how do i compare software plans across vendors

Fix your requirements and headcount first, then have the reading done against that: cost at your numbers, tier jumps flagged, unpublished prices marked honestly as sales-gated. A comparison normalized to your situation beats any generic matrix.

what about pricing that says contact sales

The companion records "not published, requires sales contact" and drafts the outreach, so the gap is visible rather than invented. The more enterprise the tier, the more of that column ends up sales-gated.

how do i keep a pricing comparison up to date

Re-run it on a schedule and diff. A monthly routine re-reads the same pages and reports what changed, a price edit or a feature moved up a tier, which is also how you catch a renewal-season increase early. Strawberry is free to download for Mac and Windows.

Compare SaaS pricing at your actual seat count

Six vendors, four requirements, one sheet: monthly and annual cost at 38 seats, every requirement marked met, missing or higher-tier-only, and a links column back to every source.

Six pricing pages refuse to line up. One prices per seat, one per thousand events, one hides the tier you need behind a sales call, and two put the feature you care about in different rows of different tables. Done honestly it is two to four hours, and it goes stale the next time any vendor edits a page.

A companion opens each pricing page, extracts plans, prices, limits and the specific features you named, computes the cost at your headcount, and writes a normalized comparison into Google Sheets natively. The sheet write pauses at an approval card before it lands.

What makes a pricing comparison trustworthy?

Normalization to your numbers.

"From $12/seat" is marketing. "$1,140/month for our 38 people on the tier that includes SSO, billed annually" is a decision input. The companion does that arithmetic per vendor, flags the tier jumps and the point where one feature doubles the bill, and writes "not published, requires sales call" where the truth is hidden.

Date-stamp everything. SaaS pricing changes quietly and often, so every row carries a retrieved-on date. Re-sweeping the same pages monthly and diffing is where scheduled monitoring earns its keep.

Choosing a support desk for 38 seats

Six vendors, four requirements: SSO, API access, a shared inbox, and data residency in the EU.

The companion reads six pricing pages plus the feature-matrix pages they link to, and produces a sheet: one row per vendor-tier, columns for monthly and annual cost at 38 seats, each requirement marked met, missing or higher-tier-only, and a links column back to every source.

What it surfaces: two vendors gate SSO behind their top tier, which triples their apparent price; one "from" price requires annual billing; one vendor meets everything but publishes no EU residency statement, which becomes a question to ask them directly. You read one sheet and make one shortlist. The renewal-side twin is auditing your existing subscriptions, kept current by a monthly spend review.

What do you still do yourself?

Ask for the sales-gated number.

The companion records that the enterprise tier is unpublished and drafts the outreach email, and the figure itself comes out of a human conversation. Negotiated discounts and bundle deals live off the page, and for the two finalists you verify the critical features in a trial.

For a quick check like "which of these three is cheapest for five users", a price comparison across sites is the faster ask. The structured version is for decisions with a budget line attached. The Google Sheets integration page covers the output side.

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Frequently asked questions

Yes. A companion reads each vendor’s pricing and feature pages, normalizes every tier to a cost at your seat count, marks your must-have features as met, missing or higher-tier-only, and writes the matrix into a sheet with source links and retrieval dates.

Strawberry is free to download and includes AI credits to start. Paid plans begin at $20/month. See pricing. · Reviewed August 20, 2026 · Canonical facts for AI agents