Summary: Digital Analytics Fundamentals

Read the summary and the most important questions on Digital Analytics Fundamentals

• 2 Unit 2

• 2.1 The importance of digital analytics

• What are the major trends that are driving change for every business

  1. The internet makes information and media available at the click of a button
  2. Mobile connects nearly everyone 24x7
  3. Cloud computing provides cheap practically infiinte computing power

• So what do we mean when say "digital analytics"?

  a) Digital analytics is the analysis of qualitative and quantitative data from your business and the competition
  
  b) to drive a continual improvement of the online experience that your customers and potential customers have
  
  c) which translates to your desired outcomes (both online and offline)

• What common business objectives are there in the online world?

  1. For ecommerce sites: selling products and/or services.
  2. Lead generation sites: collect user information for sales teams to connect with potentional leads.
  3. Content publishers: The goal is to encourage engagement and frequent visitation.
  4. Online informational or support sites: helping users find the information they need at the right time is of primary importance.
  5. For branding: The main objective is to drive awareness, engagement and loyalty.
     

• What is a macro conversion?

  The key action on any website or mobile application that tie back to a business objective. (Example: completion of online pruchase)

• What is a micro conversion?

  A behavioral indicator that a customer hasn't fully reached your main objective, but is coming closer. (Example: signing up to receive an email coupon or a new product notification)

• Explain the "continual improvement process".

  Measurement: Collecting all the data needed to answer your business questions.
  Reporting: Package the data in a readable format and then get infomration out to the decision makers, so that they can be empowered with the information they need to make business decisions.
  Analysis: Developing a hypothesis that reflects your expectations and figuring out why the numbers do or don't meet those expectations.
  Testing: Try different solutions to the problems you identified during your analysis.
  Repeat: Repeat what you learn and improve.

• 2.2 Core analysis techniques

• Two techniques that google believes are critical to good data analysis are?

  Segmentation (Example: you might segment your data by marketing channel so that you can see which channel is responsible for an increase in purchase)
  
  Context
  

  1. Set context Externally >> Can come from an industry benchmark.
  2. Set context Internally >> Helps you set expectations based on your own historical performance.

• 2.3 Conversions and conversion attribution

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• Why is attribution is important for good analysis?

  It helps to better understand the value of each marketing channel and how multiple channels work together to drive conversions.

• 2.4 Creating a measurement plan

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• Define the five-step process for creating a measurement plan to track your online performance

  Building a solid infrastructure (Time, effort, people, process and technology)
  
  

  1. Document your business objectives
  2. Identify the strategies and tactics to support the objectives.
  3. Choose the metrics that will be the key performance indicators.
  4. Decide how you'll need to segment your data.
  5. Choose what your targets will be for your key performance indicators.

• What are the skills you need on your analytics team?

  1. Someone who understands what the business objectives are and the strategies used to support those objectives
  2. Someone who understands what analytics can do.
  3. Someone with tehcnical skills who can implement an analytical tool.