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mayank-dhingra
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What is Product Analy.cs
Product analy.cs are the computa.onal analyses of data about a product. • Passive data (not explicitly under your control) • Ac.ve data (generated from your product that you have explicitly decided to capture)
Analy.cs Concepts 1. Segmenta.on – Grouping on a characteris.c (Event & Customer) 2. Funnels – Connec.ng mul.ple events together to analyze the en.re path 3. Cohorts -‐ Groups of customers that have a common characteris.c within a specified .me period (Engagement & Reten.on)
Analy.cs Implementa.on
1. Define Product Vision – What is the problem the product is solving for the user?
2. Define KPIs that meet the Product Vision – KPIs are derived from the product vision and tell you how well your product is mee.ng the vision.
3. Define the metrics that allow you to hit your KPIs -‐ Metrics are what you can manipulate to hit the targets set by KPIs
4. Define the funnels (via user journeys) that affects your metrics -‐ Important are the ones that change the metrics in some manner
Metrics
• Good Metrics are Compara.ve & Understandable • Qualita.ve vs Quan.ta.ve Metrics • Vanity vs Ac.onable Metrics • Exploratory vs Repor.ng Metrics • Leading vs Lagging Metrics • Correlated vs Causal Metrics
Aha! Moments
1. Twiaer -‐ Following 30 people 2. Facebook – 7 Friends in 10 days 3. Zynga – Day 1 Reten.on 4. Dropbox – First File Upload Categories of Aha! Moments 1. Network Density 2. Content Added 3. Visit/Usage Frequency