.svg){kind=icon}
How to connect Google Cloud Speech-To-Text and Google Analytics
Create a New Scenario to Connect Google Cloud Speech-To-Text and Google Analytics
In the workspace, click the “Create New Scenario” button.
Add the First Step
Add the first node – a trigger that will initiate the scenario when it receives the required event. Triggers can be scheduled, called by a Google Cloud Speech-To-Text, triggered by another scenario, or executed manually (for testing purposes). In most cases, Google Cloud Speech-To-Text or Google Analytics will be your first step. To do this, click "Choose an app," find Google Cloud Speech-To-Text or Google Analytics, and select the appropriate trigger to start the scenario.
Add the Google Cloud Speech-To-Text Node
Select the Google Cloud Speech-To-Text node from the app selection panel on the right.
+
1
Google Cloud Speech-To-Text
Configure the Google Cloud Speech-To-Text
Click on the Google Cloud Speech-To-Text node to configure it. You can modify the Google Cloud Speech-To-Text URL and choose between DEV and PROD versions. You can also copy it for use in further automations.
Add the Google Analytics Node
Next, click the plus (+) icon on the Google Cloud Speech-To-Text node, select Google Analytics from the list of available apps, and choose the action you need from the list of nodes within Google Analytics.
1
Google Cloud Speech-To-Text
⚙
+
2
Google Analytics
Authenticate Google Analytics
Now, click the Google Analytics node and select the connection option. This can be an OAuth2 connection or an API key, which you can obtain in your Google Analytics settings. Authentication allows you to use Google Analytics through Latenode.
Configure the Google Cloud Speech-To-Text and Google Analytics Nodes
Next, configure the nodes by filling in the required parameters according to your logic. Fields marked with a red asterisk (*) are mandatory.
Set Up the Google Cloud Speech-To-Text and Google Analytics Integration
Use various Latenode nodes to transform data and enhance your integration:
- Branching: Create multiple branches within the scenario to handle complex logic.
- Merging: Combine different node branches into one, passing data through it.
- Plug n Play Nodes: Use nodes that don’t require account credentials.
- Ask AI: Use the GPT-powered option to add AI capabilities to any node.
- Wait: Set waiting times, either for intervals or until specific dates.
- Sub-scenarios (Nodules): Create sub-scenarios that are encapsulated in a single node.
- Iteration: Process arrays of data when needed.
- Code: Write custom code or ask our AI assistant to do it for you.
5
JavaScript
⚙
6
AI Anthropic Claude 3
⚙
+
7
Google Analytics
1
Trigger on Webhook
⚙
2
Google Cloud Speech-To-Text
⚙
⚙
3
Iterator
⚙
+
4
Webhook response
Save and Activate the Scenario
After configuring Google Cloud Speech-To-Text, Google Analytics, and any additional nodes, don’t forget to save the scenario and click "Deploy." Activating the scenario ensures it will run automatically whenever the trigger node receives input or a condition is met. By default, all newly created scenarios are deactivated.
Test the Scenario
Run the scenario by clicking “Run once” and triggering an event to check if the Google Cloud Speech-To-Text and Google Analytics integration works as expected. Depending on your setup, data should flow between Google Cloud Speech-To-Text and Google Analytics (or vice versa). Easily troubleshoot the scenario by reviewing the execution history to identify and fix any issues.
Most powerful ways to connect Google Cloud Speech-To-Text and Google Analytics
Google Cloud Speech-To-Text + Google Analytics + Google Sheets: Transcribe audio from customer service calls using Google Cloud Speech-To-Text, then extract keywords. Log these keywords and their frequency in a Google Sheet, and create key events in Google Analytics to track popular spoken terms.
Google Cloud Speech-To-Text + Google Analytics + Slack: Transcribe audio from customer service calls using Google Cloud Speech-To-Text, then extract keywords and their frequency. Run a report in Google Analytics to identify significant spikes in specific keywords. Send a Slack message to the marketing team notifying them of the trend.
Google Cloud Speech-To-Text and Google Analytics integration alternatives
About Google Cloud Speech-To-Text
Automate audio transcription using Google Cloud Speech-To-Text within Latenode. Convert audio files to text and use the results to populate databases, trigger alerts, or analyze customer feedback. Latenode provides visual tools to manage the flow, plus code options for custom parsing or filtering. Scale voice workflows without complex coding.
Similar apps
Related categories
About Google Analytics
Automate marketing insights using Google Analytics within Latenode. Track user behavior and trigger actions based on key metrics. Send data to CRMs, databases, or ad platforms automatically. Latenode streamlines analysis workflows without code, offering flexible logic and integrations, unlike manual reporting or limited point solutions.
Similar apps
Related categories
See how Latenode works
.svg)
.png)
FAQ Google Cloud Speech-To-Text and Google Analytics
How can I connect my Google Cloud Speech-To-Text account to Google Analytics using Latenode?
To connect your Google Cloud Speech-To-Text account to Google Analytics on Latenode, follow these steps:
- Sign in to your Latenode account.
- Navigate to the integrations section.
- Select Google Cloud Speech-To-Text and click on "Connect".
- Authenticate your Google Cloud Speech-To-Text and Google Analytics accounts by providing the necessary permissions.
- Once connected, you can create workflows using both apps.
Can I track spoken keyword frequency in user calls?
Yes, you can! Latenode allows you to analyze call data, extract spoken keywords, and automatically update Google Analytics for detailed trend analysis, enhanced by AI-powered insights.
What types of tasks can I perform by integrating Google Cloud Speech-To-Text with Google Analytics?
Integrating Google Cloud Speech-To-Text with Google Analytics allows you to perform various tasks, including:
- Analyze sentiment of customer service calls in real-time.
- Automatically track the usage of specific product features.
- Monitor brand mentions across voice-based interactions.
- Identify common issues reported during customer calls.
- Measure the effectiveness of voice-based marketing campaigns.
Can I process large audio files using Speech-To-Text on Latenode?
Yes! Latenode handles large files efficiently with scalable infrastructure, letting you process extensive audio data without performance bottlenecks.
Are there any limitations to the Google Cloud Speech-To-Text and Google Analytics integration on Latenode?
While the integration is powerful, there are certain limitations to be aware of:
- Accuracy depends on the audio quality of the input files.
- Real-time transcription may introduce latency depending on file size.
- Google Cloud Speech-To-Text usage is subject to Google's pricing.
