Web analytics 101 - Framework for Business Objectives & Data Analysis
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Web analytics 101 - Framework for Business Objectives & Data Analysis
- 1. Web Analytics Framework Bertrand Tay HP: 90062698 E-mail: bertay@gmail.com
- 2. Google Confidential and Proprietary Why Am I Here? 2
- 3. Google Confidential and Proprietary Digital Marketing Web Analytics Lead 3
- 4. Google Confidential and Proprietary 4
- 5. Google Confidential and Proprietary 5 Agenda 1 Web Analytics & Data Analysis 2 Data Analysis Example – PPHG Setup 3 Digital Marketing Model For Web Analysts 4 Takeaways
- 6. Google Confidential and Proprietary 3 Areas Of Web Analytics Expertise 6 Data Reporting Data Capture Data Analysis
- 7. Google Confidential and Proprietary Data Analysis Process 7
- 8. Google Confidential and Proprietary 1 Web Analytics & Data Analysis 2 Data Analysis Example – PPHG Setup 3 Digital Marketing Model For Web Analysts 4 Takeaways 8 Agenda
- 9. Google Confidential and Proprietary PPHG Web Analytics Overhaul 9 Can Web Analytics help to improve Occupancy rate, especially during off-peak seasons? Reports lack actionable insight
- 10. Google Confidential and Proprietary Analysing The Problem – Aggregate Data • Website & Ecommerce tracking was basic • Profiles were tracking only at an aggregate and country level • Not tracking loyal customers 10
- 11. Google Confidential and Proprietary Actionable Insights – 3 Examples • Track the usage of promotion codes during off-season periods • Create profiles to track at a member, property, country and aggregate level • Track the behaviour of each member type and their actions 11
- 12. Google Confidential and Proprietary Implementation – Opportunities For Insights • Implement tracking code to track promotion code type and usage • Profile set-up with appropriate logic and filters • Create Visitor-level Custom Variable to track each member type and their actions 12
- 13. Google Confidential and Proprietary Evaluation - Tracking Can Improve Occupancy Rate 1. Identify decrease in booking activity for each member type and take action 2. Run promotions, especially during the off-season periods, and measure each promotion’s effectiveness quickly and optimise accordingly 3. Made the value of each member segment measurable 4. Better understand the performance of each media channel for all objectives 5. Country Managers can now make sharp strategic decisions 13
- 14. Google Confidential and Proprietary 14
- 15. Google Confidential and Proprietary 1 Web Analytics & Data Analysis 2 Data Analysis Example – PPHG Setup 3 Digital Marketing Model For Web Analysts 4 Takeaways 15 Agenda
- 16. Google Confidential and Proprietary The Model 16 Business Objectives Website Goals KPIs Targets Data Analysis Fact-finding, understanding the business Translating BOs into digital solutions Goals (Metrics) Targeted improvement (x% increase) Segmentation (Traffic Acquisition, Behaviour, Outcomes) Provides clarity on what data to look at
- 17. clickTRUE Confidential and Proprietary CRO Redesign October 17 701Panduan
- 18. Private & Confidential 18 Business Search Conversion Funnel
- 19. Private & Confidential We expect to bring the number of completed enquiries back to 9% Objective – Generate Leads Lack Of Follow Through after “Ask Me” Button Optimisation • Overall Higher Conversion for “Ask Me” • However Lower Submitted Enquiries 9% 7% 5. Micro Conversions 5. Micro Conversions 3. Macro Conversion (KPI) 1. Business Objective 2. Website Goal 4. Target
- 20. Private & Confidential Objective – Increase Enquiries Fixing The Leaky Pipe • 3 Minor tweaks to address leaks Ask Me Completions Sales Lead Generation (Business Enquiry) 1) Lack Of Assurance 2) Com plicated fields 2) Unrelated fields
- 21. Private & Confidential Design Guideline 3 Minor Tweaks I. Reordering II. Adding Reassurance III. Simplifying Fields Prior Proposed
- 22. Private & Confidential Design Guidelines I. Reordering II. Adding Reassurance III. Simplifying Fields 1. Reordering to reassure function of form. Prior Proposed
- 23. Private & Confidential Design Guidelines I. Reordering II. Adding Reassurance III. Simplifying Fields 1. Prominent Titles 2. Text to convey information may be gained. - eg. “Like to know more about…” 1 2 1 2 Prior Proposed
- 24. Private & Confidential Design Guidelines 1 I. Reordering II. Adding Reassurance III. Simplifying Fields 1. Removal of Business Name Field 2. Removal of Subject Field 1 2 2 Prior Proposed
- 25. Private & Confidential I. Reordering II. Adding Reassurance III. Simplifying Fields Type of feedback to change to Type of enquiry. Default Setting as “General Enquiry”. Comments to change to Enquiry. Are you a business owner shifted below. Design Guidelines 1 2 3 4 1 2 3 4 2 1 3 4 Prior Proposed
- 26. Private & Confidential Design Guidelines - Variations Format Variations • To test on Generic First • Follow up on variations - (Require full listing) Restaurants Hotel Automobile
