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As of 13 August 2026, AI can calculate your average sales cycle length.
Most people should do this themselves; the prompt is on this page.
Can you do it?
5 minutesto a draft.
15 minutesto something you’d act on.
Cost, all in£0
Skill neededchat-fluent
Who has to check ityou
What the alternative costsThe supplied tool information does not state a price for a CRM or analyst alternative.
If this goes wrong: you use an average based on inconsistent dates or incomplete opportunities and make a poor pipeline decision, which you can correct by rerunning the calculation with a defined dataset.
What to actually do
Do it yourself
The route this page recommends
A chat interface, chat-fluent skill, and roughly 15 minutes until you can act on the result.
How to actually do it
- Open your CRM and export the opportunities needed for the period, including an opportunity identifier, the date the opportunity entered your chosen starting stage, the closed-won or closed-lost date, and the current outcome.
- Write down the exact definitions for the start and end dates, such as entry into a qualified stage to closed-won, and decide whether closed-lost opportunities and currently open opportunities belong in the calculation.
- Remove unnecessary contact details from the export, save the remaining table as CSV, and paste it into a chatbot with the prompt above, replacing the bracketed definitions and decisions.
- Ask the model to calculate each included duration and list every excluded row with its reason, then save the response alongside the original export.
- Paste the included start dates and end dates into a spreadsheet, calculate each date difference and the average using the same exclusions, and compare the result with the model's row-level table.
- Share the verified average, median, sample size and definitions with your sales team, clearly labelling the metric as calendar days and noting any excluded or incomplete opportunities.
Prompt
Calculate the average sales cycle length from the CSV or table below. Treat [sales cycle start definition] as the start date and [sales cycle end definition] as the end date, with durations measured in calendar days. Do not invent or repair dates. List rows with missing, contradictory or suspicious dates and exclude them from the main calculation unless I explicitly approve an alternative treatment. Show the duration for every included opportunity, the number of included and excluded opportunities, the arithmetic mean, the median, the shortest and longest cycles, and the exact formula. Also provide a short note explaining how the result would change if closed-lost opportunities were excluded or included. Keep the opportunity identifier with each row, do not expose personal data, and state any assumptions before calculating. Data: [paste CRM export here]
Open it prefilled in ChatGPT or Claude, or copy it into Gemini, which takes no prefill link.
Use a tool built for this
Second choiceHand it to a person
The distant thirdA person who owns the outcome does this end to end, worth it when the failure is dear.
What it gets wrong
- AI cannot decide whether your CRM's created date, qualified date or stage-entry date is the meaningful start of your sales cycle.
- It cannot know whether missing dates reflect bad data, an unusual deal or a process change without your business context.
- It can produce a mathematically correct average from a commercially misleading population if you do not define whether closed-lost and open opportunities are included.
- It cannot replace a consistent CRM data-entry process, so the result remains unreliable when stage changes or close dates are missing.
Even on a YES, the friction has a name: judgement under ambiguity and context depth.
How we scored this
Five axes, each scored nought to two by hand: ten means AI carries the task cleanly, and the thresholds that turn a total into YES, PARTLY or NO are published in the methodology. Each axis name links to its definition.
| Axis | Score (0–2) |
|---|---|
| Output | 2 |
| Inputs | 2 |
| Verification | 2 |
| Liability | 2 |
| Effort delta | 2 |
| Total | 10 / 10 |
The methodology and its thresholds are published in full.
FAQ
- Can ChatGPT calculate my average sales cycle length?
- Yes. Give it a CRM export with a clearly defined start date and end date, and ask it to show every duration, exclusion and formula. Check the result in a spreadsheet before using it for forecasting.
- What data do I need to calculate sales cycle length?
- You need an opportunity identifier, a consistent sales-cycle start date and an end date for each opportunity. You also need to decide how to handle closed-lost, open and incomplete opportunities.
- Should sales cycle length include closed-lost deals?
- That depends on the question you are asking. Include them when measuring the full time spent on opportunities, but calculate a separate closed-won view if you are assessing the time needed to win revenue.
- Can AI calculate sales cycle length from my CRM?
- Yes, if you export the relevant opportunity dates and provide the CRM field definitions. AI can calculate and summarise the metric, but you must check that the export is complete and that the date definitions match your sales process.
Nearby answers
Assessed by gpt-5.6-luna (gpt-5.6-luna) on 2026-08-13, second-checked by an independent model. Wrong somewhere? Email [email protected] and it gets re-checked.
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