MBA Marketing Analytics: KPIs, Funnels & Customer Insights

Explore why measuring key performance indicators (KPIs) and metrics matters for product managers and founders, using dashboards to track sales, retention rate, traffic, and ROI, and to make informed decisions.

Learn the AARRR framework—acquisition, activation, retention, revenue, and referral—as a five-step funnel to analyze user behavior and revenue for product-led growth.

Apply the pirate metric framework (AARRR) to a grocery delivery app, mapping awareness, acquisition, activation, engagement, retention, revenue, and referral to optimize onboarding and cross-team collaboration.

Learn to track 60+ product metrics across acquisition, signup, engagement, monetization and retention, using a practical Excel sheet and Google sheet with Mixpanel to optimize growth.

Explore user acquisition by identifying target audiences, comparing organic and paid channels, and measuring cost per new user to assess its value and impact on lifetime value.

Learn how to acquire users by identifying the right audience, using diverse marketing channels (organic and paid), and tracking costs, smiles, and referrals across the customer journey.

Learn key user acquisition metrics: customer acquisition cost, conversion rate, time to first order, and optimize channels from app store optimization to paid campaigns for growth.

Explore modern marketing funnels from awareness to retention, tracking acquisition, behavior, and conversion with metrics like impressions, bounce rate, session duration, and app installs.

Learn to calculate customer acquisition cost (CAC) from marketing, sales, and related costs, compare it with lifetime value (LTV) and payback period, and analyze per-channel CAC performance for optimal ROAS.

Understand cost-based metrics for performance marketing, including CPM, CPC, cost per lead, and cost per acquisition, with bidding, impressions, and platform examples.

Explore how CAC and lifetime value drive profitability using the LTV to cake ratio. Apply average order value, monthly orders, gross margin, and customer lifespan insights for grocery delivery apps.

Break down tofu, mofu, and bofu to measure awareness, leads, and revenue, then optimize return on ad spend across platforms by refining titles, keywords, and bids.

Analyze marketing campaign performance for a grocery app by calculating ROI, ROAS, CTR, and signup and purchase conversion rates across email, social, pay-per-click (ppc), affiliate, and influencer campaigns.

Analyze how discount levels affect customer acquisition cost, sign-ups, purchases, and discounted ROI for a grocery app, using campaign types like email, social media, PPC, and influencers.

Analyze the funnel from impression to sign up to calculate conversion rates for each campaign across platforms, identifying where drop-off occurs and which campaign yields the most signups.

Explore channel attribution analysis to reveal how multiple touchpoints across acquisition sources contribute to revenue and calculate total revenue, user counts, and average revenue per user with pivot tables.

Segment new users by acquisition source to compare sign-ups and purchases, and analyze conversion rate, average order value, and time to first purchase.

Analyze three months of grocery app signup data to identify patterns. Compute total signups by acquisition source and average daily signups by month.

Compare landing page variants A and B through an A/B test, measuring clicks, signups, purchases, time on page, and revenue, and analyze results with pivot tables and Sumif/Averageif formulas.

Analyze how discounts impact acquisition by tracking campaign sources, impressions, clicks, sign ups, purchases, and revenue; then compute total spending, revenue, CTR, sign-up rate, ROI with pivot tables.

Introduces market segmentation, explains why it's important, and explores demographic, behavioral, and psychographic segmentation, plus k-means clustering, RFM and LTV segmentation, and customer personas, with a case study.

Learn the four core segmentation types—demographic, geographic, behavioral, and psychographic—and how to personalize messages, target campaigns, and drive engagement, retention, and revenue with RFM and LTV insights.

Explore how to segment customers by value with RFM analysis, scoring recency, frequency, and monetary spend to drive loyalty and revenue.

Explore RFM analysis to segment ecommerce customers by recency, frequency, and monetary value, identifying high-value, loyal, at-risk, and lost segments to optimize retention and marketing spend.

Segment 10,000 customers into five rfm bands and run tailored campaigns: champions with vip offers, at-risk reactivation, new customers cross-sell, and dormant revival, to boost retention and revenue.

Explore revenue and monetization concepts for a grocery delivery app. Learn about average revenue per user, lifetime value, CAC, gross and contribution margins, and RFM-based loyalty.

Build a strong foundation on average revenue per user (arpu), how to calculate it, and how upsell, cross-sell, subscriptions, bundling, and dynamic pricing boost arpu in grocery apps.

Calculate customer lifetime value by multiplying average order value, order frequency, and customer lifespan, then adjust for gross margin. Boost retention and revenue with loyalty, subscriptions, cross-selling, upselling, and bundling.

Understand the customer acquisition cost (CAC): its formula, how it links to LTV, industry benchmarks, and tactics to lower CAC through organic growth, referrals, and optimized campaigns.

Analyze break-even timing and cost structures by examining revenue, COGS, gross profit, and EBITDA. Explore the roles of CAC, ARPU, and LTV alongside contribution and gross margins to maximize profitability.

Explore unit economics to analyze per unit cost and profit, covering revenue, variable and fixed costs, margins, CAC, and strategies to optimize profitability and scalability.

Explore how marketplace growth boosts product value through liquidity and network effects, lowers CAC, raises lifetime value, and balances capital for sustainable, profitable scaling.

Learn how normalization converts diverse scales into a common 0-to-1 framework, applying direct and inverse normalization for multi-factor scoring in marketing analytics.

Evaluate Facebook, TikTok, and Instagram campaigns by computing customer acquisition cost, return on ad spend, and 30-day retention; apply normalization to build a campaign score and identify top performers.

Discover how events, event properties, and profiles power product analytics across tools like Mixpanel, using a simple birthday party example to show event sequences and associated properties.

Explore how Mixpanel tracks events, event properties, and profile properties using a demo e-commerce dataset to map the user journey from sign up to purchase.

Master Mixpanel insight reports to analyze time-series events, properties, and profiles, explore four analytics lenses—insight, funnel, flows, retention—and build metrics and cohorts for ecommerce revenue.

Learn how to build funnel reports in Mixpanel, mapping events and properties across steps, tracking conversion rates and drop-off. Break down funnels by device, region, filters, save funnel metrics.

Analyze retention and funnels using Mixpanel’s flow report to visualize how users move from signup to purchase, and identify which pages drive conversions in an e-commerce app.

Explore how flows report in Mixpanel traces user journeys, then read weekly retention cohorts to see how first-time purchasers return and buy again.

learn to build an e-commerce kpi dashboard in Mixpanel, tracking revenue over time, average order value, arpu, and funnel metrics from views to purchases, with cohort insights.

Explore a data-driven dynamic discounting approach for e-commerce, using price sensitivity, user segments, cart value, and profitability to optimize conversions and margins.

Explore building a real-time pricing engine for a hotel booking app, using demand pressure, occupancy, events, and season multipliers to adjust prices dynamically.