50+
experiments per year
A/B testing that
drives revenue
We run experiments across your website, product, and funnel to grow conversion and revenue with data, not opinions.
We reply within 1 business day. NDA available on request.
Metric-focused execution
We test hypotheses that move revenue, not cosmetic UI tweaks.
Protection from false winners
We rely on correct statistics and clean data before making decisions.
Every test ties to money
We estimate impact and roll out only changes that increase profit.
Why businesses need A/B testing
Without experiments, changes often look convincing but do not improve sales. We turn optimization into a controllable growth loop.
What we test
We adapt the experimentation program to your product type and growth objective.
Landing pages and promo funnels
Increase lead and purchase conversion through offer, structure, and CTA testing.
- Offer, messaging, and value proposition
- Block order and trust proof sequence
- Forms, CTAs, and checkout steps
Online stores
Reduce drop-offs in product page, cart, and checkout to increase revenue from existing traffic.
- Product card and trust blocks
- Cart, delivery, and payment flow
- Pricing structure and bundle offers
SaaS and digital products
Improve activation, retention, and monetization with a structured product experimentation process.
- Onboarding, paywall, and trial journeys
- Feature flow experiments
- Billing screens, offers, and bundles
Packages, plans, and pricing
Validate pricing hypotheses safely on controlled segments to maximize conversion and margin.
- Plan grid and package order
- Value communication and constraints
- Urgency triggers and price anchoring
What you receive
Deliverables are prepared so your team can immediately execute and ship improvements.
Funnel map with loss points
Prioritized hypothesis backlog
4-8 week experiment roadmap
Launch protocols and QA checklist
Reports for each experiment
Winning changes rollout list
Insights and learnings repository
Recommendations for the next cycle
Process transparency
How A/B testing works: 6 steps
A full cycle from diagnostics to rollout, with no gaps between analytics, design, and engineering.
95%
statistical rigor
2-6 wks
average cycle
Diagnostics
We align on business goals and validate tracking quality and event integrity.
We align on business goals and validate tracking quality and event integrity.
Research
We collect insights from behavior, segments, and qualitative signals.
We collect insights from behavior, segments, and qualitative signals.
Hypotheses
We formulate clear if/then/because hypotheses tied to measurable outcomes.
We formulate clear if/then/because hypotheses tied to measurable outcomes.
Prioritization
We rank ideas by impact, confidence, and effort to launch the best first.
We rank ideas by impact, confidence, and effort to launch the best first.
Launch and control
We set traffic split, run QA, and monitor execution to prevent bias and errors.
We set traffic split, run QA, and monitor execution to prevent bias and errors.
Decision and rollout
We deploy winners, document outcomes, and plan the next iteration.
We deploy winners, document outcomes, and plan the next iteration.
A/B testing packages
Choose the format based on traffic volume, release cadence, and team maturity.
Start
For rapid setup and first validated experiments
from $1339
2-3 weeks
Included:
- Data and goal diagnostics
- 5-10 prioritized hypotheses
- 1 end-to-end A/B test
- 30-day improvement plan
Growth
Balanced monthly pace for conversion growth
from $2119 / month
2 tests per month
Included:
- Full cycle research -> hypothesis -> launch
- 2 A/B tests per month
- Winner analysis and rollout support
- Unified backlog and reporting
Scale
For teams with stable traffic and fast release cycles
from $3559 / month
4-6 tests per month
Included:
- Parallel tests across multiple funnels
- Advanced segmentation and prioritization
- Quarterly experimentation strategy
- Team enablement and ongoing support
