A robust content strategy includes data analytics in its foundation. Knowing specifically who, when, where, and how much content your customers are consuming––or overlooking––gives your content strategy and overall customer experience an additional level of precision and accuracy.
Content strategy is often described as “getting the right content to the right user at the right time.” How can you accomplish this? Through spending time understanding your stakeholder’s needs, current content landscape, customers and competition.
Assessing the data and collaborating with your Data and Insights teammates strengthens each step in the content strategy process. You can’t argue with the numbers––and sometimes that’s exactly what will give your content strategy recommendation that extra boost of credibility.
Ensuring data analytics are present throughout your content strategy activities ensures a winning game plan. What is our approach? Here are some examples:
Stakeholder Interview Effectiveness
Understanding your stakeholder’s needs, objectives, and pain points are essential when initiating a content strategy. Detailed traffic reporting exposes the most active through the most overlooked content and gives a sense of which content is essential, where revision is needed, and which content no longer provides value and is ready for retirement.
Knowing the page-level traffic and SEO activity from the past year gives you a foundation to conduct a stakeholder interview meeting with accuracy and gain the most valuable feedback. On the other hand, industry trend reporting improves your understanding of the competition and their aspirations to make the most of stakeholder feedback and quickly uncover opportunities to dive into untapped areas.
Questions from a Data Analyst to understand the current state of content:
- What are the key digital marketing challenges the team(s) face today?
- How does your company measure and compare page performance?
Content Audit Guideposts
Auditing a large-scale or problematic site within a limited timeframe can be a daunting task. Assessing the content that is most valuable to your customers and knowing the focus areas is critical for efficiency and accuracy, while current and historical traffic data guides the way to uncovering unknown opportunities and new directions for the content.
Analysis of SEO keywords, descriptions, and ranking helps with formulating a plan for attaining stronger domain authority. Using analytic data supports your decision-making process for what content to prioritize, what to improve, and what to retire.
Questions from a Data Analyst to drive a precise content audit:
- Describe your digital marketing approach to new customer acquisition and customer retention.
- Describe how your digital marketing approach varies for specific products and services.
- What types of content are gated?
- Describe the most successfully performing content.
Understanding how other brands are performing within the market landscape gives powerful information for delivering unique content recommendations. Your goal should not be to catch up with the competition, but rather to discover opportunities to become a leader in untapped areas through designing unique content features. You can make it easy to identify the gaps and opportunities by sharing your investigation through a competitive content feature set chart.
Industry data analytics provide direction for uncovering these opportunities. Comparing the quality of specific content features and tools across the competition––backed by usage data––helps to accurately prioritize where it’s essential to catch up and which elements open the door to being seen as the standout owner of a valuable content feature.
Questions from a Data Analyst to understand competitor content:
- Who are your competitors?
- What type of competitor analysis have you used for optimization hypothesis generation?
Defining your audience is critical to developing a content and UX strategy from ideation through a content personalization plan to a post-launch content marketing program. Backing up persona attributes with data allows your story to be detailed and accurate. It also guides the decisions for identifying which activities, actions, and content types to expose at each level of the customer journey.
Questions from a Data Analyst to support persona definition:
- What channels are personalized (site, email, DM, call/contact center, app, other)?
- What attributes drive personalization?
Qualitative and Quantitative Approach
Knowing how to work with data will undoubtedly make your content strategy decision more impactful. To do this, you have to emphasize working collaboratively with Data and Insights teammates to ask questions that drive deeper research and validation of theories and hypotheses.
Want to learn more about how Hero’s data-driven approach to content strategy can make your customer experience more successful? Contact us.