Data storytelling: 6 steps to highlighting value for digital marketers
- Ray Martinez
- May 7
- 9 min read
Author: Ray Martinez
Early in my SEO career, I would stare at a Raven Tools or Google Analytics report as if staring at an unsolved math problem. There were so many metrics measuring so many things. I struggled because I didn’t understand how each metric contributed to the overarching story of digital marketing performance.
At that time, I didn’t understand a simple but powerful concept…
Value is added by the story we tell using data—not on data alone.
In this article, I’ll walk you through why data-driven storytelling matters for digital marketers, with examples from my own experiences, and how it adds value for your stakeholders.
Table of contents:
What is data storytelling?
Data storytelling uses channels, segments, dimensions, and metrics to build a compelling narrative that can guide strategic decisions. Simply put, it connects real-world actions to online performance by using data to tell a story.
For example, a former client (a D-I university that won a national football title) would see spikes in impressions, clicks, and users during game days throughout the season. There was also a rise in ‘direct’ traffic.
When I asked the client if they had done anything else to advertise, they said they had little banners with their domain printed across the stadium. Those banners appeared on nationally televised games, resulting in millions of impressions and weekly traffic spikes, which skewed data and obscured progress.
Understanding these real-world spikes helped me measure my partner’s ad’s effectiveness (by measuring branded traffic via organic search and user spikes for the ‘Direct’ default channel group). That additional information provided a complete picture, which helped me better understand and position gains and losses for the client.
Having that context also helped me do something else important—it helped me avoid looking foolish by wrongly taking credit for other channels’ and team’s efforts.
So, how do you craft an effective data story? The following steps discuss the critical components of creating a compelling narrative:
Define clear goals and choose KPIs that tell the story
Collect diverse data points for a comprehensive story
Analyze patterns to highlight key insights
Use your key insights to build a narrative arc
Create visualizations that make your data accessible
Showcase ROI in real-world terms
Step 1: Define clear goals and choose KPIs that tell the story
Do you know what you’re measuring and why you’re measuring it?
Early in my tenure at Archer Education, the SEO team and I spent much of our time educating partners on why ranking improvements, impression and click growth, and earned links should matter to them.
Simply put, we weren’t discussing what mattered to our partners.
What did matter to our partners? As a team, we often asked ourselves this question. We had different partners with different needs. Some partners focused on application volume, others on enrollments, and some on leads.
Some metrics were consistent across all clients, while others were more niche. Adjusting to client needs is not only a best practice, but also a must for practitioners who work across various industries with varying objectives and goals.
Pro Tip: Take the time to learn what success looks like from your client’s perspective. At Archer, we schedule in-depth discovery calls to align with stakeholders on their goals. My thought process around this is simple—ask what success looks like in your stakeholder’s role and the larger organizational goals. If they meet monthly with the board, create a report that gives them key points or an executive summary to highlight value. That type of added value goes a long way in retaining clients.
Step 2: Collect diverse data points for a comprehensive story
As digital marketers, we have a wide array of metrics to review. So, we mapped our key metrics according to what our partners cared about. Looking at metrics across various platforms, we tried to align each metric with a ‘why’ statement (e.g., why should the client pay attention to this metric?).
It looked something like the table below:
Metric | Definition | Why it matters to clients | Example goal |
Impressions | The total number of times an ad or content is displayed to users. | Indicates brand visibility and the reach of marketing efforts. | Achieve 100,000 impressions per quarter for program ads. |
Clicks | The number of times users clicked on an ad, email, or content link. | Measures user interest in programs and marketing content. | Increase clicks by 20% on organic program pages. |
Total users (GA4) | The total number of unique users that interacted with the site within a given timeframe. | Reflects the overall reach and ability to drive traffic to the website. | Grow total users by 15% YoY for specific program pages. |
Engagement rate (GA4) | The percentage of engaged sessions (active interactions lasting 10+ seconds, with a conversion or 2+ pageviews). | Demonstrates the quality of user interactions and relevance of site content. | Maintain an engagement rate of 60% for core program pages. |
Leads (GA4 or CRM) | The total number of users that completed a desired action (e.g.,filling out an inquiry form). | Highlights initial interest and potential for future enrollments. | Generate 500 leads per quarter through inquiry forms. |
Applications (CRM) | The total number of completed applications submitted by prospective students. | Measures intent and indicates a lead’s transition to a more serious prospect. | Receive 200 completed applications per program each quarter. |
Enrolls (CRM) | The total number of students who enroll in a program. | The ultimate success metric is tied to revenue and program growth. | Enroll 15 students per program in each cohort. |
When selecting your metrics, consider what you need to build your story. Including too many metrics and data points creates a convoluted message. Refer back to the goals you agreed upon with the client to determine the necessary metrics. If you’re looking at lead-based goals, you’ll want to understand traffic and conversion (versus an awareness-based goal, where you might want to look at metrics like impressions or page views).
You should also look at other data points outside the various reporting platforms. At Archer, Admissions and Retention teams guide prospective students through enrollment. The Admissions team’s role is similar to that of a sales team—their metrics help dissect lead quality. This level of granular conversion data helps us understand what our prospective students (customers) need.
Think about what your process looks like: If you’re a lead generator, do you have regular feedback and down-funnel performance tracking on lead quality? If you’re in eCommerce, did you see an uptick in traffic or cart abandonment?
Knowing your process will lead you toward your richest sources of data.
