What is data science? A combination of various tools, Google Algorithms, and Artificial Intelligence strategies, designed to follow the hidden patterns using the raw data is referred to as data science. Data science is creating its impression across every domain.
A Study by Maryville University states that around 1.7 MB data will be generated every second for everyone on the planet by the end of 2020.
Why do you need it?
Data science provides valuable information about a website’s performance and these insights can help you in improve your SEO Strategies. Data science is used to make assumptions about upcoming trends and customer behavior using Google Analytics and Artificial Intelligence. For example, Netflix uses insight from data science to produce its original series that drives user interest.
Apart from identifying opportunities, data science also handles high volume of data and helps in making better decisions. Businesses can easily take an insight for the importance of a marketing campaign with the help of data science.
How does data science help SEO?
Data science helps a Businessman to make a straight forward decision by letting himself:
Visualize which combinations have the potential to make the biggest impact.
Create marketing campaigns aligned with the needs of their audience.
Understand buyer’s preferences and identify pain points.
Identify referral sources of converting traffic.
Verify loading time, indexing, bounce rate, response errors, and redirects.
Verify the most and least crawled URLs.
Identify pages that crawlers aren’t supposed to index.
Identify sources of unusual traffic
How do you apply data science to your SEO data?
Follow the below ways to apply data science to your SEO campaigns:
1. Select your data sources
Understand that the quality of your data sources directly impacts your data insights. You need the right tools to track important metrics more precisely. The top four tools that can help you gather the right data and make better decisions are Google Analytics, SEMrush, and Ahrefs.
Search and the ecommerce holiday season: Capturing key moments that matterTop five SEO tools to generate more leads in 2020An introduction to Google Ads Video Ad Sequencing (VAS)Yext researches what American customers are looking for throughout the year
2. Think “ecosystem” instead of “data” and “tools”
Do not rely on one solution if your SEO is complex and integrates with various other digital marketing areas like content marketing, CX management, CRO, and sales. The “data science” approach to SEO is about integrating methods, tools, and practices in a way that draws deep and accurate insights from the cumulative data mix. Consider the SEMRush console we discussed above. The traffic stats it presents work on the assumption that all traffic is genuine. What if there are bad bots at play here? It makes a lot of sense to bring in a traffic quality checking tool into the mix, something like what Finteza does.
It offers you advanced bot detection tech, along with a whole suite of conversion funnel optimization modules, to help you not only make more sense of your data but also to put the insight into action, to drive business KPI scores.
3. Align SEO with marketing initiatives
Backing your SEO with other marketing initiatives makes it stronger. Collaborate with sales, developers, UX designers, and customer support teams to optimize for all search ranking factors.
Use data science to determine a universal set of SEO best practices each team can follow to achieve your goal. Try tracking the evolving relationships between independent and dependent variables to get a better idea of what actions are important to your business. To fully understand how your SEO affects other channels, capture and analyze data from:
Top conversion paths
Conversions and assisted conversions
Gain a clear understanding of your customers’ journeys to establish a stronger alignment between various marketing activities and attribute the outcomes to separate campaigns easily.
4. Visualize with data science
Find it hard to digest numbers piled onto a spreadsheet? Taking a hierarchical approach to your data can cause you to miss out on important hidden between the lines. On the other hand, draw different benefits from data visualizations like:
Compare and contrast
Process large data volumes at scale
Accelerate knowledge discovery
Reveal hidden questions
Spot common patterns and trends
Test it out yourself.
5. Take help of A/B testing
For Complete Blog:
0 Comments