Product Analytics and Experimentation Corporate Training
Instructor-led training that turns product teams into confident experimenters
Master event data, dashboard design, insight storytelling, and rigorous experimentation through guided hands-on labs with realistic product datasets.
Instructor-led group trainingVirtual / on-site / off-site10 languagesDelivered inEnglish, Spanish, Mandarin, German, Arabic, Portuguese, Hindi, French, Japanese, Italian100+ countriesWe have delivered inUnited States, United Kingdom, India, Canada, Germany, France, Netherlands, UAE, Saudi Arabia, Singapore, Australia, Japan, Brazil, South Africa and 90+ more countries
How we build an experimentation-ready team
The Edstellar ANALYTICS Capability Model
Diagnose
Assess your team's analytics maturity: event tracking quality, dashboard discipline, and testing culture.
Standardize
Define event taxonomies, metric definitions, and experiment templates everyone trusts.
Practice
Build dashboards, design experiments, and analyze results in guided hands-on labs with realistic data.
Measure
Track experiment velocity, decision quality, and metric integrity like a mature product analytics function.
Scale
Spread experimentation playbooks and self-serve analytics across every product squad.
Need more than one program?Get a group quote
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Program Overview: What is Product Analytics and Experimentation?
Product Analytics & Experimentation is an instructor-led corporate training program that teaches product teams to measure, understand, and improve their products with data. Your team learns event data modeling, dashboard design, insight storytelling, experiment design, and A/B testing statistics, then practices every skill in guided hands-on labs with realistic product datasets. The program suits product managers, analysts, and growth teams.
The program runs over 28 instructor-led hours across seven modules, moving from analytics foundations to advanced experimentation. Guided labs have teams build tracking plans, model event data, design dashboards, and analyze funnels, retention, and segments. Instructors coach experiment design, hypothesis framing, and sample sizing, correcting the statistical traps that distort results. It closes with the End-to-End Experiment Program capstone, where teams design, run, and read out a real experiment.
Product decisions too often run on opinion and loud voices, while dashboards no one trusts gather dust. Worse, teams run experiments badly: peeking at results early, underpowered samples, and conclusions that do not survive scrutiny. This program teaches teams to instrument products properly, analyze with statistical discipline, and argue from evidence.
For the capstone, each team ships an end-to-end experiment program for a product it owns: a tracking plan and event taxonomy, a dashboard answering the product's key questions, an experiment backlog with prioritized hypotheses, and a completed A/B test with sample sizing, guardrail metrics, and a written read-out defending the ship-or-kill decision. Instructors challenge the read-out the way a data review board would. The team keeps experiment templates and analysis playbooks it can apply to live products immediately.
The program moves from analytics foundations to advanced experimentation: tracking plans, funnel and retention analysis, segmentation, hypothesis testing, sample sizing, and reading test results without common statistical traps. Participants leave with reusable dashboards, experiment templates, and analysis playbooks they apply to live products immediately. Content adapts to your product, metrics, and analytics stack.
What's Included in this Workshop for Your Enterprise Teams
- 1
Event tracking plan
Design a clean tracking plan for a realistic product in a guided lab.
- 2
Product dashboard kit
Build dashboards for activation, engagement, and retention.
- 3
Experiment design template
Write testable hypotheses with success metrics and guardrails.
- 4
A/B test analysis playbook
Analyze a real test dataset and decide ship, iterate, or stop.
- 5
Insight storytelling guide
Turn analysis into narratives stakeholders act on.
- Instructor-led sessions in hybrid, onsite, or live virtual formats
- Dedicated training advisor for scheduling and coordination
- Pre-program skills assessment for every participant
- Lab workbooks, experiment templates, and reference guides
- Post-program assessment with a team skills report
- Digital certificate of completion for participants
Build your team's skills. Anywhere in the world.
Real-world use cases
from day one
Instructor-led training
for your teams
Delivered globally
in 100+ countries
Enterprise Training Solutions Customized for Your Company
One partner for instructor-led corporate training, delivered the way your teams work.
