Hype Cycle Stage Calculator
The formula
What the hype-cycle stage tells you
A rule-based reading of Gartner's five-phase curve from three signals: attention growth, real adoption, and the gap between buzz and demonstrated viability.
Calculation: Rule-based mapping of interest, adoption and evidence onto Gartner's five phases. Enter your inputs and every substitution is shown below the result.
Reading the result
The expectation-vs-evidence gap is the cycle's engine — the peak is where the gap is largest, and the trough where reality has caught up.
Rules of thumb: Typical cycle: peak to trough in 12–24 months; trough to plateau 5–10 years
Limitations and best practice
Any single score can be gamed by a press cycle; use the phase as a discussion frame, never a trade trigger.
This calculator gives an estimate based on standard formulas; it is not professional financial, medical, legal or engineering advice. Verify anything you plan to act on with a qualified professional and your own records.
Frequently asked questions
Do all technologies finish the curve?
Can the trough be a buy signal?
Source & methodology
Gartner Hype Cycle methodology.
Hype Cycle Stage: what this tool answers
You are counting something that matters — this tool counts it exactly, including the edge cases calendars hide. Searchers land on a Hype Cycle Stage page for three reasons — to plan, to compare options, and to check that somebody else’s arithmetic is honest. This tool serves all three, and everything after the calculator explains the model instead of hiding it.
A calculation like this one is worth roughly as much as a careful sentence: it forces several vague considerations into one comparable quantity. Once Hype Cycle Stage is on the table, the argument can stop being about impressions.
Like most useful measures, Hype Cycle Stage is a summary, and summaries hide as much as they reveal. The companion outputs and the input table are here to reopen what the headline compressed.
Nothing below is stock text pasted around a number: the worked example computes likely cycle phase = Peak of Inflated Expectations from this tool’s own defaults. Read the sections in order and you will be able to reproduce every figure by hand.
How Hype Cycle Stage is computed, line by line
The engine implements a single stated model: Rule-based mapping of interest, adoption and evidence onto Gartner's five phases. There is no hidden coefficient and no login-gated precision — the formula printed is the formula executed, which is also what makes the result citable.
Interest growth rate (%) (example value 180) is a numeric input whose unit is fixed by the label; a wrong unit is a wrong answer wearing a plausible disguise. Rates are the most mis-transcribed input on any page like this; copy it from the document rather than retyping from memory.
Market adoption (%) (example value 2) is a measured number in the unit named by the label; the formula does not convert for you. Check the convention first: if the source says “6.5 % per year”, type 6.5 and let the formula do the rest.
Media buzz score (1–10) (example value 9) is a quantity rather than a category — precision here is cheap and worth having. Replace the example with the figure from your own records — the tool recomputes instantly and the printed steps follow your numbers.
Product viability score (1–10) (example value 4) is a plain measured quantity — the unit shown in the label is the unit the formula expects. This input feeds the formula directly; a defensible figure here is worth more than false precision anywhere else.
Hype Cycle Stage on the example inputs: the complete substitution
Rather than describe the calculation, here it is end to end — every substitution in order, starting from the inputs above. Starting figures: Interest growth rate (%), Market adoption (%), Media buzz score (1–10), Product viability score (1–10). The computed likely cycle phase comes out at Peak of Inflated Expectations, which the interpretation band labels “Maximum buzz, thin delivered product — the correction zone”.
- Compare hype 9 against viability 4 with adoption at 2% and interest growth 180%
- Mapping lands on Peak of Inflated Expectations
Expectation-vs-evidence gap — 5.0. If your inputs change, this is usually the first companion figure to move.
Adoption maturity — 2.0 %. Read next to the headline, this is the figure that shows the shape of the trade-off.
Interest momentum — 180.0 %. If your inputs change, this is usually the first companion figure to move.
Overwrite any input above and every line of this example updates with it — the substitution is live, not a screenshot of somebody else’s numbers.
Interpreting the Hype Cycle Stage verdict
Nobody acts on a bare figure — they act on a figure with a comparison attached. The default case lands in the “Maximum buzz, thin delivered product — the correction zone” band, and bands are deliberately wide because real situations overlap. The practical reading rules: ask what would have to change to move you one band. If the answer is “a small, plausible input difference”, the band itself is not the finding — the uncertainty is.
In Business & Entrepreneurship, Hype Cycle Stage is one instrument in an orchestra: on its own it is a number, next to Expectation-vs-evidence gap and Adoption maturity it becomes a diagnosis. The tools linked above exist so the headline never has to carry that weight alone.
Common mistakes with Hype Cycle Stage (and the fix)
Any single score can be gamed by a press cycle; use the phase as a discussion frame, never a trade trigger. This calculator gives an estimate based on standard formulas; it is not professional financial, medical, legal or engineering advice. Verify anything you plan to act on with a qualified professional and your own records.
Reusing a Hype Cycle Stage from last season. In Business & Entrepreneurship the inputs are the thing that drifts; the formula does not.
The subtlest error is answering the wrong question precisely. Confirm that likely cycle phase is actually the quantity your decision needs — the arithmetic is flawless either way, which is what makes the mistake invisible.
A quick check for any Hype Cycle Stage figure
- Confirm the example values are plausible for your own situation before replacing them.
- State, in one sentence, which convention each rate, unit or period in the form is using.
- Confirm the inputs are dated — a Hype Cycle Stage figure should carry the date it was computed.
- Recompute once with the dominant input deliberately set low, and see whether the decision changes.
- Record the date and the inputs alongside the number so future-you knows what was assumed.
- Run the ±10 % stress on the top two levers and check that your conclusion survives both.
Five steps from raw inputs to a figure you can defend
The tool does the arithmetic; the routine below is what makes the arithmetic trustworthy. Five steps, a minute total — and afterwards you will know not just what the number is, but which assumption produced it.
