Sales & CRM

How to run a win/loss analysis as Real Estate Founders

Sales & CRMFor Real Estate Founders3 apps11 steps~22 min to set up

You lost three deals in Q1 and you're not sure why. Your broker relationships live in your head, your email threads are in Gmail, your OM follow-up notes are in a spreadsheet you update every few weeks when you remember to, and your pipeline stages are tracked in a HubSpot instance you set up in 2022 and never fully configured. When a deal dies, you do a mental post-mortem and move on. You never actually pull the pattern: which property types are closing, which brokers keep going dark, which pricing objections keep killing term sheets. Without that data surfaced somewhere, you're making the same mistakes in Q2.

Build this on Starch → See the apps used

Sales & CRMFor Real Estate Founders3 apps11 steps~22 min to set up

Outcome

What you'll set up

A CRM that tags every lost deal with a reason, a stage, a broker, and a property type — so you can actually run a query instead of guessing

A recurring win/loss digest that tells you which deal attributes, broker sources, and market conditions correlate with closes vs. drops, emailed to you weekly

A searchable history of every deal conversation — emails, meeting notes, and stage transitions — so you can trace exactly where a deal broke down

The Starch recipe

Apps, data, and prompts

The combination of Starch apps, the data sources they pull from, and the prompts you use to drive them.

Apps used

CRM Growth Analyst Meeting Notes

Data sources & config

Starch syncs your Gmail data on a schedule so deal email threads auto-attach to CRM records by property address or contact. Google Calendar is connected via scheduled sync so meeting context flows into deal timelines. For any broker portals, CoStar deal rooms, or seller data rooms that don't have a direct API, Starch automates them through your browser — no API needed. HubSpot, if you're migrating from it, connects from Starch's integration catalog and the agent queries it live to import your existing pipeline.

Prompts to copy

Build me a CRM for a real estate acquisitions business. Each deal should have fields for property address, asset class (multifamily, industrial, office, retail), source broker, asking price, our offer price, cap rate, stage (sourced, LOI, under contract, closed, dead), and a loss reason field that appears when a deal is marked dead. Loss reason options: pricing, financing, seller went with another buyer, deal quality, passed on diligence. I want to be able to ask 'which brokers sent me the most dead deals in the last 90 days' and get an answer.

Connect my Gmail so every email thread tied to a deal address auto-logs to that deal's timeline. Flag any deal where I haven't had contact in more than 21 days.

Set up a weekly win/loss digest. Every Monday at 7am, pull all deals that moved to closed or dead in the past 30 days. Group them by asset class, loss reason, and broker source. Show me the close rate by asset class, the top three loss reasons this month vs. last month, and which brokers have the highest dead-deal rate. Email it to me.

Run these in Starch → or paste them into your favorite agent

Walkthrough

Step-by-step

1 Start from the Starch CRM app template and describe your deal schema: asset class, source broker, offer vs. ask, cap rate, and a required loss-reason field that activates when a deal is marked dead. Starch builds the schema; you're not configuring a list of dropdowns manually.

2 Connect Gmail via scheduled sync. Starch pulls your message threads and matches them to CRM deals by property address or contact name, building a communication timeline on every record automatically.

3 Import your existing pipeline — from HubSpot, a spreadsheet, or wherever it lives. Connect HubSpot from Starch's integration catalog and the agent queries it live to migrate contacts and deal history, or paste in your CSV and Starch maps the fields.

4 Back-fill loss reasons on any closed or dead deals from the past 12 months. Starch surfaces a queue of deals with blank loss-reason fields; you work through them once so your baseline analysis has real data.

5 Set up meeting notes capture for all broker calls and seller walkthroughs. Starch transcribes in real time and appends a summary, key decisions, and action items directly to the relevant CRM deal record.

6 Connect Google Calendar via scheduled sync so Starch can match calendar events to deal records — every site visit, broker intro call, and investor walkthrough shows up on the deal timeline without manual logging.

7 Ask your first win/loss question: 'Show me all deals that died at LOI stage in the last 6 months, grouped by asset class and loss reason.' Starch queries your CRM and returns the breakdown. No export. No pivot table.

8 Build the weekly win/loss digest automation. Describe it in plain language: every Monday morning, pull deals that moved to closed or dead in the last 30 days, compare close rates by asset class, surface the top loss reasons, and email you the summary. Starch schedules and runs it.

9 Add a broker performance view: 'Create a view that shows every broker I've worked with in the last 12 months, how many deals they sourced, how many closed, how many died, and the most common loss reason for their dead deals.' Use this before you prioritize who to call this week.

10 Set a deal-staleness alert: any deal that has been sitting in the same pipeline stage for more than 30 days without a logged touchpoint triggers a Slack message to you. Starch runs this check daily.

11 After 60 days of data, ask Starch to summarize the pattern: 'Which combination of asset class, price range, and broker source has the highest close rate in my pipeline?' Use this to tighten your sourcing criteria going into next quarter.

See this running on Starch

Connect your tools, describe what you want, and the agent builds it. Closed beta is free.