- 27. Private & Confidential Conclusion Greater Follow Through • 477 more submitted enquiries (35% increase) • Higher Submitted Enquiry 11% 7 %
- 28. Private & Confidential The Model 28 Business Objective Website Goal KPI Targets Data Analysis Generate leads for businesses Generate leads for businesses online Submitted Enquiry 15% increase in macro conversions Micro Conversions
- 29. Private & Confidential 1 Web Analytics & Data Analysis 2 Data Analysis Example – PPHG Setup 3 Digital Marketing Model For Web Analysts 4 Takeaways 29 Agenda
- 30. Google Confidential and Proprietary Key Takeaways • Web Analytics works best when business objectives and measurement expectations are clearly defined in advance. • Utilise the Data Analysis Process & Web Analytics Model for focus and clarity. • Focusing on Data analysis makes you a better web analyst • Never be afraid to take action on your insights as long as it’s to achieve the client’s business objectives. 30
- 31. Google Confidential and Proprietary 31
Editor's Notes
- I’m here as an interview candidate and this is my 2 nd interview. We’re having this sesssion because Angkea noticed that I’d done a Google Analytics 101 presentation for GA events in both Singapore and KL and hoped that it would be beneficial for the team.
- Introduction – Let’s introduce ourselves before we kick this off. I’ll start. I was a web Analytics Lead at clickTRUE I have worked on different verticals and have hands-on regional experience across various Digital Marketing Disciplines including SEM, Display, Social Media, Mobile, EDM and Web Analytics
- Analytics 101 is targeted towards offline marketers who are thinking of picking up Google Analytics, and you’re a digital marketing audience, I’ll be skipping a lot of stuff about the tool and talk more about Data Analysis and finding actionable insights. I don’t really know the level of experience here so I’m going to keep things very casual and interactive.
- There are 3 areas of expertise in web analytics. Data Capture is the coding and implementation of web analytics tracking. Data Reporting is where we update clients on their performance and sometimes unfortunately this is where we end up data puking. Analysing data is the fundamental stage of creating actionable insights. The process of doing so helps us add value to clients, and also improve our value of work in data capture and data reporting.
- There are 3 areas of expertise in web analytics. Data Capture is the coding and implementation of web analytics tracking. Data Reporting is where we update clients on their performance and sometimes unfortunately this is where we end up data puking. Analysing data is the fundamental stage of creating actionable insights. The process of doing so helps us add value to clients, and also improve our value of work in data capture and data reporting.
- Pan Pac wanted to overhaul their existing Web Analytics implementation because they felt that existing reports were just not insightful enough. For example, part of their core business is maximising daily room occupation. Empty rooms like these, no matter how warm and homely, it negatively affects their bottomline. So one of the key questions was: Can Web Analytics help to improve Occupancy rate, especially during off-peak seasons?
- So we noticed 3 significant problems with their existing setup. Web & Ecommerce tracking was basic. It was just the normal GATC implemented with the basic Ecommerce tracking codes placed at the thank you page of the booking journey. Also, profiles were only tracking at an aggregate and country level, so it was not as easy to measure an individual property’s performance Additionally, we found out from the client that a significant source of revenue were from loyalty program and alliance members, as well as agents. There was no web data available for these loyal customers and their behaviours.
- So we came up with 3
- So here are 3 of the implementations we decided on
- With just 3 implementations, we are now able to: Identify periods when each member types make their booking, and take action Run specific promotions, especially during the off-season periods Measure the value of each member segment. Measure the effectiveness of the various promotions Helps the Country Manager make strategic decisions with comparable property data All this from as low as a property-level perspective and upwards.
- Data Analysis is a challenging area of expertise because of all the potential roadblocks, possibilities and data overload. On top of that, we are expected to provide actionable insights that clients appreciate. Especially when there‘s a lack of clarity on objectives, we will tend to feel this way Over the next few minutes, I‘ll share with you an example of analysis work I did for a client and hopefully you‘ll get some insights from it.