Deal stages represent the progression of opportunities through your sales process. Each stage reflects a specific milestone in the buyer's journey and has associated probabilities, automation rules, and conversion metrics. Understanding how stages work is essential for accurate forecasting, effective pipeline management, and optimizing your sales process over time.
Understanding Default Pipeline Stages
SalesSheet.ai's default pipeline includes six carefully designed stages that map to a standard B2B sales process. Here's what each stage represents and when to use it:
- Lead (10% probability): Initial contact or opportunity identification. Use this stage when you first learn about a potential opportunity, whether from inbound interest, cold outreach, or referrals. Deals in this stage haven't been qualified yet.
- Qualified (25% probability): The prospect has been vetted and meets your ideal customer profile. Move deals here after confirming budget, authority, need, and timeline (BANT). The prospect has shown genuine interest and has a legitimate need for your solution.
- Proposal (40% probability): A formal proposal, quote, or pricing has been sent. The prospect is actively evaluating your solution alongside potential alternatives. This is where you differentiate your offering and handle objections.
- Negotiation (60% probability): Active discussions about pricing, terms, implementation timeline, or contract specifics. The decision to buy has largely been made; you're now working through final details. Legal and procurement may be involved.
- Closed Won (100% probability): Deal successfully closed with signed contract and committed revenue. Deals moved here contribute to your won revenue metrics and conversion rate calculations.
- Closed Lost (0% probability): Deal didn't proceed. Could be lost to a competitor, budget cuts, timing issues, or the prospect choosing not to proceed. Tracking loss reasons helps identify patterns and improve win rates.
These probabilities represent the historical likelihood of deals in each stage eventually closing. For example, if 40% of deals that reach the Proposal stage ultimately close, that stage should have a 40% probability.
Moving Deals Between Stages
The simplest way to move a deal is to drag and drop its card from one stage column to another on your pipeline board. When you release the card, it updates immediately and any stage-based automation triggers fire automatically.
You can also move deals using the detail panel. Open any deal and click the stage dropdown in the header, then select the target stage. This method is useful when you're already reviewing deal details and want to update the stage without returning to the board view.
For bulk updates, select multiple deals by holding Shift and clicking on deal cards, then right-click and choose "Move to Stage." This is efficient when you need to progress multiple deals after a team meeting or review session.
The AI can also move deals via natural language commands. Say "Move the Acme deal to Negotiation" or "Update all my deals in Proposal to Negotiation stage." The AI confirms before making bulk changes to prevent accidental updates.
When you move a deal backward in the pipeline (e.g., from Proposal back to Qualified), SalesSheet.ai prompts you to add a note explaining why. This creates accountability and helps track where deals stall or regress in your process.
Configuring Stage Probabilities
Win probability is the percentage likelihood that a deal in this stage will eventually close. These probabilities directly impact your weighted pipeline forecast and expected revenue calculations.
To adjust stage probabilities, go to Pipeline Settings and click on any stage to edit. Update the "Win Probability" field to reflect your actual conversion data. For best results, calculate probabilities based on historical performance rather than gut feeling.
To calculate accurate probabilities, review your closed deals from the past 6-12 months. For each stage, divide the number of deals that reached that stage and eventually closed won by the total number of deals that reached that stage. For example: If 45 deals reached Proposal stage and 18 of those eventually closed won, your Proposal stage probability should be 40% (18 ÷ 45).
Review and update probabilities quarterly as your sales process evolves. SalesSheet.ai's analytics can show you actual conversion rates per stage to help inform these updates. Go to Reports > Pipeline Analysis > Stage Conversion Rates to see this data.
More accurate probabilities lead to better forecasts. If your forecast consistently over- or under-predicts actual revenue, check whether your stage probabilities align with reality.
Setting Up Stage Automation
Automation rules trigger actions when deals enter or exit a stage, ensuring consistent execution of your sales process without manual work.
To create stage automation, navigate to Pipeline Settings > Stages and select the stage you want to automate. Click "Add Automation Rule" and configure triggers and actions.
Common automation patterns include:
- Entering Qualified stage: Create a task to schedule a discovery call, send an internal notification to sales leadership, update deal priority to "Medium"
- Entering Proposal stage: Create a task to follow up in 3 days, send the standard proposal email template, log an activity noting proposal sent date
- Entering Negotiation stage: Notify the sales manager for review, create tasks for legal review and reference calls, add "negotiation" tag to the deal
- Entering Closed Won stage: Create handoff tasks for customer success team, send congratulations email to customer, trigger revenue recognition in finance systems
- Entering Closed Lost stage: Require a loss reason, create a task to request feedback, add contact to nurture campaign for future opportunities
- Time-based rules: Alert if a deal stays in a stage longer than the average duration (e.g., over 14 days in Proposal stage)
Automation ensures no steps are skipped and creates consistency across your team. It's especially valuable for onboarding new reps who may not yet know all the process steps.
Analyzing Stage Performance
Understanding how deals flow through stages helps you identify bottlenecks, optimize conversion rates, and improve forecast accuracy.
Go to Reports > Pipeline Analiticos to view stage performance metrics including:
- Conversion rates: Percentage of deals that progress from one stage to the next
- Average time in stage: How long deals typically spend in each stage before moving forward
- Stage velocity: Speed of progression through your pipeline, measured in days per stage
- Drop-off analysis: Where deals most commonly exit the pipeline without closing
- Stage value distribution: Total deal value currently in each stage of your pipeline
If you notice low conversion rates between specific stages, investigate why. Are qualification criteria too loose? Do proposals fail to address key concerns? Is your pricing not competitive in the Negotiation stage?
If deals spend excessive time in a particular stage, that's a bottleneck. Common causes include waiting for legal approvals, delayed prospect responses, or unclear next steps. Add automation or process improvements to speed up these stages.
Dica Pro: Define Exit Criteria for Each Stage
Create a simple checklist of what must be true before a deal can progress to the next stage. For example, before moving from Qualified to Proposal, confirm: budget discussed, decision-makers identified, timeline established, pain points documented, and competition understood. This prevents premature advancement and maintains pipeline integrity.
O que Esperar
After implementing stage best practices, you should see:
- More accurate sales forecasts as probabilities align with actual conversion rates
- Consistent deal progression as automation ensures critical steps aren't skipped
- Better visibility into pipeline health and potential bottlenecks
- Reduced time spent on manual tasks through stage-triggered automation
- Improved team alignment on what each stage represents and when to advance deals
- Data-driven insights about which stages have the highest drop-off rates
Equipes typically see forecast accuracy improve by 15-25% within 60 days of implementing proper stage management and accurate probabilities.