Marketing budgets increased in 2022 after dropping to a historic COVID-19-related low in 2021. But content marketers can’t celebrate yet. That extra budget increases the expectation that marketers prove content delivers business results. Content marketers must step up their marketing data analytics approach to show how content delivers business results.
Doing so brings two fundamental benefits.
First, marketing data analytics helps content marketers communicate the benefits of content to non-marketing peers.
Marketers can get buy-in and build stronger relationships with business stakeholders by linking content assets to concrete business results like marketing qualified leads (MQLs).
Second, marketing analytics also equip content marketing leaders to make data-informed decisions about where to invest money and talent resources.
Marketers can de-emphasize poorly performing platforms and formats and invest more in higher-performing alternatives. That can increase the ROI from content marketing.
In fact, more than a third of marketers named analytics as the emerging technology likely to impact their strategy. Whether you’re just getting started measuring the impact of content or looking to refine your current program, follow these four steps to define your strategy for marketing analytics.
Step 1: Decide what you want to know from marketing data analytics.
More is not necessarily better when it comes to analytics, despite the availability of free or low-cost marketing analytics tools. After all, every metric you decide to track requires investment from the marketing team to make it useful. You need to track it over time, clean the data, de-duplicate it, and validate that it complies with your organization’s governance policies. And if you want to present it to anyone, you’ll need to visualize the data to make it consumable.
To avoid wasting resources tracking marketing analytics you ultimately don’t use, start by asking what you need to know. Pay attention to the questions you ask while planning your content strategy or quarterly calendar. Examples include: What content formats produce the highest volume of engagement? Which ones produce the deepest engagement (meaning, they drive conversions)? What content surprises do you see in terms of over- or under-performance?
Step 2: Understand what your business partners want to know from marketing data analytics.
You can engage with your business partners to understand their questions and identify corresponding data and analytics that could help answer them. By deciding which marketing analytics will help, you both commit to assessing impact according to the same terms. You also improve collaboration and alignment to determine which metrics to track, retire, or add as circumstances change.
Step 3: Ensure balance in the marketing data analytics you track.
journey. For example, striking a balance between “attention” or “attraction” metrics like site visits, banner clicks, and email opens and “engagement” metrics such as repeat visitors, social shares, or weekly newsletter sign-ups.
Other organizations may instead categorize metrics according to the business performance standard of leading indicators, lagging indicators, and operational indicators. Leading indicators predict specific actions, lagging indicators tell you what happened in the past, and operational indicators tell you about the effectiveness of your marketing processes. All three may align better with what business stakeholders expect to see.
Step 4: Leave room for soft metrics.
The evolving world of marketing data analytics can bring immense benefits. But that doesn’t mean marketers can or should abandon all non-quantitative approaches to assessing value. This applies to how marketers view the outcomes they can measure and how they communicate about aspects of marketing that remain inscrutable.
One example of the need for nuance in leveraging metrics relates to timelines. Some initiatives produce clear, short-term, and measurable benefits. A seasonal or event-related campaign is an example of that. Other initiatives, such as branding partnerships, are long-term by design to deliver value incrementally, often in ways that are difficult to quantify. The latter isn’t necessarily less helpful for its lack of transparency, but you need to evaluate it differently.
The core takeaway is that marketing analytics is critical in identifying high-value content topics and formats, measuring content’s impact on business results, and communicating that impact to others. But it is just one input you should use to define your content strategy, create a plan for executing it, and assess how well it served the business.
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