Capterra reviews to Power BI
Capterra ranks and filters listings on their review scores, which makes those scores a demand-gen number. Reviewflowz publishes an OData feed, so every Capterra review lands in Power BI as an ordinary row, with its pros and its cons in two columns of their own.
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Capterra reviews As written Quick to run one site, blind across eleven
Pros
Rota building is genuinely quick and the mobile app has never dropped a shift change on us.
Cons
Reporting stops at a single site. We run eleven and there is no way to see them in one view.
201 to 500 employees 2 September 2026
Power BI Reviews - Rating
- 3.0
- Company size
- 201 to 500
- Pros
- Rota building is genuinely quick and the mobile app has never dropped a shift change on us.
- Cons
- Reporting stops at a single site. We run eleven and there is no way to see them in one view.
Pros and Cons are two columns in the feed, not one blob of text.
The number that decides whether buyers see you
Capterra ranks and filters category listings on their review scores, so that number is not a satisfaction metric filed under customer success. It decides whether somebody building a shortlist ever sees your product, which puts it on the dashboard where the pipeline and the category spend already live.
And the number on your profile is not the number you are ranked on. The profile prints a lifetime average, while the ratings half of a category Shortlist score reads the last twelve months. A 4.6 built on a review drive two years ago sits there looking healthy while the twelve-month figure has already slid to 4.2.
In Power BI that window is one measure. A CALCULATE and a DATESINPERIOD over the review date, on a card beside the all-time average, and the gap between the two is on screen every time anyone opens the report. Nobody recounts anything at quarter end.
The feed does the arithmetic you would otherwise rebuild. Beside the per-review table there is a monthly rollup carrying the review count, the average score and the count of ones, twos, threes, fours and fives. You write measures over that rather than summarising every review you have ever had.
Power BI
ReviewSummary
Northline Scheduling Capterra reviews Rating 12m = CALCULATE(AVERAGE(Reviews[Rating]),
DATESINPERIOD('Date'[Date], MAX('Date'[Date]), -12, MONTH))Paste one URL. There is nothing to install.
Reviewflowz publishes an OData v4 feed and Power BI’s built-in OData connector reads it. Get data, OData feed, paste the URL, tick the tables you want. Nothing to install: no connector file dropped into a custom connectors folder, no gateway to stand up, no Power Query M to write. The same URL opens in Excel or Tableau if somebody asks for it there instead.
The credentials are one token you create inside Reviewflowz. Paste it into the user name field and leave the password blank. That is the whole authentication story, and it ends the moment you revoke the token.
Then Power BI refreshes on its own schedule. Incremental refresh works too, because the review date is a real datetimeoffset the feed filters on with ge and le joined by and, which is exactly what Power Query folds a RangeStart and RangeEnd window into.
A deletion is a row, not a silence. Alongside the reviews the feed carries a change stream of inserts, updates and deletes, so a reviewer who edits their review after you ship the thing they asked for, and a review Capterra takes down, both reach the model as events. The report never quietly diverges from the listing.
Power BI Get data Basic authentication. The token goes in the user name field and the password stays empty.
Nothing to install. Power BI has read OData for years.
The pros and the cons are two columns
Capterra asks for pros and cons in separate boxes, and Reviewflowz keeps them separate all the way through. The feed carries Pros and Cons as two properties rather than one blob of review text, so in Power BI they are two fields in the pane and a cons-only visual is a visual rather than a text-parsing project.
Both are filterable at the source. A filter of Cons ne null arrives as a smaller table before it reaches your model, which is worth having on a listing with two thousand reviews behind it and a dataset somebody has to refresh on a schedule. Score, review date, reviewer and title filter the same way.
Read the cons with the rest of the row attached: the score that came with it, the month, and the company size band the reviewer selected. A complaint is then a segment and a date rather than floating context, and three of them in a fortnight from accounts of the same size is a release note instead of a mood.
The pros column is for a different reader. It is the same reviewers saying, in their own words, what they would defend, which is what whoever writes your category landing page has been asking sales for.
Power BI Reviews Two fields -
“Reporting stops at a single site. We run eleven and there is no way to see them in one view.”
3.0 201 to 500 employees
-
“Rolling a new depot on took most of a week because every rule has to be typed again.”
3.0 51 to 200 employees
-
“Rota building is genuinely quick and the mobile app has never dropped a shift change on us.”
5.0 11 to 50 employees
-
“Swaps used to be four texts and a phone call. Now the team sorts it out before I see it.”
5.0 1 to 10 employees
Two properties on one table. A cons visual is a visual, not a parsing project.
Your product, or your fit
A Capterra reviewer states the size of the company they work at, and that band lands on every row. So a slide in the score has a shape. Split the last twelve months by size and it is rarely uniform: the small accounts are fine, the large ones are not, and their cons keep circling the same missing thing.
That is the difference between “the rating dropped” and “accounts over two hundred people cannot get one report across more than one site”, and only the second can be handed to somebody with a fix. One bar chart, average score by size band. Nobody builds a dashboard for that. Somebody adds a visual.
It also tells you which problem you have. If the score holds everywhere except one band, that is a fit problem and the fix is qualification, positioning and who your ads chase. If it sags across every band at once, that is the product.
