# How to find out why your deals stall or get lost

> Find the real reasons deals stall or get lost from your calls, emails and Slack, not the closed-lost dropdown. Day AI does it in place of your CRM or on top of Salesforce or HubSpot.

Updated October 29, 2026

**The short answer.** To find out why your deals stall or get lost, read the deals themselves: the calls, emails and Slack threads across each whole deal, not the loss-reason dropdown a rep fills in after the fact. Day AI does this for revenue teams in place of their CRM, or on top of Salesforce or HubSpot: you describe a property like Loss reason or Stall risk, and an agent fills it for every deal from your conversations. You can ask the agent to backfill it across the deals already in Day AI, and every value shows what it was derived from.

Say you're a new AE at an audit-software company, and it's 8:40 on a Monday. You've just inherited a set of accounts, and one deal hasn't moved stage in weeks. You open it in Day AI, and the whole deal is there. After every recorded call, Day AI proposed MEDDPICC score updates from the whole deal's context, the rep before you approved them, and they were written to HubSpot. The people from each call are attached to this deal, not a neighboring one. So the gap is plain: the Economic Buyer score shows that nobody who signs has been on a call. On your first call with the buyer, you ask who else needs to be in the room. When it ends, Day AI proposes updated scores from the whole deal again, and you approve them in seconds. The team's old home-built workflow saw only one call at a time and sometimes picked the wrong deal. This one told you why the deal stalled before you said hello.

**Where the usual answer goes wrong.** Most advice tells you to add a closed-lost reason field, make it required and review the report each quarter. That's the step that fails: the field is filled by the person with the least reason to be candid, after the deal is over, from a list that can't hold more than one cause. The conversations are the record, and the reasons a deal stalls are in them weeks before anyone marks it lost. You may already have the pieces: call recordings, a loss-reason field, a quarterly win-loss review. That was the right start. Day AI reads the deals for you, so the field is filled from what was said. Day AI provides the context graph and agent control plane to quickly and securely upgrade your company brain.

## The Read-the-Deal method, with Day AI

The method has five steps. The first two decide what you're looking for and where the evidence lives. The next two catch stalls while the deal is open and losses the moment they happen. The last one turns single deals into patterns you can act on. Day AI does the reading at every step, and a person decides what to do about it.

1. **Name the reasons you want to see.** A short list of loss reasons and stall signals, written down once. In Day AI, each one is a property you describe in plain words.
2. **Read the whole deal.** Every call, email and Slack thread on the deal, from the first meeting on. In Day AI, the agent fills each property from all of them, and you can ask it to backfill across the deals already in Day AI, including ones you lost before you started.
3. **Check open deals for stalls every week.** Look for the signs while a rep can still act. In Day AI, a skill on a schedule does the check and sends each owner what it found.
4. **Write the loss record when the deal is lost.** Not a dropdown, a short account with evidence. In Day AI, a skill runs when a deal moves to closed-lost and writes it.
5. **Compare across deals.** Group lost and stalled deals by reason, read the evidence behind each group, and pick one fix. In Day AI, you ask the agent in chat or save a view of deals by reason.

## How to find out why deals stall or get lost with Day AI

Everything below happens in Day AI, whether you run it as your CRM or keep Salesforce or HubSpot. When you keep them, Day AI syncs with Salesforce or HubSpot through their MCP servers, which allow reads and writes when the write tools are turned on, so the reasons your agent fills can be written back to the deal in your CRM.

### Step 1: Connect your conversations to Day AI

The reasons are only as good as what the agent can read. Each rep connects Gmail and Google Calendar, and Day AI's notetaker records meetings and adds them to the record when they end. If your calls are in Gong, connect it and your call history comes in with transcripts; Granola connects with transcripts and notes. Add the Day AI app to the Slack channels where deals get discussed. Each person sets sharing rules for their email, and an agent sees only what the person it works for can see.

