positive can still hide a client journey where one in four respondents report a negative experience.

That was the problem I wanted the business’s feedback programme to solve. Not simply collecting more praise, but showing where the client experience was working, where it was weakening and what management should investigate next.

When I took ownership in 2022, Customer Thermometer was largely functioning as an email-signature feedback widget. Clients could leave a rating, but the business had limited control over when feedback was requested and little connection between a response and the interaction that prompted it.

The business was also becoming larger and more operationally complex through acquisition. My point of view was simple: feedback should follow meaningful client behaviour. If requests were tied to specific moments in the relationship, the programme could scale with real activity and produce information management could act on.

Designing for behaviour, not survey volume

I simplified the client-facing experience first. I tested numerical scores, colour-led systems, thumbs-up icons and different visual treatments before settling on four deliberately plain choices: Great, Good, Average and Poor. I applied the same test-and-learn approach to subject lines, sender identity, wording, timing and follow-up.

The more consequential decision was where feedback should appear. I embedded requests into three defined CRM events: completion of an annual review, completion of a business opportunity and two weeks after a client’s first MyViewpoint login.

That changed the programme’s growth model. Feedback volume no longer depended on sending more campaigns. It increased because more clients were completing genuine journeys.

From 2022 to 2025, annual requests grew from 209 to 2,916 and responses from 65 to 1,436. Written comments increased from 12 to 518. Response rate rose from 31.1% to 58.3% in the first full year following the redesign and remained at 49.2% in 2025.

Making the data trustworthy

Scale created a second problem: more feedback is not automatically better information.

Historical records across Customer Thermometer and the CRM did not always align. Clients could respond more than once, identifiers had changed and CRM statuses were not always reliable evidence that communication had actually been sent.

I worked with Technology to define how responses should be retrieved, matched and treated when systems disagreed. The principle was conservative: if the evidence was not strong enough, it should not be forced into the analysis.

The work examined 8,240 feedback sends and 4,015 response records. It excluded 195 responses that could not be linked confidently to an individual send and identified 26 CRM records marked as Draft that had demonstrably generated responses. The cleaned dataset contained 2,709 unique responded feedback sends and 1,080 written comments.

The objective had shifted from reporting the largest possible number to creating management information that could withstand challenge.

Turning feedback into a management tool

I then defined the business requirements for a dedicated CRM feedback dashboard. Technology designed and built the technical solution; my role was to establish what stakeholders needed to see, how the information should behave and what comparisons would be useful.

The dashboard gives adviser managers, board members and communications colleagues access to adviser-level feedback, response rates, rating distributions, written comments and recurring themes. Behind the four simple client-facing ratings sits a numerical weighting that allows feedback profiles to be compared consistently.

This matters because headline satisfaction can hide materially different experiences. Annual Review feedback remained more than 97% positive in the cleaned dataset. But Opportunity Won response rate fell from 28.0% in 2024 to 15.9% in 2026 YTD, with positive sentiment at 88.9%.

MyViewpoint showed the sharper signal. In 2026 YTD, 70 responses from 369 requests included 18 negative responses, meaning 25.7% of responding clients reported a negative experience.

Inside an overall company satisfaction figure approaching 95% positive, that issue would have been easy to miss.

Extending insight into advocacy

By 2025, several years of strong client feedback created another opportunity: make genuine client experience visible publicly.

I established the business’s Trustpilot presence in May 2025 and treated review acquisition as another client journey rather than a one-off request. Across the available invitation data, 569 delivered invitations generated 118 reviews, with an 83.0% open rate, 40.2% click rate and 20.7% invitation-to-review conversion rate.

More than half of those reviews were completed after a reminder. That was useful behavioural evidence: non-response often reflected timing rather than unwillingness to advocate.

By 20 August 2026, the profile had reached 175 reviews, a 4.9 TrustScore and 96% five-star reviews.

What changed

The programme began as a passive feedback tool. It became a repeatable client insight system connected to real customer journeys, CRM data, management reporting and public advocacy.

Its value was not simply that it collected more responses. It gave the business a more useful way to listen: one that could distinguish a healthy overall relationship from a weaker individual journey, connect qualitative comments with operational data and support management, Consumer Duty, compliance oversight and reputation.

Technology enabled that capability. My contribution was defining what the programme needed to become, how clients should experience it and how the business should learn from what they did next.

By replacing a passive annual survey with event-driven triggers across key journey milestones, the redesign transformed a low-engagement reporting tool into a high-signal client intelligence system.

Annual responses scaled from 65 to 1,436, while written qualitative feedback surged from 12 to 518 detailed comments, shifting the dataset from superficial star ratings to actionable, touchpoint-specific insight. This elevation in data quality unmasked underlying operational friction during onboarding and review cycles that had previously been hidden by an overall 95% satisfaction score.

By routing low-score alerts directly into adviser task queues, teams triggered immediate follow-ups to resolve fee confusion and onboarding friction, preventing formal client complaints and keeping at-risk assets under management

A note on the data

The value of this work is not simply that the business can say its clients are happy. It is that the business can now show it with confidence.

The feedback system I developed gives the board a much clearer and more reliable view of client experience because the data is tied to real client journeys, checked against CRM records and stripped of anything that cannot be confidently verified. That means strong results can be trusted, but weaker experiences are also much harder to hide inside an overall average.

Even under that level of scrutiny, the picture remains extremely positive. The business’s overall client satisfaction is close to 95% positive, while Annual Review feedback is above 97% positive.

That is the wider impact of the work: the business now has a system that can identify where the client experience needs attention while also giving senior leaders credible evidence that, across the business, clients genuinely rate the service very highly.