Try it on Starch →

Worked example

Q1 2026 Deal Review — 14 Deals, 3 Closes

Sample numbers from a real run

Deals sourced (Q1)	14
Deals closed	3
Deals dead — pricing objection	5
Deals dead — seller chose another buyer	3
Deals dead — diligence pass	2
Deals still active	1
Close rate: multifamily	40
Close rate: industrial	11
Avg days sourced-to-LOI on closed deals	18
Avg days sourced-to-LOI on dead deals	34

At the end of Q1, you have 14 deals in your Starch CRM with full loss reasons logged. Your Monday digest surfaces something you hadn't consciously noticed: your three closes were all multifamily in the $3M–$6M range, all sourced by two brokers — David Ramos at Colliers and Priya Mehta at Marcus & Millichap. Your five pricing-objection deaths were all industrial assets over $8M, all sourced through one brokerage you've been treating as a top relationship. The industrial deals took an average of 34 days to reach LOI vs. 18 days for the deals that closed — they were slower from the start. You also see that every deal that died in diligence had no site visit logged in the CRM meeting notes before LOI, which correlates with two corners being cut early. With this in front of you, you deprioritize industrial sourcing this quarter, double down on the two brokers with actual close track records, and add a mandatory pre-LOI site visit as a pipeline gate. None of this required a spreadsheet. You typed a question, read the answer, and made the call.

Measurement

How you'll know it's working

Close rate by asset class (multifamily vs. industrial vs. retail vs. office)

Top 3 loss reasons by volume, tracked month over month

Average days from sourced to dead vs. sourced to closed (deal velocity by outcome)

Broker close rate: deals sourced vs. deals closed per broker relationship

Pipeline stage drop-off: what percentage of deals die at LOI vs. under contract vs. diligence

Comparison

What this replaces

The other ways teams handle this today, and how the Starch version compares.

HubSpot + manual spreadsheet post-mortem

HubSpot tracks your pipeline but has no real estate deal fields out of the box, and the win/loss analysis still lives in a spreadsheet you have to populate manually after the fact.

Salesforce

Salesforce can be configured to do this, but you'll spend weeks on setup or pay a consultant — and it still won't auto-surface patterns; that's a report someone has to build.

Juniper Square

Juniper Square is built for LP and fund reporting, not deal-level win/loss analysis; your pipeline ops and investor comms end up in separate systems anyway.

Airtable CRM template

Airtable gives you flexibility but no AI querying, no email thread sync, and no automated digest — you're still doing the analysis yourself every quarter when you remember to.

On Starch RECOMMENDED

One platform — crm, growth analyst, meeting notes all running on connected data. Setup in plain English; numbers stay current via scheduled syncs and live agent queries.

Try it on Starch →

FAQ

Frequently asked questions

Does Starch store my deal data, or does it just query it live?

For your CRM records and Gmail threads, Starch syncs the data on a schedule and stores it — that's what makes the Monday digest and historical pattern queries possible. For apps you connect from the integration catalog (like HubSpot if you're migrating), the agent queries them live. Starch is not a long-horizon data warehouse, so if you need years of archived analytics with complex custom rollups, that's worth knowing upfront — but for deal-by-deal win/loss tracking over rolling quarters, the scheduled sync handles it well.

What if my deal data is spread across Gmail, a spreadsheet, and an old HubSpot I barely used?

That's the normal starting point. Connect Gmail via scheduled sync and Starch begins pulling thread history. Connect HubSpot from Starch's integration catalog and the agent queries it live to import existing deals. For spreadsheets, paste them in and describe what each column means — Starch maps the fields. You'll want to spend an hour back-filling loss reasons on historical dead deals, but after that the system runs forward on its own.

Can I track LP relationships and investor communications in the same CRM as my deals?

Yes. Describe it when you set up the CRM: 'I want a contact type for LPs, with fields for commitment size, fund, last distribution date, and last communication date. Link LP contacts to the deals they're invested in.' Starch builds that schema. Your deal pipeline and investor comms live in the same system instead of separate tools.

Is Starch SOC 2 certified? My LPs ask about data security.

Starch is not SOC 2 Type II certified today. That's worth knowing if your LPs have formal vendor security requirements. There's no on-prem or self-hosted option either. For most operator-stage real estate businesses this isn't a blocker, but it's honest to name it.

What if a broker uses a deal room or portal that doesn't have an API — like a CoStar deal room or a private seller data room?

Starch automates those through your browser — no API needed. If you can log in and click through it, Starch can navigate it. You'd describe the workflow: 'Go to this deal room URL, download the new documents posted this week, and attach them to the matching CRM deal record.' That's a first-class Starch automation, not a workaround.

Will the weekly digest actually tell me something useful, or is it just a data dump?

You describe what you want to see: close rates by asset class, top loss reasons this month vs. last month, which brokers have the worst dead-deal rate. Starch runs the analysis against your live CRM data and emails you the findings. It's not a pre-built report you can't change — you write the prompt, and if the first version doesn't surface what you care about, you edit it.