Webinar Strategy — 15 Episodes

The Complete AI Consulting
Webinar Blueprint

A start-to-finish consulting simulation across 15 episodes. One running use case. From understanding the business to delivering the final solution — exactly how real consulting works.

Design Philosophy

Why this is radically different

Every other webinar series teaches tools in isolation — "here's how to use Power BI," "here's how to build an LLM app." IntelliBridge's consulting series is structured as a single end-to-end consulting engagement that unfolds over 15 episodes.

Learners don't just watch — they role-play as the consultant. They receive a client brief, run discovery calls, procure and clean data, build solutions, and present to stakeholders. By the end, they have a complete consulting case study in their portfolio — not a certificate, but proof they can do the job.

The series follows the real consulting lifecycle used by firms like Deloitte, EY, and McKinsey — adapted for solo/freelance consultants working with Indian SMEs and startups.

🛍️

Running Use Case: GlowKart

GlowKart is a fictional Indian D2C beauty brand doing ₹8Cr ARR. They sell via Shopify + Amazon India + their own app. They've raised Series A and their investors want data-driven growth — but the founder has no analytics team. They've hired you as their first Data & AI consultant.

Across 15 episodes, you'll take GlowKart from zero data maturity to a fully operational analytics + AI stack — dashboards, customer segmentation, demand forecasting, AI chatbot, and executive reporting. The datasets, Slack messages, emails, and stakeholder profiles are all pre-built for realistic simulation.

D2C / E-commerce ₹8Cr ARR Shopify + Amazon Series A No data team Indian market
Journey Map

5 Phases. 15 Episodes. One engagement.

Each phase mirrors a stage of a real consulting project — the exact sequence a working consultant follows.

1–3
Discovery & Scoping
4–6
Data Procurement
7–10
Solution Build
11–13
Delivery & Handoff
14–15
Scale Your Practice
I

Phase 1 — Discovery & Scoping

Episodes 1–3 · Before you touch any data, you need to understand the business
EP 01
The AI Consulting Landscape & Your First Client Call

Set the stage: what does a Data & AI consultant actually do? How is it different from being a Data Scientist employee? Then simulate your very first "discovery call" with GlowKart's founder — learning to ask the right questions, not jump to solutions.

What You'll Learn
  • AI consulting market in India — size, demand, salary bands (₹15L–40L+)
  • Freelance vs embedded vs agency models — pros/cons of each
  • The consulting mindset: "problems first, tools later"
  • How to run a discovery call — the 12 questions that matter
  • Reading between the lines: what the client says vs what they need
Live Exercise
  • Role-play: "Discovery call with GlowKart founder Priya Mehra"
  • Pre-recorded video of Priya describing her problems (actors/script)
  • Learners take notes, identify pain points, flag red flags
  • Group debrief: what did you catch? What did you miss?
📄 Deliverable: Discovery Call Notes Template + GlowKart Pain Point Map
⏱ 90 min 🎯 Beginner-friendly 📍 No technical pre-req
EP 02
Understanding the Business: Metrics, KPIs & Data Maturity

Before you propose any solution, you need to understand how GlowKart makes money. Dive into D2C unit economics, key metrics (CAC, LTV, AOV, repeat rate), and assess their current data maturity level using a structured framework.

What You'll Learn
  • D2C business model deep-dive: how Indian D2C brands work
  • Key metrics every consultant must know: CAC, LTV, AOV, contribution margin
  • Data Maturity Assessment Framework (5-level model)
  • Mapping business problems to data solutions
  • Stakeholder mapping: who has influence, who has budget
Live Exercise
  • Score GlowKart on the Data Maturity Framework (they'll score ~Level 1.5)
  • Build a stakeholder map: Founder, Marketing Head, Ops Lead, Investor
  • Identify top 3 "quick win" opportunities vs long-term bets
  • Draft: "Here's what I think your top 3 problems are" email to the founder
📄 Deliverable: Data Maturity Scorecard + Problem Prioritization Matrix
⏱ 90 min 🎯 Business thinking 📍 No code
EP 03
Writing the Proposal: SOW, Pricing & Project Plan

Now you convert your discovery into a formal proposal. Learn how to write a Statement of Work (SOW), structure milestones, estimate effort in hours, and price the engagement — with specific guidance on Indian freelance/consulting rates.

