The other day I was thinking about an old job I had before starting Pepperland, back when I was a Digital Analytics Manager at a large multinational corporation. In my role, I was tasked with helping the marketing team that I was a part of learn how to leverage analytics and become more data-driven.

I think I did a decent job at it, but as I reflect on how I handled things through the lens of what I know now, I’m a bit embarrassed by some of the mistakes I made.

One example was how I presented data at our monthly “MOR” meetings (short for monthly operating review) and quarterly “QORs” (quarterly operating reviews).

Pressured to simply get the word out on “what happened,” I’d use my slides to present the data and trends. “Here’s how many visits we got.” “Here’s how many visitors turned into leads.”

No story behind the data.

No insights. No explanations. No thoughts about what could be done differently.

There wasn’t a single thing that I was measuring and presenting that I had direct or primary responsibility for improving.

One of my old slides. Sigh.

The result? My boss seemed excited that these monthly meetings finally included metrics and data (at least initially), but my peers seemed less than thrilled. I could feel people in the room cringe when it became my turn to speak as if they were about to be publicly shamed.

What I Could Have Done Differently

Rather than using my time to present the data, as though I was some oracle who could see things that nobody had access to, I wish I focused my time presenting how I had helped to make the organization more empowered with data. That might include:

  • How many analytics training sessions were held
  • How many new dashboards or custom reports were created
  • A summary of updates or improvements to the implementation of our measurement solution

The real measure of my success should have been how many others were using data to tell their own story. I should have enabled them to be the data-driven heroes.

My hope is that by sharing these reflections, those who are reading this and in a similar role can hopefully avoid making some of the same mistakes I made.

Here are some additional ways you can make your marketing review meetings more data-driven:

1. Use Meetings to Focus on the Outliers

Being data-driven means that you are driven by the data. “Driven” implies action.

The only way you can take action from data is if you know what needs to be improved or corrected. An easy way to do this is to find the outliers or anomalies in your data.

If I were to step back in to my old role today, here’s how I might advise my peers to prepare their own slides and notes for the meeting.

  1. A quick review of KPIs. Did we hit the goal? How far over/under? Time: 2 Minutes
  2. What worked well. Where was the primary improvement compared to the previous month? What steps can be taken to continue or strengthen this trend in the month to follow? Time: 4 Minutes
  3. What fell short. What performed below expectations? What lessons were learned from it? What is going to be done differently in the month ahead to course-correct? Time: 4 Minutes.
  4. (Optional) Things to brag about. Most people take pride in their work, and want an opportunity to show off a little. If time allows, build this in. Otherwise, cut it and find other opportunities to showcase the fun stuff. Time: 5 Minutes.
  5. Peer Feedback. This is an opportunity for others to react to the data and the insights provided. Time: 5 Minutes

This structure puts the emphasis on insights gleaned from the data, and the actions that will be taken as a result of those insights.

Tip: An easy way to quickly identify outliers in Google Analytics is to change the report from default view to the “Comparison” view. This will provide you a visual of which rows performed better or worse than the site average. The larger the bar, the greater the variance from the norm.

Identifying Outliers in Google Analytics


Once you have identified the outlier, click on that row, and add a second dimension to try to identify why that segment underperformed. Was it a problem with mobile-friendliness? A new referral source that generated low-quality traffic?

If you’re more analytically adept, I recommend reading Avinash Kaushik’s article on leveraging statistical control limits as an additional way to identify outliers.

2. Encourage A “Top-Down” to “Bottom-Up” Measurement Framework

Marketing KPI Organizational Hierachy

At the end of the day, a business exists to make money. As a C-level executive, there are likely only a few metrics that will indicate the health of a business, and whether or not the organization is hitting its goals.

If meeting discussions are focused on the outliers and actions that will be taken as a result of them, there’s no need to include more than a few primary KPI’s in the c-level’s dashboard. But by eliminating the noise, the people in the room still need to be prepared to explain the underlying factors that contributed to a goal to being met or missed.

This requires that a review of a more granular set of data occurs prior to the c-level meeting. Essentially, data from lower levels in the organization should be rolling up, in stages, from the very bottom to the very top.

In order for this to happen effectively, you need to first establish S.M.A.R.T. goals based on the organizations top-level objectives. This means that in order to have data flow from the bottom-up, you first need to plan from the top-down.

Let’s say the organization sets a goal of increasing revenue by 20% in the year ahead. Here are some goal-setting questions that could be asked from senior leadership all the way down to the individual contributor level:

  • C-Level: What percentage of this should come from new business?
  • Sales/Marketing VP: If our average deal is worth 50K, how many deals do we need to close in order to hit 20 million? How many deals will we have to work to hit that goal? How many qualified leads would we need?
  • Marketing Manager: How many leads and visits will we need to capture in order to hit our qualified lead goal? How would this need to breakdown by market segment, acquisition channel, or campaign?
  • Email Marketing Specialist: How many clicks from email do we need to generate in order to hit our conversion goals? How much does the database need to grow in order to hit that number? What does our click-rate need to be? What about our open rate?

This approach should lead to the creation of a meaningful hierarchy of key-performance-indicators, or KPIs, that should be measured at each level in the organization—each set rolling into a higher-level KPI, helping to explain why the higher-level metric is what it is.

This also helps those who are lower in the organizational hierarchy more clearly tie their actions back to revenue. It helps create a more direct line from a Facebook Page Like to a won deal, or an increase in search rankings to an uptick in qualified leads.

3. Eliminate Surprises

When I first stepped into an analytics role, I often felt perplexed as to why my peers weren’t embracing the powerful measurement tools that were being made available to them. As I think about it now, I believe it was partially due to the lack of training and education on what the data meant, and how it could be used.  Another factor may have been doubts about the accuracy of the data (something we at Pepperland can help with).

I think the biggest hesitation came from the fear that data would suddenly shine a light on failure that had gone undetected until it was too late to do anything about it.

If you’re only pulling up your reports and dashboards on a monthly basis, you’re setting yourself and your team up for many painful surprises. This is a good way to ensure people WON’T be excited about the data.

Today, data has become so accessible there’s really no excuse for your team to not be able to walk in to the office every morning, and within 10 seconds or less immediately know if they’re hitting their goals or not. Tools like Databox allow you to create customized dashboards that display data in real-time from nearly every tool a marketer uses – Facebook, Google Analytics, HubSpot – you name it.

Flat Screen Analytics Dashboard at Pepperland's Office

In our agency’s office, we have a flat screen TV that rotates through several Databox “datawalls” throughout the day. We’ll often break into conversation around a new content idea that’s triggered when we see a new keyword emerge on our Google Search Console dashboard, or when we see a conversion rate dip in our HubSpot data.  It’s allowed us to gather insights and react in real-time, so there’s never any surprises.

What Would You Add?

I’m confident that the ideas above will help you and your organization become more data-driven and hold more meaningful monthly meetings, as I’ve experienced it first hand. What would you add to this list or do differently? What barriers have you encountered in your own organization, and how have you overcome them? I invite you to share your ideas and experiences in the comments below.

Google Analytics Quality Review