Step 1 — one document, one pass. Open the statement, label or record that holds interest growth rate (%), market adoption (%), media buzz score (1–10), product viability score (1–10) and transcribe straight into the form. Transcription from a single source removes the mismatch errors that appear when figures are assembled from three different places. If the verdict changes with a ten-percent nudge, report the nudge alongside the number.
Step 2 — start from the case you can defend. Enter pessimistic-but-honest figures first; the optimistic run is a ceiling, not a plan. A conclusion that holds on conservative inputs holds everywhere. The test of a good estimate is not that it feels right but that it changes what you do.
Step 3 — play with the inputs on purpose. Ten percent up, ten percent down, one field at a time. Within a few minutes you will know this calculation better than most people who quote its results. A figure nobody can reproduce is a figure nobody will act on twice.
Step 4 — stress before you commit. A decision that survives a ten-percent squeeze on its two biggest inputs needs no luck to be sound. One that does not survive is a decision about hope, not about arithmetic. Most surprises in numbers are surprises about inputs, not about formulas.
Step 5 — record the context, not just the number. Note today’s date and the inputs alongside the Peak of Inflated Expectations output. Six months from now the context is what turns this figure into a trend. Half of a good calculation is knowing which input you would hate to be wrong about.
From calculation to decision: where Hype Cycle Stage earns its keep
In Startup Metrics the figure computed here is usually the first one somebody asks to see. Having it — with the formula behind it — changes your position in the conversation from participant to reference. The fastest sanity test is to guess the answer first and see how far the calculation disagrees.
Used properly this is a five-minute filter that saves weeks. Compute Hype Cycle Stage, reject what fails, and only then bring in the expensive analysis for the survivors. When two sources disagree, it is almost never the arithmetic that differs.
Nothing here is stored or transmitted, so the habit of checking is free: open the page, re-enter current figures, compare with the number you saved last time. Say the answer out loud before you save it; if it sounds wrong, the model did not change, your understanding did.
Hype Cycle Stage — frequently asked questions
What is a typical Hype Cycle Stage?
There is no honest universal average for Hype Cycle Stage, but there is a reference point: the defaults on this page produce Peak of Inflated Expectations (Maximum buzz, thin delivered product — the correction zone). Replace the inputs with your own and compare — that comparison is the useful meaning of “typical”.
How do I calculate Hype Cycle Stage by hand?
Three steps: write the formula (Rule-based mapping of interest, adoption and evidence onto Gartner's five phases), insert your values, and simplify. The worked example section shows exactly that chain for the default inputs; replicating it once on paper teaches you more about Hype Cycle Stage than any number of calculator runs.
Is the Hype Cycle Stage result of Peak of Inflated Expectations good or bad?
Neither, on its own — the label “Maximum buzz, thin delivered product — the correction zone” is the band this figure falls in for the example inputs, and your own inputs will place you elsewhere on the same ladder. Judge the number against your history and your alternatives.
How often should I check Hype Cycle Stage?
Whenever an input changes by more than a few percent, and otherwise on the rhythm of your decisions — before a purchase, a review, a renewal. Hype Cycle Stage is a snapshot, not a subscription; stale snapshots are the most common silent error in Business & Entrepreneurship planning.
Is Hype Cycle Stage accurate?
The arithmetic is exact: Rule-based mapping of interest, adoption and evidence onto Gartner's five phases is evaluated with full floating-point precision and every substitution is printed in the worked example. What limits accuracy is input quality and the model’s assumptions, so treat the Peak of Inflated Expectations result as the correct answer to the question you typed — and check the assumptions section before acting on it.
Do all technologies finish the curve?
No — many die in the trough; the plateau assumes a viable product eventually exists.
Can the trough be a buy signal?
Historically yes: trough entrants often build the plateau winners at deflated competition and attention.
Is my data private on this page?
Yes — computation happens locally in your browser, with no account, no tracking of your inputs and nothing sent to a server. The printed formula is the whole story of what happens to your figures.
Glossary for Hype Cycle Stage
- Expectation-vs-evidence gap
- 5.0 for the Hype Cycle Stage worked case; it sits next to the main result because it carries context the headline leaves out.
- Adoption maturity
- 2.0 % in the default Hype Cycle Stage calculation — one of the secondary figures an experienced reader checks before trusting the primary number.
- Interest momentum
- 180.0 % for the Hype Cycle Stage worked case; it sits next to the main result because it carries context the headline leaves out.
- Likely cycle phase
- The primary output of this tool: Peak of Inflated Expectations for the default inputs, computed exactly from Rule-based mapping of interest, adoption and evidence onto Gartner's five phases.
- Worked example
- The calculation written out in full so that nothing on this page has to be taken on trust.
- Verdict band
- The plain-language label — here “Maximum buzz, thin delivered product — the correction zone” — mapping the computed figure onto experience-based ranges for Business & Entrepreneurship.
Where the Hype Cycle Stage model comes from
The model is published arithmetic implemented exactly as written: Rule-based mapping of interest, adoption and evidence onto Gartner's five phases. Source of record: Gartner Hype Cycle methodology. Specialist software layers extra coefficients on top of the same algebra; none are hidden here, and that transparency is what makes a disagreement traceable to a specific input instead of a black box.
This page is an estimation aid, not professional advice. The design rule is simple: two people entering identical figures must get identical answers. The promise to the reader is narrow and testable: same inputs, same output, no silent rounding, and no figure presented without the formula that produced it.
Next steps after the calculation
Re-run whenever a start date moves — time calculations compound small shifts into large misses.
This page was written for people planning around a point or span in time, and the promise is that nothing above required trust. Bookmark the tool, re-run it whenever an input moves by more than a few percent, and keep the date with the number.