Sales & CRM

How to run a win/loss analysis as Chief of Staff and Founder's Office

Sales & CRMFor Chief of Staff and Founder's Office3 apps12 steps~24 min to set up

You're the person who gets asked 'why did we lose that deal?' and has to spend three hours reverse-engineering an answer from HubSpot close reasons (which reps fill out inconsistently), scattered Slack threads, Gmail chains, and whatever notes ended up in Notion — if anyone wrote notes at all. Win/loss analysis is one of those strategic priorities that always gets bumped for whatever is on fire today. When you do find time, you're exporting CSVs, cross-referencing deal stages in HubSpot against QuickBooks invoices, and trying to remember which calls happened around each decision. The CEO wants a clean story for the board. You have a mess.

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Sales & CRMFor Chief of Staff and Founder's Office3 apps12 steps~24 min to set up

Outcome

What you'll set up

A live win/loss dashboard that pulls closed deals from HubSpot, surfaces close-reason patterns, and groups losses by competitor, deal size, and sales stage — no manual exports

An automated analysis that cross-references deal outcomes with email thread history and meeting notes, so you can see what actually happened in lost deals, not just what the rep checked in a dropdown

A recurring digest that sends you a structured win/loss summary every month before your board or leadership meeting, so you're not rebuilding it from scratch each time

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

Sales Agent CRM CRM Growth Analyst

Data sources & config

Starch syncs your HubSpot data on a schedule — contacts, companies, deals, and owners come in automatically, so your win/loss dashboard is always current. Starch also syncs your Gmail on a schedule, so email thread context is available alongside deal records without manual linking. Apollo.io can be connected from Starch's integration catalog if you want to enrich lost accounts with firmographic data; the agent queries it live when the analysis runs. If you track competitor intel in Notion, Starch syncs your Notion pages on a schedule and can surface that context inside the same workflow.

Prompts to copy

Build me a win/loss analysis dashboard using our HubSpot deal data. I want to see all deals closed in the last 90 days, broken down by won vs lost, with columns for deal size, close reason, sales cycle length, industry, and the rep who owned it. Group the losses by close reason and show me which segments we lose most often.

For each lost deal in the last quarter where deal size was over $25k, pull the Gmail thread history and summarize what happened — specifically what objections came up and at what stage the deal stalled. Organize these by the close reason the rep logged.

Set up a monthly automation: on the first Monday of each month, pull all deals closed in the prior month from HubSpot, calculate our win rate by deal size tier and industry vertical, and email me a structured summary with the top 3 loss patterns and which competitors appeared in the notes.

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

Walkthrough

Step-by-step

1 Connect HubSpot — Starch syncs your deals, contacts, companies, and owners on a schedule. Your 90-day closed-deal history is available immediately; no export required.

2 Connect Gmail — Starch syncs your messages on a schedule so email threads tied to lost deals are queryable. This is where the real loss context lives, not the dropdown the rep filled out.

3 Open the Sales Agent CRM app as your starting point. Fork it and tell Starch: 'Reshape this for win/loss analysis — I don't need the pipeline view, I need a closed-deal table with win/loss outcome, close reason, deal size, sales cycle length, and rep name.'

4 Add a win/loss breakdown panel. Tell Starch: 'Add a section that groups lost deals by close reason and shows count and total ACV for each group, for any date range I select.'

5 Layer in email context. Tell Starch: 'For each deal in the table, let me click into it and see a summary of the Gmail thread — key objections, who was in the conversation, and what the last outbound message said before the deal went cold.'

6 Identify competitor patterns. Tell Starch: 'Scan the Gmail threads and deal notes for any mention of competitor names. Pull out which competitors appear most often in lost deals and at what deal size.' This is the kind of cross-reference that used to take you an afternoon.

7 Segment by deal size and vertical. Tell Starch: 'Break win rate down by deal size tier ($0-10k, $10k-50k, $50k+) and by the industry field in HubSpot. Show me where our win rate drops and where we're strongest.'

8 If you want firmographic enrichment on lost accounts, connect Apollo.io from Starch's integration catalog. Tell Starch: 'For lost deals in the last quarter, pull the employee count and funding stage for each company from Apollo and add those columns to my dashboard.'

9 Build the recurring digest. Tell Starch: 'Every first Monday of the month, pull all deals closed in the prior month, calculate win rate by tier and vertical, identify the top 3 close-reason patterns for losses, and email me a structured summary with those numbers plus any new competitor mentions.'

10 Add a deal narrative generator for board prep. Tell Starch: 'When I'm preparing for a board meeting, let me select a date range and generate a two-paragraph win/loss narrative I can drop into the board deck — overall win rate, biggest loss pattern, and one specific deal example that illustrates the trend.'

11 Share with your VP of Sales or revenue lead. Tell Starch: 'Create a view of this dashboard I can share with our VP of Sales that shows only their team's deals and removes the email thread detail.' You stay in control of what's visible.

12 Set a quarterly reminder to review close-reason taxonomy in HubSpot. Win/loss analysis is only as good as the data reps log — this dashboard will make the gaps obvious, which gives you the evidence to push for cleaner hygiene.

