Owner retention and churn

What it is

A manager's inventory belongs to owners. When an owner leaves, the home and its revenue go with them.

Owner churn = owners lost in the period ÷ owners at the start. Retention = 1 − churn. Measure by owner, by home, and by revenue, because one owner can have several homes.

Why operators track it

• Inventory is the business. Lost homes must be replaced before there is growth.
• Leading indicators. Statement errors, net revenue below projection, and slow communication are worth watching as possible early signs. Test this in your own data.
• Acquisition cost. Replacing an owner takes sales and onboarding effort.
• Owners have options. Other managers, self-managing, or selling the home.

How it is calculated

Owner churn = owners lost in period ÷ owners at start of period

• Lost: contract ended, or notice given and effective in the period. Pick one date.
• Separate homes sold by the owner from owners who switched or self-manage, but report both.
• Revenue churn weights by trailing 12-month GBV.

Worked example

Example data The same made-up portfolio is used on every hospitality page: a manager with 120 homes, four of them shown in detail.

The example manager had 120 owners on July 1, 2026. Six left during Q3 and nine joined. Owner churn = 6 ÷ 120 = 5.0% for the quarter. The six lost owners had $410,000 of trailing GBV out of $6,200,000, so revenue churn was 6.6%.

How to read it

• Do not net new owners. Growth can hide churn.
• Read the reasons. Sold the home, moved to self-managing, moved to another manager, or dissatisfied.
• Cohorts. Compare owners by tenure.
• We do not publish a benchmark. Levels vary by market, season, and property type.

Definitional choices and common pitfalls

• Owner or home. Report both.
• Effective date. Notice date or contract end date.
• Controllable. Separate homes sold from owners who switched managers.
• Revenue weighting. Trailing GBV or net owner revenue.

How different roles use it

Questions it answers

• How many owners did we lose and why?
• Is churn higher for owners whose net is below projection?
• Which markets lose the most homes?

How to present it in a report

• Owners at start, lost, added, end.
• Churn by reason and by tenure.
• An at-risk list with signals.

Data you need

Fields

What the raw data looks like

Example data A few rows as they might come out of the source system.

Where this data usually lives

• CRM and guest tools hold owner contracts and leads, guest messages, reviews, and upsells. Sales projections often live in spreadsheets.
• Property management system (PMS) holds units, the calendar with block types, reservations, rates, fees, and often owner statements and trust accounting. For example: Guesty, Hostaway, OwnerRez, Track, Streamline, and Escapia. Some larger managers run their own in-house PMS.
• Trust accounting and owner ledgers, in the PMS or a separate accounting tool, hold owner balances, management fees, expenses, reserves, and distributions.

The same field can live in more than one system. Agree with the customer which one is the source of truth.

Common data gaps and traps

• Exit reason not captured.
• Contracts in a CRM separate from the PMS.
• Owners with several homes counted as several owners.

Related metrics

• Owner statement accuracy
• Projection accuracy
• Net owner revenue

FAQ

Should sold homes count as churn?

Report them, but separate them from owners who chose to leave.

Owner or home churn?

Both. One owner leaving can take several homes.

Is there an industry churn rate?

We do not publish a benchmark. Levels vary by market, season, and property type.

owner_churn   = COUNT(owners active at period_start with end_date in period) / COUNT(owners active at period_start)
revenue_churn = SUM(trailing_gbv of lost) / SUM(trailing_gbv of active at start)

SELECT COUNT(DISTINCT owner_id) FILTER (WHERE end_date >= '2026-07-01' AND end_date < '2026-10-01')::numeric
     / COUNT(DISTINCT owner_id) AS owner_churn
FROM owner_contracts
WHERE start_date < '2026-07-01' AND (end_date IS NULL OR end_date >= '2026-07-01');

metric: hospitality.owner_retention
grain: one row per owner contract
inputs:
  - contract start, notice, end
  - exit reason
  - trailing GBV
logic:
  - churn = lost / active at start
  - revenue churn weighted by trailing GBV
edge_cases:
  - re-signed owners: not churn
  - home sold: separate reason
  - started mid-period: exclude from denominator

Version 1.0 · Last reviewed 2026-10-20 · Machine-readable definition