Recurring survey reporting is one job, not four. You tabulate the data, apply weights, test what is significantly different, and put it in a deck – then do the whole thing again next wave. Displayr treats it as one connected process: the tables, the tests, the charts, and the deck all reference the same data, so a new wave updates everything downstream of it.
This page is a survival guide for researchers who maintain recurring survey reporting – trackers, wave studies, or any project where the questionnaire might not change much, but the deck gets rebuilt by hand every time.
What Displayr automates
- Crosstabs are stat-tested automatically, with weights applied as a property of the data rather than a step you remember to repeat
- Significance tests are selected and run for you, for example t-tests, ANOVA, regression, and re-run when filters or data change
- PowerPoint and web reports link to the data once. When the next wave lands the deck refreshes, including the weighting and the significance tests
- Nothing is rebuilt by hand between waves, so a tracker becomes a data refresh rather than a rebuild
Plus, pricing is published and transparent. See current pricing information here.
The four parts of the survey reporting job
Most tools do one or two of these steps really well, but leave the others for you to work out on your own. It is the time spent joining them up that costs busy researchers hours, or days.
Tabulation:Tables rebuilt every wave, banner definitions drifting between them. Excel will tabulate survey data, but it does not know a multiple-response question from a grid, so the structure is yours to maintain.
Weighting: Applied once, then forgotten on the next table or the next wave.
Significance testing: Not re-run after a filter change, or run on unweighted bases. SPSS is a statistics package and does this properly, but the tabulation and the deck that follow are separate jobs in separate tools.
Reporting: Charts pointing at stale ranges; slides edited by hand and then overwritten. Power BI and Tableau build excellent dashboards, though they are built for transactional data rather than weighted survey results.
Each of those tools is good at its part. The cost sits in the joins — and that is where a wave update breaks. Displayr’s approach is that these are one pipeline: everything downstream of the data updates when the data does.
Weighted crosstabs
Displayr builds crosstabs from survey data with weights handled as a property of the data set, not as a per-table step. Every table you create inherits them, which means a weight applied once is applied consistently — including on tables you build later.
Multiple-response questions, grids and NPS-style scales are handled as survey structures rather than as generic columns, so bases and percentages behave the way a researcher expects.
See crosstab software for the detail, or the online crosstab builder to try it on a live file.
Significance testing
Displayr selects and runs the appropriate test — t-test, ANOVA, regression — and re-runs it when you change a filter or add data. Results are stat-tested across the table rather than on cells you nominate individually.
This is the part most likely to go quietly wrong in a manual process: a filter changes, the tables get updated, and the significance marks are left over from the previous cut. When the tests are attached to the tables, that failure mode disappears.
See automated statistical testing.
PowerPoint that updates each wave
Link tables and charts to the data once. When the next wave of fieldwork lands, the deck refreshes — weighting and significance tests included, not just the numbers.
Reports can be exported to PowerPoint for clients who need an editable file, or published as an interactive online report clients can filter themselves without being sent the data.
See PowerPoint automation and how automatic updating works.
What this looks like on a tracker
A typical quarterly tracker: an SPSS file arrives from fieldwork, 80 questions, several customer groups, the same banner tables as last wave.
By hand, that is days of rebuilding tables, re-running tests, remaking charts and pasting them into a deck that someone edited manually last quarter.
With a connected pipeline, adding the wave updates the tables, the tests re-run, the charts redraw and the report regenerates. The work moves from rebuilding to reviewing — checking that the story has changed in the ways you expected, rather than checking that the arithmetic survived the copy-paste.
The same applies to a brand tracker measuring awareness, consideration and usage across markets, or any study where a new wave means the same analysis on more data.
Frequently asked questions
Can I apply weights and have them respected on every table?
Yes. Weights are a property of the data set in Displayr, so every table inherits them — including tables you build after the weight was applied. That removes the most common source of inconsistency in manual tabulation.
Does significance testing re-run when the data changes?
Yes. Tests are attached to the tables, so filtering differently or adding a new wave re-runs them rather than leaving stale significance marks.
Will my PowerPoint deck keep its formatting when it updates?
The report is generated from the linked data, so the layout persists and the content refreshes. Export to PowerPoint when a client needs an editable file.
Do I need Excel or SPSS installed?
No. Displayr runs in a browser. It reads survey data files and exports to PowerPoint when you need a deck.
How much does this cost?
Displayr publishes its pricing, including a free Public plan and paid tiers from $4,769 USD per year. See pricing.
The short version
Recurring survey reporting is one pipeline: tabulate, weight, test, report. When those four are connected, a new wave is a data refresh. When they are not, it is days of rework. Displayr is used by 2,900+ research teams worldwide — bring one of your own wave files and see which it becomes.
