Stack I
CRM & Revenue Data
HUBSPOT · SALESFORCE
We validate every experiment against the CRM data your business already runs on, so results connect directly to pipeline and revenue, not a separate analytics silo nobody checks.
Experimentation as a Service
You're running experiments. You're not running a system.
We help mid-market and private equity companies between $30M and $500M ARR turn scattered growth experiments into one connected system - strategy, delivery infrastructure, and revenue optimization working together, so a result that works in one team doesn't just die there.
- Strategy consulting
- Delivery infrastructure
- Revenue optimization
- Built on real data
The Gap
Where the win stops traveling.
-
C-SUITE / EXECUTIVE
Every experiment that works stays exactly where it started.
You've watched a good result surface in one team and go nowhere - no system exists to notice it, validate it against revenue, or push it out to the rest of the business. It just becomes a story someone tells in a meeting once.
→ STAYS ISOLATED -
REVOPS LEADERSHIP
The infrastructure for testing doesn't exist.
Process documentation, MarTech, and operations live in separate systems maintained by separate teams - so even when someone wants to run a coordinated experiment, there's no shared foundation to run it on.
→ NO SHARED FOUNDATION -
MARKETING LEADERSHIP
A campaign wins. Nobody builds on it.
Attribution and results live in one dashboard, one person's head, one quarter. Without a framework connecting today's win to tomorrow's roadmap, marketing keeps rediscovering the same insight from scratch.
→ WINS DON'T COMPOUND -
SALES LEADERSHIP
A pricing test moves deals. Nobody proves it.
The change felt right, reps liked it, and it never got measured against actual pipeline and revenue - so it can't be defended, scaled, or repeated with confidence.
→ NO REVENUE PROOF
Value Leakage
The value leaks between the test and the system.
- NO SHARED FRAMEWORK
- RESULTS NEVER SCALE
- DISCONNECTED INITIATIVES
- NO REVENUE VALIDATION
Experiment run
Result measured
Insight documented
Shared across teams
Becomes standard practice
You're already running the experiments. The gap is between what a test proves and what the business actually adopts - and it compounds every quarter nobody closes it.
Maturity
The four stages of an experimentation program.
Isolated tests
Individual teams run experiments independently - no shared framework connects one test to the next.
Documented, not scaled
Results get written down somewhere - nothing systematically turns a win into standard practice.
Connected, not validated
Experimentation feeds a shared process - but results rarely get tied back to real revenue.
A continuous system
Strategy, delivery, and revenue optimization work as one tested loop - winners get scaled on evidence, not enthusiasm.
The Promise
What changes after the system is in place.
In focus
One framework, every result.
A win in one team gets recognized and adopted everywhere else - because strategy, delivery, and revenue optimization finally run as one connected system instead of three separate departments.
THE PROMISE
Next
A backlog prioritized by revenue, not novelty.
Experiments get sequenced by potential impact - not by whichever idea is easiest to test this week.
PRIORITIZATION
Next
Infrastructure built before the first test runs.
Process documentation, MarTech, and operations get organized into a real system - so testing has somewhere to live instead of depending on one person's initiative.
INFRASTRUCTURE
Next
Every result validated against revenue.
A promising test gets confirmed against pipeline and ROI before the company invests further - not adopted on a good feeling in a meeting.
VALIDATION
Next
Winners become standard practice, deliberately.
A defined scaling process turns a single successful experiment into how the company operates - not a story that fades by next quarter.
SCALING
Next
A team that keeps running it after we leave.
Documentation and training mean the framework survives past the engagement - this isn't a consulting deck, it's a system your team owns.
HANDOFF
Methodology
The DevriX Experimentation Method.
Six stages across a twelve-week framework. We build the strategy and the infrastructure before running a single test - because an experiment with nowhere to scale is just an interesting result nobody acts on.
Phase 01 / 06 · WEEKS 1–4 · STRATEGY CONSULTING
Before anything gets tested, decide what actually matters to the business.
We start with your goals and set KPIs grounded in real market research and technology consulting - not a generic growth playbook stretched to fit every client the same way. This means understanding your competitive position, your buyer segments, and where the biggest levers for growth actually sit, before a single experiment gets designed. Most companies skip this step and go straight to testing, which is how you end up with a portfolio of clever experiments that don't add up to a strategy.
Output
A documented growth strategy with defined goals and KPIs, grounded in your actual market position.
Phase 02 / 06 · WEEKS 4–8 · WORKFLOW & INFRASTRUCTURE MAPPING
An experiment needs somewhere to run. Most companies don't have that yet.
