Data literacy: Six actions for data-savvy marketers in 2023

Published Apr 4 2023 Last updated Apr 18 2024 7 minute read
steps to data literacy

In our recent study, The Marketing Data State of Play 2023, we explored the biggest challenges marketers face with collecting, managing, and analyzing data. Fifty-nine percent of marketers said that their teams are "highly data-driven," but many respondents said they weren't data-savvy people themselves.

It’s clear that businesses need more data-literate employees who can accurately derive insights from their marketing analytics. That means every modern marketer needs to have a baseline knowledge about deriving insights from data.

So what can you do to improve your data literacy as a marketer?

We’re here to help with six actions you can take as a marketer to improve your data fluency.

  1. Mandate data skills
  2. Streamline data hygiene processes
  3. Focus on actionable metrics
  4. Master data visualization
  5. Embrace self-service
  6. Power up your single source of truth

1. Mandate data and analytics skills

It's no secret that collecting, managing, and analyzing data is essential to achieving business objectives.

Given the sheer amount of data readily accessible today, it’s important to learn the necessary skills to work with data proficiently. Data analysis skills are no longer just “nice-to-have” but instead “need-to-have.”

Don’t worry, though. You won’t have to be “highly technical” to be a data-driven marketer. We understand that learning new skills, especially data skills, can seem daunting.

By setting actionable yearly goals for yourself, and your team, you’ll surely learn what you need to know to analyze data, think critically, and present the information in a dashboard.

The three most important skills we recommend learning are:

  1. Mathematics: You should get comfortable with percentages, probability, and statistics.
  2. Spreadsheets: Spreadsheets can take you a long way if you are willing to go beyond the basics. Specifically, Pivot tables, VLOOKUP(), IF Statements, and REGEX will be your best friends.
  3. Data visualization: Being able to explain the insights you’ve found from data is an essential skill. It’s a complex field, so check out our in-depth guide to analyzing marketing data which we've linked below.

Learning all of these skills in one day isn’t possible. We highly recommend prioritizing continuous learning so you can stay ahead of the curve and grow your marketing career.

When you’re ready, we’ve created some awesome resources that detail the critical skills every marketer needs.

Recommended reading: Upskilling - the critical skills every marketer needs to know, How to analyze marketing data

2. Streamline data hygiene processes

It is much easier to work with data that is easy to read, consistent, and organized. Chances are, as a modern digital marketer, you’re working with at least two or three marketing tools, each with its own raw dataset.

Data cleaning is the process of taking that raw data and turning it into a clean, ready-to-analyze dataset.

Raw data may be full of errors and inconsistencies that could interfere with creating accurate insights and reports from the analysis. Learning what data cleaning options exist is essential for any marketer's tool belt.

Raw data is impossible to analyze, while clean data is business-ready and can easily provide insights.

How to clean data

The right way to clean your data will depend on the data you’re working with. You’ll first want to identify what you need the data for and how you intend to use it. Ask yourself the question, “What is data cleaning going to do for me?”

Once you’ve figured out your needs and sourced the relevant data, there are a few data-cleaning best practices that can be used and adapted to fit your use case.

  1. Ensure the data is up to date
  2. Remove duplicate data
  3. Identify and correct missing values
  4. Check the data fields
  5. Remove any outliers

Now that you’re off on your data-cleaning journey, you’ll find that cleaning data takes a little more time than cleaning your closet. 

That’s okay because there are tools made to make the process easy, simple, and in some cases, automated.

If the data set is small enough, you may be able to perform the data cleaning manually using excel or simple formulas. As your business, campaigns, and volume of data grow, you’ll need to consider using tools that will identify and clean the data for you.

We built our hub model with this in mind. That way, it’s one seamless process to collect, organize, store, and share your data anywhere.

However, every organization requires a different approach that meets its specific needs. Rather than jumping into a data cleaning solution, evaluate your own needs and capabilities first.

Recommended reading: What is data cleaning - the ultimate guide

3. Focus on actionable metrics

When someone decides to buy something, they have likely done their research or engaged with your brand in some way before purchasing. As a marketer, you’re probably running multiple campaigns that have numerous pieces to them. The more campaigns you run, the more potential buyers can interact with your business. Those are called touchpoints.

Some touchpoints happen online and are easily trackable. Some touchpoints happen offline, meaning they are much more difficult to track, like word of mouth. 

All of these interactions come together to make a customer's buyer journey. A buyer’s journey is rarely linear, so it’s difficult to understand what specific touchpoint got the buyer to purchase.

Often, the contribution of multiple interactions moves the needle for someone to do business with you.

That’s where marketing attribution comes into play. It is a way to determine which parts of your campaigns work best to drive conversions.

There is one large problem, though. There is no one right way to perform marketing attribution due to the challenging nature of attracting a customer and getting them to purchase. That’s because:

  • Some marketing touchpoints are not trackable
  • Certain touchpoints are codependent
  • Different attribution models will give different answers

Because of this, relying on one metric alone to understand performance could lead to pitfalls down the road.

A prime example is ROAS (return on ad spend). Let’s say you’re only measuring performance based on this advertising-specific metric. The three problems that can occur are:

  1. ROAS and volume are not directly correlated
  2. ROAS is only focused on the short term
  3. ROAS assumes perfect attribution

Instead, choose a few actionable metrics to help you generate insights and improve attribution

Actionable metrics are measurable, relevant to your business, and made to help you improve your marketing performance and drive business success.

