Your Product Decisions Are Based on Gut Feeling, Not Data.
Your product team is shipping features without knowing if they work. You have analytics tools but no experimentation culture. Feature impact is measured by vibes, not data.
The data challenges keeping you up at night
Features ship, but impact is unknown
Your team launches features on schedule, but weeks later nobody can tell you if they moved the needle. Product reviews become opinion contests instead of data-driven discussions. Feature success is measured by delivery, not outcomes.
A/B testing is ad-hoc or non-existent
You know you should be testing more. But setting up experiments is painful, sample sizes are unclear, and results take too long. The few tests you run don't have statistical rigor — so nobody trusts the results anyway.
Analytics tools exist but don't answer questions
You have Amplitude, Mixpanel, or GA4. Your team can see pageviews and clicks. But when the CEO asks "what's driving retention?" or "which features correlate with activation?" — silence.
Product and data teams don't speak the same language
Product managers write specs, but instrumentation is an afterthought. Events are inconsistently tracked. By the time data is available, the team has moved on to the next sprint.
How we solve this for your role
Product Analytics Architecture
We design and implement an event tracking strategy that answers your actual product questions — not just "what happened" but "why" and "what should we do next." Deliverable: Event taxonomy, tracking plan, and instrumentation guide your team can maintain.
Experimentation Infrastructure
We build (or fix) your A/B testing pipeline. From hypothesis framework to statistical analysis, we create a system where running experiments is easy and results are trustworthy. Deliverable: Experimentation playbook + infrastructure setup.
Feature Impact Measurement
Every feature gets a measurable success metric before development starts. We build automated impact reports so your team knows — quantitatively — what's working and what's not. Deliverable: Feature impact framework + automated dashboards.
Data-Driven Product Culture
We train your PMs to think in hypotheses, design experiments, and interpret results. The goal: your team becomes self-sufficient in making data-informed product decisions. Deliverable: PM analytics training + decision framework documentation.
From first call to measurable results
Product Analytics Audit
We audit your current tracking, identify gaps in your event taxonomy, and interview PMs to understand what questions they can't answer today. We map the path from current state to product analytics maturity.
Tracking Plan + Quick Wins
We deliver a comprehensive tracking plan and fix the most critical instrumentation gaps. Your team gets their first "aha" dashboard showing product insights they couldn't see before.
Experimentation Setup + Training
A/B testing infrastructure goes live. We run 2-3 pilot experiments with your team, demonstrating the full cycle from hypothesis to statistical result to product decision.
Ongoing Experimentation Support
Monthly retainer for experiment design review, results analysis, and product analytics strategy. We help your team run 3-5x more experiments with proper rigor.
How a product team went from 0 to 15 experiments/month
A B2B SaaS product team was shipping features based on customer requests and stakeholder opinions. They had Amplitude installed but couldn't answer basic questions about feature adoption or user activation. We redesigned their event taxonomy, built an experimentation framework, and trained PMs to run their own A/B tests. Within 8 weeks, they went from zero structured experiments to 15 per month — and discovered that 40% of their "most requested" features had no measurable impact on retention.
What our clients say
"The Valiotti Data team has built an analytics infrastructure for Simple App. They analyzed all data streams, designed a data lake, developed microservices for statistics collection, deployed a Kafka cluster to achieve scalable and fail-safe streaming. Next, they deployed Clickhouse…
"Valiotti Data helped us build a new data pipeline from scratch, replacing legacy tools such as Pentaho IDE with modern ones. They suggested the implementation of a modern data warehouse architecture for analytics and tuned instances to work with software.…
"We’ve worked directly with Nikolay on multiple long and short-term projects. The results were outstanding! Nikolay and his team delivered fantastic results in a professional manner for a global SaaS company based in Europe with +800 employees. They possess technical…
Ready to close your data leadership gap?
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