
Learn to create a campaign journey map in Miro using a ready template, symbol library, and frames, linking awareness to conversion across paid and owned channels.
Define what a metric is and explain its art of measurement. Identify three metric types—platform, engineered, and derived—and six marketing categories: exposure, engagement, perception, experience, acquisition, and conversion.
Overview
In the previous lecture, Case Study #1: Metrics Identified, we shortlisted five KPIs based on the Etsy case study. You can now test what you've learned by trying to calculate the campaign performance for the five KPIs using a real dataset. To recap, the five KPIs, benchmarks and targets are as follows:
Total revenue | Benchmark = $18,000 | Target = $20,000
Conversion rate | Benchmark = 1.3% | Target = 1.6%
Clickthrough rate | Benchmark = 2.3% | Target = 2.5%
Cost per click | Benchmark = $0.5 | Target = $0.4
Post engagement rate | Benchmark = 2.1% | Target = 2.4%
The attached Excel (XLS) file contains three worksheets (i.e. google analytics, instagram, and facebook). These three worksheets provide sample data for the Etsy case study.
What you need to do
Download the XLS file from Resources titled Etsy_campaign_dataset - ACTIVITY-BRIEF.xlsx
Using this dataset, try to calculate the actual performance for the five KPIs, and establish how far above or below the benchmark and target this campaign was. It's ok if you don't know how at this stage. Just try your best.
Optionally, try analyzing the dataset and come up with some interesting observations. Here are some questions you can consider answering:
Was this campaign a success? i.e. Were the KPI targets achieved?
What sources drove the highest conversion rate (e.g. Facebook, Instagram, etc)?
On average, do video posts perform better than image posts on Instagram?
Did the link posts on Facebook generate higher click-through rates than the photo posts?
When you're finished, you can check your answers by watching the next lecture in the next lecture.
Explore web and app analytics, including how tracking codes and tagging feed events into analytics tools, dashboards, and data processing; learn key metrics, segmentation, cohort analysis, drill-downs, and conversion optimization.
Learn how to use GA4 explorations to create custom visualizations, control chart granularity, and analyze metrics like sessions, bounce rate, and duration with dimensions such as traffic sources and country.
Explore social media monitoring, learn to build keyword profiles with boolean logic, and capture mentions via crawlers, APIs, or firehose. Understand features, metrics, use cases, and limitations.
Learn how to perform social listening with Sprout Social through a hands-on demo, covering keyword profiles, source selection, exclusions, themes, sentiment, and basic reporting for cross-platform monitoring.
Explore owned social analytics, distinguishing it from social listening, and compare native versus third-party tools for aggregation, visualization, publishing, and metrics like reach and engagement rate.
[Update] Since filming this lecture Meta has rolled out an update to the Meta Business Suite insights tool that now includes a 'people-who-engaged' metric, called Engaged Users. You can refer to the next lecture, Engaged Users Metric in Facebook Insights, for more information.
Explore online advertising, covering display ads on the open internet and walled gardens, and how programmatic buying uses DSPs, SSPs, and ad exchanges to optimize impressions, reach, and clicks.
Measure campaign effectiveness across omnichannel online and offline campaigns using a pre and post survey approach, tracking awareness, usage, consideration, ad recall, and brand uplift.
Learn how email marketing works, including measurement of opens, clicks, and conversions using drag-and-drop campaign builders. Manage lists and templates, run A/B tests, and integrate Google Analytics for content optimization.
Explore customer relationship management (CRM) and how cloud-based tools capture and analyze prospect and customer data. Log deals, manage opportunities and pipeline, and automate outreach with marketing automation and forecast.
Feeling overwhelmed with your marketing data? You're not alone! 83% of marketers say they struggle "to adapt to the volume of data" created by their marketing efforts, while 80% feel that there are "too many performance metrics" to keep track of. Today, it's essential for everyone to possess a foundation in data literacy. Whether you're an analyst, a brand manager, creative, or even a CMO, understanding how to collect, interpret and action your marketing data is quickly becoming the standard, rather than the exception.
I designed this course based on more than 10 years of knowledge and experience working directly in the field of data analytics and market research. We'll cover everything from theory to application, to ensure you're equipped with the knowledge to make sense of your marketing data and make logical, data-driven decisions both quickly and consistently.
With 17 hours of video across 50+ lectures and 40 downloadable resources, this course is packed with everything you need to learn in order to become an analytics PRO. Some of the things you'll learn include:
Fundamental concepts in marketing and the measurement of marketing
What are some of the most common measurement platforms, from web and app analytics to email marketing measurement
How to build an analytics strategy within your business
How to map out a marketing campaign user journey for more effective measurement
How to select the right metrics based on your business objective
How to identify and set benchmarks for your metrics
How to optimize your marketing through data and experimental testing
How to measure returns on marketing investment