See this running on Starch

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

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Worked example

Q1 2026 Win/Loss Review — 150-person SaaS company, 3 AEs

Sample numbers from a real run

Deals closed Q1 (total)	47
Deals won	19
Deals lost	28
Win rate (overall)	40
Win rate, deals under $15k ACV	61
Win rate, deals over $40k ACV	22
Lost deals citing 'price' as close reason	11
Lost deals where competitor mentioned in Gmail thread	9
Avg sales cycle, won deals (days)	34
Avg sales cycle, lost deals (days)	51

When the CoS ran this analysis heading into the Q1 board meeting, the headline number — 40% win rate — wasn't the story. The story was in the segmentation. Deals under $15k ACV were closing at 61%, which looked fine. But deals over $40k ACV were winning at only 22%, and the average sales cycle on those losses was 51 days versus 34 days on wins. That gap had never been visible because no one had sliced it that way. The Gmail thread analysis added the second layer: of the 9 lost deals where a competitor appeared in the email history, 7 of them involved the same vendor — one that had apparently launched a new mid-market tier in January. The rep close-reason field said 'price' on 6 of those 9, which was technically true but missed the actual dynamic. The CoS walked into the board meeting with a two-paragraph narrative, the segmentation table, and a specific recommendation: stop sending AEs solo into $40k+ deals without a solutions engineer on the second call. That recommendation came from reading 9 Gmail threads. Previously, building that answer would have taken most of a day. The Starch dashboard surfaced it in 20 minutes.

Measurement

How you'll know it's working

Win rate by deal size tier (e.g., sub-$15k vs $15k-$40k vs $40k+) — because overall win rate hides where you're actually losing

Average sales cycle length, won vs lost — a widening gap signals where deals are getting stuck

Loss reason distribution by ACV — tells you whether price sensitivity is real or a cover story for something else

Competitor appearance rate in lost deals — how often a named competitor shows up in email threads or notes in a given quarter

Close-reason data completeness rate — what percentage of lost deals have a logged close reason at all; below 80% means your analysis is built on a partial dataset

Comparison

What this replaces

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

Manual HubSpot export + Google Sheets

You can build most of this in Sheets if you have a few hours and a clean HubSpot dataset — you almost certainly don't have either, and it's a one-time snapshot rather than a live view you can run again before the next board meeting

Gong or Chorus (conversation intelligence)

Best-in-class for call analysis and deal coaching, but requires reps to record every call and costs $100+ per seat per month — doesn't help when your loss context lives in email threads rather than calls

Clari or Bowtie (revenue analytics)

Powerful for pipeline forecasting and funnel analytics at scale, but priced for 20+ person revenue teams and requires significant RevOps setup time that typically lands on you

Asking your VP of Sales for a readout

Free, but you'll get whatever narrative confirms their priors; the email thread analysis Starch can run is the check on that narrative, not a replacement for the conversation

On Starch RECOMMENDED

One platform — sales agent crm, crm, growth analyst 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

Our reps fill out close reasons inconsistently — will the analysis still be useful?

Yes, and it will make the inconsistency visible. The Gmail thread analysis works independently of what the rep logged — Starch summarizes what actually happened in the conversation regardless of the dropdown value. When you see 'price' logged 11 times but 9 of those threads mention a specific competitor, you have evidence for a coaching conversation with your VP of Sales. The dashboard will also show you what percentage of lost deals have any close reason logged at all, which is usually the first uncomfortable number.

Does Starch store our deal and email data, or is this just queried live?

HubSpot and Gmail are both scheduled-sync connections — Starch syncs the data on a schedule and stores it in your Starch workspace. This is what makes the cross-referencing possible: the agent can join deal records with email threads without hitting API rate limits mid-query. Starch is not SOC 2 Type II certified today, which is worth knowing if your security team asks.

Can I include Salesforce data instead of HubSpot?

Salesforce is available from Starch's integration catalog — connect it and the agent queries it live when your win/loss dashboard runs. It won't be a scheduled sync the way HubSpot is, so very large deal histories may take a moment to load, but for a quarterly win/loss review the query is typically fast enough to be practical.

How does this handle deals that were worked by multiple reps or had rep turnover?

HubSpot tracks deal owners and you can pull the full owner history as a field. Tell Starch to include owner changes as a column — deals with mid-cycle rep changes are worth flagging separately since they often skew your sales cycle data and may reflect internal process issues rather than external competitive dynamics.

Can I share this dashboard with the CEO or board without giving them access to all the underlying email threads?

Yes. Tell Starch to build a board-facing view that shows only the aggregated metrics and the narrative summary — win rate by segment, loss reason distribution, competitor frequency — without the deal-level email detail. You control what each view surfaces. The email thread analysis can stay in your working view while the CEO gets the clean version.

What about deals that were lost before we started using this — can I run historical analysis?

HubSpot's scheduled sync pulls your existing deal history, not just new deals going forward. Gmail syncs 30 messages per page from existing threads. For deals closed more than a year ago, email threads may be incomplete if messages were archived or deleted, but the HubSpot deal data itself should be available for any deal in your CRM history.