Cluster Analysis: How to correlate personas and keywords - and what to do next.

Unlocking insight: learn which personas convert on specific keywords so you can create a personalised experience

In this video we will breakdown how we were able to identify which personas converted on certain keywords and how we used this to run message tests that improved performance across paid search.

Problem: Conversion rates were low in a highly competitive market. We suspected the messaging on our keyword specific landing pages wasn’t suited to the people who were converting.  We need to validate which personas were converting on certain keywords, so we could better write more personalised copy.

Analysis: We ran a cluster analysis to illustrate performance of specific campaigns/ keywords and how they perform by Job Title.

Outcome: We uncovered high correlation with specific job titles, which helped us experiment with different message themes to drive up the conversion rate.

All in all, understanding the relationship between personas and keywords is crucial for marketing success. Our goal is to explore how cluster analysis can help you identify which personas are driving conversions on specific keywords and how to leverage this insight for a more personalized user experience.

The Challenge: Underperforming Conversion Rates

Many businesses struggle with low conversion rates due to misaligned messaging on keyword-specific landing pages. To address this, it’s essential to validate which personas are converting on certain keywords and tailor your copy accordingly.

Conducting a Cluster Analysis

Cluster analysis is a powerful tool for revealing hidden patterns in your marketing data. Here’s how to implement it:

1. Data Collection: Gather campaign and keyword data, focusing on job titles of converting users.
2. Cluster Formation: Group data based on similarities in job titles and conversion behavior.
3. Correlation Identification: Pinpoint high correlations between job titles and keyword performance.
4. Insights Generation: Determine which personas are converting on which keywords.

Uncovering Key Insights

A well-executed cluster analysis can reveal significant correlations between job titles and conversion rates. For example:

• Marketing Managers: High conversion rates for keywords like “marketing strategy” and “brand development”
• Product Managers: Strong performance for keywords such as “product roadmap” and “feature prioritization”

Practical Application: Personalizing Your Approach

Armed with these insights, you can create more targeted messaging on your landing pages. This personalized approach not only boosts conversion rates but also enhances the overall user experience.

Key Takeaway: Personalized messaging on keyword-specific landing pages that addresses the pain points and jobs to be done of specific personas will drive higher conversion rates and improve cost per opportunity.

Steps to Personalization:

1. Identify Key Personas: Use your data to determine which personas are most likely to convert on specific keywords.
2. Tailor Messaging: Craft your content to address the unique needs of these personas.
3. Test and Optimize: Continuously run message tests to find the most effective themes and copy.

Running Effective Message Tests

Message tests are crucial for optimizing your marketing strategy. Experiment with different themes to determine what resonates best with your target personas:

• Pain-Point Focused: Address specific challenges faced by the persona.
• Benefit-Oriented: Highlight key outcomes from using your solution.
• Job-Specific: Tailor messaging to the persona’s specific role and responsibilities.

By implementing these strategies, you can create a more personalized marketing experience that drives higher conversions and improves overall campaign performance. Remember, the key to success lies in understanding your audience and continually refining your approach based on data-driven insights.

Questions still on a CMO’s mind:

Q1: How can we effectively integrate cluster analysis into our existing marketing processes without disrupting our current operations?

A1: Unlock the potential of your current marketing operations by seamlessly integrating cluster analysis. Start by identifying key touchpoints in your data collection process where persona and keyword information can be gathered. Leverage your existing analytics tools to form clusters, or invest in specialized software for more advanced analysis.

Key Steps:

• Audit current data collection methods
• Train your team on cluster analysis techniques
• Implement a phased approach, starting with high-impact campaigns
• Establish regular check-ins to review and refine the process

By taking a systematic approach, you can incorporate cluster analysis without disrupting your current operations, allowing for a smooth transition to more data-driven, personalized marketing strategies.

Q2: What specific metrics should we track to measure the success of our personalized messaging strategy, and how quickly can we expect to see meaningful results?

A2: To measure the impact of your personalized messaging strategy, focus on these key metrics:

• Conversion Rate Lift: Compare conversion rates before and after implementing personalized messaging
• Cost Per Opportunity (CPO): Track changes in CPO as messaging becomes more targeted
• Click-Through Rate (CTR): Monitor improvements in CTR for personalized landing pages
• Time on Page: Measure increased engagement through longer page visit durations
• Customer Feedback: Gather qualitative data on message relevance and resonance

Timeline for Results: While some improvements may be noticeable within weeks, expect to see significant, measurable results within 3-6 months of full implementation. This allows time for message testing, optimization, and data accumulation across various campaigns and personas.

Q3: How can we ensure that our personalized messaging remains scalable and adaptable as our target audience evolves or expands?

A3: To maintain the effectiveness of your personalized approach as your business evolves:

1. Build a Flexible Framework: Create a modular messaging system that allows for easy updates and additions as new personas or keywords emerge.
2. Implement Continuous Learning: Set up regular review cycles to reassess persona-keyword correlations and adjust messaging accordingly.
3. Leverage AI and Machine Learning: Invest in tools that can automatically identify new patterns and suggest messaging updates.
4. Cross-Functional Collaboration: Foster ongoing communication between marketing, sales, and product teams to stay aligned with evolving customer needs.
5. Diversify Data Sources: Continuously expand your data collection methods to capture emerging trends and audience shifts.

By focusing on adaptability from the outset, you’ll create a personalized messaging strategy that can grow and evolve alongside your business, ensuring long-term success in an ever-changing market landscape.

Remember, the key to scalable personalization lies in creating a system that’s data-driven, flexible, and responsive to change. By addressing these strategic concerns, you’ll be well-positioned to implement and maintain an effective, personalized marketing approach that drives results now and in the future.