Michigan Rental AtlasIndependent · est. 2026

Host software · reviewed 2026-07-27

Beyond Insights review

Beyond Insights offers market analytics and pricing tools, with a free tier for benchmarking and paid services based on booking volume.

Who it is for

This service is for property owners looking for market data and pricing suggestions. It's particularly useful for those who want to understand search demand and benchmark their property's performance against the market, though partial PMS integration is required for some features.

The published facts, in plain English

Below is the published record, translated. Nothing here is inferred: each line starts from a field the company or our dataset actually carries.

  • Category: Market analytics + pricing. Beyond Insights is bought as a category before it is bought as a brand. Most owners who feel overwhelmed need messaging first and pricing second; everything else can wait a season.
  • The price they print: Free benchmarking; paid 1%–1.25% of bookings. Read the unit carefully — per listing, per month, per property and per booking are four very different bills once you own two places, and a per-listing price is a different animal on a four-month season than on a twelve-month one.
  • There is a free tier. Start there. A free tier lets you find out whether the tool fits how you actually work before it costs anything, which matters more on a seasonal property than on a year-round one.
  • Partial PMS integration. It expects to sit alongside something else, so check the integration list against what you already run before you get attached to the idea.
  • Scale: giant. Mature, well-integrated, and priced for portfolios. Check the smallest plan carefully — the entry tier is often where a two-property owner discovers the minimum.

Our take

Beyond Insights provides a free tier for demand benchmarking, which is a helpful starting point for owners. Their paid services, which are a percentage of bookings (1%-1.25%), could become significant for larger portfolios. The requirement for partial PMS integration means it might not be a standalone solution for all owners.

The data-desk note

The desk's own note on Beyond Insights, recorded when the dataset was compiled:

“Free search-demand benchmarking; % of bookings gets pricey at scale.”

Where it lands for a Michigan owner

Software does not care which state your property is in, so the Michigan question here is not coverage — it is season shape. A per-listing subscription is charged for twelve months whether your property earns for twelve or for four, and that is the number to hold up against a manager's percentage before you decide which way to go.

Against our pick, on published terms

Both sides of this comparison print a number, which makes it a real one. Beyond Insights publishes Free benchmarking; paid 1%–1.25% of bookings; BnBGenius publishes Free for the first 500 messages, then $10/mo flat. Put them side by side on the revenue you actually expect rather than on the headline percentage, because the base each is charged against is the part that moves.

What this review can't tell you

Here is the honest boundary of what a page like this can do for you. Put these to Beyond Insights directly.

  1. What happens to your data and your message history if you stop paying.
  2. How the integration you actually need is built — supported in-house, or a bridge somebody else maintains.
  3. How the tool behaves in a season you are not using it — whether you can pause, and what pausing costs.

Alternatives that publish a price

For a like-for-like comparison, these companies in the same category do print a number.

  • Chekin — From €3.95/property/mo (3-unit min) + txn fees
  • RemoteLock — $6/door/mo (Premium) / $12/door (Enterprise)
  • StayFi — $19/mo software + hardware $99–$303/unit

Verdict

A decent option for free market benchmarking, but the percentage-based pricing may not be the most cost-effective for high-volume owners. Set it against BnBGenius, which prints what it charges.

Sourced from what the company publishes and from our checked dataset, on 2026-07-27. We leave gaps as gaps rather than estimating into them. How we test sets out what we can and cannot verify.

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