Marketing Analytics in Google Sheets
| Course Details | ||||||||
|---|---|---|---|---|---|---|---|---|
|
||||||||
| Languages | ||||||||
|
||||||||
| Outcomes | ||||||||
|
||||||||
| Price & Terms | ||||||||
|
||||||||
| Technical | ||||||||
|
||||||||
| Specification | ||||||||
|
||||||||
Clean shared paid search data in Google Sheets with validation rules and regex functions, then chart it and build a filterable campaign dashboard.
This Google Sheets course works with Bing and Google Ads paid advertising data and deals with two problems that make campaign performance hard to read: a sheet that many people edit at once, and campaigns and ad groups named by different conventions. You set rules that keep entries consistent, use regular expressions to rename and group campaigns, and present the cleaned metrics in charts and a dashboard you can filter by source and campaign.
What You Will Achieve
- Add dropdowns, checkboxes and text rules so a shared sheet accepts only valid campaign entries
- Use pattern-matching formulas to rename campaigns, pull out brand names and create campaign IDs
- Pick a chart type that suits a paid search metric, such as click-through rate over time or spend by ad group
- Link dropdown filters for source and campaign name to a table and charts that update together
Program Overview
Clean Data Entry with Validation
Introduces the Bing and Google Ads dataset and the validation options that keep a sheet consistent when many people add to it.
- Why clean data entry matters
- Dropdowns built from lists and ranges
- Cell criteria, text validation and checkboxes
- Fixing campaign name errors
Regular Expressions for Campaign Names
Uses pattern matching to reconcile naming conventions that differ between paid advertising campaigns and ad groups.
- Writing and testing regular expressions
- Filtering and summing cost with REGEXMATCH
- Renaming and extracting with REGEXREPLACE and REGEXEXTRACT
- Campaign IDs that include the source
Paid Search Charts and Dashboard
Turns the cleaned campaign data into charts, then combines them into a paid search dashboard filtered by source and campaign name.
- Line and stacked area charts for trends and cost
- Column, bar and 100% stacked bar charts for ad groups
- Pie, scatter, bubble and doughnut charts
- A dropdown-driven filtered table and dashboard
Certificate Awarded (Paid)
Job Outlook
These skills are used in paid search and digital marketing reporting, where analysts clean campaign data, compare Google Ads and Bing performance and share dashboards with colleagues.
Good for: Marketers and analysts who already work in Google Sheets and report on paid search campaigns run across Google Ads and Bing.
Keep in mind: The chapters center on paid search data from Google Ads and Bing, with cost, click-through rate, impressions and goal completions as the working metrics.
Bottom line: A focused run through keeping shared ad data tidy with validation and regex functions, ending in a dashboard filtered by source and campaign.
Frequently Asked Questions
Which advertising data are the spreadsheets built on?
Every chapter works with one paid advertising dataset from Bing and Google Ads, organized by campaign and ad group, with metrics such as cost, cost-per-click, click-through rate, impressions and goal completions.
Which regex functions appear in the lessons?
The lessons use REGEXMATCH to test strings, filter tables and sum campaign cost, REGEXREPLACE to rename brand campaigns and ad groups, and REGEXEXTRACT to pull out brand campaign names and build campaign IDs.
What does the final dashboard let you do?
The closing chapter prepares the data, adds dropdowns for source and campaign name, and feeds a filtered, regex-driven table into doughnut, bar and bubble charts, so the whole view changes when a filter is applied. It also asks who the dashboard is meant for.
There are no reviews yet.