How to Connect Retently to Excel (4 Methods Compared)

The Problem With Getting Workbook Data In and Out of Retently

You have an Excel workbook full of customer records — renewal dates, account tiers, churn risk flags, contact emails. Retently holds the NPS scores and campaign data for those same customers. Getting both to talk to each other without a manual step in the middle is harder than it should be.

Retently is good at running structured NPS programs and surfacing feedback at scale. But moving that feedback into an Excel workbook for analysis — or pushing a customer list back in before a campaign launch — involves a round-trip that most teams are doing by hand. The usual path is to export from Retently, download the CSV, open it in Excel, fix the date format, add a category column, merge it against an existing workbook sheet, and save a new version with today's date in the filename.

Below are the four common ways teams handle this. Only the last one scales.

Method 1: Manual CSV Export

Open Retently, pull the export for the period you need, download the file, open it in Excel, discover that the score column imported as text, convert it to a number, manually add the Promoter/Passive/Detractor labels, align the columns to your existing workbook format.

The first run through that sequence is annoying. After the sixth quarterly review it has become its own undocumented process that only one person on the team knows how to do correctly without breaking something.

The volume compounds the problem. A 90-day feedback pull might be 1,400 rows. Doing anything useful with 1,400 rows of unformatted Retently data by hand — sorting by detractor, filtering by campaign, joining against an account list — is the kind of work that fills an afternoon and produces a file no one is certain is current.

Method 2: Power Automate

Power Automate has a Retently connector. You can build a flow triggered by a new feedback entry, a campaign event, or a schedule, and push data into an Excel worksheet on SharePoint or OneDrive.

Quick check before you go further: are you comfortable with Power Automate's flow builder? Do you know how to set up a scheduled recurrence trigger versus an event trigger? Have you mapped dynamic content from an API response to table columns before? If those questions feel like they require research, this path will take longer to set up than the time it saves. Method 4 is probably a better fit.

If you are still reading: the connector works. You authenticate to Retently, pick your trigger, map fields to an Excel table, test a row, and discover that the comment text is arriving with inconsistent encoding. You fix that, retest, push it live.

The ceiling is that Power Automate fires one row at a time.

When you need a historical bulk export — all 1,400 responses from Q1, not just new ones as they arrive — a per-row trigger is not the right tool. You are now looking at a pagination loop, error handling per row, and a task history that becomes unreadable when row 312 fails silently.

You probably just need the feedback in the workbook before Thursday's QBR. You probably have no idea how to build a pagination loop in Power Automate — most people do not, and building automations was not in the job description. So you put in a request to whoever on your team handles this kind of thing, and then you wait.

Method 3: The Previous Generation — Connector Add-Ons

Until recently, the most practical option for repeatable Retently-to-Excel workflows was a category of add-ons that let you configure field mappings, save templates, and re-run syncs on a schedule. You picked the Retently endpoint, mapped the columns, saved the config, and ran it.

That was a real step up from manual CSV imports. Consistent column order, reusable configs, a documented run procedure the team could actually follow.

But every decision still lived with the operator. Which fields to pull, how to handle nulls, what the category column logic should be, what to rename when Retently updated a field name. The add-on did the transport; the thinking about what to transport and how was still entirely yours. And when your workbook structure changed, the config broke until someone went back in and fixed the mapping by hand.

This generation solved the consistency problem. It did not solve the judgment problem.

The Easy Way: Using SheetXAI in Excel

There is a different way to approach this. SheetXAI is an AI agent that lives inside your Excel workbook. It reads your data, understands the context, and through its built-in Retently integration it can pull feedback, sync customers, and push tags back to Retently without leaving the workbook. No export configuration, no flow builder, no category labels to type 400 times. You just ask.

Example 1: Pull campaign NPS data into a dashboard worksheet

Fetch Retently NPS reports for all campaigns and populate my Excel dashboard — one row per campaign with name, score, and promoter/detractor percentage columns

Every campaign lands in a row. Percentages computed inline. The workbook stays in Excel; you did not open a browser tab to get the data.

Example 2: Upsert a customer list before a campaign launch

Take the 500 rows in my Excel New Customers sheet and upsert each one into Retently using email as the key — apply the tier tag from column D to each record

Instead of exporting a CSV and re-importing it through the Retently UI, you describe the sync and SheetXAI handles the field matching and API calls in one pass.

Try It

Get the 7-day free trial of SheetXAI and open any Excel workbook with a Retently customer list or a set of survey results, then ask it to sync, enrich, or export. The Retently integration is included in every SheetXAI plan.