Key Takeaways:
- Agentforce, Salesforce's game-changing autonomous AI, needs high-quality historical data to reach its full potential.
- Clean, relevant data is more critical than ever in the AI age to ensure AI models learn from dependable information.
- Own Discover emerges as a powerful solution, making historical Salesforce data easily accessible and actionable for AI-driven insights.
Salesforce admins, brace yourselves: Agentforce is here, and it's hungry for data.
Dreamforce 2024 put the spotlight on Agentforce, Salesforce's latest AI innovation that promises to revolutionize how we interact with and leverage data. But as AI agents become more sophisticated, a crucial question emerges: How can teams effectively manage and extract value from the vast troves of historical data these agents need to function optimally?
In a recent webinar hosted by Own, industry veterans tackled this challenge head-on. Moderator Selma Chang, Senior Product Marketing Manager at Own, was joined by Adrian Kunzle, CTO of Own with over two decades of Salesforce and financial data expertise, and Gina Marques, Director of Business Applications at Own and Salesforce MVP.
Adrian says, "Agentforce is interesting because I think for the first time, they really tried to take what is actually proving to be a fairly complex problem and distill it down into something that, if you're on the Salesforce platform, actually becomes much easier to try and play around with."
Read on to explore how Agentforce is reshaping Salesforce data management and why solutions like Own Discover are becoming critical for organizations looking to fully harness AI.
Agentforce: Salesforce's AI Revolution
Agentforce represents a significant leap forward for Salesforce. Unlike previous iterations of AI tools on the platform, Agentforce isn't just for tech giants or companies with deep pockets. It's designed to democratize AI usage for Salesforce users of all sizes.
Adrian explains: "The barrier to getting going just got dramatically reduced with the work that they've done around Agentforce." This accessibility is crucial for organizations looking to leverage AI without extensive technical resources.Key features of Agentforce include:
- Natural language processing for more human-like interactions
- Data-driven decision-making and action-taking capabilities
- Built-in "guardrails" to ensure responsible AI use
- Seamless integration with Salesforce's existing ecosystem
"What was really powerful about what I saw with Agentforce was the Atlas AI engine, which is obviously leveraging a lot of the data out of Data Cloud, out of other endpoints, can now handle a lot of that ambiguity in the conversation," says Adrian.
Gina also shares her primary excitement about Agentforce: "I think it's the AI capabilities, right? So these agents can give insights and recommendations and kind of augment some of the human things that are happening today."
She also notes that implementing these AI features is becoming more manageable for admin and developer teams: "It's not as scary to me as the admin developer team to be able to deliver this quickly."
Data Cloud: The foundation for AI success
Underpinning Agentforce is Salesforce's Data Cloud, which has evolved significantly from its origins as a basic data lake. Now a centralized customer data hub, Data Cloud connects various data sources to build comprehensive customer profiles. This rich, interconnected data forms the foundation that enables Agentforce to function effectively.
"Data Cloud has obviously been on its own journey with Salesforce for the last few years," Adrian notes. "It kind of started out life looking a bit like a data lake. And then, I think what they were really trying to get after has now, I think, finally come to fruition."
The new integration allows companies to leverage their entire data history, not just recent information. This powerful combination of Agentforce and Data Cloud promises to revolutionize how businesses interact with their data and customers, opening up new possibilities for AI-driven insights and actions. As Gina points out, it's likely to "flip the switch on how admins work," enabling them to proactively bring new capabilities and insights to their organizations.
The power of looking back: Why historical data matters
As Agentforce and Data Cloud push Salesforce capabilities forward, there's a growing emphasis on the value of looking backward. Historical data, often overlooked or underutilized, is becoming a crucial asset in the AI-driven Salesforce ecosystem.
Adrian emphasizes this point: "One of the areas people are going to have to spend some time thinking about is how do we get to a point where that data is of high quality. It's something that we trust to feed into these engines."
What do we mean by high-quality data? It really comes down to the “three R’s”- resilient, relevant, and ready. Resilient data is data that has been protected and primed for future use. It’s secure, reliable, and capable of withstanding disruptions. Relevant data is tailored to your needs—data that brings historical context to life and enables predictive insights. Ready data is instantly accessible, prepared to be activated and drive decisions without delay.
