In the 20th century, marketers relied on coupons, customers’ anecdotal feedback, and mainstream media subscriber numbers to understand their reach and impact. It was an educated guessing game at best to discover what worked and what didn’t.
But in the digital world, numbers abound for marketers to analyze and interpret their audience and customer behavior. Still, marketing analytics remains a challenging discipline.
To help you realize you’re not alone in the analytics conundrum, we asked the experts presenting at Content Marketing World what they see as the biggest challenge in marketing analytics. Fortunately, they shared their concerns and came through with advice on how to overcome the hurdles.
Seeing all the data as necessary
Holding onto the past belief that capturing every behavior and all the attributes about an individual you can is the road to despair. That level of granularity is going away and — with modern models and methods — is proving to no longer be cost-effective. — Jim Sterne, president, Target Marketing of Santa Barbara
Having too much and not enough
One of the biggest challenges in marketing analytics today is the overwhelming amount of data available and the complexity of integrating data from multiple sources. With the proliferation of digital channels, social media, and various marketing tools, organizations often struggle to consolidate and make sense of the vast amounts of data generated. Organizations need to invest in data analysts, who are part of the marketing organization, to seamlessly integrate data from various sources. — Royna Sharifi, senior marketing campaign manager, Amazon Web Services
Treating it like a scientific walk in the woods
Overkill. Sometimes seeing the forest from the trees is more important than just analyzing the trees. — Michael Bonfils, global managing director, Digital International Group
Failing to integrate analytics
One big challenge in marketing analytics is the “overwhelm” factor. Most of us manage multiple tech platforms. While we can aggregate insights from several platforms into one set of dashboards, it takes skill and effort to configure and maintain it. It’s worth it, but it’s not easy. Get expert help or risk procrastinating to your own detriment. — Bernie Borges, vice president, global content marketing, iQor
Missing dashboards
We see that many companies either don’t measure or don’t measure the right things. For us, as a company, it is essential to set up a report or dashboard for every client. This way, we always focus on the right KPIs (established when setting objectives). We don’t just report at the end of a campaign but also during its execution. This allows us to constantly adjust and optimize. — Pauline Lannoo, head of digital strategy, The Fat Lady
Bungling for business objectives
The biggest problem is the failure to connect the goal to the measurement. Marketers will often rely on vanity metrics or irrelevant metrics as indicators of success when they might not indicate the achievement of a goal.
If you’re just looking to increase traffic or brand awareness, page views might be one good metric to report on. If you’re trying to sell more products or services, page views only matter if they turn into conversions. Match your key performance indicators (KPIs) to your objectives and key results (OKRs). — Brian Piper, director of content strategy and assessment, University of Rochester
Interpreting by many
Lack of consistent reporting language. Organizations are collecting and have access to more data than ever before, yet this data is often siloed in different tools.
Because of this, data can mean different things to different people. What defines a visit in one tool may not be the same as in another. Also, organizations often try to marry together anonymous and known data, which can be nuanced. It is important to define a consistent reporting language to get the most out of your marketing analytics. — Jill Roberson, senior vice president, digital marketing, Velir
Giving ‘fuzzy’ AI assessments
Few tools exist to monitor whether AI presents your content, so marketers have little to no insight. I know of two ways to get an idea of AI’s interaction with your content.
One is in GA4, where you can track AI bots. Create an exploration with “page referrer” as the dimension and “sessions” as the metric. Then apply this filter: ^https:\/\/(www\.meta\.ai|www\.perplexity\.ai|chat\.openai\.com|claude\.ai|chat\.mistral\.ai|gemini\.google\.com|bard\.google\.com|chatgpt\.com|copilot\.microsoft\.com)(\/.*)?$
The other way is in Semrush through its keyword position report for tracked keyphrases or the SERP features section in a domain overview.
All these assessments are fuzzy at best but do offer directional information if your informational content is seeing decreases in clicks. Fortunately, or unfortunately, the need to monetize AI will result in much more straightforward AI insights and tools for brands and partners. — Haley Collins, director of operations, GPO
Going for the quick and easy decision
Marketers often have numerous systems tracking different metrics and no way to integrate and normalize that data. This means we tend to over-rely on whichever tool we think is easiest to get whatever data people ask for most frequently instead of using the data to make better content marketing decisions overall.
For example, although it’s been over a year since GA3 quit collecting data, a lot of marketers still have not defined their goals or optimized their GA4 reporting. I even know of one team that hasn’t turned G4 on yet.
It’s hard for me to imagine having an entire year without any web analytics to learn from. — Erika Heald, founder and chief content officer, Erika Heald Marketing Consulting
Minimizing the power of GA4
Getting what you need out of GA4. There are two approaches here: Have team members dedicate the time and energy to learn it or outsource to an agency or consultant. — Dennis Shiao, founder, Attention Retention
Paying the price
The cost is a big challenge. These tools are inaccessible for many smaller companies and independent content marketers, and that needs to change. — Beth Elderkin, content marketing manager, Informa Connect
Lacking accountability
Definitely attribution. This means taking more ownership of the full cycle from external agencies and building up internal expertise and capabilities over time, particularly around basic tracking. — Tony Byrne, founder, Real Story Group
Believing in unicorns
The biggest challenge by far is holistic attribution, IMO. The unicorn of multi-touch hasn’t really been actualized, and plenty of marketing can drive results that’s never attributed – without that attribution, funding becomes questionable. — Jenn VandeZande, editor-in-chief, SAP CX + Industries
Having only one key to the vault
Many marketing analytics are gatekept by one individual or team. Evangelize this data to everyone so they can monitor how their content is doing and keep eyes on it themselves. This will make organizations more data-focused and proactive with this information. — Zack Kadish, senior SEO strategy director, Conductor
Missing collaboration between marketing and sales
There is a disconnect between the top of the purchase funnel metrics (marketing) and the bottom of the purchase funnel metrics (sales). The crux of the matter lies in transitioning prospects from the top of the funnel seamlessly to the bottom of the funnel, ultimately driving conversions and maximizing sales potential. — Pam Didner, vice president of marketing, Relentless Pursuit LLC
Lagging skills and time
The biggest challenge with analytics is not devoting resources and time to keeping your systems up to date. It’s critical to assign an analyst or expert to handle the ongoing maintenance and updates required to keep your systems in step with your evolving marketing campaigns and strategy.
Keeping that analyst in the loop as things evolve — so they can make appropriate updates to your systems — is the only way you can properly and confidently report on actual results. Without this, you risk getting an inaccurate or incomplete picture of what’s actually happening. — Monica Norton, vice president, communications and content, Nextiva
Ignoring inclusivity
Transitioning from third-party data to first-party data and quantifying data points in a cohesive, equitable way is what many are navigating now and even more so in the coming years ahead. How do we accurately (and equitably) define an ideal customer profile (ICP) without bias, pulled from trusted sources that give us a good holistic picture to speak to? Many brands have not done the leg work with the shift as privacy is changing, and capturing accurate data is even more critical.
Put together a process that embraces DEIBA (diversity, equity, inclusion, belonging, and accountability) best practices or work with trained professionals who can help integrate that into the capture, nurturing, and output process. — Troy Sandidge, founder, Strategy Hackers
Making the most of the analytics that matter
Whew, that’s a lot of challenges with marketing analytics. How many resonate with your situation? Fortunately, awareness is the first step to overcoming them. So, now that you know you’re not in a unique situation, make a plan today to tackle one piece of advice on how to solve it.
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Cover image by Joseph Kalinowski/Content Marketing Institute