Be precise about what a row carries. The size band is there. The reviewer’s job title and industry are not, for any platform, because the feed never loads the raw payload they live in. Nor are Capterra’s four sub-ratings for ease of use, customer service, features and value: every row carries the overall score.
Average score by company size
Last 12 months, 61 reviews
The score holds everywhere except the largest accounts. That is a fit problem, not a product problem.
Capterra reviews arrive in bursts
Most Capterra reviews are asked for. A review drive produces a cluster of rows inside a fortnight, then months with almost nothing, and a listing that looks dormant from outside is usually just between campaigns. Charted by month that is obvious, so a quiet month stops being a scare and a spike gets read for what it is.
Which is why a lifetime average is the wrong shape for this platform and a rolling window is the right one. The drive you ran two years ago is still holding the number on your profile up. It stopped counting toward the twelve months Capterra ranks on some time ago, and a dated chart is the only place that shows.
The count is the other half of your position anyway. Beside the ratings component, Capterra weighs how many reviews a product collected in the past twenty-four months and how recent they are. Put both windows on the same page and the next drive gets a date on it rather than a feeling.
The monthly rollup makes that cheap to draw. One row per listing per month, with the count and the average already in it, so the volume chart runs over a few hundred rows rather than every review you have ever received.
Power BI ReviewSummary Capterra reviews per month, by score
Northline Scheduling. 61 reviews over twelve months, averaging 4.2.
March and August are review drives. The March one came back green and the August one did not, which is the slide the twelve month measure is falling through.
One token per connection, and you can take it back
A connection is a token: created in Reviewflowz, revoked in Reviewflowz. Give the agency running your category page one of its own, end the engagement, revoke it, and their report stops refreshing that afternoon. No shared password, and no export you cannot un-send.
A token carries the access of the person who made it. If that user only sees a subset of your listings, so does every report built on it. The permissions are the ones you already set up rather than a second set that drifts, and each token records when it was last used, so a connection nobody has refreshed since March is visible instead of assumed.
The feed serves the account, so the filtering happens in Power BI where the report lives. One connection feeds the category page the whole company reads and the narrow low-score page the product lead opens.
Setup is the same at one listing or eight. Connect the Capterra listing, create the connection, paste the URL into Power BI. Under five minutes on the Reviewflowz side, with no call with a salesperson standing in front of it.
Last used 12 minutes ago
Last used yesterday
Last used 3 September
Their report stopped refreshing that afternoon.
One token per report, and its access is the access of the person who created it.
Basic auth. Token as the user name, blank password.
Put the score you are ranked on in the report you already open
Set up in under five minutes. No demo required.
How do Capterra reviews actually get into Power BI?
Through an OData v4 feed that Reviewflowz publishes. You create a connection in Reviewflowz and copy its feed URL, then in Power BI choose Get data, OData feed, and paste it. Authenticate with the token as the user name and a blank password. Power BI’s navigator lists the tables and you load the ones you want. There is nothing to install: the OData connector ships with Power BI.
Which columns arrive?
One row per Capterra review with the score, the review date, the title, the overall text, the pros, the cons, the link, the language, the reviewer’s name, the company size band, the tags, the topics and the listing it came from, plus the vendor reply and its date. Alongside it are tables for your review profiles, your ratings history, a monthly rollup and a change stream of inserts, updates and deletes.
What is not there: the reviewer’s job title and industry, which the feed does not carry for any platform, and Capterra’s four sub-ratings. Every row carries the overall score only.
Do we get Capterra’s four category scores as separate measures?
No. Ease of use, customer service, features and value for money stay on the Capterra profile page. Reviewflowz does not read them, so there is no column for them and a chart of four category trends would be fiction. What the feed adds instead is the cut the profile page will not give you: the score by month, by company size band, with the pros and the cons in columns of their own.
Does the report refresh on its own?
Yes. Power BI’s scheduled refresh pulls from the feed on whatever cadence you set, and incremental refresh works as well because the review date is a datetimeoffset the feed can filter on. On the Reviewflowz side a Capterra listing refreshes on a four hour floor, so the rows are in the feed well before Power BI asks for them.
Can I narrow what the feed returns?
Yes, with an ordinary OData filter. The score, the review date, the reviewer, the reviewer’s company size band, the title, the overall text, the pros and the cons are all filterable with eq, ne, gt, ge, lt and le joined by and, so a one-star dataset or a cons-only dataset is a query string rather than a second pipeline. Everything else you slice in Power BI, where the report lives.
Does this cover GetApp and Software Advice too?
No. Reviewflowz reads your Capterra listing. It does not merge Capterra, GetApp and Software Advice into a single review, and there is no separate GetApp or Software Advice ingest, so nothing here should be read as covering all three.
Does the first load include our Capterra history?
Yes. Connecting the listing pulls its review history up to your plan’s review limit, so the twelve-month measure and the size-band chart have something to work on the same afternoon rather than in three months. After that the feed carries what changed.
Which plan includes the BI feed?
The BI feed is a Premium feature and it is not part of the free trial, so budget for that rather than discovering it on day three. Everything else works the way the trial suggests: you connect a Capterra listing yourself and see your reviews in minutes.
Do I need a demo to get started?
No. You connect your Capterra listing and create the BI connection yourself, in under five minutes. If you get stuck, support is the people who build it.