The fastest rep on a team I work with gets proposals signed in two days on average. The slowest takes twelve. Both are competent sellers with similar territories. The difference is not talent. It is process, timing, and a handful of habits that show up clearly when you measure time-to-sign across the team.
Time-to-sign is one of those metrics that sounds simple but tells you a lot. It measures the gap between when a document is created and when it comes back signed. That gap is full of signal: rep behavior, buyer friction, template quality, deal complexity. When you surface it as a leaderboard, broken down by rep, you turn a hidden variable into a coaching conversation.
This post walks through how to build that report in HubSpot using Portant's Document Object properties, what to do with the data once you have it, and how to use a leaderboard without turning it into something toxic.
Why time-to-sign matters for sales velocity
Sales velocity has four levers: number of deals, average deal size, win rate, and cycle length. Time-to-sign sits inside cycle length, but it is the part most teams ignore because they do not have the data.
Think about where a deal actually spends its time. Early stages are about discovery and qualification. Those are hard to compress because they depend on buyer readiness. Late stages, the period after a proposal or contract goes out, are different. That window is more within your control.
How fast a document gets in front of the right person. Whether it needs revision. How clearly the terms are presented. Whether the buyer has a reason to sign today or next month. All of that affects time-to-sign.
When time-to-sign is short, deals close faster, forecast accuracy improves, and pipeline does not age in late stages where it gives everyone false confidence. When time-to-sign is long, you get stale deals clogging the bottom of the pipeline, reps spending energy following up on documents that should have been signed a week ago, and revenue slipping from one quarter to the next.
I have seen teams cut their average time-to-sign by 40% just by making it visible. No new tools, no new process. Visibility alone changed behavior because reps started asking, "What is that person doing differently?"
What time-to-sign actually measures
Time-to-sign is the duration between when a document is created and when its status changes to signed. In Portant, that maps to two properties on the Document Object in HubSpot:
- Document Created: the timestamp when Portant generated the document
- Document Status: the current state of the document, which updates to "Signed" when a signature is completed
The calculation is straightforward. For any document where Document Status equals Signed, subtract the Document Created timestamp from the Signed timestamp. The result is your time-to-sign for that document.
When you aggregate across documents, you get averages per rep, per template, per deal stage, or per deal size. That is where the interesting patterns appear.
A third property worth knowing is Portant Workflow Name. This tells you which template or workflow generated the document. It becomes important when you want to compare performance across different proposal formats or contract types.
If you have not set up Portant's Document Object in HubSpot yet, the guide to viewing created documents in HubSpot walks through the setup. Once documents exist as their own records inside HubSpot, every report I describe here becomes available through standard HubSpot reporting.
How to set up a time-to-sign report in HubSpot
Here is the step-by-step setup I use with the teams I work with.
Step 1: Create a custom report using Deal properties
Go to Reports, then Create report, then Custom report builder. Choose Deals as your primary data source, then add Document Object as a secondary source. This gives you access to both deal-level fields (owner, amount, stage) and document-level fields (created date, status, workflow name).
Step 2: Filter for signed documents
Add a filter where Document Status equals Signed. This excludes drafts, documents that were sent but not yet signed, and anything that was voided or expired. You only want completed signatures in this report.
Step 3: Calculate the duration
HubSpot's custom report builder lets you create calculated fields. Create a field that calculates the difference between the Document Created timestamp and the date when Document Status changed to Signed.
If your HubSpot tier supports calculated properties, you can also create a deal-level property that holds this value for use in other reports. For teams on Professional where calculated fields are more limited, you can approximate by using the Document Created date as start and filtering by the date range when status changed. The exact method depends on your HubSpot subscription, but the data lives in the same place either way.
Step 4: Break it down by Deal Owner
Set Deal Owner as your row or group dimension. This gives you one row per rep, with their average time-to-sign across all signed documents. Sort ascending to see your fastest signers at the top. That is your leaderboard.
Step 5: Add a second dimension for deeper analysis
This is optional but useful. Add Portant Workflow Name as a second dimension to see which templates get signed fastest. Or add Deal Amount as a range to see whether larger deals take longer (they usually do, but not always by as much as you would expect).
You can also break it down by deal stage at the time of document creation. This tells you whether proposals sent from an earlier stage get signed faster or slower than those sent later, which is a signal about buyer readiness and timing.
Breaking down the data: what to look for
Once the report is running, here are the dimensions I review with ops teams.
By rep
This is the core leaderboard view. When one rep averages two days and another averages twelve, the question is not "who is better?" The question is "what is different?"
Maybe the fast rep sends documents at the end of a live call while both parties are still engaged. Maybe the slow rep batches document creation to Friday afternoons and buyers do not look until Monday. Maybe one rep always includes a clear next step in the email and the other sends a bare link.
The point of the rep breakdown is not ranking. It is pattern recognition.
By template
Use the Portant Workflow Name property to compare templates. If your standard proposal gets signed in three days on average but your enterprise agreement takes nine, that might be expected. But if two proposal templates aimed at the same buyer segment show very different time-to-sign numbers, the slower template probably has a formatting, length, or clarity problem.
This is useful data when you are deciding whether to update, consolidate, or retire a template. Time-to-sign tells you which formats buyers respond to fastest.
By deal size
Larger deals generally take longer to sign because more stakeholders are involved and legal review is more thorough. But the relationship is not always linear. I have seen mid-market deals take longer than enterprise because the mid-market buyer has no procurement process and the document sits in someone's inbox until they remember to read it.
