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5 min

Why your analytics land with a thud

by Ben Magnuson October 28, 2020

It may be easier than ever today to collect data, but many marketers still find themselves scratching their heads when trying to decide how best to sift through it to uncover the gems. What’s often even more difficult, however, is developing reports that incite action and encourage future investment in the right strategies and optimizations–especially when findings challenge the status quo.

In this session, presented at the 2020 Virtual LMA Annual Conference, I explore how to deliver reports that your stakeholders will actually care to read. Specifically, I dive into how you can shift your reporting strategy to ensure you are:

  • Establishing the right baselines and goals to help you more accurately benchmark your progress towards KPIs
  • Moving beyond simply showing your work to provide the right level of context around data trends that matter
  • Including stakeholders in the development of metrics to prevent surrogation, or the confusion of strategic intent with the metrics meant to represent it
  • Creating an influential narrative around your results that helps you overcome bias, combat conventional thought and improve decision making

Following the session, I received a handful of questions I run into frequently with clients. I’m sharing the answers below in hopes that they can help your reports go from thud to bang.


Q: You have shown many different types of charts. Design-wise, do you have any tips to determine which type of infographic works best for which type of data?

A: This will vary depending on your data, but you can get really far by just sticking to bar graphs or line graphs.

As with every rule, there are exceptions. However, for the most part, line graphs are best to show differences over time. Bar graphs show quantitative differences between different data dimensions.


  • Need to show pageviews to the website this year by month? Use a line graph.
  • Want to show how much traffic each website section gained last month? Use a bar graph.

Although this may feel stale, you can add so much to the design of these charts with annotations and highlighting. The fact that these graphs are so popular works in their favor; your audience won’t need to onboard themselves to the purpose of the visualization.


Q: You showed the example with the huge table/chart with the green highlights and noted it was asking the audience to determine their own takeaways. I present internally to fellow marketers. What are your recommendations to maximize their knowledge, but still offer them great internal service?

A: Typically where I fail in using an overwhelming chart like the example I showed stems from me not taking the time to build a new concept, or prove that I’m showing the maximalist view because I’m anticipating questions.

The chart in question is creating a “Read %.” It’s a novel metric that takes the amount of pageviews that scrolled at least half the page of an article and divides it by total pageviews.

With proper onboarding, this would be best served by just showing the most “read” articles to the audience with a minimum number of pageviews. This provides the depth of this more advanced reporting to other members of your team without having their eyes glaze over when faced with all of the numbers and math involved in deciphering them.


Q: How do you deal with data discrepancies between platforms? e.g. Google Ads and Google Analytics?

A: This is a difficult question without an easy answer.

At a minimum, make sure when comparing numbers you are doing an apples-to-apples view. For example, if you are looking at a Google Analytics view that filters out internal traffic, it may not match up with an external source that doesn’t.

But there will always be discrepancies across different systems, even when measuring the same traffic. Prioritize the sources that actually record the actions.

In this example, Google Ads and Google Analytics will commonly cause frustration when Ads is showing more clicks than Analytics is showing users for a particular ad campaign.

When this happens, I trust Analytics to tell me how many users actually arrived, even if I ended up paying for more clicks. If somebody clicks on an ad and x’s out quickly, there is a good chance the GA script never fired to show the user. But that is more accurate to me on actually telling me the impact of the ad than counting clicks.


Q: Can you talk more about the importance of Marketers learning SQL and/or database management in the near future?

A: I have always learned best by getting hands on with the products and technology involved in my direct job but also others’. However, I have also wasted time training on things that were not worth the time and did not prove useful.

Learning SQL or training on database management would set you apart in your job and help create a lot of value. But I would only recommend doing it if you wanted that to be a large part of your job and have the opportunity to work on SQL or with data at least weekly. These skills take time and effort, and atrophy really quickly when not used.


Q: You touched on this some, but what key analytics do you go back to and track to show the clearest picture of web traffic activity?

A: For the website as a whole, I focus on users. Sessions and pageviews paint how engaged your users are in that if you have many more pageviews than sessions, and sessions than users, it shows they are coming back and viewing multiple pages per session. But it’s users you want to acquire.

But beyond that, at a site level, I try to focus on key user events that depend on website goals:

  • New subscribers
  • Contacting firm or attorneys
  • Key resource downloads

Within individual sections, there is a lot of variance in what’s important. Thought leadership, for example, is more heavily dependent on organic traffic than Services and Industries. Because of this, I’m more interested in organic entrances and scroll depth than Services, where I am more interested in how much traffic to those pages were successful in keeping users on the site.


Q: What is your view on bounce rates. I struggle with this, but since law firm websites generally aren’t focused on conversion, sometime bounce rates can indicate the user found the information they were looking for.

A: As a sitewide metric, it is not helpful for sites as large as legal websites. Here are areas where you should pay attention to high (>50%) bounce rates:

“Listing” pages:

  • These are called different names, but pages such as your Professionals search, Services page and Insights page should not have high bounce rates. The entire point of those pages is to help their audience find what they are looking for. If people are bouncing at high rates, the page isn’t doing its job.

Pages with high organic entrances:

  • The exception is articles, which will have high bounce rates due to the nature of the content. It’s not bad to try and convert as much of that traffic to stay as you can, but, no matter what you do, it will be difficult to get an article below 50%.
  • Search engines don’t like it if they send their audience to a link and they bounce right away–they are definitely tracking this and penalizing sites when it happens. To help combat this, create reports of your highest bounce rate (non-Insight) web pages with at least 50 pageviews. See if there are any commonalities between them, or if there are design issues that may be causing visitors to bounce. This could be a great place to utilize User Testing for more qualitative information.


If you have another question, or you’re looking to improve your analytics reports, contact us to learn more about how One North can help you better put your data to use.

Ben Magnuson
Associate Director, Data Strategy

As Associate Director, Data Strategy at One North, Ben supports clients by applying a strong data focus to marketing initiatives across channels and tools. He starts by gaining an understanding of each client’s unique goals and tactics, and guides them toward a strategic analytics program. He focuses on the creation of a meaningful feedback loop to help support and steer decision-making.