Request a Training Quote- Customized Training Delivery
- Scale Your Training: Small to Large Teams
- In-person Onsite, Live Virtual or Hybrid Training Modes
- Plan from 2000+ Industry-ready Training Programs
- Hands-On Labs on Live Infrastructure, Led by Industry Experts
Product Analytics and Experimentation Course Topics and Program Outline
A hands-on curriculum that takes your product team from event data basics to running a rigorous experimentation program, with guided labs in every module.
Built by Edstellar with product analytics and experimentation practitioners
Built by product analysts and experimentation specialists who run testing programs in production, shaped around your product and analytics stack.
We assess your team's analytics maturity, tracking quality, and experimentation habits before training begins.
Your team learns event data modeling, metrics design, and experiment fundamentals in expert-led sessions.
Participants build dashboards, design experiments, and analyze test data in guided hands-on labs.
Teams run a full experiment program in the capstone and leave with templates ready for live products.
From first event tracked to shipped experiment, every skill is practiced in hands-on labs.
Delivered as
Delivered in hybrid, onsite, or live virtual formats, scheduled around your team's working hours.
Draft a tracking plan with events, properties, and metric definitions for a sample product.
learna)Product analytics vs business intelligence
b)Event-based data models
c)Designing a tracking plan
d)Data quality, identity, and sessions
e)Choosing north-star and input metrics
Model a messy event stream into clean session and user tables with documented definitions.
learna)From events to modeled tables
b)User journeys and sessionization
c)Cohorts and user properties
d)Handling messy, missing, and duplicate data
e)Documenting metrics and definitions
Build a product health dashboard and present a three-minute insight story from it.
practicea)Dashboard design principles
b)Activation, engagement, and retention views
c)Choosing the right visualization
d)Insight storytelling for stakeholders
e)Dashboard maintenance and trust
Design a complete experiment: hypothesis, metrics, guardrails, and a sample-size calculation.
practicea)Anatomy of a good hypothesis
b)Success metrics, guardrails, and secondary metrics
c)Randomization and test groups
d)Sample sizing and test duration
e)Common design pitfalls and how to avoid them
Analyze a real A/B test dataset, check validity, and write a ship or iterate recommendation.
practicea)Experimentation platforms and feature flags
b)Statistical significance, simply explained
c)Confidence intervals in plain language
d)Peeking, multiple testing, and other traps
e)Segmenting results and checking validity
Run a funnel and retention analysis on a dataset and prioritize three product opportunities.
applya)Behavioral segmentation
b)Funnel analysis and drop-off diagnosis
c)Retention curves and cohort analysis
d)Correlating behavior with outcomes
e)Prioritizing opportunities from analysis
Deliver an experiment roadmap, a analyzed test result, and an executive readout for the case product.
applya)Integrated product case briefing
b)Analytics audit and opportunity mapping
c)Experiment roadmap and prioritization
d)Running and analyzing the flagship test
e)Executive readout and rollout plan
Customize this program tailored to your team?
Tell us your training needs: what your team already works with, the level they’re at, and the topics you want them to focus on. We’ll adjust the modules, duration and hands-on labs, and send you a customized outline for your group.
Key Skills and Outcomes Your Team Will Gain
Analytics and experimentation skills your product team applies to live products from the first week after training.
Design event tracking plans
Define events, properties, and metric definitions that produce trustworthy product data.
Model product data cleanly
Shape raw events into session and user tables with documented, shared definitions.
Build dashboards people use
Design activation, engagement, and retention dashboards with clear, honest visualizations.
Tell stories with insights
Turn analysis into narratives that stakeholders understand and act on.
Design rigorous experiments
Write testable hypotheses with success metrics, guardrails, and proper sample sizing.
Analyze A/B tests correctly
Read test results with sound statistics while avoiding peeking and validity traps.
Find opportunities in data
Use segmentation, funnels, and retention analysis to prioritize what to build and test next.
Teams that Benefit from this Product Analytics and Experimentation Group Training
Designed for product managers, analysts, designers, and engineers who want data-driven product decisions. Content adapts to each cohort's product, metrics, and analytics stack so every team practices on realistic data it recognizes.
