Real Estate · RetentionTenant Retention & Renewal Prediction
AI that spots which residents and tenants are unlikely to renew months before they give notice, and lease renewal software that turns the warning into an offer they accept.
TRUSTED BY TEAMS
Tenant retention is usually decided long before a resident gives notice — by a repair that took too long, a rent that drifted above the market, or a building they stopped using.
Sodio builds renewal prediction that reads those signals across a portfolio, flags residents and tenants who are unlikely to renew while there is still time to act, and connects to lease renewal software that handles the offer, the pricing and the signature. It works for resident retention in multifamily buildings and for commercial tenants alike.
/// COMPARE
When Renewal Prediction Is Worth Building
A warning is only useful if someone can act on it, and a model is only useful if it has enough past renewals to learn from.
Worth building when
- Your portfolio has enough renewals each year to learn from
- You record why people leave, or are willing to start
- Your team can act — fix issues, call, adjust terms
- Tenancy, payment and repair data sit in systems you can reach
Not yet, when
- A small portfolio where you know every tenant by name
- There is no record of who left or why
- Every tenant receives the same renewal letter regardless
- The data lives only in individual managers' heads
/// WHAT IT COVERS
What Renewal Prediction and Retention Software Cover
Renewal risk scoring
Early warning
Renewal workflow
Renewal offer pricing
Retention actions
Feedback and sentiment
Move-out reasons
Commercial renewal signals
Retention reporting
Platform integration
/// THE RENEWAL TIMELINE
Retention Starts Long Before the Renewal Letter
Months before the lease ends
Risk scored from payments, repairs and engagement
Risk starts to rise
Flag raised with the reasons, and a suggested action
The team intervenes
Outstanding issues resolved; a conversation arranged
Renewal terms are sent
Offer priced from your own data and sent for e-signature
The tenant replies
Acceptance, negotiation or notice recorded
The outcome is known
Result fed back into the model, with the reason if they left
/// THE SIGNALS
The Signals That Come Before a Move-Out
///WHAT TURNOVER COSTS
What Tenant Turnover Really Costs
The weeks or months a unit or floor sits empty.
Learn MoreCleaning, repairs, repainting and replacing what has worn out.
Learn MoreMarketing, agent or broker fees, and concessions to attract the next tenant.
Learn MoreViewings, applications, inspections and move-in administration.
Learn MoreIncentives and fit-out contributions for a new commercial tenant.
Learn More/// COMPARE
Standard Renewals, Lease Renewal Software or
Renewal Prediction
/// COST AND TIMELINE
What Drives the Cost and Timeline
A pilot tested on your past renewals and move-outs typically runs within 30 days. If it would have flagged enough of them in time, a production version follows within 90.
The cost moves with six things: the size of the portfolio; how many data sources are involved — platform, maintenance, payments, tenant app; whether it covers residential, commercial or both; the renewal workflow and e-signature; the offer pricing module; and the reporting your team needs.
/// FAQ
Frequently Asked Questions
From the signals that usually come before someone leaves — repairs that took too long, changes in how they pay, falling use of the building's services, complaints, and how their rent compares with the market — combined with what happened to similar tenants in the past. The model scores each tenancy and explains which signals are driving the score.
For residential tenancies, typically several months before the lease ends — early enough to fix a problem before a resident starts looking elsewhere. Commercial tenants plan moves much further ahead, so their signals are watched from a year or more before expiry.
It can suggest renewal terms, balancing an increase against the cost of losing the tenant, using your own portfolio data. It does not use pooled, non-public rent data from competitors: algorithmic rent-setting built on shared competitor data has drawn antitrust action in the US, and the final decision stays with your team.
Anything that describes who a tenant is rather than how their tenancy is going. Family status, age and other protected characteristics are excluded, as are proxies for them, because fair housing law in the US and equality law in the UK apply to renewals just as they do to lettings.
Yes, with different signals. For offices and retail, space use, headcount changes, engagement with building services and the lease's break and expiry dates matter more than payment patterns, and the conversation starts much earlier.
First by testing it on last year's renewals and move-outs — how many would it have flagged in time? Then, after launch, by comparing retention where the team acted on the warnings with retention where it did not.
/// RELATED SERVICES
Related Industries and Services
Routes where scope overlaps with real estate software.
/// GET STARTED
Start With Last Year's Move-Outs
Share a year of renewals and move-outs from your portfolio. We will assess, free, how many of the tenants who left could have been flagged in time — and what it would have taken to keep them.