How to Use and Add Context to Data Visualizations Found in Your Digital Marketing Tools 

Getting the Whole Story from Your Data   

Digital marketing has evolved to include analytics platforms featuring data visualizations meant to provide metrics in a scannable format via charts and graphs. These utilize labels on the axis, color coding, and sometimes annotations to better visualize your marketing progress from a high level. However, those beautiful illustrations often lack context and aren’t meant to be taken at face value.   

While you are immediately presented with data visualizations when opening a tool like GA4 or LOOP Analytics, these also help navigate you to areas requiring a deeper dive. The mountain ranges, uneven bars, and colorations in your charts and graphs can be misleading. It is best to have the background information driving those results before interpretation and strategy implementation.   

In this blog, we look at adding context to your data visualizations to get the full story, allowing for more accurate reporting and better data-driven decisions. We look at the following considerations that may impact interpretation:    

• What was happening historically?
• What changes occurred in the landscape?
• How does the data impact your most valuable KPI?

Using context will help navigate any instant reaction to upward/downward slopes, numbers in green/red, or other graphics by providing the relevant details that make this data usable. 

What was happening historically?  

When looking at analytics, we recommend setting a time frame to start contextualizing data to help narrow down potential effects and make your data set easier to manage. Once selected, consider the events and other external factors within that period:    

• Economic fluctuations and seasonality  
• Campaigns or promotions   
• Search engine algorithm updates    

Many businesses may experience natural ebbs and flows due to the economy and any seasonality aligning with products or services. Still, other considerations may include the economic fluctuations country or industry-wide and logistical shifts thanks to supply chain, technology, or other changes affecting operations. You can catch these shifts and establish trends using your industry expertise and resources and by doing a comparative analysis using your marketing tools to show performance over time. 

Additionally, campaigns or promotions are important to consider as these are essentially strategic experiments that could cause spikes or dips compared to times without increased or targeted marketing. When these efforts are highly targeted, overall metrics may seem unaffected. However, looking into specific metrics of that target audience offers real signs of success or the need to revise strategy.   

Finally, algorithm updates cause fluctuations in your data during their rollout period that may not affect your long-term performance. Jumping the gun on strategy adjustments during these hiccups can cause unnecessary consequences. These updates improve the search experience for all users, rewarding sites with helpful content and reducing the impact of spam and other “search-first” or computer-generated content. However, the probable cause of a permanent dip in trends will be that your competitors received a boost versus your content being “punished” with a lower ranking. You can use this guide to see if the dips in your metrics are due to an algorithm change. 

What changes occurred in the landscape? 

The landscapes of both Google and Bing are in constant flux from algorithm changes and added features like rich and AI-generated search results. These changes can cause ranking, traffic, and lead declines as they get prioritized higher up the scroll, pushing organic results down. Additionally, your competitors aren’t sitting idly by. Changes made by these companies can also affect your analytics. Knowing how you show up in the landscape is key to getting the full story from your analytics. Our greatest recommendation is to use TopSpot’s Four Steps process in conjunction with the review of any data.  

• Step 1: Review the landscape using the keywords you are targeting. Ask yourself, are you showing up, and if so, how? Go beyond rankings and observe the search features included and how your competition shows up.  
• Step 2: Evaluate search queries using the B-SMART method. Are there areas you should consider, and how does this landscape differ?   
• Step 3: Evaluate your leads in LOOP Analytics. Are you seeing quality leads or irrelevant form-fills and solicitations? This is an insight into your customer base and the success of your marketing.   
• Step 4: Look at the SEO trends of these leads to see if they match up with your efforts in steps one and two. Existing leads can tell us a lot about what is working and what to consider.  

This process simplifies data analytics and how to manage the number of metrics available by allowing marketers to experience search through their customers’ shoes—painting a clearer picture for results in analytics tools. 

How does the data impact your most valuable KPI—your leads? 

We’ve discussed that there are tons of marketing metrics to track, many with accompanying visualizations, but the most important consideration to any analytics approach is how those metrics relate to lead data. Leads are the highest priority KPI because they are the greatest indication of marketing success and the metric that most impacts your business’s bottom line. This is why our Four Steps center on lead data and how metrics such as rankings and traffic affect those leads.     

To help relay data and their visualizations, consider embedding your visualizations within a narrative that includes the journey taken in the Four Steps. Guiding users through the key insights and implications of the data with this storytelling technique presents a clearer understanding of your digital marketing strategy, the effect on KPIs, and what actions you can take based on the insights derived. 

What’s Your Takeaway? 

Reactionary approaches to data visualization don’t always work as those charts and graphs do not display what’s happening outside the tool populating those results. Take data visualizations as an opportunity to find out what’s causing those peaks and valleys to improve your leads and marketing tactics. Finally, when sharing data visualizations from tools include additional information from the Four Steps to better illustrate results to those reviewing. The results should focus on the quality versus quantity of leads, which will allow better adjustments in strategy. 

For more information on data visualizations and interpreting data via the Four Steps, contact your Account Team. Not a TopSpot partner? Contact us to learn more.