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Chapter 12 Measuring Brand Awareness, Campaign Evaluation and Web Analytic

Chapter 12 Measuring Brand Awareness, Campaign Evaluation and Web Analytic. Learning objectives. Understand why it is important to measure brand awareness Identity the indicators to use for campaign and brand evaluation Learn about web analytics and its relevant tools and concepts

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Chapter 12 Measuring Brand Awareness, Campaign Evaluation and Web Analytic

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  1. Chapter 12 Measuring Brand Awareness, Campaign Evaluation and Web Analytic

  2. Learning objectives • Understand why it is important to measure brand awareness • Identity the indicators to use for campaign and brand evaluation • Learn about web analytics and its relevant tools and concepts • Understand basic metrics and their correlations with business objectives

  3. Digital Marketing

  4. Measurement in digital marketing • Measurement and evaluation: feedback mechanism for improvement of activities • Conversion • Natural conversion • Transacted conversion

  5. Measurement in digital marketing • Brand awareness – importance • High levels of brand awareness do not always directly correlate to higher levels of conversion • Building sustainable brand (including in a digital sphere) takes time

  6. Web Analytics

  7. Introduction to Web Analytics • Origin Data Mining • Web Analytics Definition objective tracking, collection, measurement, reporting, and analysis of quantitative Internet data to optimize websites and web marketing initiatives” (Web Analytics, 2006) • Improvingwebsite design • Evaluating online marketing initiatives

  8. Introduction to Web Analytics • Data must be brought into context • Web Analytics tools to capture data • Business objectives as goals • Analysis and interpretation by humans • Data collection methods • Log files • JavaScript Taggiing • Web Beacons • Packet Sniffing

  9. Web Analytics Market • Many tools available: difficult to distinguish • Separation • Data storage • Control of data • Open source vs commercial • Saas or in-house installation • Support • Biggest companies with 75% of market penetration (2009) • Adobe • Google (most used) • IBM • Webtrends

  10. Web Analytics Process Framework

  11. Web Analytics Process Framework • Business Requirements • information needs analyses • information architecture audit • Planning for Web Analytics • building of knowledge about Web Analytics metrics analysis possibilities • identification of needs • mapping to a suitable tool • Developing a Data Collection Capability • implementing and setting up the tool • Generating value through Web Analytics • pattern analysis and reporting: statistics and reports • action taking • Evaluation of Actions • Evaluating and monitoring • benchmarking metrics

  12. Key Performance Indicators (KPIs) • Metrics: defined measurable attributes • most important metrics: KPIs • KIPs depend on the goals of your organization • Examples • conversion rate • customer loyalty • bounce rate

  13. Google Analytics Example • standard Google Analytics layout and menu • example of an behavior flow of an example website.

  14. Reports and campaign tracking

  15. Reports and campaign tracking • The need of proper campaign tracking and reporting – measuring the results • Campaign tracking tools: • Google Analytics (the most popular) • Facebook Insights • LinkedIn Insights • YouTube Analytics • Others

  16. Reports and campaign tracking • UTM parameters: short texts to the end of a URL in order to depict and track the success of marketing campaign • Five parameters of UTM: • Campaign • Source • Medium • Content • Term

  17. Ethical dilemmas • The ethical considerations in marketing research are closely related with the concept of privacy. • Four aspects of information exchange: • Information requests and disclosures statements • Information provision and marketing contact • Information capturing without consent • Information practices

  18. Quantitative data analysis methods • The main quantitative data methods used are: • Regression Analysis • Correlation Analysis • Hypothesis Testing • The importance of sample size

  19. Qualitative data analysis methods • The main qualitative analysis methods are: • Focus groups • Interviews • Online ethnography

  20. Conclusion • Developing successful brands and campaigns needs proper analytics activities and evaluation. • Adopting research methodologies and practices in an ethical manneris also core objective for digital marketeers.

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