Make roadmap decisions with data
For product managers who want trustworthy metrics, rigorous tests, and insights that sharpen prioritization.
Workflow friction
- Decisions driven by opinion and HiPPO
- Metrics nobody agrees on
- Tests that never reach conclusions
How the program helps
- Define metrics the whole team trusts
- Run experiments that settle debates
- Prioritize roadmaps from evidence
Practice use cases
- metric definition labs
- experiment design clinics
- roadmap prioritization drills
Level up product analytics craft
For analysts who support product teams and want stronger experiment design, cleaner models, and sharper storytelling.
Workflow friction
- Ad-hoc requests with no standards
- Analyses stakeholders ignore
- Testing done without rigor
How the program helps
- Design bulletproof experiment analyses
- Build self-serve product datasets
- Communicate insights that drive action
Practice use cases
- stats refresher labs
- tracking plan builds
- storytelling workshops
Validate design with real behavior
For designers who want behavioral data and experiments to validate and refine product experiences.
Workflow friction
- Designs shipped without validation
- Research that never scales
- UX debates settled by taste
How the program helps
- Validate designs with behavioral data
- Test variants with real users at scale
- Connect research to product metrics
Practice use cases
- funnel analysis labs
- A/B test design practice
- insight presentation drills
Ship experimentation-ready products
For engineers who implement tracking and feature flags and want clean, testable product instrumentation.
Workflow friction
- Tracking added as an afterthought
- Flags that linger and rot
- Data engineers cannot trust
How the program helps
- Implement clean event tracking
- Build reliable feature flag setups
- Instrument products for testability
Practice use cases
- tracking implementation labs
- flag hygiene clinics
- data quality drills
Each department track uses realistic product datasets and scenarios wherever possible, so practice mirrors real product work.
Prerequisites: Product managers, product analysts, designers, and engineers benefit most. Basic comfort with data helps but is not required: statistics are taught in plain language and labs adapt to each cohort's product and analytics stack.
Analyst to Experimentation Lead
A progression path that grows with product careers, from reading dashboards to leading an experimentation program.
One program that grows with product careers, from first dashboard to running a full experimentation practice.
Mixed cohort, or several teams at once?
We can tailor the training to different teams, roles, and experience levels within the same program.
Certificate of Training Completion.
On successful completion, employees receive an Edstellar course completion certificate, recognizing their commitment to ongoing learning and professional development. It validates the skills they have built and motivates them to keep growing and contribute to organizational success.
Earned, not attended. Awarded on completion of all hands-on labs and the capstone project.
Training Delivery Modes: Virtual, Onsite and Hybrid
Choose the format that fits your team: live virtual sessions, onsite workshops at your office, or a hybrid mix of both.
Hybrid Training
A blended format: some sessions at your office, some live online, with one consistent curriculum and shared lab work.
- Mix onsite workshops with live virtual sessions
- One curriculum across both formats
- Shared lab exercises and group reviews
- Flexible scheduling around business hours
Onsite Training
The instructor delivers the full program at your location, using your data and supplier scenarios in the labs.
- Delivered at your office or facility
- Labs use your real categories and data
- Face-to-face coaching in every session
- Team workshops that build shared playbooks
Live Virtual Training
Live online sessions with breakout labs, screen-shared exercises, and real-time instructor feedback.
- Live instructor-led online sessions
- Breakout rooms for small-group labs
- Digital workbooks and templates
- Recorded sessions for later review
Need a training format that works for your team?
Full days, half days across weeks, or split by module. Tell us the delivery window and we schedule the cohort around it.
Frequently Asked Questions
Share your team size, preferred dates, and delivery format through the request form. A training advisor responds within one business day with a group quote.
Yes. A discovery call helps us understand your team's maturity and goals so we can tailor the curriculum before scheduling.
Yes. Live virtual sessions run with breakout labs and real-time instructor feedback, and recordings are shared for review.
Yes. Onsite delivery brings the instructor to your location, and labs can use your own data and scenarios.
The program runs 28 instructor-led hours, typically spread across multiple days to fit your team's schedule.
Question not answered here?
