Leveraging Data To Make Informed SEO Strategies

Leveraging Data To Make Informed SEO Strategies

Data-driven SEO is an approach to search engine optimization (SEO) involving the use of data to inform and guide the optimization process. SEO should always have been guided by data, as an approach, data-driven SEO has been aided by the advances of machine learning- a (semi) automated statistical model to reliably find patterns in data and better understand SEO, and secondly cloud computing facilities like Google Cloud Platform (GCP), Amazon Web Services (AWS) and Microsoft Azure to store SEO data at scale and run ML models

The approach typically involves the use of a variety of data sources and tools, and analyze the data on factors like search results (e.g. search intent), website traffic performance, user experience, technical data (content indexation) and conversion rates.

Case study on: The Power of Data-Driven SEO

Glassdoor.com, before its sale to Recruit Holdings in 2018, had an impressive 29,500,000 in monthly traffic, which is almost entirely organic. This success was the result of a meticulous, data-driven approach to SEO. Glassdoor’s strategy involves analysing data from various internet sources to identify content gaps and create high-value, well-optimized content. The approach led to over 200,000,000 backlinks from more than 200,000 websites, establishing their influence and authority in the online employment industry.

Glassdoor used data to identify valuable content assets and gaps, creating content that brought them closer to their prospects. This data-driven strategy significantly influenced their rankings in search results for the online employment industry.

What Types of Data are Important in SEO?

Types of data that matter in SEO, providing unique insights that can inform SEO strategy:

• Traffic data
• Keyword research data
• Backlink data
• Competitor data
• Content data
• User behaviour data
• Technical SEO data
• Conversion rate data

Importance of Data in SEO

Data takes the guesswork out of SEO, allowing you to focus on what works based on empirical evidence. For instance:

• Keyword research data helps you understand your target audience’s pain points.
• Bounce rate data can help you address issues affecting user engagement.
• Engagement metrics show which content resonates with your audience.

How To Use Data in SEO Strategy

1. Define clear objectives for SEO. Set SMART (Specific, Measurable, Achievable, Relevant, Time-Bound) SEO objectives that help in navigating the volume of available data and prioritizing key areas for your campaigns.

2. Establish baseline metrics and KPIs. KPI identification for measuring current performance provides a reference point for evaluating the impact of your SEO strategy.

3. Understand user intent. Analyzing search intent behind keywords for effectively optimizing your content. The Google Search Console tool is used to track click-through rates (CTR) for individual pages, indicating how well your content matches user intent.

4. Choose High-Opportunity Keywords. Identify “low-hanging fruit” keywords with significant search volume and evaluate their business potential before targeting them.

5. Gather and Analyze your website data. Google Analytics tool is used for tracking your website traffic and user engagement metrics, providing insights into your search performance and aiding you in identifying areas for improvement.

6. Conduct competitor analysis. Tools like Semrush help you in finding keyword gaps and backlink opportunities.

7. Create a data-driven SEO strategy. Creating an informed SEO strategy should include creating an ideal customer profile, targeting the right keywords, conducting a site-wide audit, and creating a content calendar.

8. Double-down on high-performing keyword categories. Identify which keywords drive the most organic traffic and conversions on your site. Use Google Search Console to see which terms rank highest and attract the most click-throughs from search results.

9. Making the best content effective. Examine your highest-performing content to identify factors that make it engaging for users. It includes several aspects: word count, tone of voice, presentation, originality, expertise demonstrated, and call-to-action (CTA).

10. Analyze which user journeys lead to the highest levels of conversions. Look for commonalities in these high-converting paths and aim to replicate these elements across the site.

11. Prioritize core web vitals. Google’s PageSpeed Insights is used for evaluating a site’s performance across Core Web Vitals metrics. Implementing recommended fixed improve the site’s user experience.

12. Optimizing and enhancing the site’s mobility usability. Mobile accounting for about 63% of organic search traffic in the U.S. For example, Google’s Lighthouse tool is used for testing and implementing required improvements.

13. Analyze backlinks for more targeted outreach. Studying the site’s backlink data for optimizing link-building strategy.

14. Collaborate with cross-functional teams. It includes communicating the value of SEO to all stakeholders and aligning it with broader business goals.

15. Monitor and iterate. Continuously monitoring progress and being prepared to iterate based on new data and insights.

Tools for implementing the strategies effectively:

• Google Analytics
• Google Search Console
• Ahrefs
• Semrush
• Screaming Frog SEO Spider
• PageSpeed Insights
• Lighthouse

Final Thought:

The use of the right data helps in making informed strategies, cutting through the noise and achieving better results on the search engine results pages (SERPs). The final step of data-driven decisions is to put your strategies into action and benchmark against your previous performance.

Leveraging data as a foundation for decision-making, enables creating more effective SEO strategies. From capitalizing on high-performance keywords to enhancing mobile usability and optimizing backlink strategies, each data-driven action helps in solidifying your online presence and improving rankings