What You'll Learn
  • Anatomy of a consulting SOW: scope, deliverables, timeline, pricing, exclusions
  • Pricing models: fixed-fee vs time & material vs retainer vs value-based
  • Indian market rates: ₹1,500–5,000/hr freelance, ₹2L–10L project-based
  • Milestone-based billing: how to protect yourself and the client
  • Red flags in client conversations that signal scope creep
  • Terms & conditions: payment terms, IP ownership, NDAs for India
Live Exercise
  • Write a real SOW for GlowKart — 3-month engagement, 3 phases
  • Phase 1: Data foundation & dashboards (₹1.5L)
  • Phase 2: Customer analytics & segmentation (₹2L)
  • Phase 3: AI chatbot + recommendation engine (₹3L)
  • Peer review: swap SOWs and critique each other's pricing & scope
📄 Deliverable: Complete GlowKart SOW (reusable template) + Pricing Calculator Sheet
⏱ 90 min 🎯 Critical consulting skill 📍 Google Docs / Notion
II

Phase 2 — Data Procurement & Foundation

Episodes 4–6 · The client said yes. Now you need to find, extract, clean, and structure the data.
EP 04
Data Audit: What Exists, What's Missing, What's Broken

Your first week at GlowKart. You're given access to their Shopify admin, Google Analytics, a bunch of Google Sheets, and "some data in an Excel file Rahul maintains." This is reality — and your job is to audit what's usable, what's garbage, and what's missing entirely.

What You'll Learn
  • The Data Audit Framework: sources, schemas, quality, freshness, gaps
  • Common data sources for Indian D2C: Shopify, Razorpay, Shiprocket, Meta Ads, GA4
  • How to interview non-technical teams about their data ("Where does this number come from?")
  • Data quality scoring: completeness, accuracy, consistency, timeliness
  • Creating a Data Catalog from scratch
Live Exercise
  • Provided: GlowKart's actual messy data exports (Shopify orders CSV, GA4 export, Meta Ads report, Google Sheets inventory tracker)
  • Audit each source: schema, row counts, missing values, date ranges
  • Build a Data Catalog in a spreadsheet
  • Write a "Data Readiness Report" for the founder: "Here's what we have, here's what we need"
📄 Deliverable: Data Audit Report + Data Catalog Template
⏱ 90 min 🎯 Hands-on data work 📍 Python / Excel / SQL
EP 05
Data Extraction & Pipeline Design

Now that you know what data exists, you need to extract it, centralize it, and build a lightweight pipeline that the client can maintain after you leave. This is where consulting differs from being an employee — you build for handoff, not for yourself.

What You'll Learn
  • API-based extraction: Shopify REST API, Razorpay API, Meta Marketing API
  • Flat file extraction: CSV exports, Google Sheets API, email-attached reports
  • Designing a "good enough" pipeline for SMEs (not enterprise overkill)
  • Storage options for Indian SMEs: Google BigQuery (free tier), PostgreSQL, Supabase
  • Schema design: star schema basics for analytics
  • Documentation for handoff: the "runbook" concept
Live Exercise
  • Extract GlowKart's Shopify orders via API (Python script)
  • Load into a PostgreSQL/BigQuery staging table
  • Build a simple transformation: raw orders → clean fact_orders table
  • Write a 1-page "Data Pipeline Runbook" for GlowKart's ops team
📄 Deliverable: Working Python ETL Script + Pipeline Runbook
⏱ 120 min 🎯 Technical depth 📍 Python, SQL, APIs
EP 06
Data Cleaning, Transformation & The "Single Source of Truth"

GlowKart's data is now centralized — but it's still messy. Duplicate orders, inconsistent product names, missing customer emails, timezone mismatches between Shopify and GA4. Clean it, transform it, and build the single source of truth the whole company will use.