Step 3: Analyze patterns to highlight key insights
Now that you’re armed with metrics, you want to benchmark your metrics and measure against that as a baseline. For some clients, you might look at year-over-year data, quarter-over-quarter, month-over-month, or all of the above.
In higher education, universities will see seasonality-related traffic lulls from June until mid-August and mid-November until late January. These periods are breaks for many industries, while the busiest time of year has anomalous traffic and conversion spikes for others.
Do you see drops or gains in traffic for a page or channel? How was conversion impacted? How did your competitors fare? Asking the right questions leads you from reading metrics to gathering insight.
Pro Tip: Ask your partner about other efforts they’re working on. This can help you gain deeper insight into what’s happening from a site traffic standpoint. For example, I’ve witnessed partners that ran out of “Yellow Ribbon” funding (a government-funded program designed to enroll veterans) see their branded search volume and clicks halved overnight. What looked like a major loss in traffic was anticipated by the partner.
Step 4: Use your key insights to build a narrative arc
Now that you’ve gone from metrics to critical insights that can guide your data story, see how they fit into the overall picture.
In higher education, we look at the student journey. Degrees are an extended sales cycle product. Prospective students often interact with multiple channels on their journey. At Archer, we achieved stakeholder buy-in once we could highlight the impact of cost per acquisition via organic efforts. Sharing these metrics with our internal paid team created efficiencies that spread across channels. For example, if our SEO efforts drive higher enrollments for a particular program, our paid team can pull back on spending. This especially matters when transactional keywords have a high CPC or CPL.
Look at your metrics and what they tell you about your users. Learning about their age or location indicates lifestyle, interests, and other pertinent information that tells your story. Where did the conversion points happen? How many touchpoints did they hit along that path?
Another great indicator of the narrative arc is content. An omnichannel approach to content translates to varied content types along your customer journey. For example, users landing on a paid landing page are conversion-oriented traffic, whereas users landing on a blog post will be spread across the various stages of a conversion funnel. In higher education, prospective students that don’t convert on paid ads translate to branded search. They’ll interact with Meta Ads, Google Ads, blogs, faculty profiles, and social media posts. Each channel plays its part in moving the prospective student towards applying.
Step 5: Create visualizations that make your data accessible
Now that we’ve discussed gathering your data and translating it into a narrative arc, how do we illustrate that value? I’ve seen performance decks fall flat with unclear or cluttered charts that added little to the conversation.
Anything that doesn’t add value is a distraction. Always remember what you’re trying to convey when creating a data visualization. What is the information pertinent to your narrative?
I created a table below to highlight different types of visualizations and when they are applicable. These are canned, but create an organized picture of the purpose and use case. (The table itself is meta because it’s an effective example of visualizing data clearly.)
Visualization type | When to use it | Purpose | Examples |
Bar chart | Comparing discrete categories or tracking changes over time. | Highlight differences or trends in performance. | Compare engagement rates across campaigns or leads generated by channel. |
Line chart | Showing trends or performance over a continuous period. | Identify patterns or seasonality. | Track monthly impressions or click-through rates trends. |
Pie chart | Representing proportional data to show composition. | Understand the percentage breakdown. | Show the share of traffic from different channels or device types. |
Stacked car chart | Comparing parts of a whole across multiple categories. | Compare contributions to a total. | Visualize contributions of social media platforms to total conversions. |
Scatter plot | Identifying relationships or correlations between two variables. | Explore relationships between data points. | Correlate ad spend and conversions or analyze user engagement vs. session time. |
Heat map | Visualizing data density, intensity, or performance variations across multiple categories. | Spot patterns or high-performing areas for design, conversion, and user experience. | Analyze click performance across a webpage or traffic. |
Create compelling visualizations that establish visual focal points for each step along your user/customer journey. I often liken data visualizations to storyboards from the golden age of advertising—a good storyboard sold clients on the big idea.
“Truly great images make all the other millions of images you look at unimportant. You gotta look at an image and understand it in a nanosecond.” — George Lois
Step 6: Showcase ROI in real-world terms
Now, it’s finally time to illustrate value to your client.
Showcasing ROI corresponds with step one of this process. What’s your goal and track to get there? Did organic conversions go up? Do you have access to backend analytics from a CRM or eCommerce platform?
Returning to my earlier example, my team and I discovered that our old reporting format wasn’t showcasing the success we brought to our clients—we were shouting into the void about traffic, while our partners were interested in enrollments.
SEO Manager Sean Taylor, Vice President of Analytics Cherie D’Souza, and I took on the task of working with our clients to better understand their requirements. The reality was that every partner had overlapping needs with various levels of customization. It’s a process we’re still refining and working on.
In our efforts, we had regular discussions with clients around lead mapping, goals, and sources to learn their requirements. This is valuable because it creates a framework for what stakeholders/clients prioritize. This exercise requires and encourages collaboration across client and internal teams. It shouldn’t be a conversation that only occurs once—it should be an ever-evolving dialogue around conversion and business goals.
Review and refine your data story for maximum impact and client retention
After you've crafted your story, it's time to practice and present it. Focus on showcasing the value you bring to your client at every step. As you deliver your narrative, leave room for questions and discussion.
Clients often provide valuable data or insights during these conversations, which can help refine and strengthen your reporting to better reflect your value and encourage client retention down the line.
Ray Martinez is the VP of SEO at Archer Education, where he leads a dedicated team comprised of senior analysts, specialists, and project managers. Together, they craft, implement, oversee, and evaluate SEO strategies for prestigious higher education institutions across the globe. Twitter | Linkedin
