Product
Strategy and roadmaps.
Strategic guidance for product development, market positioning, and growth — from defining the vision to prioritizing the roadmap, with AI integration where it creates real value.
What's included
- Product vision and strategy
- Roadmap planning and prioritization
- Zero-to-one product definition
- Market research and competitive analysis
- AI integration strategy
- Concept validation with coded prototypes
- End-to-end product lifecycle, concept through post-launch
- Experience metrics — HEART, adoption, retention, task success
- Product and UX team leadership and mentorship
- Stakeholder alignment and communication
From concept to launch
Experience+ takes work end to end — product, code, marketing, and strategy, from concept to launch. On the product side, that means setting a clear vision, translating it into a prioritized roadmap, and staying with it through development and post-launch iteration rather than handing over a deck and leaving.
A lot of that work is turning ambiguity into something a team can execute. High-stakes direction from leadership tends to arrive as a sentence, not a plan; our job is to give it a shape — scope, sequence, and a definition of done — and to build that structure in places where the process doesn't exist yet.
We've shaped product direction across B2B, B2C, SaaS, e-commerce, startups, and enterprise — from zero-to-one platforms to product suites spanning seven distinct products.
Zero to one, and one to many
These are two different jobs. Zero to one is about finding the shape of the product before the runway runs out: framing the opportunity, defining the smallest thing worth building, and proving it with real users. CloudNatix was exactly that — a platform designed from nothing across a 3.5-year engagement, ending in up to 60% lower compute costs and a 5× productivity improvement for the teams using it.
One to many is the opposite pressure: keeping a growing portfolio coherent. At Oracle that meant design leadership across three PaaS/IaaS suites — seven products in all — where the strategic work was deciding what had to stay consistent across them and what was allowed to differ.
Productized offering
Discovery Sprints
When a roadmap decision is stuck, a structured, fixed-scope sprint takes one product question from framing to a user-tested prototype — a decision in days, not quarters. Run remotely or on site, with a dedicated site of its own.
- One roadmap question, scoped together up front
- A prototype built and tested with real users inside the sprint
- A clear, evidence-backed decision your team can plan against
Roadmaps that stay alive
A roadmap is a living argument about what matters most, not a document you publish once a year. We build one that moves with market trends, user needs, and business priorities — and that says plainly what is not being built, which is the half most roadmaps leave out.
A plan written by people who don't ship tends to come apart at the first estimate. Because the same studio designs and builds, we can pressure-test scope with engineering while the plan is still cheap to change, and validate direction with a working coded prototype instead of a static mock.
AI where it creates real value
Every product team is being asked about AI. We help you answer with substance: identifying where AI genuinely improves the product or the process, and where it's a distraction. The 'plus' in Experience+ isn't just AI — it's whatever amplifies outcomes.
That answer is rarely a feature list. It's a short set of places where a model earns its cost, measured against the same adoption and task-success metrics as everything else on the roadmap — and an honest account of the places where it doesn't.
Should we build this with AI?
Eight real asks that land on product teams. Call each one yourself, then see where we land and why — the reasoning is the part worth arguing with.
Theme 200 user-interview transcripts into patterns for a research readout.
Earns its cost. This is pattern-finding across a corpus no human can hold in their head at once, and every theme is checked against the transcripts before it ships. The cost of a wrong theme is a researcher's afternoon, not a bad release.
Add an AI assistant to the product's front page so users can ask it questions.
Doesn't earn its cost. Almost always, the questions people would ask it are ones the navigation should have answered. Bolting a bot onto a confusing product gives you two confusing products, and the bot is the one that will be quoted back to you when it's wrong.
Generate a first-pass component library from the design tokens.
Earns its cost. Mechanical, verifiable, and reviewed by the same engineer who would otherwise have typed it. The work being replaced is transcription, not judgment — which is the clearest case there is.
Let a model rearrange each user's dashboard automatically based on their behavior.
Doesn't earn its cost. People build spatial memory of an interface and navigate it without looking. Silently moving things costs more in confusion than the personalization returns — offer the rearrangement, don't perform it.
Draft release notes from the merged pull requests each cycle.
Earns its cost. Small, bounded, high-frequency, and low blast radius — someone skims it before it publishes. This is the shape of task where AI quietly pays for itself and nobody writes a case study about it.
Replace a round of usability testing with synthetic AI users.
Doesn't earn its cost. A simulated user can't be surprised, confused, or irritated, and those three reactions are the entire reason the method exists. Useful for rehearsing your script before real sessions; never a substitute for the finding.
