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Product Research
Roadmaps get set by the loudest stakeholder and the most recent customer call. Research replaces both with evidence about demand.
Trade-offs, not ratingsConjoint and forced ranking, because rating scales inflate everything and separate nothing.
Observed task failureUsability testing surfaces problems self-report never captures.
Fits a development cycleShort validation studies that run inside a sprint, where they are most useful.
In simple terms
You tell us what is on the roadmap. We measure what users actually want using methods that force trade-offs, so the sequence rests on demand rather than internal advocacy.
What Product Research is. Product research covers need identification, concept and feature validation, competitive positioning and prioritisation input, so roadmap decisions rest on measured demand rather than internal advocacy.
What makes this different. Fieldwork quality is decided long before anyone answers a question: in the screener, the instrument design and the quality control. That is where most of our effort goes, and it is why the findings hold up.
What the service covers
These are the areas we work across, such as the ones below. We combine them in the proportion your question needs, and we tell you which ones your question does not need.
Need identification
Research into what users are trying to accomplish and where current tools fail them, including your own.
Concept validation
Concepts tested with target users before build, against the alternatives in their real choice set.
Feature prioritisation
Demand measured through trade-off methods rather than direct rating, which inflates everything.
Competitive positioning
How your product compares on the dimensions that actually drive selection.
Questions this answers
If something like this is on your agenda, the engagement is already half scoped.
- Which features do users actually want, as opposed to say yes to?
- What should be next on the roadmap, on evidence?
- Will users pay more for this, or just prefer it?
- Which requested feature would be used by almost nobody?
- How does our product compare on the dimensions that drive choice?
How you can use this
A few of the situations where this service does real work.
Sequencing a roadmap
Every stakeholder has a priority and there is no shared basis.
Validating before build
A feature is scoped and untested with users.
A feature nobody uses
Something shipped and adoption did not follow.
Pricing a new capability
You need to know if users would pay for it.
What changes for your business
The practical difference between running on this and running on what you have now, such as the following.
You get evidence where none was published
Primary research reaches the questions no dataset answers, which is most of the questions that actually matter.
The data is clean enough to rely on
Screening, quality control and documented exclusion rules mean findings survive scrutiny rather than collapsing under it.
You get topline fast
Headline findings arrive within days of fieldwork closing, so decisions do not wait on the full report.
Respondents tell you the truth
Independent fieldwork changes what people are willing to say, particularly about what is going wrong.
You can run it again
Instrument, screener and methodology are handed over, so tracking the same question over time costs a fraction of the first wave.
You test before you commit
Concepts, prices and propositions get checked with real respondents while changing them is still cheap.
Who this is for
Roles that commission this work most often include those below. Each asks a different question and gets a different cut of the same evidence.
Research and insight teams
We need fieldwork we cannot run in-house.
Specialist capacity to your standards, with instrument, dataset and methodology handed over for reuse.
Product and marketing leadership
What do our customers actually think, rather than what we assume?
Evidence from real respondents, with verbatims, so findings can be acted on rather than debated.
Strategy and commercial leadership
Is there enough here to justify the investment?
Primary evidence on demand, pricing and competitive position where no published data exists.
Operations and quality leadership
Is what we designed actually happening in practice?
Independent observation and measurement, reported by location and behaviour so it supports coaching.
Investors and diligence teams
Can we verify this independently before we commit?
Primary market and customer evidence gathered to a defined protocol, with full quality control.
Typical clients
How we work
The third step is the one that makes the output usable, and it is the one most work of this kind skips.
Understand the decision
We start from what the findings have to support, because that decides sample, method and the precision you actually need to buy.
Design and field properly
Screener, instrument and protocol built and piloted before full fieldwork, with quality control running throughout rather than checked at the end.
Read it for your position
Findings are interpreted against your market position and the decision in front of you, not reported as a neutral data dump.
Deliver so it can be reused
Dataset, verbatims, instrument and methodology handed over, so the next wave costs a fraction of the first.
What you receive
Full dataset with respondent metadata and quality flags
Topline findings within days of fieldwork close
Analytical report with verbatimscross-tabs and implications
Instrumentscreener and methodology note for reuse
Access to Phi, our AI research platformincluded
Every engagement comes with access to Phi. Ask questions of your own findings in plain language, pull the evidence behind any number, and keep querying long after the work is delivered. Your team gets the working intelligence, not just the document.
Open PhiWays to start
Tell us the decision and the date it has to be made by. We will recommend the smallest engagement that gets you there.
Pilot wave
A small first wave to validate approach, screener and instrument.
Full fieldwork
Complete fieldwork to target quota, with analysis and reporting.
Tracking programme
The same instrument repeated on a set cycle, reported as change over time.
Common questions
How do you avoid users just agreeing with everything?
Trade-off methods such as conjoint and forced ranking, which require giving something up and produce far more reliable signal than rating scales.
Can this run inside our development cycle?
Yes. Short validation studies fit within a sprint cadence, and that is usually where they are most useful.
Who owns the work?
You do. It is exclusive to you, it is not resold, and working files are handed over unlocked.
Will you sign an NDA?
Yes, before the first conversation if you prefer.
Tell us the decision you are facing
Send us the question, the context and your timeline. You get back a recommended first step, what evidence it needs, and what it costs. Not a capability deck.