We map the delivery infrastructure, process documentation, management operations, and your MarTech stack into a real operating system. This is the unglamorous work that makes everything after it possible: without it, every experiment depends on one person remembering to coordinate across teams, and that doesn't scale past the first few tests. Where infrastructure gaps exist, this stage surfaces them before they become the reason a good idea never ships.
Output
A documented delivery infrastructure that supports ongoing experimentation, not just the first one.
Phase 03 / 06 · EXPERIMENT DESIGN
Design what's actually worth testing first, not whatever's easiest.
Every candidate experiment gets prioritized against potential revenue impact, not ease of execution or internal enthusiasm. We build a backlog, not a list - sequenced, scoped, and tied to a hypothesis about what will actually move the number that matters.
Output
A prioritized experiment backlog tied to revenue impact, with a clear hypothesis behind each one.
Phase 04 / 06 · EXECUTION & TESTING
Run the experiments across the channels where they'll actually matter.
Demand generation, conversion optimization, SEO, paid advertising - each experiment runs through the same framework instead of as a disconnected departmental effort. Coordination isn't a nice-to-have here, it's the difference between a test that produces a clean read and one that gets confounded by three other things changing at the same time.
Output
Live, coordinated experiments running across your priority channels, each isolated enough to produce a real answer.
Phase 05 / 06 · WEEKS 8–12 · REVENUE OPTIMIZATION
A result doesn't count until it's validated against revenue.
We tie every experiment back to actual revenue and ROI data, so a promising test gets confirmed against the number that matters before the company commits further investment to it. This is where enthusiasm gets replaced by evidence, and where a genuinely good idea earns the resources to scale.
Output
Experiment results validated against real revenue and ROI data, not surface-level engagement metrics.
Phase 06 / 06 · SCALING & HANDOFF
The test proved something. Now it has to become how the company works.
We build the scaling process for winning experiments and train your team to run the framework after the engagement ends. The goal isn't a report you file away - it's a system that keeps producing results long after we've stepped back, because your team knows how to run it themselves.
Output
A documented scaling process and a trained internal team, running the framework independently.
The Stack
The tools, and why these ones.
Our tools are chosen because they enable each step of the workflow - not because they're the best-known platforms in the category.
One connected system
Stack II
Experimentation & Analytics
VWO · OPTIMIZELY · GA4
We run and measure experiments on whichever platform actually fits your stack, coordinated through the same strategy and reporting, not managed as separate, disconnected tools.
Stack III
Synthesis & Insight
CLAUDE AI
Used to analyze experiment results and market data at scale, surfacing patterns and prioritizing what to test next faster than manual analysis allows. It structures the input; the data decides the output.
Deliverables
What you walk away with.
Deliverable 01
Growth Strategy and KPIs
A documented strategy grounded in your actual market and revenue goals.
Deliverable 02
Delivery Infrastructure
A real operating system for experimentation to run inside, not individual effort.
Deliverable 03
Live, Validated Experiments
Coordinated tests, measured against real revenue impact, not vanity metrics.
Deliverable 04
Scaling Playbook and Training
A documented process and a trained team that keeps the system running after we leave.
Typical engagement runs the full twelve-week framework - strategy, infrastructure, and revenue optimization - with experimentation continuing afterward as an ongoing program.
Case 04 // HubSpot to Salesforce Migration
A forms-driven site moved before the contract expired.
An expiring HubSpot contract left a narrow window to consolidate sales and marketing into Salesforce. Forms were spread across multiple content types and embedded through several different methods. We planned the migration, replaced every element tied to the old automation tool and kept the site running through the switch.
- Full form inventory across content types and embed methods
- No interruption to lead capture during the transition
- Launch phase closed within the agreed week
Who This Is For
Who this is for.
Mid-market and private equity companies between $30M and $500M ARR - SaaS, technology services, professional services, fintech, healthtech, energy.
