Build a customer reviews dashboard your board can trust

What to take away

Decide the single decision the customer reviews dashboard must support before you pick a tool or a chart type.
Define each metric with a written formula, a data source and an owner, so two readers reach the same number.
Keep personal data out of review analytics unless you have a lawful basis and a retention rule recorded.
Test the dashboard against one month of real figures before you show it to anyone senior.

Decide which number your team will act on when it moves. The rest follows from that decision.

Define the metrics before you build anything

Start with one decision per metric

Write the decision at the top of the page. A response time metric exists so a manager can move staff onto unanswered reviews in a busy week. If no action follows a change, the metric is decoration.

Metric definition checklist

Decision written at top of page
Keep set to six to ten metrics
Groupvolume, sentiment, response, commercial
Record formula and source system
Name the metric owner
State period and duplicate rule
Document lawful basis for tracking

Keep the set small. Six to ten metrics suits most retail teams. Group them into volume, sentiment, response and commercial impact.

Write the formula and the source

For each metric, record the formula, source system and named role responsible. For review counts, ratings, replies and incentive flags, use records from a platform such as Trustpilot, Feefo, Reviews.io, Yotpo or Bazaarvoice; use Google Business Profile for Google reviews, and commerce order records for revenue. Assign a customer experience manager to response operations, a data analyst to definitions and reconciliation, a finance analyst to revenue and a privacy lead to data handling.

Review content that identifies a person is personal data, so document a lawful basis under the UK GDPR and a retention rule. Where analytics uses cookies or similar storage and access technologies, follow the Privacy and Electronic Communications Regulations 2003 (PECR) and the ICO's guidance on storage and access technologies; explain the collection transparently and obtain consent where required.

Handle the legal and platform rules

Reviews you publish must be genuine

You cannot suppress negative reviews to lift a headline score, or present invented reviews as customer feedback. Do not rely on the Consumer Protection from Unfair Trading Regulations 2008 alone: the Digital Markets, Competition and Consumers Act 2024 includes rules addressing fake reviews. The Competition and Markets Authority (CMA) is the UK enforcement authority, so set metrics that reward fair handling rather than simply a higher score.

The CMA's GOV.UK guidance, Online reviews and endorsements: advice for businesses, explains these duties in plainer language, including incentivised reviews and disclosure. Use it when deciding what your dashboard must record.

Incentives and disclosure need their own field

Add a field that marks whether a review came from an incentivised request. Without it, your sentiment trend mixes two populations and you cannot explain a shift.

If your setup already has gaps, record them as data-quality caveats rather than smoothing them over. Missing incentive flags, duplicate reviews and incomplete exports can all affect the trend a board sees.

Build, test and hand over the dashboard

Assemble the monthly view

A workable monthly view has five metrics: reviews received, average rating, response rate, revenue influenced and unanswered reviews. Define reviews received as the count of new reviews in the period, average rating as the mean rating for those reviews, response rate as answered reviews divided by reviews received, and unanswered reviews as those with no reply at month-end. Revenue influenced needs a clear definition. For example, a retailer might count orders placed within seven days of a customer reading a review page, and label the figure as influenced rather than attributed.

Build the monthly view in Looker Studio, Power BI or Tableau. Bring in the review-platform records and commerce order data, and make sure the period and definitions match across the sources.

Worked example, illustrative figures only. A shop gets 500 reviews in a month and replies to 400: an 80% response rate. Average rating is 4.3. Review pages influenced £18,000 of orders.

That month's programme cost is £2,400: £400 software and £2,000 staff time. The dashboard shows influenced revenue to programme cost of 7.5 to 1 and lists 100 unanswered reviews as an open task.

Test it, then hand it over

Run the dashboard against one closed month and check every figure against source systems by hand. If two people cannot reproduce the same number, the definition is wrong, not the software.

For handover, use a monthly reporting template with fields for metric, definition, period, source, owner, result and data-quality caveat. Record the refresh date and retention rule, then set a quarterly review date so the next owner inherits the policy.

Common questions

How many metrics should a review dashboard show?

Six to ten is workable for most retail teams. Start with reviews received, average rating, response rate, revenue influenced and unanswered reviews, then add a metric only when it supports a clear decision.

Can we track reviewers across other sites?

For cookies or similar storage and access technologies, follow PECR and the ICO's guidance on storage and access technologies; obtain consent where required. If you identify people across sites, also assess your UK GDPR obligations and explain the data use clearly.

Should influenced revenue be called attributed revenue?

No. Attribution claims a direct causal link, while influenced revenue is a softer measure and should be labelled as such in every export.

How often should the dashboard change?

Review the metric set quarterly, and change definitions only at a period boundary so historical comparisons stay honest.