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These 4 Analytics Oversights Mess With Your Content Performance Plan

No matter how successful your content is, you can always identify and pursue optimization opportunities and use your analytics data to guide you.

Unfortunately, even the most experienced content marketers struggle to track the most helpful metrics and access, organize, and interpret the data. Even minor miscalculations can take content performance in the wrong direction.

Trust Insights’ chief data scientist Chris Penn recently chatted with Amanda Subler on Ask the CMWorld Community. He outlined common mistakes marketers make and how to make measurement plans more effective. Watch this video and/or read on for additional tips and techniques.

Mistake 1: Confusing metrics with KPIs

A metric is not the same as a key performance indicator (KPI).

Metrics are “business-as-usual” measures – quantifying things that add value to your organization but aren’t focused on the most critical goals.

KPIs are “numbers that, if they go in the wrong direction, you might get fired.”

Consider the metric of site traffic, for example. “If you’re a hardware store and your website traffic goes to zero, will you go out of business? Probably not. But if you’re Amazon and your site traffic goes to zero, well, yes, you could be in big trouble,” Chris says.

KPIs center on the numbers that validate your job performance. Chris explains: “What number will get you a bonus? What number will get you a ding on your performance review or get you fired? Once you’ve cleared that up, you’ll know which metrics are your KPIs.”

Select the metrics that relate to the KPI that matters most – the outcome the top brass at your company cares about the most. “You need to be able to draw a line between what your boss is being held accountable for and what your content is successfully accomplishing,” Chris says.

Mistake 2: Failing to set measurement priorities strategically

Not all metrics are equal in their ability to provide useful performance insights. But before you dismiss standard content marketing measurements like page views or social media followers as meaningless vanity metrics, Chris advises you to let the numbers – not untested assumptions – guide your decision-making.

“You have to run an analysis on all your available data to determine which (variables) are contributing to priority outcomes – such as an increase in revenue or closed won deals,” he says.

For example, in his work, Chris commonly runs data through a multiple regression analysis – a research technique used to see all possible combinations of your content variables so you can gauge their comparative value. This analysis can show which metrics have the strongest mathematical likelihood of driving a performance result that matters to your business.

“Only after your analysis reveals that number can you say, ‘OK, it’s clear social media followers aren’t driving any of the outcomes we care about,’” Chris says.

Mistake 3: Dumping too much data into dashboards

An analytics dashboard can make it easier to see which content is measuring up and falling short. But what data – and how much of it – should you include on the dashboard to get that clear picture?

Chris says marketers often assume the more data points crammed onto a dashboard, the more valuable it will be to content stakeholders. But it’s the opposite: “There is no such thing as the one dashboard that has all the answers in it. There’s no ‘one ring to rule them all,’” he says.

He develops relevant dashboards by asking clients to create a matrix of all levels in their organization ­– managers, directors, executives, etc. Roles are listed at the top, with job functions detailed at the bottom. “Every box in that matrix needs its own dashboard because what the CMO cares about may not be what the marketing manager needs to know. Creating a dashboard that tries to answer questions for everyone at once will end up failing to help with anything,” he says.

Instead of attempting to illuminate every potentially relevant data point, focus on the information that enables each role to make its most critical decisions. “Otherwise, you could end up creating these Frankenstein monstrosities, where people score all sorts of data everywhere but never increase their understanding of what actions to take,” Chris says. “Data without decisions are distractions, and a dashboard without decisions is just a decoration – you’re not going to use it, and it’s going to be a giant waste of your time to build.”

To approach dashboard development in a more manageable and useful way, Chris points to a method dubbed user stories by his Trust Insights co-founder Katie Robbert. Her process starts with filling in the blanks in this sentence with a key need or goal for your role:

“I need [a specific insight] so that I can achieve [a desired outcome].

For example, as a CMO, your user story might look like this:

“I need to understand my attribution analysis so that I can effectively allocate budget.”

A content marketing creator might use this sentence:

“I need to see which content is performing best from a revenue perspective so that I can create more content like it.”

As the SEO manager:

“I need to see which of our pages rank in organic searches most often so that I know which pages I need to fine-tune.”

“Once you’ve written out the story of exactly what you’re trying to learn, then you can create a dashboard to track performance against it,” Chris says.

Mistake 4: Rushing to act before understanding

Selecting the right metrics to track and building clear dashboards are table stakes for a data-driven content marketing strategy. But having that data on hand won’t help unless you know how to accurately interpret its meaning to know which actions will enable you to amplify or optimize your content’s performance.

Data analysis is not an easy skill to master, let alone apply to your content decision-making. But fortunately, Chris says, if you’ve done your tagging and tracking correctly, you can use Google Analytics to see what content is driving the best results – a strong step towards understanding how to amplify its success.

 “If I had to pick one report you should learn, and learn well, it would be conversion path analysis, which you’ll find in the new Google Analytics 4 under the advertising menu on your admin console,” he says.

Generating complex data reports like this requires some extra set-up steps – including setting goals in Google Analytics and conversion tracking in Google Tag Manager. But once you’ve done this, you can visualize comparative content channel performance for each stage of your funnel. You can see where your content may be losing steam across the buyer’s journey, indicating an area in need of optimization or a fresh approach.

Spend a bit more time on Google Analytics configuration (or have a data science specialist help you). You can create what Chris calls a most valuable pages (MVP) analysis to track the content pages and assets visited most by consumers as they progress toward conversion.

 “If you can find out what your most commonly visited pages are at each stage, it will tell you what content is working,” Chris says. “Then, you can make sure those are the pages you’re sharing on social media, putting in your newsletter, recommending at the bottom of your blog posts, because you’ll know, from a mathematical perspective, that they are going to nudge people towards conversion.”

 Make decisions with insights, not instinct

Finding out the most successful content assets is critical information, but even a powerful tool like Google Analytics can’t tell you why those assets outperform others.

“You’re never gonna get those answers out of analytics ever,” Chris says. Understanding the root cause of an action recorded in your analytics requires a different type of analysis – the kind you’ll need direct access to accurate qualitative insights to achieve.

“You’ve got to be able to do surveys, focus groups, polls … stop naval-gazing and go out and talk to customers,” Chris says.

Without that deeper audience understanding to help fill in the whys behind the what in your analytics, there will always be a gap between your measurement strategy and fully data-driven content decision-making.

Here’s how Chris looks at it: “You are data-driven if you make decisions with data first, which means you’re not first relying on prior experience, assumptions, or instinct. You are making decisions based on the reality that you can see.”

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Cover image by Joseph Kalinowski/Content Marketing Institute