01
CEOs, COOs, CFOs
You're dealing with
- Outdated expertise holding the company back from confidently exploring new strategies
- Too many competing priorities keeping a real experimentation system off the roadmap
- No visibility into whether growth initiatives are producing revenue, or just activity
You'll get
- Strategic scaling guidance grounded in real data, not outdated assumptions
- Risk mitigation through structured, data-driven testing before major investment
- Clear visibility into which growth initiatives are actually producing revenue
02
RevOps Managers & Directors
You're dealing with
- Process documentation, MarTech, and operations scattered with no unified system
- Manual coordination required every time an experiment spans multiple departments
- Data silos that make it impossible to see one view of what's actually working
You'll get
- A real operating system for experimentation, not more manual coordination
- Data integration and reporting that shows the full picture
- Cross-functional workflow connecting strategy, delivery, and revenue teams
03
Marketing Directors & VPs
You're dealing with
- Campaigns that test well once and never become a repeatable process
- No framework for prioritizing which experiments are actually worth running
- MarTech not built to support continuous, coordinated testing
You'll get
- A pipeline built on a continuously tested and optimized system
- Attribution and ROI measurement across every experiment you run
- MarTech that supports ongoing experimentation instead of working against it
04
Sales Directors & VPs
You're dealing with
- Pricing or packaging tests that show promise but never get validated against revenue
- Initiatives that never get tested and refined systematically
- No account intelligence about which experiments actually influence a deal
You'll get
- Revenue goal attainment through experiments validated against real pipeline impact
- Higher sales velocity from continuously optimized messaging and positioning
- Decision frameworks connecting experimentation directly to revenue
Who this isn't for
- Companies looking for a single, isolated project rather than an ongoing system. Experimentation compounds over the full framework, not in one test.
- Teams unwilling to actually scale a winning experiment once it's proven. The value here is turning results into practice, not running tests for their own sake.
- Businesses without a CRM or core revenue systems in place. We validate against that data - we don't stand up the systems from nothing.
Outcomes
Strategic outcomes, measured.
KPI/01
41%
ARR growth at Patchstack after product, billing, and go-to-market data landed in one revenue model.
KPI/02
30%
Less rep time per deal on entry and reporting, once properties, scoring, and workflows were standardized.
KPI/03
2.4x
Pipeline volume at EnviroKlenz after web and attribution integration put both companies on one measurable stack.
Testimonial
Proof, not promise.
CASE FILE · NitroPack
When it comes to a high-scale revenue delivery initiative, DevriX gets the job done, period. They quickly jumped in on a partially-started project and led it to completion in record time. They worked with our team to iron out the finer details while building the full picture. Communication, attention to detail, and attentiveness were all 5-star. Stellar work.
Mihail Stoychev
Co-founder, CEO of NitroPack (acquired by WP Engine)
Why Us
Why not just run experiments internally?
01
“We'll just run experiments internally when we have time.”
Internal experimentation without a dedicated framework happens in bursts, disconnected from any consistent process, and a promising result rarely turns into standard practice without someone responsible for scaling it. We bring the framework and the discipline that turns individual tests into compounding growth.
02
“Why not just hire a growth consultant for a one-time engagement?”
A one-time engagement delivers a set of recommendations, not a running system. We build the actual delivery infrastructure and validation process that keeps experimentation happening continuously, long after the initial strategy phase ends.
03
“Isn't this just conversion rate optimization?”
No - conversion optimization is one piece. We connect strategy consulting, delivery infrastructure, and revenue optimization into a single system, so experiments across the entire business get prioritized, tested, and scaled together, not run as isolated CRO projects.
We validate every experiment against real revenue impact, not vanity metrics.
We build the delivery infrastructure experiments actually need to scale.
We connect strategy, execution, and revenue optimization into one system.
We stay through scaling, not just the initial test.
Get Started
Stop running tests. Start running a system.
A 30-minute call. We'll look at your current growth initiatives and show you where a promising result never got the chance to scale. No deck.
Technical Buyer
Answers for the technical buyer.
01 Why do enterprises need experimentation as a service when exploring new verticals?
The main reason is risk mitigation. Venturing into a new vertical carries real risk, and a structured, data-driven approach to experimentation lets you assess the potential of a new strategy before committing significant investment, rather than finding out after the fact.
02 Why does risk mitigation actually matter for a growing company?
It lets you allocate resources more efficiently. Identifying and prioritizing risk means your team can focus effort on what's genuinely critical to the business, instead of spreading investment evenly across untested ideas.
03 How is this different from a traditional growth strategy engagement?
A traditional engagement usually delivers a set of recommendations and moves on. We build a dynamic, continuously running system that combines assessment, strategy, and data-driven testing, so the approach keeps adapting instead of going stale the moment the initial project ends.
04 What role does outsourcing this to an agency actually play?
An outside team brings a dynamic, cross-industry perspective and the infrastructure to run continuous experimentation, which is difficult for an internal team to build and maintain alongside its regular responsibilities.
05 Can you integrate with our existing CRM and marketing systems?
Yes. We connect experimentation and its results directly to the CRM and marketing systems you already use, so validated results feed the same reporting your team already relies on.
06 How long does the full framework take?
The core framework runs across twelve weeks - strategy consulting in the first four, delivery infrastructure in the next four, and revenue optimization in the final four - with experimentation continuing afterward as an ongoing program.