What You'll Learn
  • Data cleaning patterns: deduplication, null handling, type casting, outlier treatment
  • Joining data across sources: matching Shopify customers with GA4 sessions
  • Building dimension tables: dim_customers, dim_products, dim_dates
  • Creating derived metrics: LTV, cohort labels, RFM scores
  • Data validation: writing assertions and tests (dbt-style thinking)
  • Version control for data: why and how
Live Exercise
  • Clean GlowKart's orders data: fix duplicates, standardize product categories
  • Build dim_customers with derived fields (first purchase date, total orders, LTV)
  • Create an RFM segmentation from scratch using SQL
  • Validate: write 5 data quality checks and run them
📄 Deliverable: Clean Analytics Schema + Data Dictionary + RFM Table
⏱ 120 min 🎯 Data engineering mindset 📍 SQL, Python, dbt concepts
III

Phase 3 — Solution Build

Episodes 7–10 · Data is ready. Now build the solutions the client is paying for.
EP 07
Executive Dashboard: The First "Wow" Moment

The fastest way to prove value as a consultant is a dashboard the founder checks every morning. Build GlowKart's executive dashboard — revenue, orders, CAC, LTV, top products — with drill-downs for the marketing and ops teams.

What You'll Learn
  • Dashboard design thinking: what does the CEO need vs what the marketing team needs
  • The "5-second rule" — if the insight isn't obvious in 5 seconds, redesign
  • KPI hierarchy: north star → supporting metrics → diagnostic metrics
  • Power BI or Streamlit: choosing the right tool for the client's team
  • Connecting live data sources to dashboards
  • Mobile-first design for founders who check on their phone
Live Exercise
  • Build GlowKart's executive dashboard with: revenue trend, daily orders, CAC by channel, product mix, cohort retention chart
  • Add a marketing view: channel-wise spend vs revenue, ROAS
  • Add an ops view: fulfillment SLA, return rate, inventory alerts
  • Present it as you would to the founder — live practice
📄 Deliverable: Working Dashboard (Power BI / Streamlit) + Dashboard Spec Doc
⏱ 120 min 🎯 High-impact delivery 📍 Power BI / Streamlit
EP 08
Customer Segmentation & Cohort Analysis

GlowKart's marketing head asks: "Who are our best customers? Who should we target for repeat purchases? Who's about to churn?" This is where you go beyond dashboards and deliver analytical insights that directly influence marketing spend.

What You'll Learn
  • RFM segmentation → actionable customer personas
  • Cohort analysis: monthly cohort retention curves
  • Churn prediction: defining churn for D2C (no subscription = tricky)
  • Building a simple ML model for churn likelihood (logistic regression / XGBoost)
  • Translating model output into business recommendations
  • "So what?" — the consultant's most important question
Live Exercise
  • Run RFM segmentation on GlowKart customers → 5 named segments
  • Build cohort retention chart → identify drop-off month
  • Train a churn prediction model → identify top 500 at-risk customers
  • Write a 1-page "Customer Intelligence Brief" for the marketing head
📄 Deliverable: Customer Segments + Churn Model + Intelligence Brief
⏱ 120 min 🎯 Analytics + ML 📍 Python, Pandas, Scikit-learn
EP 09
Demand Forecasting & Inventory Intelligence

GlowKart's ops lead is drowning — overstocking slow SKUs, running out of bestsellers. Build a demand forecasting model and an inventory alert system that saves the company real money. This is the kind of project that gets you referrals.

What You'll Learn
  • Time series forecasting for D2C: seasonality, promotions, new launches
  • Model selection: ARIMA vs Prophet vs LightGBM for demand
  • SKU-level forecasting: handling long-tail products
  • Reorder point calculation and safety stock logic
  • Building an automated alert: "These 12 SKUs will stockout in 8 days"
  • ROI framing: "This model saves GlowKart ₹15L/year in dead stock"
Live Exercise
  • Build a Prophet model on GlowKart's top 20 SKUs
  • Generate 30-day demand forecast per SKU
  • Calculate reorder alerts with safety stock buffer
  • Build a simple Streamlit app: "Inventory Intelligence Dashboard"
📄 Deliverable: Forecasting Model + Inventory Alert App + ROI Summary
⏱ 120 min 🎯 Applied ML 📍 Python, Prophet, Streamlit
EP 10
AI Chatbot & Recommendation Engine for GlowKart

The "Phase 3" deliverable — build an AI-powered customer support chatbot (WhatsApp-ready) and a simple product recommendation engine. This is the highest-value, most impressive deliverable in the engagement and the centerpiece of your consulting portfolio.

