3 Tips to Improve your Agency’s Data Visualization


With data visualization becoming an essential differentiator in the core functions of an agency or media company, it’s becoming increasingly important for your team to leverage this competitive advantage with client reporting. Data Visualizations isn’t only about showing information in easily digestible and discernable shapes, is ultimately an expression of the value your agency has driven to your clients.

When demonstrating that value and showing the return on their investment, it’s not always what you say to your clients, it’s how you say it.

After spending time analyzing our customers’ performance through data visualization, we’ve realized that it’s often the smallest adjustments make the biggest impact. Below you will find a list of the three most common areas of opportunities agencies miss when leveraging data visualization:

How to Improve Your Data Visualization:

  1. Tell a Story:

With the introduction of social media, video platforms, graphics platforms, and the like, visualization and storytelling have hit an apex. And no wonder – storytelling is being touted as the most powerful strategic business tool.

Due to its black and white nature, data alone makes it difficult for agencies to articulate a story through data. The good news is storytelling through data visualization is still grounded in the fundamentals studied and analyzed by Aristotle and Socrates called dramatic structure.

In order to tell the right story through your data visualization, you need to stick to the storytelling essentials you learned back in high school:

  1. Audience: Consider the audience for whom the data is being collected. The audience and their experience level in marketing will guide you in structuring the data into formats and modalities that lend themselves well to understanding.
  2. Conflict: Most clients lean into agencies to help alleviate pain points in their growth – we call this the “conflict.” When telling your agency’s story through data, make sure to articulate the conflict your client faced at the onset of their engagement through starting state reporting – or the “before.”
  3. Resolution: Many agencies lead with this part of the story, rather than building towards it. While it’s tempting to just jump to the conclusion, building your client’s understanding of the story and them revealing the triumphant resolution to the conflict will biologically tether them to the results. Consider these reports to be the “after.”

The bottom line is – People don’t remember facts, they remember stories. For your agency to differential itself, your clients need to feel connected to the story you’re writing for their business, rather than simply ingest the raw data.

  1. Less is More.

The MarTech industry is on the verge of critical mass with the sheer volume of data it’s distributing to its users. Ten to fifteen years ago, marketers would have found it inconceivable to have as much access – as quickly as we do  – to the raw data of our user’s behaviors.

With so much data – and subsequent analysis – comes the temptation to share every nuance and detail of the tactics you’ve deployed to in your marketing strategy to your client. You and I might geek out a subtle change to the copy which doubled the conversion rate of a display ad, but the reality is your client simply wants to know the bottom line.

While it might be tempting to send every tiny detail of the campaign your running, the human brain can only retain a sequence of roughly seven numbers. When communicating keep it simple, build reports that clearly articulates the top priorities of the campaign. Whether it’s website traffic, leads, or controlled ad spend, this information should be front and center at the top of your client reports.

  1. Design Matters.

If you’re using visuals, it should go without saying that that the esthetic will influence a client’s overall perception of your agency and their ability to ingest the story you’re telling. Design – specifically color and graphics – have a massive amount of impact on the overall effectiveness of your data visualization.


Color has proven to have influence over our everyday lives both psychologically and biologically. In business, color plays a vital role in brand recognition and color has even been shown to have a 60-90% influence over a decision to purchase from a brand or service. With as much influence over branding as it has, the color of the graphics you are using should also be considered when visualizing data.

When considering the color of the data you are looking to express, certain colors are better than others when expressing data with certain types of data graphics. For example, a heat map or a geographical map would use a gradient to represent the density of data points. In contrast, a bar graph might use multiple solid colors that are easily distinguishable but retain the same level of brightness.

Lastly, consider color accessibility when sending your clients reports. With color blindness affecting 1 in 12 men and 1 in 200 women around the world, your agency should consider leveraging colors, textures, or formatting that renders graphics discernable to the broadest possible audience.


Given that the purpose of data visualization to make it easier for the end user to interpret and understand, the graphics that you use to represent data is paramount. Data visualization should be simple, clean, and clear; less is more when it comes to selecting graphics to represent data.

Keeping in mind that different kinds of graphics express different stories ( see tip #3 above ), finding the right type of graphic to represent your story comes down to four categories:

  • Data Comparison – Data Comparison graphs are best used for well … comparing data against other data sets or over time. Examples of this kind of data graphic would be line charts, bar charts, column charts, or tables.
  • Relational Data – Relational data graphs are best used when expressing data sets that have multiple variables that relate to one another. Examples of this kind of graphic would be a scatter chart or a bubble chart.
  • Data Composition – Likely the data representation you’re most familiar with, Data Composition allows you to express data that is dynamic ( meaning changing over time ) or static. Examples of this kind of graphic would be pie charts, waterfall charts, or a stacked area chart.
  • Distribution Data – Distribution Data would be leveraged to represent the frequency of data over certain intervals or periods of time. Depending on how many variables are included in this data set, examples of this kind of graphic would be 3D area charts, scatter charts, or histograms.

One final thought:

Your data should establish yourself as the leader in the space. Keep it clean, keep it simple, and position yourself as the expert in your domain. Once your data tells that remarkable story, your clients will love seeing those daily, weekly, or monthly reports in their inboxes.

These tips are just the start of creating remarkable data visualization at your agency. If you’re interested in learning more, check out our ultimate data viz guide.

We want to hear from you, what tips do you have for improving data visualization?


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