Classify inbound support tickets by intent and route them.
Earns its cost. Classification with a measurable error rate, a cheap fallback when it misses, and enough volume that even imperfect accuracy pays. The failure mode is a ticket in the wrong queue for an hour.
Have AI generate the product roadmap from your backlog and market data.
Doesn't earn its cost. A roadmap encodes bets about a market, and constraints only your team knows — who's leaving, what the biggest customer threatened, which system can't take another feature. A model will produce something plausible, and plausible is precisely the failure mode.
The test is the same every time: does it have a measurable error rate, a cheap fallback when it's wrong, and a person who owns the output? Miss any of the three and you have a demo, not a feature.
The same goes for how your team works. We use AI-powered research and prototyping tools to compress the distance from idea to validated concept to engineering hand-off, and we model that workflow in the open — shared use cases, regular learning sessions, hands-on experimentation — so the practice stays after the engagement ends.
Positioning that holds up
Positioning is a research problem before it's a messaging problem. We map the competitive set, read where the market is actually moving, and find the claim your product can defend — then check that claim against what users say in their own words, rather than what the category says about itself.
Experience is the product
Strategy that ignores the interface is theory. The roadmap decisions that matter most usually show up as friction in a flow, so we keep design principles, user needs, and business objectives aligned as one conversation rather than three — with the people designing the screens in the room when the priorities are set.
Where experience quality needs to be measured, we use established frameworks rather than opinion. The DocuSign redesign of sending and signing was measured with Google's HEART metrics — happiness, engagement, adoption, retention, task success — so improvements to the experience could be argued in the same terms as everything else the business tracks.
What HEART actually measures
Five metrics, five different questions — and five different ways to be misread. Select one to see what it captures, how we instrument it, and where taking it at face value will cost you.
Happiness
The attitudinal signal — how people feel about the product: satisfaction, perceived ease, willingness to recommend it to someone else.
In-product micro-surveys, post-task ease ratings, CSAT or SUS, and review sentiment — sampled continuously rather than in one annual push.
Only the people still using the product answer. A rising score can simply mean the unhappy ones already left.
Engagement
Depth and frequency of voluntary use inside a window — the actions that indicate real value, not just presence.
Key-action frequency per active user per week, session depth, and the share of accounts doing the job the product exists to do.
More time in the product is not automatically good. If a task should take thirty seconds, rising engagement is friction wearing a disguise.
Adoption
New users or accounts starting to use the product — or an existing base picking up a capability you just shipped.
Activation inside a fixed window after signup, first-time feature use, and upgrade rate, always measured against a defined cohort.
Launch spikes flatter adoption. Without retention beside it, a good campaign looks identical to a product that works.
Retention
Users who stay active from one period to the next — the metric tied most directly to whether the product is worth what it costs.
Cohort curves at 7, 30, and 90 days, churn broken out by segment, and the resurrection rate for accounts that lapse and come back.
An aggregate number hides the split between a healthy core and a leaky new-user cohort. The shape of the curve matters more than the headline.
Task success
Whether people can actually complete the core jobs: effectiveness, efficiency, and error rate on the flows that matter most.
Completion rate and time on task from moderated and unmoderated testing, matched against funnel drop-off in product analytics.
Analytics tell you where people fail, never why. The number needs recorded sessions behind it before anyone ships a fix.
Inside your team, not beside it
We work as senior practitioners embedded in your team — direct access to the person doing the work, no hand-offs to junior staff. Where the engagement includes leading product and UX people, that means mentorship, professional development, and a culture where good ideas can come from anywhere and get tested quickly.
It also means doing the unglamorous connective work: gathering feedback from the customers, partners, and internal teams who live with the product, and communicating the same direction credibly to engineers and executives alike. Trust across those groups is what keeps a roadmap from quietly drifting away from the people it's for.
Productized offering
Fractional Product Leadership
Senior product leadership without a senior product hire — a product leader embedded in your team two or three standing days a week, owning the roadmap, positioning, and the metrics success is judged by, while still doing the hands-on work. Three-month minimum, with a dedicated site of its own.
- Standing days every week, so context compounds instead of resetting
- Roadmap, prioritization, and stakeholder alignment owned end to end
- Your product and design people mentored as the work happens
Outcome-focused
We measure success by the results we help you achieve — adoption, retention, task success, and business impact — not by the volume of deliverables. Strategy work ends with a plan your team can execute, and metrics that tell you it's working.
That means agreeing up front on what would count as success, instrumenting it, and being willing to change the roadmap when the numbers disagree with the plan.