What You'll Learn
  • RAG architecture for customer support: knowledge base → retrieval → response
  • Building a product FAQ chatbot using Gemini/OpenAI API + vector store
  • Handling Indian use cases: Hinglish queries, regional language fallback
  • Product recommendation: collaborative filtering on purchase history
  • WhatsApp integration pathway (Twilio / Meta Business API)
  • Cost estimation: API costs at GlowKart's query volume
Live Exercise
  • Build a Streamlit chatbot with GlowKart's FAQ + product catalog as knowledge base
  • Add a recommendation module: "Customers who bought X also bought Y"
  • Test with 10 real-world queries (including Hinglish ones)
  • Estimate monthly API cost for 5,000 queries/month
📄 Deliverable: Working Chatbot + Recommendation Engine + Cost-Benefit Analysis
⏱ 150 min 🎯 GenAI applied 📍 Python, LLM APIs, RAG, Streamlit
IV

Phase 4 — Delivery, Handoff & Stakeholder Management

Episodes 11–13 · The work is done. Now present it, hand it off, and close the engagement properly.
EP 11
The Consulting Presentation: Storytelling with Data

You've built dashboards, models, and an AI chatbot. Now you need to present all of it to GlowKart's founder and their investors in a 30-minute session. This episode teaches the art of consulting storytelling — the "so what" that makes clients pay for the next engagement.

What You'll Learn
  • The Pyramid Principle: answer first, then evidence (McKinsey framework)
  • Structuring a consulting deck: situation → complication → resolution
  • Data visualization for non-technical audiences: less is more
  • Handling tough questions: "How confident are you in this model?"
  • Presenting ROI: framing everything in rupees saved or earned
  • The "leave-behind" — a 2-page executive summary for the investor
Live Exercise
  • Build a 15-slide consulting deck for GlowKart (template provided)
  • Present to the group — 10-minute presentation + 5-minute Q&A
  • Peer feedback: "Would you pay for the next phase after seeing this?"
  • Write a 2-page executive summary for GlowKart's board
📄 Deliverable: 15-Slide Consulting Deck + 2-Page Executive Summary
⏱ 120 min 🎯 Communication mastery 📍 Google Slides / Canva
EP 12
Handoff, Documentation & Making Yourself Replaceable

A great consultant builds solutions the client can maintain without them. This episode covers how to document everything, train the client's internal team, and hand off cleanly — while positioning yourself for a retainer or the next phase.

What You'll Learn
  • Technical documentation: what to document, how much detail, what format
  • Training the client's team: running a "knowledge transfer" session
  • Code handoff: repo structure, README, environment setup guide
  • Dashboard maintenance guide: "If this breaks, do this"
  • The paradox: making yourself replaceable is what makes clients keep you
  • Positioning for Phase 2: "Here's what I'd recommend next"
Live Exercise
  • Write a README for the GlowKart analytics repo
  • Create a "Maintenance Playbook" for the dashboard and chatbot
  • Draft a "Phase 2 Proposal" email: next engagement ideas + pricing
  • Role-play: the handoff meeting with GlowKart's newly hired analyst
📄 Deliverable: Handoff Docs + Maintenance Playbook + Phase 2 Proposal Draft
⏱ 90 min 🎯 Professional maturity 📍 Docs, GitHub, email
EP 13
Closing the Engagement: Invoicing, Testimonials & Case Studies

The engagement is done. Now close it properly — send the final invoice, collect a testimonial, write a case study for your portfolio, and request referrals. This "last mile" is what separates consultants who get one client from those who build a practice.

What You'll Learn
  • Final invoicing: GST for freelance consultants in India, payment terms
  • How to ask for a testimonial (the exact email template)
  • Writing a portfolio case study: STAR format for consulting
  • Requesting referrals without being awkward
  • Post-engagement follow-up: 30-60-90 day check-ins
  • Turning one project into three: the referral flywheel
Live Exercise
  • Generate a GST-compliant invoice for the GlowKart engagement
  • Write the GlowKart case study for your portfolio (template provided)
  • Draft a testimonial request email to Priya Mehra
  • Draft a referral ask: "Know anyone else who needs this?"
📄 Deliverable: GST Invoice Template + Portfolio Case Study + Referral Email Templates
⏱ 90 min 🎯 Business operations 📍 Docs, spreadsheets
V

Phase 5 — Scale Your Consulting Practice

Episodes 14–15 · You've completed one engagement. Now build a sustainable practice.
EP 14
Building Your Brand & Finding Clients

GlowKart is one client. You need a pipeline. This episode covers personal branding, portfolio websites, LinkedIn positioning, Upwork/Toptal strategy, cold outreach, and how to sell to Indian SMEs and startups who don't even know they need a data consultant.