Breaking it down by deal amount range (for example, under $10k, $10k to $50k, over $50k) gives you benchmarks for what "normal" looks like at each tier. Without those benchmarks, you cannot tell whether a rep's slow average is a coaching issue or a deal-mix issue.
By deal stage
If you track which stage a deal was in when the document was created, you can see whether timing affects signature speed. Documents sent during a verbal commitment stage, when the buyer has already said yes, should get signed faster than documents sent during evaluation, when the buyer is still comparing options.
If that pattern does not hold, your stage definitions might need attention. Or reps might be sending contracts before the buyer is actually ready, which creates a long wait that looks like a signature problem but is really a qualification problem.
Coaching from the data without creating toxic competition
A leaderboard works when it drives curiosity. It stops working when it drives anxiety or blame.
Here is how I recommend using the data. Share it in a team setting, but frame it as a learning exercise, not a performance review. Ask the top performers to explain what they do differently. Often the answers are simple and tactical: they preview the document on the call before sending, they include a one-line summary of what the buyer agreed to, they set a follow-up task for the next business day.
Do not attach compensation or public rankings to time-to-sign without context. A rep who handles complex multi-party deals will naturally have a longer average than a rep who sells single-signer renewals. Comparing them on the same axis punishes the wrong behavior.
Instead, compare within cohorts. Group by deal type, deal size, or region, then look at relative performance within those groups. That way you are comparing like with like.
The goal is for every rep to learn from the best habits in the room, not for the slowest rep to feel singled out.
When long time-to-sign is acceptable
Not every long time-to-sign is a problem. Here are situations where I expect the number to be higher and do not push for improvement.
Complex multi-party deals. When a contract needs signatures from multiple stakeholders across different companies, each party adds time. A five-day average for a three-party agreement is fast, not slow.
Enterprise procurement. Large organizations have legal review cycles, procurement queues, and approval chains that are outside your rep's control. Tracking time-to-sign still matters here, but the benchmark should be set against similar enterprise deals, not the team average.
Custom scope or pricing. If the document is a first draft that both sides expect to negotiate, the clock starts ticking on a process, not on a yes-or-no decision. These deals should still be tracked, but separately from standard template sends where the buyer just needs to read and sign.
Seasonal or budget-driven timing. Some buyers cannot sign until a budget cycle resets or a fiscal year begins. Time-to-sign in these cases reflects buyer constraints, not rep performance.
The right response to long time-to-sign is segmentation. Separate the deals where speed is within your control from the deals where it is not, then focus coaching energy on the first group.
Connecting time-to-sign to revenue and forecast accuracy
Time-to-sign directly affects two things leadership cares about: when revenue shows up and how reliable the forecast is.
Revenue timing is straightforward. Every day a document sits unsigned is a day revenue is delayed. For subscription models, that delay compounds because the start date shifts and the first renewal pushes further out. For project-based revenue, unsigned contracts delay kickoff, which delays billing milestones.
Forecast accuracy is more subtle. When deals sit in "contract sent" for weeks, they inflate the pipeline. Sales leaders see a full late-stage pipeline and forecast optimistically. But if the average time-to-sign for those deals is trending upward, the pipeline is aging, not progressing. Tracking time-to-sign lets you adjust the forecast by discounting deals where the document has been out longer than your benchmark without buyer engagement.
Some teams I work with add a simple rule: if a document has been out for more than 2x the average time-to-sign for that deal type and there is no buyer activity, the deal gets flagged for review. That flag does not mean the deal is dead. It means someone needs to have an honest conversation about where it actually stands.
Putting it together
The time-to-sign leaderboard is not a vanity metric. It is a window into how your team closes, which templates work, where buyers hesitate, and whether your forecast reflects reality.
The setup takes an afternoon. Create the report in HubSpot using Portant's Document Object properties, break it down by rep and template, and share it with the team. Then let the data start the conversation.
If you are using Portant with HubSpot, the Document Created and Document Status properties are already on every document record. If you are not using Portant yet, the HubSpot integration is where to start. Portant is the number one HubSpot-certified document automation app, with 920,000+ users and 5.1M+ documents automated. Every document becomes its own record in HubSpot, which is what makes reports like this possible in the first place.
Start building your first workflow and you will have the data for a time-to-sign leaderboard within a week.
Frequently asked questions
What HubSpot tier do I need for this report?
You need at least HubSpot Professional to use the custom report builder with multiple data sources. If you are on Starter, you can still track time-to-sign manually using the document timeline on individual deals, but the aggregated leaderboard report requires Professional or Enterprise.
Can I track time-to-sign for documents that were not signed?
Yes, and you should. Documents that were sent but never signed tell you about drop-off, not speed. I recommend a separate report that filters for Document Status not equal to Signed and shows how long those documents have been outstanding. That report surfaces stale deals and templates with low completion rates.
How often should I review the leaderboard?
Monthly is a good rhythm for most teams. Weekly can feel like surveillance. Quarterly is too slow to catch trends. Monthly gives you enough data points to see patterns without making reps feel micromanaged.
What if my team is small and the leaderboard only has two or three people?
The leaderboard still works, but the value shifts from rep comparison to trend analysis. Track each person's time-to-sign over time and look for changes month over month. If someone's average suddenly doubles, that is a conversation worth having, even in a small team.
