Google (digital) analytics

Descrição

Mapa Mental sobre Google (digital) analytics, criado por Arun Shiva em 11-03-2015.
Arun Shiva
Mapa Mental por Arun Shiva, atualizado more than 1 year ago
Arun Shiva
Criado por Arun Shiva mais de 9 anos atrás
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Resumo de Recurso

Google (digital) analytics
  1. Definition: 1) the analysis of qualitative and quantitative data from your website and the competition, (2) to drive a continual improvement of the online experience that your customers, and potential customers have, (3) which translates into your desired outcomes (online and offline).
    1. Quantitative date --> customer data across all customer touch points (eg: game consoles, mobile, tablet, refridgerators etc)
      1. Qualitative --> collect the date through survey
        1. Business objectives
          1. E-commerce
            1. Lead generation
              1. collecting customercontact information for sales leads
                1. Online info/support
                  1. Help customers find the information
                    1. Branding
                      1. Drive awareness
                        1. Content publishing
                          1. Ads shown to visitors for customer engagement
                    2. Sell products
                    3. Outcomes
                      1. Conversions
                        1. Macro-conversions
                          1. Eg: purchase complete action
                          2. Micro-conversions
                            1. Behavioural indicators (eg: Sign up for email coupons or newsletters
                              1. Behavioural datas
                          3. Outcomes of objectives
                          4. Continual Improvement
                            1. Collecting data (MEASURE)
                              1. Reporting of data (DASH BOARDS)
                                1. DATA analysis (competitive analysis for benchmarking to Industry benchmark) --> developing hypothesis
                                  1. Testing --> discovering improvement opportunities
                          5. Core analysis techniques
                            1. Segmentation
                              1. To analyse the subsets of the data
                                1. USES -->What caused the change to the aggregated data?
                              2. Context
                                1. To review performance : Is it Good or Bad?
                                  1. Internal
                                    1. Historical - internal data
                                    2. External
                                      1. Industry benchmark data
                                  2. Consumer journey: Measurement
                                    1. Conversions
                                      1. Micro & Macro
                                      2. Conversions attributions
                                        1. Attribution is assigning credit for a conversion
                                          1. Last-click attributions
                                            1. last mareketing activity gets all the credit
                                              1. Ist click attribution
                                                1. Assigning all the revenue on the Ist channel (eg: customer journey start place--> search ads)
                                          2. Measurement plan
                                            1. Step 1. Business objectives
                                              1. step 2. Identify strategies and tactics
                                                1. Step 3. Choose KPI's
                                                  1. Step 4: Choose segments
                                                    1. Step 5: Targets
                                                    2. Measurement of Strategies and tactics
                                                2. Planning : 5 stages
                                                  1. Stage 1: Define measurement plan
                                                    1. Stage 2: Technical Infrastructure
                                                      1. Query string parameters, Server redirects, Flash and Ajax events, multiple sub-domains and responsive web design
                                                        1. Stage 3: Implementation plan
                                                          1. Stage 4: Implement --> reliable, accurate data
                                                            1. Stage 5: Maintain and refine
                                                            2. Standard dimensions --> basic page tag
                                                              1. Business outcomes --> goals & ecommerce
                                                                1. clean and accurate data --> filters/settings
                                                                  1. Marketing channels --> campaign tracking and adwords linking
                                                                    1. Simplified reporting --> customer reports and dashboards
                                                                  2. Objectives, goals, KPI's and target to be measured --> Marketing team
                                                              2. How Google analytics works
                                                                1. 1. Data collection
                                                                  1. Dimensions -> QUALITATIVE data (user characteristics, actions and their sessions)--> behavioural data
                                                                    1. eg: User--> geographical data, session dimension--> traffic source
                                                                    2. Metrics --> QUANTITATIVE data (user characteristics, actions and their sessions)
                                                                      1. Numerical data
                                                                        1. Audience metrics (eg: No. of visitors
                                                                          1. Behaviour metrics (eg: avg number of pages user sees during a session)
                                                                            1. Conversion metrics (eg: conversion rate)
                                                                        2. 2. Configuration
                                                                          1. 3. Processing
                                                                            1. 4. reporting

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