If you keep Salesforce or HubSpot, connect its MCP server in Day AI and allow the write tools so the agent can update fields on the deal. Each person connects with their own login. In the connector's settings, set each write tool to Always allow, Needs approval or Off. With Needs approval, Day AI asks in the conversation before each write, so a person approves every change before it reaches the deal in your CRM.

### Step 2: Describe your loss reasons and stall signals as Day AI properties

Ask your agent in Day AI chat to create a property on deals, or create it yourself. Make Loss reason a picklist with the options you want to compare, such as no decision-maker engaged, lost to a competitor, no budget, timing, or a gap in the product. Then describe how to choose each one in plain words, and how to tell when there isn't enough evidence to choose. Add a second property for the competitor named on the deal, and a text property for Stall risk that names the specific thing holding the deal up.

Day AI fills these from the deal's emails, meetings and Slack. You can ask the agent to backfill them across the deals already in Day AI, so deals you lost before you set them up get a reason too; check a few before you rely on them. Every value shows its sources, and you can ask the agent what changed and why. When a rep disagrees with a value, they can see what the agent read and change it.

### Step 3: Turn on a weekly stall check in Day AI

Give your agent a skill that runs every Monday morning on a schedule in your timezone. Tell it what a stall looks like for your team: the buyer hasn't replied in two weeks, no next step was agreed on the last call, nobody who signs has joined a call, a competitor came up and was never addressed, or the deal has sat in its stage much longer than your other deals. It reads each open deal's conversations and sends each owner the deals that match, by email or Slack, with the message or call behind each flag.

You can also ask the agent in chat at any time which stages deals sit in longest and which open deals look stalled. It answers from your pipeline, with win and loss rates, stage conversion and how long deals spend in each stage.

### Step 4: Turn on a closed-lost write-up in Day AI

Add a skill that runs when an opportunity changes stage, and limit it to your closed-lost stage. When a deal is marked lost, the agent reads its calls, emails and Slack threads and writes a short account: what the buyer said they needed, where the deal slowed, who was never in the room, and what it thinks decided it. Every point cites its source. It sends the write-up to the deal owner and their manager.

Start the skill in learning mode if you want to see a few write-ups before it acts. Reply to one with what to change ("always say which stage it stalled in"), and the agent edits the skill so later runs follow it.

### Step 5: Compare across deals in Day AI

Once the properties are filled, look across deals. Ask your agent in Day AI chat questions like "Across the deals we lost this quarter, what did buyers say about price, and what else came up on those calls?" The answer cites the calls and emails it came from, so you can open the clip and hear it. Save a view of lost deals grouped by Loss reason, and a view of open deals with Stall risk filled in, and share them with the team.

Then choose one fix per quarter and give it an owner. If "no decision-maker engaged" leads, the fix is in discovery, not pricing. Change the stall check to watch for that sign earlier, and the next quarter's view shows whether it worked.

## A 30-day rollout with Day AI

### Week 1: Connect sources and describe the properties in Day AI

Connect email, calendar, the notetaker or Gong, and the Slack channels where deals are discussed. Create Loss reason, Competitor and Stall risk, then ask the agent to backfill them across the deals already in Day AI.

### Week 2: Check Day AI's backfill against what your team remembers

Pick ten lost deals your managers know well. Open each Loss reason value in Day AI, read what it cites, and adjust the property descriptions where the agent chose wrong. When the agent chose wrong, the description usually needs a sharper rule for that option.

### Week 3: Turn on the stall check and the closed-lost write-up in Day AI

Start both skills, the closed-lost one in learning mode. Reps and managers reply to the output with what to change.

### Week 4: Run your first review from Day AI

Run the pipeline review from the saved views and the agent's answers in chat. Leave with one fix and one owner, and add the sign you're fixing to next week's stall check.