Put it in the request. A training specialist answers it directly, within one business day.
Where this Training Fits in Your Team's learning path.
Product analytics and experimentation come third, after product management basics and web analytics. Your team first knows what the product is trying to achieve and how to measure usage. The final step uses experiments and analytics to drive product-led growth.
Why Choose Edstellar as Your Product Analytics and Experimentation Corporate Training Provider
Edstellar delivers analytics training built around your product, metrics, and stack, with every skill practiced in guided labs.
EXPERT TRAINERS
YEARS DELIVERING
ORGANIZATIONS TRAINED
CERTIFIED
Tailored
Every cohort works on realistic product datasets and your metric definitions, so practice transfers to live products.
Proven Methodology
A Diagnose to Scale method refined across product teams builds analytics skill in a logical, lasting sequence.
Practice-Based Learning
Guided hands-on labs in every module turn analytics theory into dashboards and experiments your team keeps.
Expert Trainers
Product analysts who run experimentation programs in production teach from real testing experience.
Global Scale
Hybrid, onsite, and live virtual delivery trains product teams across regions on one consistent curriculum.
Measurable Outcomes
Pre and post assessments plus a skills report show exactly how analytics capability improved.
Connect Product Metrics With Valid Experiments and Clear Decision Recommendations
Edstellar develops product analytics skills from event definitions to experiment interpretation. Participants clean event data, build dashboards, and examine funnels and retention before designing and analyzing tests. An experiment roadmap and executive readout combine the work, with review of measurement consistency, statistical validity, guardrails, and the evidence behind product recommendations.
- Step 01
Consult
We explore product questions, analytics experience, and difficulties with event definitions or test interpretation to identify gaps in measurement, experimentation, and decision communication.
- Step 02
Plan
We establish tracking plans and product data models before dashboards, hypothesis testing, and A/B analysis, then connect segmentation and retention findings to an experiment roadmap.
- Step 03
Align
We align product analytics and experimentation expertise with cross-functional roles, calibrating statistical explanations and tooling to the cohort's data comfort and product environment.
- Step 04
Customize
We adapt sample event streams, funnels, and test datasets to familiar product journeys, preserving messy records and validity questions that participants must resolve.
- Step 05
Execute
Participants define metrics, calculate sample needs, and interpret A/B results, receiving feedback on guardrails, test validity, segment comparisons, and the strength of recommendation evidence.
- Step 06
Evaluate
We assess the experiment program for consistent tracking definitions, defensible test design, accurate result interpretation, and a roadmap and readout that acknowledge unresolved uncertainty.
Also from Edstellar
Talent assessments
Psychometric, behavioral, leadership and 360-degree assessment.
→Training needs analysis
Needs analysis, gap identification, and a training roadmap.
→L&D consulting
Learning strategy, content, technology and ROI measurement.
→OD consulting
Org design, succession planning and cultural change.
→Managed training services
Training outsourcing, vendor management, logistics and administration.
→Coaching solutions
Executive and manager coaching that keeps skills in use.
Start an RFP shaped to your needs.
Answer three quick questions about team size, scope, and how often you need the program run, then send the request from the last step. Everything you choose travels with it, so you only fill this in once.
How many team members need training?
Product Analytics & Experimentation Training Packages & Pricing
Where L&D holds an annual budget, license packages price the whole year at once instead of raising a purchase order per workshop. Hours and licenses are pooled across teams, programs and locations, so unused capacity is not stranded in one department.
Starter
120
trainee licenses64 hours of group training
Tailored for SMBs
Growth
320
trainee licenses160 hours of group training
Ideal for growing SMBs
Enterprise
800
trainee licenses400 hours of group training
Designed for large corporations
Custom
Unlimited
trainee licensesDuration set by the rollout
Multi-region and multi-year
Training Packages & Pricing
Choose the training format that works for your team. Pricing is customized based on your requirements, cohort size, and delivery needs.
Request Product Analytics and Experimentation Training for Your Team
Tell us about your product team, metrics, and analytics goals. We will tailor the program scope, schedule, and delivery format to your needs and share a group quote.