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Analytics and Search Strategy

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Digital Marketing - Study Notes:

From data to insights

Data within analytics platforms provides insight into customers across numerous dimensions. These include location, web pages viewed, demographics, and device usage.

Insights from the past can drive insights into the future. For example, you can use historical comparative data to forecast future performance:

  • Comparative data looks at variance between two data sets over the same or different period of time and shows percentage or actual change. 
  • Choose recent comparable data sets, such as similar months, and work out the percentage difference.
  • If conditions remain the same across metrics such as conversion rate and media costs, multiply this month’s data by the percentage difference from the comparable period to forecast a likely outcome.
  • This can then be used to decide on future media budgets and expected returns.
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Christopher Coomer

Chris is a results-driven VP of data, analytics, and business intelligence driving data management, analytics strategies, and technical architecture to scale optimized enterprise operations. As a trusted advisor and strategic business partner, Chris develops meaningful data insights and infrastructures through business intelligence and data analytics strategies to optimize business functions and drive impactful ROIs. Chris is also an enthusiastic and passionate educator in the field of data and analytics and marketing at The University of Tampa.

Christopher Coomer
Cathal Melinn

Cathal Melinn is a well-known Digital Marketing Director, commercial analyst, and eommerce specialist with over 15 years’ experience.

Cathal is a respected international conference speaker, course lecturer, and digital trainer. He specializes in driving complete understanding from students across a number of digital marketing disciplines including: paid and organic search (PPC and SEO), analytics, strategy and planning, social media, reporting, and optimization. Cathal works with digital professionals in over 80 countries and teaches at all levels of experience from beginner to advanced.

Alongside his training and course work, Cathal runs his own digital marketing agency and is considered an analytics and revenue-generating guru - at enterprise level. He has extensive local and international experience working with top B2B and B2C brands across multiple industries.

Over his career, Cathal has worked client-side too, with digital marketing agencies and media owners, for brands including HSBC, Amazon, Apple, Red Bull, Dell, Vodafone, Compare the Market, Aer Lingus, and Expedia.

He can be reached on LinkedIn here.

Cathal Melinn
Clark Boyd

Clark Boyd is CEO and founder of marketing simulations company Novela. He is also a digital strategy consultant, author, and trainer. Over the last 12 years, he has devised and implemented international marketing strategies for brands including American Express, Adidas, and General Motors.

Today, Clark works with business schools at the University of Cambridge, Imperial College London, and Columbia University to design and deliver their executive-education courses on data analytics and digital marketing. 

Clark is a certified Google trainer and runs Google workshops across Europe and the Middle East. This year, he has delivered keynote speeches at leadership events in Latin America, Europe, and the US. You can find him on X (formerly Twitter), LinkedIn, and Slideshare. He writes regularly on Medium and you can subscribe to his email newsletter, hi, tech.

Clark Boyd

ABOUT THIS DIGITAL MARKETING MODULE

Data and Data Visualization
Christopher Coomer Christopher Coomer
Presenter
Cathal Melinn Cathal Melinn
Presenter
Clark Boyd Clark Boyd
Presenter

The Data and Data Visualization module opens by discussing the fundamentals of data, how CRM data enables informed business decisions, and how to link CRM data with channel sources to more accurately attribute search performance. It covers the importance of testing hypotheses to ensure their validity, applying in-flight optimization to enterprise-level omnichannel campaigns, and using comparative data to forecast future search campaign performance. You’ll also learn about the benefits of good data visualization and the difference between reporting dashboards and data visualization tools. The module concludes with a practical focus on using Excel formulas, charts, Pivot Tables, and Calculated Fields to present and visualize campaign data.