We’ve already discussed the central role that AI-ready data plays in effectively building and training an AI model. But, what happens when the data you need to train your model is scattered and separated not just across clouds, but across entirely different platforms and ecosystems? On top of this, building and training an AI model that meets a particular business need is often beyond the scope of a business owner or HOD.
It’s clear to see that data itself is not the only challenge in AI training and deployment, but also data accessibility as well as the technical skills required. What’s the solution for a growth-minded organization eager to leverage the powerful computing capabilities of AI?
This challenge is exactly what Salesforce and Google set out to solve! Through their extensive partnership, Salesforce and Google are committed to empowering businesses by putting the power of AI in their hands. To do this, they’ve created an innovative integration between Salesforce Data Cloud and Google’s BigQuery data warehouse and Vertex AI machine learning platform.
Let’s take a closer look at the capabilities of both of these integrations and what they can offer businesses in terms of real-life benefits.
Data Cloud and Google Vertex AI: AI capabilities at your fingertips
Data Cloud’s integration with Vertex AI means you can build, train and customise your own AI models for business use, with help from valuable CRM data! Vertex allows users to build their own AI models from scratch, which they can then use across the Salesforce customer 360 ecosystem, powering more personalised, effective customer experiences.
The AI models can be customised to meet specific business needs such as predicting customer behaviour, retention and churn likelihood, and generating optimal strategies accordingly. The great thing about Vertex is it gives you full control over the end-to-end process of creating and deploying an AI model, from training and testing to monitoring and deploying and further analysis and testing.
Zero-copy data access means that you can optimise your AI model training using your customer data from Data Cloud. Combining Vertex’s advanced yet accessible machine learning capabilities with robust CRM data allows businesses to supercharge their model training, improving predictive accuracy and performance.
Data Cloud and BigQuery: seamless customer personalisation at scale
Personalisation is the name of the game for the partnership between Data Cloud and Google’s BigQuery. Initially, this might sound unnecessary, given that CRM platforms already power terrific personalised customer interactions. But, Data Cloud and BigQuery give businesses the power to take customer personalisation to the next level.
Data Cloud and BigQuery’s integration provides uninterrupted data access platforms, enabling businesses to create more comprehensive, up-to-date customer profiles. A secure link between Data Cloud and external data aggregated via BigQuery allows businesses to access their data across platforms and clouds.
The data will show up in your Salesforce platform, completely zero-ETL (Extract, Transform, Load). This means you don’t have to amend or change your data architecture beforehand, saving you time and reducing operational complexity, while maintaining data governance and integrity.
Through this connection, you can build more detailed, revealing and informative customer profiles and create even more personalised, tailored customer communications and experiences.
Through the combined forces of Salesforce and Google, it’s now easier than ever to leverage the power of AI and the cloud to build stronger and more sincere customer relationships by optimising your business data usage.
At a glance: The business benefits of Data Cloud and BigQuery + Vertex AI
We’ve covered a lot in the previous two sections, so let’s do a quick review of the business benefits that the Data Cloud/BigQuery and Data Cloud/Vertex AI integrations offer:
Data Cloud and BigQuery
- Share data immediately between Data Cloud and BigQuery with zero-copy or Zero ETL.
- Save time and reduce operating costs by eliminating the need to adapt or set up data architecture for cross-platform sharing.
- Connect your customer data seamlessly to derive new insights that drive better decision-making across the customer lifecycle
- Create more complete, accurate customer profiles and share these profiles from Data Cloud across any Google Cloud platform.
- Use these enhanced customer profiles to build better customer journeys, create more tailored communications and provide more personalised customer experiences.
Data Cloud and Vertex AI
- Leverage out-of-the-box machine learning capabilities to build and train customised AI models.
- Eliminate unnecessary development costs by building and training your own AI model.
- Enjoy full control over the development and customisation of your models based on your unique business requirements.
- Use relevant CRM data to help train your AI model for more accurate, efficient predictions and recommendations.
- Improve ROI across customer engagements and campaigns using the insights, prediction and recommendations from your Data Cloud/Vertex AI AI-powered AI models.
Conclusion
While the partnership between Salesforce and Google has put even more power in the hands of businesses, there are still a few developmental roadblocks to overcome. Utilising the full force of Data Cloud and Customer 360 requires strong technical prowess and know-how of the Salesforce ecosystem.
At CloudSmiths, we’re Salesforce veterans and are well-versed in mapping business objectives and requirements to Salesforce features and capabilities.
Getting the most out of your Data Cloud/BigQuery and/or Data Cloud/Vertex AI projects requires you to have a strong Salesforce foundation, tailored to your business needs. We can guide you in setting up and optimising your Data Cloud usage for maximum ROI and efficiency.
If you’re ready to learn more about our extensive experience with Data Cloud and Salesforce Customer 360, book a consultation with us.