What You'll Learn
  • Personal brand architecture: "I help [audience] do [outcome] using [method]"
  • Portfolio website: what to include, what to skip (live reviews)
  • LinkedIn strategy for consultants: content, DMs, inbound
  • Upwork / Toptal / Contra: creating winning profiles & proposals
  • Cold outreach to Indian SMEs: the email, the WhatsApp message, the follow-up
  • Pricing psychology: why charging more gets you better clients
  • Networking: local startup events, founder communities, referral circles
Live Exercise
  • Write your LinkedIn headline + "About" section (consultant positioning)
  • Draft 3 cold outreach messages for different types of clients
  • Create an Upwork profile + 1 sample proposal for a real gig listing
  • Peer review: live critique of learner portfolios & LinkedIn profiles
📄 Deliverable: LinkedIn Profile Copy + Cold Outreach Templates + Upwork Profile
⏱ 120 min 🎯 Growth & sales 📍 LinkedIn, Upwork, Portfolio site
EP 15
From Solo Consultant to Micro-Agency: Scaling & Productizing

The final episode. You've landed clients and delivered results. Now think bigger: productizing your services, building a small team, creating recurring revenue, and eventually building a micro-agency. Featuring a guest — an Indian AI consultant who's made this journey.

What You'll Learn
  • Productizing services: "Data Audit Package" → "Analytics Setup Package" → "AI Chatbot Package"
  • Recurring revenue models: monthly retainers, maintenance contracts, "AI-as-a-Service"
  • Building a team: hiring freelancers, managing delivery, QA
  • Scaling from ₹5L/year to ₹25L+/year: the levers
  • When to register a company: LLP vs Pvt Ltd in India
  • Long-term vision: consulting → SaaS → product
Live Exercise + Guest Session
  • Design your 3-tier service menu with pricing
  • Draft a retainer proposal for GlowKart (₹50K/month ongoing support)
  • Guest AMA: An Indian AI consultant shares their journey, mistakes, and advice
  • Final portfolio review: present your complete GlowKart case study to the cohort
📄 Deliverable: Service Menu + Retainer Template + Complete Portfolio Case Study
⏱ 150 min 🎯 Entrepreneurship 📍 Guest speaker + workshop
At a Glance

All 15 episodes at a glance

Ep Title Phase Key Deliverable Duration
01First Client Call & AI Consulting LandscapeDiscoveryDiscovery Notes Template90 min
02Business Understanding: Metrics & Data MaturityDiscoveryData Maturity Scorecard90 min
03Writing the Proposal: SOW, Pricing & PlanDiscoveryComplete SOW + Pricing Sheet90 min
04Data Audit: What Exists, What's MissingDataData Audit Report + Catalog90 min
05Data Extraction & Pipeline DesignDataETL Script + Pipeline Runbook120 min
06Data Cleaning & Single Source of TruthDataClean Schema + Data Dictionary120 min
07Executive Dashboard: The First "Wow" MomentBuildWorking Dashboard + Spec Doc120 min
08Customer Segmentation & Cohort AnalysisBuildSegments + Churn Model + Brief120 min
09Demand Forecasting & Inventory IntelligenceBuildForecast Model + Alert App120 min
10AI Chatbot & Recommendation EngineBuildWorking Chatbot + Cost Analysis150 min
11Consulting Presentation: Storytelling with DataDelivery15-Slide Deck + Exec Summary120 min
12Handoff, Documentation & Knowledge TransferDeliveryHandoff Docs + Phase 2 Proposal90 min
13Closing: Invoicing, Testimonials & Case StudiesDeliveryInvoice + Case Study + Templates90 min
14Building Your Brand & Finding ClientsScaleLinkedIn + Outreach + Upwork Profile120 min
15Solo Consultant → Micro-AgencyScaleService Menu + Retainer Template150 min

By Episode 15, every learner has:

A complete consulting case study (GlowKart) in their portfolio with working code, dashboards, ML models, an AI chatbot, a consulting deck, and all business templates (SOW, invoices, proposals). Plus the skills and confidence to go find their first real client.

IntelliBridge · Data & AI Consulting Webinar Blueprint · April 2026