Understanding the 4 main types of digital analytics is crucial for measuring and optimizing your online presence. This guide explores descriptive, diagnostic, predictive, and prescriptive analytics.
As a digital analytics agency, we utilize all four categories to extract powerful insights for clients. Descriptive analytics form the foundation while advanced predictive and prescriptive methods take things to the next level.
Descriptive Analytics: What Happened?
Descriptive analytics focuses on reporting what happened through historical data. Key metrics include:
- Web traffic metrics like visitors, page views, bounce rates, etc.
- Sales and conversion metrics like revenue, transactions, and conversion rates.
- Rankings for SEO performance.
- Social media analytics like shares, likes, and comments.
Descriptive analytics are visualized through reports and dashboards. They provide a snapshot of past performance.
For a digital analytics agency, descriptive analytics allows us to monitor websites and campaigns. We can track volumes, analyze trends, and benchmark metrics over time.
Example of Descriptive Analytics
E-commerce Site X had 115,000 visitors last month and viewed 350,000 pages, with an average session duration of 1:50 minutes. Revenue was $25,000 at a 2.5% conversion rate. The top landing pages were Home, Category A, and Product Y.
This outlines volumes and conversion metrics to assess what transpired.
Diagnostic Analytics: Why Did it Happen?
While descriptive analytics show what happened, diagnostic analytics aim to explain why it occurred.
By analyzing user behavior data, we can determine the causes behind metrics. This provides insight to improve experiences.
Examples of diagnosing issues include:
- Analyzing exit pages to identify UX problems
- Exploring traffic source conversions to find the best channels
- Optimizing site search terms for better discovery
For a digital analytics agency, diagnostics allow us to dig deeper into data to inform better decisions. We can identify issues and opportunities to optimize performance.
Example of Diagnostic Analysis
Product page bounce rates are 50%+ on mobile. Diagnostics show small text and button sizes cause accidental exits. Optimizing for fat fingers should increase conversions.
Here, behavior analysis revealed the reason behind high bounce rates. This knowledge can be used to implement improvements.
Predictive Analytics: What Will Happen?
Predictive analytics forecast future outcomes using statistical models and machine learning algorithms.
Techniques include:
- Regression analysis to model trends
- Classification models to predict categories
- Recommendation engines to serve relevant content
For a digital analytics agency, predictive analytics empowers us to set realistic targets and personalize experiences by understanding potential future events.
Example of Predictive Analysis
Forecasting models indicate e-commerce conversions will increase by 20% next quarter based on rising traffic and decreasing bounce rates. Additional sales representatives may be required to handle the uptick.
This demonstrates how predictions enable provisions to be made through data-backed projections.
Prescriptive Analytics: What Should I Do?
Finally, prescriptive analytics recommend the best course of action given business objectives, past data, and predicted outcomes. The focus is optimal decision-making.
Examples include:
- Marketing mix modeling for ideal budget allocation
- Simulation testing for best page layouts
- Algorithmic optimization for maximizing success metrics
For a digital analytics agency, prescriptive analytics powers superior optimization recommendations tied directly to client goals. It enables data-driven decisions focused on ideal results.
Example of Prescriptive Recommendation
Decrease cost-per-click bids for keywords generating high impressions but sub 2% click-through rates and reallocated budget to more commercial terms with 10%+ CTRs to increase ROI by 15%.
Rather than just predict performance, this analysis prescribes the tactical steps to directly improve it.The 4 types of analytics work together to extract powerful insights from data. Descriptive metrics show what happened while diagnostic analysis determines why it occurred. Predictive models forecast future activity as prescriptive algorithms recommend how to enhance it. Utilizing all four enables a digital analytics agency to drive superior results.