If you want to learn more about what actionable metrics we recommend (hint: LTV and MER). We've even created resource guides just for this occasion.

Recommended reading: Why you shouldn't focus on ROAS alone, The digital marketing attribution problem

4. Master data visualization

We know we mentioned data visualization earlier in this post, but since it’s so important, we dedicated an entire section to it.

Mastering the art of data visualization will help you improve your data literacy skills in three key ways:

  1. It will make analyzing data much easier
  2. It's easier to convey messages with images than numbers
  3. Your career will benefit from learning how to visualize data

Since this is all about data visualization, who would we be if we didn’t tell you about the different ways to visualize data?

To name a few….

  1. Bar charts
  2. Scatter plots
  3. Infographics
  4. Animated graphs
  5. Mind maps
  6. Decision trees
  7. Interactive visualizations
  8. Word clouds

There are many more ways to communicate data. But before you pick a method and start visualizing your data, it’s important to understand what message you want to convey and where you will present your findings. 

Different visualization methods serve different purposes

If you’re about to present your newly tracked actionable metrics (see what we did there?) to leadership, an infographic may not present the data effectively. Alternatively, if you’re presenting data in a more fun way, a bar chart may not be the hit.

We recommend that every marketer upskill to become a data visualization mastermind. The good news is that you won’t have to start from scratch.

These days, there are so many data visualization tools on the market that it can be overwhelming.

Each tool ranges from free and easy to use to expensive and complex. Again, it depends on what your needs are.

If you’ve already started typing “best data visualization tools” in ChatGPT, you can pause there. We’re one step ahead. We’ve compared our top five data visualization tools here.

Recommended reading: All about data visualization

5. Embrace self-service (so you don't need data scientists for everything)

The role of a digital marketer is changing and evolving rapidly. Marketers are being tasked with accomplishing more with fewer resources. New skills are in demand each year, and it’s up to the individual marketer to improve their data literacy skills.

Our claim is supported by Juuso Lyytikkä, Funnel’s VP of growth, with more than 10 years of experience leading high-growth marketing teams. In an interview, Juuso recaps his entire career, and it’s clear that marketing has changed drastically. 

So what will be the most important skill for marketers to develop to become more data literate?

Marketers need to develop their data fluency and data literacy skills above all else. Three factors contributing to this are:

  1. Marketers are expected to be data savvy
  2. There is a massive increase in data volume with the number of platforms businesses use
  3. Over-attribution of conversions in some platforms leads to inaccurate data, leading to a lack of trust in the data

Juuso continues exploring how marketers need to operate similarly to data analysts since they are closer to the data.

We recommend reading the entire interview recap (linked below), but for now, back to embracing self-service.

So, as a marketer, how do you identify knowledge gaps and improve data literacy?

Luckily for you, the internet is full of free and paid resources to help you utilize data better to become a data-driven digital marketing wizard.

Start by identifying what you want to accomplish and then reverse-engineer to narrow down what data literacy skills you’ll need. 

Here are some ideas of where to start when trying to upskill:

  • Sign up for and learn how to use data visualization tools like Google Data Studio
  • Research and take online courses, LinkedIn learnings, and tutorials covering the data literacy training you want to learn
  • Connect with other data-driven marketers to share experiences, ask for advice, and learn about their skillset
  • Look for opportunities to improve your data literacy within your organization by speaking with your marketing team, peers, or manager

By fostering a curiosity to learn and a self-service mindset, you will surely learn the necessary skills to gain a competitive edge as a marketer.

Recommended reading: The role of the digital marketer is changing

6. Power up your single source of truth

We almost made a “one place to rule them all” joke, but that didn't pass.

In all seriousness, having a centralized place to house all your data sources will help you easily derive insights from your marketing data, customer data, and any other relevant data sources.

In fact, with the sheer volume of data created daily, having one place to manage it all will save you time and energy.

We know that marketing data is being used to influence the strategic direction of entire businesses. So, how can marketers take control of their data to ensure they have accurate insights?

There are five main ways to create your single source of truth, all with varying levels of difficulty and cost. We’ll name a few here, but you can read the full breakdown in our guide, which is linked below.

  1. The classic copy and paste, usually to a spreadsheet
  2. Plugins that help you automate the "copy and paste" actions into visualization tools like looker studio
  3. Building a data stack consisting of different software tools to manage a piece of a given data process
  4. An all-in-one tool that does what your data stack does, minus the five different monthly payments
  5. A marketing data hub that automates many of the pieces in the data process without needing to code

So which tool is right for you?

The data challenges marketers face presents themselves differently for every team. Choosing the right tool will ultimately depend on your preferences and business needs.

Regardless of which route you take, having a centralized and trustworthy source of marketing data will get you one step closer to more successful marketing efforts. 

So whether you're copy-pasting or enjoying your new marketing data hub, don't forget that with great data comes great power — the power to rule them all (including your competitors.)

Recommended reading: Solve the marketing data challenge

Final Thoughts

Improving your data literacy skills isn't going to be something that you can do overnight. Especially since marketing is an ever-changing field. What works today, may not be relevant tomorrow.

By following these six steps (and reviewing the recommended readings), we're confident you'll be well on your way to improving your data literacy skills. At the very least, you'll learn the vital data skills you can use and translate across your career.

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