Excel for Data Analytics in Marketing


Excel is one of the most well-known and widely used spreadsheet software programs in the world. In fact, a study in 2019 revealed roughly 54% of global businesses use Excel. This is due to the sheer utility that comes packed with the powerful software. Excel is especially useful when applied to the field of marketing analytics as it enables marketers to store, manipulate, analyze, and  visualize data in an agile way.


This article examines the use cases of Excel when applied to Marketing Analytics and provides guidance on how to learn essential skills for both new and veteran marketers. With the right know-how and experience, Excel is able to provide marketers the critical ability to drive data-informed marketing and business decision making to maximize marketing return on investment (ROI). Companies that leveraged data for 50% or more of their marketing efforts were able to track and see the value in their marketing.

What is Marketing Analytics?

Marketing Analytics is leveraged by businesses to design and deliver data-driven marketing strategies. Marketing Analytics enables businesses to maximize their return on investment (ROI) on various marketing efforts, such as email or social media campaigns, and more.

What is Microsoft Excel?

Microsoft Excel (or Excel for short) is a spreadsheet software program used for data storage, manipulation, analysis, and reporting. In Excel, data is stored in what is called a spreadsheet that is used to organize and manipulate data for further analysis to extract useful insights.

How is Excel Used for Marketing Analytics?

When applied to the field of marketing analytics specifically, Excel is used for to store and retrieve consumer data, manipulate data, perform analysis, and generate reports related to marketing that are useful for driving business decision making. Marketing analysts will often use the many tools that Excel offers to clean data sets, perform data wrangling, statistical analysis, and create data visualizations or dashboards.


The process of using Excel starts with loading in existing consumer data with a .CSV format from various marketing channels and tools such as:

·      Websites (i.e., bounce rates, clickthrough rate (CTR), page views, conversions)

·      Social media (i.e., impressions, reach, engagement)

·      Mobile Apps

·      Google Analytics (web traffic)

·      And more

What Are the Excel Skills Every Marketing Analyst Should Know?

Here are some skills that are essential for any successful marketing analyst in the field of marketing analytics:

Data Wrangling

As a marketing analyst, you’ll often be tasked with examining and analyzing data

within Excel. But before conducting any analysis on a dataset, it is essential to perform some data wrangling to ensure your data is error-free and ready for analysis. Data wrangling (a.k.a. data munging) is the process of cleaning and modifying your data in preparation for further analysis.

To clean the dataset, probe the data for any errors (such as spelling or typos) that could potentially skew the data and to make the appropriate modifications. Excel offers many formulas and tools useful for data wrangling. Some formulas useful for cleaning include TRIM, SUBSTITUTE, and PROPER. The TRIM function, for example, is useful when cleaning text strings. TRIM takes one cell input an argument and will remove any leading and trailing spaces, as well as any extra spaces between words within a string of text.


Below is a step-by-step visual example of how the TRIM function works inside an Excel spreadsheet:

Notice how numerous cells circled in column A contain leading spaces? This will produce an error if we attempt to retrieve the data using VLOOKUP or XLOOKUP (more on this later). We can use the TRIM function to eliminate the all trailing spaces
We insert an empty column (B) next to column A and type out the TRIM formula inside cell B2. The TRIM requires an arguement that specified which cell to trim, so we input cell A2 since we want to trim the data inside this cell.
Copy and paste* the formula to trim the remaining cells in column A. *Note: you should select the paste as cells option.

Data Analysis

Once the data has been properly cleaned and modified, it’s time to further analyze the data to gather insights. Potential datasets you’ll be tasked with examining vary from survey results, reports pulled from Google Analytics, and more. Statistical analysis can be formed on numerical data in a data set useful formulas such as AVERAGE, MEDIAN. For categorical data, use MODE and COUNTIF functions to pull quantifiable insights.


Pivot tables are a great tool to quickly summarize datasets, providing useful insights and the ability slice and dice data to pull the specific information you need.

Data Reporting

Gathering insights from data is not enough. As a Marketing Analyst, its essential that you can clearly communicate your findings to stakeholders in a clear, concise, and compelling way.

Visualizations are a great way to communicate and share your findings. Excel allows you to create graphs and charts to create visuals of different parts of your dataset. Note that your stakeholders will often include persons and groups without expertise in the field of marketing, data, and or analytics, so you’ll need to need to keep this in mind creating visualizations. Think of including labels on the axis within your graphs and maybe a legend to guide viewers on the stories your visualizations are trying to convey.

How to Learn and Practice Excel Skills for Marketing Analytics

There is a plethora of both free and paid online courses available to learn how to use Excel for marketing analytics. Most courses offer the benefit for you to not only learn Excel but can also provide professional certificates. These certifications are invaluable, as you can showcase earned certifications and credentials on your resume to help land you entry-level roles in the field of marketing analytics.

Online learning platform DataCamp offers numerous courses covering beginner to expert level concepts for data analysis that can be used applied to Marketing Analytics. Course ‘Data Analysis in Spreadsheets’ is especially good for learning the formulas mentioned throughout this article.