## Where the usual way breaks

- **The dropdown holds one guess.** Reps pick the safest option after the deal is over, and "price" is the safest of all. In Clozd's study of 1,000 closed-lost deals, the CRM reason matched what buyers said only [15% of the time](https://clozd.com/blog/5-lies-your-crm-is-telling-you-about-your-buyers). In Day AI, the reason is filled from what was said on the deal, and the value shows what it was derived from.
- **Loss reviews happen after it's too late.** A quarterly review explains deals you can no longer save. In Day AI, the weekly stall check reaches the owner while the deal is still open.
- **A call-by-call summary misses the deal.** A workflow that reads one call at a time can't see that the decision-maker never showed up across six of them, and can file its notes on the wrong deal. In Day AI, every property is filled from the whole deal's history.
- **Interviews cover a handful of deals.** Buyer interviews are the best evidence you can get, and most teams can run only a few each quarter. In Day AI, every deal gets read, and recorded interviews join the same record.
- **New reasons start empty.** Add a field for a new competitor today and every past deal is blank until someone types it in. In Day AI, you can ask the agent to backfill a new property across the deals already in Day AI.

## Frequently asked questions

### How do I find out why our deals stall or get lost?

Read the deals, not the dropdown. Write down the reasons you want to track, have each one filled from every call, email and Slack thread on the deal since the first meeting, check open deals for stalls every week, and write a loss record the moment a deal is marked lost. Then compare across deals and trace every pattern back to the conversation it came from. In Day AI, you describe properties like Loss reason and Stall risk, and an agent fills them for every deal from your conversations as they happen. You can ask the agent to backfill them across the deals already in Day AI, and every value shows the conversations it was derived from.

### Why are the closed-lost reasons in our CRM wrong?

Because the rep who lost the deal picks one option from a list after the fact, and buyers rarely tell reps the whole story. In Clozd's study of 1,000 closed-lost deals, the CRM reason matched what buyers said in interviews only 15% of the time. A single dropdown also can't hold the four or five things that usually add up to a loss. Day AI fills the loss reason from what was said on the deal's calls and emails and shows what it was derived from.

### How can I tell a deal is stalling before it's lost?

Look for the signs in the conversations: no reply from the buyer, no next step agreed on the last call, a decision-maker who has never joined, a competitor mentioned and never answered, and a deal that has sat in one stage far longer than your others. Check every open deal for them each week, including the ones nobody has raised. Day AI can run that check as a skill on a schedule and send each owner the deals that need a move, with the conversation behind each flag.

### Can Day AI tell me why we lost a deal?

Yes. Turn on a skill that runs when a deal moves to closed-lost, and the agent reads that deal's calls, emails and Slack threads and writes up what happened, citing the call clip or message for each point. Add a Loss reason property and it is filled as deals move, and you can ask the agent to backfill it across the deals already in Day AI, including the ones you lost before you set it up. You can then ask your agent in chat what your lost deals have in common.

### Should we still run win-loss interviews with buyers?

Yes, when you can. Buyers say things after a decision that they won't tell a rep during it, and an interview is the best way to hear them. Most teams can only interview a handful of deals, though, so read every deal's conversations as well. If you record the interview with Day AI's notetaker, it joins the same record the agent reads for every other deal.

### What is Day AI?

Day AI is the customer memory and agent platform for go-to-market teams. Even the best CRM only holds a fraction of what actually happened with your customers. Day AI is what comes after CRM. It builds a self-updating customer record from every meeting, email, and call, and runs governed agents that create finished work on top of it, with every fact and every action traced to source conversations. It does everything teams use a CRM for, without the data entry, and does what a CRM never could. Agents prospect, prep every meeting, draft follow-ups, keep the pipeline clean, and much more, giving every rep added selling capacity that used to require hiring additional people. It runs in place of Salesforce or HubSpot or as a layer on top of them.

Researched and drafted with Day AI's own agents, reviewed by the Day AI team.

Canonical: https://day.ai/guides/find-out-why-deals-stall-or-get-lost