Unlocking insights from the past
Historical data checks the “relevant” box by providing valuable context and trends that current data alone cannot reveal. This depth of information enables a deeper understanding of customer behavior and business patterns over time. However, accessing and utilizing historical data comes with its own set of challenges:
- Time-consuming and complex extraction: Traditional methods of accessing historical data often involve lengthy, complicated processes.
- Data silos: Historical data is frequently trapped in backups or legacy systems, making it difficult to integrate with real-time systems.
- Data quality concerns: A lot of historical data is not high quality and does not meet the criteria mentioned above." As Adrian points out, "It becomes much, much harder to understand whether the engine is providing you with a bad recommendation or a good recommendation because the lineage of the data that it's using is just that much more complex and hard to trace."
- Volume and timelines: Another challenge is ensuring that data is flowing through in a timely manner, as the volume has massively increased.
Gina adds a practical perspective on these challenges: "Things like data breaches and data security obviously increase. Where's this data used? Where is it going? It's something that we're constantly thinking about."
To address these challenges, organizations need to implement comprehensive data management strategies. That includes storage solutions, retention policies, and thorough archiving. "Thank goodness we have implemented Continuous Data Protection for our org as well,” says Gina.
By effectively leveraging historical data, businesses can enhance the performance of AI tools like Agentforce, leading to more accurate insights, better decision-making, and improved customer experiences.
Own Discover: Unlocking the potential of historical data
As organizations grapple with the challenges of managing and leveraging their historical data for AI-powered tools like Agentforce, solutions like Own Discover are becoming increasingly critical. Discover is a data service that captures automated backup snapshots and pipes this data into your existing data visualization tools or AI models.
Adrian explains the genesis of Discover, drawing a parallel between its purpose and that of Agentforce: both aim to simplify complex processes that were previously difficult for users to manage on their own.
Own Discover is purpose-built to simplify access and analysis of historical data stored in backups. Adrian highlights its key features and benefits:
- Easy data access: Users can quickly select the Salesforce objects they need from their backups, specifying the desired time range. Within hours, depending on the dataset size, they have a fully queryable dataset ready for analysis with tools like Tableau, Looker, or Power BI.
- Rapid iteration and experimentation: Discover significantly reduces the time and effort required to explore different aspects of historical data, making it easier to uncover valuable insights. If your business teams decide they need to pull in new Salesforce field that was not in the existing scope, there’s no need to connect new data pipelines and wait for new data to collect. Users can go back in time to collect all of that data for any new field requirements.
- Seamless Data Cloud integration: Historical data can be exposed to Data Cloud and linked with existing Salesforce customer profiles. This integrated data then feeds into Agentforce's Atlas engine, enhancing AI-driven customer interactions.
- See how your data changes over time: Discover enables trend analysis on historical data that might not be available in current Salesforce records, such as tracking changes in assets under management over time or forecasted pipeline changes throughout a quarter
The value proposition of Discover lies in its ease of use and the speed at which it enables data exploration and insight generation. Adrian emphasizes the importance of this agility: "Being able to play is incredibly important. But right now, if you're trying to play with any historical data, you are fundamentally bound by the time it takes to collect that data."
By providing quick and easy access to historical data, Discover enables organizations to fully harness the potential of AI-driven tools like Agentforce. It bridges the gap between vast stores of historical data and the need for comprehensive, high-quality data to feed AI systems, making complex data processes accessible to a wider range of users within an organization.
The AI-driven future of Salesforce
Agentforce and Data Cloud are ushering in a new era of Salesforce innovation, but their true power lies in how effectively we harness our historical data. As Adrian emphasizes, "The time is now to explore and experiment," and Gina reminds us, "Don't be afraid to try something." With data quality as the cornerstone of success, solutions like Own Discover are becoming crucial for unlocking the full potential of your Salesforce data history.
This article is based on a webinar moderated by Own Senior Product Marketing Manager Selma Chang and featuring Own CTO Adrian Kunzle and Own Director of Business Applications Gina Marques. Download the datasheet to learn more about how Own empowers you to protect and activate the value of your data.
