Economic marketing strategies that improve profitability and growth
Overview
We prioritize measurable improvements in revenue and profitability.
Approach
What we do
Our approach integrates behavioral economics with quantitative marketing.
Improved marketing ROI through price optimization
We focus on outcomes that matter to the business owner.
Segmented strategies that match customer willingness to pay
Economic intuition guides our hypothesis generation for tests.
Clear metrics tied to unit economics and lifetime value
We measure impact in units that matter: margin, LTV, CAC.
Testing roadmap to reduce acquisition cost and churn
Every engagement starts with a quick diagnostic to find priorities.
Capabilities
We recommend A/B tests where practical and quasi‑experimental designs otherwise.
We quantify tradeoffs between revenue growth and margin pressure.
Why it matters
We provide concise executive summaries focused on decisions.
How we work
We document assumptions, methods, and observed outcomes for transparency.
Engagement models
Pricing is treated as a lever, not a one‑time decision.
Deliverables
Segmentation is driven by value and behavioral signals.
Services
Channel spend is allocated against expected unit economics.
We prefer incremental experiments to large untested changes.
Success criteria
Our analyses rely on first principles and observed data.
We avoid overfitting by validating results across cohorts and timeframes.
Timeline expectations
Experimentation roadmaps prioritize low‑cost, high‑information tests first.
We translate elasticity estimates into pricing scenarios for decisions.
Pricing transparency
Retention efforts are evaluated by their impact on lifetime value.
We track marginal returns by campaign and cohort.
Client onboarding
Attribution models are adapted to client context and available data.
We recommend investments where marginal return exceeds cost of capital.
Data governance
Scenario planning helps prepare for demand volatility and competition.
We use controlled experiments to isolate causal effects.
Pricing models
Customer feedback complements quantitative signals when interpreting results.
We set up dashboards with clear leading and lagging indicators.
Process
Forecasts include confidence intervals and sensitivity checks.
We support cross‑functional rollout of pricing and promotional changes.
A/B testing
Our deliverables emphasize actionable next steps and owners.
Segmentation methods
All tests have predefined success criteria and stop rules.
Forecasting
Implementation recommendations consider technical and operational constraints.
Case studies
We avoid vanity metrics and prioritize economic KPIs.
Competitive positioning analysis informs pricing and messaging choices.
Lead Economist
We document tradeoffs and unintended consequences of each option.
Marketing Strategist
Training and handover are part of every engagement.
Data Scientist
We help set governance for pricing and promotional decisions.
Experimentation Lead
We aim to reduce acquisition costs while protecting margin.
Client Success Manager
Optimization is an ongoing cycle of test, learn, scale.
Strategic pricing and segmentation
Team
We emphasize scalable measurement frameworks from the start.
Data integrations are scoped to deliver core insights quickly.
We prioritize investments with clear path to payback.
Communication templates support consistent stakeholder updates.
We recommend data retention and privacy practices consistent with regulations.
Our methods adapt to both B2B and B2C contexts.
Careers
Attribution
We maintain independence to ensure unbiased recommendations.
Pricing experiment increased margin without raising churn
We support implementation across marketing, product, and finance teams.
Segmentation reduced acquisition cost and improved CLV
We balance short‑term revenue with long‑term customer value.
Channel mix optimization reallocated spend to higher performing cohorts
We use control groups to measure incremental lift accurately.
Contact
We design experiments to be operationally feasible and informative.
We translate technical findings into clear business decisions.
Optimization loops
We document assumptions and update them as new data arrives.
Customer surveys
We help clients select tools that fit their scale and budget.
Competitive analysis
We emphasize reproducibility of analyses and tests.
Value propositions
We avoid risky large bets without staged validation.
Channel economics
We provide templates for pricing governance and approvals.
Governance and compliance
Our recommendations include monitoring plans post‑launch.
We review customer journeys to identify profitable intervention points.
Diagnostic and priorities (1–2 weeks)
We test value propositions alongside price to capture preferences.
Pilot experiments (4–8 weeks)
We tailor reports for executive and operational audiences.
Scale validated tactics (2–6 months)
We quantify uncertainty and present ranges rather than single estimates.
Handover and capability building (2–4 weeks)
We consider both acquisition and retention when sizing opportunities.
Ongoing optimization and governance (ongoing)
We seek simple rules that are easy to operationalize.
Integration with finance
We prioritize actions that improve cash flow and margin expansion.
We coach teams to run their own experiments after handover.
Retention programs
We avoid speculative claims and focus on verifiable outcomes.
We design pricing tests to minimize customer dissatisfaction risks.
LTV modeling
We review past promotions to learn and reduce future mistakes.
We use cohort analysis to separate structural and campaign effects.
Unit economics review
We set clear timelines and deliverable milestones for each project.
We align on definition of success before any experiment begins.
Experiment design
We ensure statistical rigor while keeping business relevance central.
We present both short‑term and strategic options for clients.
Channel strategy
We recommend guardrails to prevent margin erosion during growth pushes.
We focus on scaling proven experiments efficiently.
Mission
We seek to make marketing decisions replicable across teams.
Values
We emphasize data provenance and version control for models.
Core metrics
We support continuous improvement through periodic audits and retrospectives.
Vision
We recommend pricing cadence aligned with market feedback cycles.
Key operating values
We provide clear handoffs to internal teams after engagement.
Analytical heritage
We document lessons learned and update playbooks accordingly.
Customer lifetime value
KPI selection
We document lessons learned and update playbooks accordingly.
Acquisition efficiency
We propose budgets tied to expected marginal return thresholds.
We recommend governance to ensure consistent pricing decisions over time.
Resource allocation
We build dashboards to monitor both performance and risk indicators.
Pricing experiments
We use sensitivity analysis to test robustness of recommendations.
Behavioral insights
We ensure experiments respect legal and ethical constraints.
Cross‑functional alignment
We recommend ongoing cadence for learning and re‑prioritization.
Scenario planning
We help clients build internal capability for economic marketing.
Cash flow impacts
Reporting cadence
We suggest communication plans for price and promotional changes.
Stakeholder updates
We include handover materials and training sessions where needed.
Tooling recommendations
We track post‑implementation performance against forecasts.
Data sources
We set up alerting for unexpected performance deviations.
Retention economics
We prioritize tests that also deliver customer insight.
25757, Philippines, Manila, Bonifacio Street, 44
Open in mapsReporting and dashboards
We provide peer benchmarks when appropriate and available.
Book a strategy call to assess economic impact