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Google Analytics AI

AI based on Google Analytics Data

Introduction

What is Google Analytics?

Google Analytics is a web-based tool that helps businesses track and analyze their website traffic. It provides detailed insights into user behavior, such as how visitors find the site, which pages they visit, and how long they stay. This information aids in optimizing marketing strategies and improving user experience.

What is CogniVis AI?

CogniVis AI is a platform that enables you to pull data from different sources and combine them with each other to create practically useful AI tools. Sources may include your internal company knowledgebase and a variety of most popular business apps like GitHub, Jira, Slack, and more.

This enables you to easily create AI chatbot assistants (internal), custom generators and even embeddable AI chat widgets trained on your data.

How CogniVis AI works with Google Analytics?

The Google Analytics Connector retrieves all website traffic, behavior, and conversion data from the specified Google Analytics properties and views.

What exact sources are pulled:

  • Audience Data
  • Number of users
  • New vs. returning visitors
  • Acquisition Data
  • Traffic sources (organic search, direct, social, referral)
  • Campaigns and mediums
  • Behavior Data
  • Pageviews per page
  • Average session duration
  • Bounce rate
  • Exit pages

Configuration

Create new Project

Set up a new project in Google Cloud.

Activate the Google Analytics Console API

Expand the sidenav, then go to APIs & Services and choose Enabled APIs & Services.

At the top, select + ENABLE APIS AND SERVICES.

Find and select the Google Analytics Admin API and Google Analytics Data API.

Press the Enable button.

Configure the OAuth Consent Screen

Go to the OAuth consent screen.

Select External for User Type if you do not have a Google Organization.

Enter a name, provide the email addresses for contact, and press SAVE AND CONTINUE button.

Click ADD OR REMOVE SCOPES.

Include the scope .../auth/analytics.readonly for the Google Analytics Admin API. Click UPDATE and then SAVE AND CONTINUE.

Provide at least one test user email. Only the email addresses added in this section will be able to initiate the OAuth flow for indexing new emails.

Press on SAVE AND CONTINUE, check the changes, and then select BACK TO DASHBOARD.

Create Credentials

Navigate to the Credentials tab, press + CREATE CREDENTIALS and choose OAuth client ID.

Select Web application and assign it a name such as CogniVis Connector.

In Authorized JavaScript origins, enter https://INSTANCE.platform.cognivis.ai

In Authorized redirect URIs, enter https://INSTANCE.platform.cognivis.ai/admin/plugins/google-analytics/auth/callback

In place of the INSTANCE, put the name of your instance.

Clicking Create will display the option to download the credentials as a JSON file. Download it for use in the next step.

Add the connector to CogniVis

Navigate to CogniVis Connectors

In your platform, go to the Admin Panel, which you can find in the top right corner of the screen.

Go to the Plugins section in the menu on the left side of the screen.

Then, search for and Edit the Google Analytics Plugin.

Provide Credentials

Attach the previously downloaded JSON file.

Authenticate with Google Analytics

Press Authenticate with Google Analytics button. Finishing the OAuth flow will enable CogniVis to index emails the user has access to read. Remember that only email addresses added in Test users will be able to initiate the OAuth flow to index new emails.

Warning: Limitations for very Big Datasets
By default, the GA4 plugin is limited to the latest 500 detailed records of every dimension. All record over 500 will get automatically aggregated, which may lead to slight differences in reported data, and possible inaccuracy for some specific use cases. If you would like to make sure this limit is higher on your instance, please contact our team directly.

Free trial

If you are interested in creating your own automations and workflows with artificial intelligence based on your data, you can request a free trial of our solution. Please book a demo with us to get started.

book a demo

On-premise

Enterprise organizations can choose to deploy this connector on-premise. On-premise deployment provides additional security and privacy, it means that the connector will be hosted on your own servers which you can control and manage.

This option is suitable for organizations that have strict data privacy and security requirements, want to integrate with their existing infrastructure, or need to comply with specific local regulations.

Contact our team & learn about options of deploying this connector on premise.

book a demo learn more about on-premise ai

Use cases

Check out potential benefits and use cases for this connector.

Enhanced Audience Targeting

By integrating Google Analytics audience data into an AI model, businesses can create more targeted marketing campaigns. AI can analyze details like new vs. returning visitors to tailor ads, predict user preferences, and recommend personalized content, improving engagement and conversion rates.

Optimized Content Strategy

AI can utilize behavior data such as pageviews and exit pages to understand which content resonates most with users. This can guide content creators in crafting articles, videos, or other media that align with audience interests, thereby keeping users engaged and reducing bounce rates.

Improved Customer Retention

Through acquisition data analysis, AI can identify which channels bring in high-quality traffic. Understanding the effectiveness of different traffic sources allows businesses to focus on high-performing channels, improving customer retention and increasing the lifetime value of each user.

Predictive Traffic Insights

By analyzing traffic sources and campaign data, AI can forecast future traffic patterns. This allows businesses to anticipate peak traffic times and prepare resources accordingly, ensuring optimal site performance and a seamless user experience even during high-traffic periods.

Conversion Rate Optimization

AI can scrutinize user behavior and session duration to identify factors influencing user decisions. By understanding how visitors navigate before converting or dropping off, businesses can tweak their websites to enhance user experience and potentially increase conversion rates.

Advanced Segmentation

AI models can leverage Google Analytics data to create advanced user segments based on detailed behavior patterns. This segmentation can be used to deliver tailored experiences to different user groups, enhancing personalization and customer satisfaction.

Automated Reporting and Insights

AI can automate the analysis of complex datasets from Google Analytics, providing clear, actionable insights without manual intervention. This saves time and resources, allowing teams to focus on strategic decision-making and implementation.

Enhanced UX Design

By analyzing bounce rates and exit pages, AI can provide insights into potential UX design flaws. Businesses can use this data to refine website layouts, smooth navigation issues, and enhance overall user satisfaction, leading to increased retention.

Dynamic Campaign Adjustments

AI can monitor real-time campaign performance, using insights from Google Analytics to automatically adjust advertising strategies. This ensures that marketing efforts are always optimized for the best ROI, adapting to changing user behaviors and market conditions.

Data-Driven Decision Making

Integrating Google Analytics data with AI enables businesses to make decisions based on comprehensive, data-backed insights. This reduces guesswork, increases the effectiveness of strategies, and ultimately leads to better business outcomes.

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  • Introduction
  • Configuration
    • Authorization
    • Indexing
  • Free trial
  • On premise
  • Use cases
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