Analytics are most useful when they help you make one clear decision. You do not need a complex report. You need a consistent time period, a baseline, a record of what changed, and enough patience to see whether the change repeats.
GreenQR Link lists scan activity, pageviews and visitors, plus countries and cities, referrers and UTMs, devices and operating systems, and browsers and languages. Those fields provide context. They do not tell you a visitor’s name, motivation, or final purchase outcome.
A seven-step reading workflow
Use the same sequence each time you review a promotion. Consistency reduces the temptation to explain a result before you have enough evidence.
1. Open the relevant analytics
Start with the QR code, link, or page connected to the activity you want to understand. Confirm that you are looking at the correct item before interpreting any number.
2. Choose a useful time period
Use a period that matches the business question. A weekend promotion may need a daily view; a recurring counter sign may need several weeks. Remember that the current plan table lists one month of statistics retention on Free and three months on Pro.
3. Establish a baseline
Record a normal period before making a change. Note pageviews, visitors, scan activity, and any useful supporting dimensions that are present. A baseline gives you something more reliable than memory to compare against.
4. Compare like with like
Compare similar days, hours, or campaign periods when possible. A busy Saturday should not automatically be compared with a quiet Monday, and a holiday week may not represent normal demand.
5. Look for a pattern, not one isolated number
A rise repeated across comparable periods is more useful than a single spike. Referrer, UTM, country, city, device, browser, operating-system, and language data can add context when those fields are available.
6. Change one thing at a time
Adjust one variable—such as sign position, call-to-action wording, or the destination shown—while keeping the rest of the setup stable. Several simultaneous changes make the result difficult to interpret.
7. Measure again and record the decision
Review the same metrics after a comparable period. Keep a short note of what changed, what happened, and what you will test next. The note is often as valuable as the chart.
Illustrative scenario: a weekday lunch offer
Illustrative scenario: A café has one QR code beside the register. During a typical Tuesday lunch period, its dashboard shows 28 pageviews and 23 visitors. The café records those figures as a baseline. The numbers are hypothetical; they are not GreenQR Link customer results.
The following Tuesday, the café keeps the code, destination, hours, and offer the same but changes the sign from “Scan here” to “Scan for today’s lunch menu.” The comparable period shows 41 pageviews and 34 visitors. That is a useful signal that the clearer wording may have helped.
It is not proof. Foot traffic, weather, a local event, or repeat visits may also have affected the result. The responsible next step is to keep the clearer wording for another comparable period and see whether the pattern continues—not to claim that the sign caused a precise percentage increase in sales.
Use supporting dimensions carefully
Supporting fields can help you form better questions. A high share of mobile activity suggests that the destination deserves a careful mobile check. A browser pattern can prompt compatibility testing. A UTM label can help separate tagged campaign traffic when the link was configured correctly.
These fields should not be stretched beyond their purpose. Language settings do not prove nationality. City data does not prove a visitor was standing at a particular store. A referrer does not always describe the complete journey, and missing referrer data does not mean the visit was invalid.
Common interpretation mistakes
- Pageviews are page loads, not confirmed purchases or enquiries.
- Visitor figures are estimates and should not be treated as a list of identifiable people.
- A scan or visit does not reveal why the person acted.
- Country and city data are broad geographic signals, not exact addresses.
- Referrer information may be missing, and UTM reporting depends on consistent tagged links.
- If the same QR code appears in several physical places, its combined activity does not identify the winning placement.
Keep a small decision log
A spreadsheet or notebook is enough. For each test, record the date range, the QR code or page reviewed, the baseline, the one change you made, the result, and the next decision. If an unusual event affected the period, write that down too.
Record context
Note the dates, placement, message, destination, opening hours, and anything unusual that could affect activity.
Run a fair next test
Keep the setup stable, change one variable, and allow a comparable period before deciding whether the result is useful.
The useful question is “what should I test next?”
Analytics rarely provide a complete explanation on their own. Their practical value is narrower and more reliable: they show patterns worth checking. Use those patterns to choose one sensible change, measure again, and keep the conclusion no stronger than the evidence.
Need the metric definitions?
Read the product reference for the current analytics categories, plan retention periods, and the limits of what each field can show.
Review the analytics reference