Salesforce Customer 360 and Data Cloud — A Historical Perspective
I’ve had an incredible 18-plus years in the Salesforce ecosystem. I have been the Customer, Consultant, Salesforce Product Manager, Product Leader, and most recently, an ISV Partner on my quest to empower organizations to make confident and timely decisions using high-quality data.
After having many, many conversations at Salesforce events, in Chatter, and on Slack, replying to people stating, “I don’t understand what Data Cloud is all about or what the big deal is,” I realized my own journey allowed me to reflect on Salesforce’s Customer 360 journey, with one of the most recent and impactful chapters being Data Cloud.
I will share with you my perspective on why I believe Salesforce Data Cloud is the best solution today for organizations to have a current, complete, consistent, contextual, and compliant understanding of their Customer, Partner, Supplier, and Employee interactions. With this data foundation, companies can take advantage of the latest AI, Automation, Analytics, and Activation capabilities to power their engagements at the moments that matter. In a world surrounded by IoT, this positions organizations to be the best Customer Company they can be.
No, I did not just bring these “buzzwords” together for SEO benefits. I have been on this journey and see its viability.
Intrigued? Please read on.
My Journey to Simplifying Customer 360
In 2005, I was part of Genentech’s sales force automation (SFA) selection team. We were intrigued by the SaaS model with the automatic version upgrades, having experienced the heavy lift of managing on-prem applications that distracted from delivering on business needs. One essential requirement: whichever application provider we chose needed to support the life sciences selling motion: engaging the person, i.e., the medical professional, vs. account contacts.
I still remember the data modeling discussions in our offices, where we shared the importance of understanding the multiple organizations a person may be actively engaged with. Ultimately, we became (one of) the first customers to broadly adopt Person Account.
By 2008, we had migrated over a dozen brand-specific apps to our single Salesforce instance. We also extended Salesforce SFA with custom case management capabilities, as our customers wanted to know about the status of their reimbursement support cases. We negotiated an “infrequent user” license model, which now feels like the basis of Platform or Experience Cloud licensing. The idea of a single source of truth to empower field reps in their customer engagements made sense to us. In 2009, Salesforce launched Service Cloud, where the CRM platform expansion confirmed our ideas had true merit.
We also had (believe it or not) an effective Customer Master Data Management solution for our Prescriber, Practice, Payer, and Plan data. Furthermore, we respected the contextual firewall requirements for what a salesperson could access compared to someone in development. We used “intentionally duplicate” account records to simplify the security model while using externally managed unique identifiers to maintain a 360 understanding when required.
When Roche acquired Genentech, I gained a deeper appreciation for well-defined data models and data processing solutions. We would migrate an entire business unit’s legacy data to our application portfolio within three months. At that point, I was responsible for the Data and Integration Centers of Excellence, Customer Data Management, and Spend Compliance solutions.
This efficiency was powered by a well-integrated and frankly complex mix of technologies. We were leveraging (this will be important later in this article) different technologies for Customer Master Data Management (MDM), Data Profiling, Address Cleansing, Account Enrichment, Integration (3 different tools for ETL, ESB, and EII Data Federation), Reporting, and of course our Operational Data Store (ODS), Enterprise Data Warehouse, and Data Marts databases. Furthermore, we needed to establish bi-directional integration among all of these components and our business applications. After all, the most valuable data within a database holds no business value if not applied in business applications to address specific business needs. We truly did a good job integrating and acting on data, especially for the times.
When I joined Salesforce, my goal was to help organizations achieve a better understanding of their customers without needing such levels of expertise. For the next decade and more, I would serve as a product, CSG, and data strategy leader, spearheading innovative initiatives to help customers realize more value from their data.
Salesforce’s acquisition of Jigsaw and the launch of Data.com empowered organizations to replace months of integration with minutes of configuration, incorporating reference data and “in-app matching and enrichment” within a business application for the first time. This enabled customers and consultants alike to use firmographic insights, quickly discover if they had the right (or wrong) accounts, the level of intentional or unintentional duplicates, and create a better 360 understanding within an individual CRM org.
In 2014, I was tasked to build and lead Salesforce’s Data Strategy Practice within the Customer Success Group. We operationalized these practices to help Salesforce customers determine their data health and found impactful patterns to create a 360 view understanding of their customers across different orgs and Salesforce clouds.
Salesforce’s Portfolio Growth Leading to Data Cloud
Salesforce’s B2C acquisitions broadened the data challenges we needed to tackle to include different data models, data scales, and complexities. The patterns observed to meet the needs of B2C retail customers prompted the inception of Customer 360.
It was at this time I wrote requirement 0 to productize the Customer 360 vision, describing the data and schema discrepancy challenges that needed to be addressed across data sources to have an effective understanding of customer interactions.
Through our experiences, we kept learning and innovating. We identified the right customer records and delivered unified profiles across sources with millions of records in real time. We identified best practices to accelerate time to business value. We even got a few (ok many) patents for these approaches. We also confirmed the business need is not to have a single, golden customer record, but a contextual and compliant view of the customer within a business function or line of business. e.g. what Customer Service agent needs to and is allowed to see is often different than a Sales rep can or wants to see.
Given the continous need to separate business applications from analytical environments, a typical leading enterprise architecture looked like the below picture in 2019.
One of the key challenges in every enterprise architecture has been how to know two different customer records were, in fact, about the same customer. This has been the domain of Master Data Management, where a typical project could take 9–18 months and cost $500K-$5M.
Customer 360 Data Manager GA’d at Dreamforce’19, enabling customers and consultants to significantly reduce the prior 9–18 month MDM efforts to create trusted and reliable customer profiles to just 4–8 weeks.
Yet, with the desire to give customers choices who may already have a CDP, data lake, or MDM, we were still talking about a complex technology portfolio with multiple integrations to manage. Slides presented in 2019 detailed how a customer can choose different Salesforce products based on their data management needs.
I credit Salesforce’s leadership for recognizing that while having choices is good, this was too complex to explain, sell, and implement. Thus, the portfolio continued to evolve, true to the vision of helping organizations achieve Customer 360 in the most impactful way possible.
Goal: help Sales, Service, Marketing, and Compliance leaders across industries realize the benefits of complete, current, contextual, and compliant understanding of their customer interactions, while helping IT leaders get out of the business of building and maintaining multiple single sources of truth.
Today, with Data Cloud
The Data Cloud announcement at DF22 was particularly exciting for me. It brought together the compute power and scale of Customer 360 Audiences, initially designed for marketers, with data unification capabilities and enterprise focus of C360 Data Manager. This integration aims to consolidate various “single source of truth” platforms into one ultimate single source of truth for all enterprise needs.
Setting aside the marketing story and sales pitch, I truly believe Data Cloud is the best solution alternative for CIOs, CTOs, and business leaders today.
Under a single umbrella, customers can:
- Bring data from any data source into a common environment
- Perform necessary data management and data enrichment tasks with AppExchange ISV solutions extending the power of the product, while simplifying integration and staying within the trust model
- Rapidly perform necessary data modeling, data transformation, and identity resolution tasks without the need to implement and integrate multiple technologies
- Develop solutions tailored to specific business use cases across the enterprise, with data quality checks and implementations ensuring data reliability and effective credit use
- Respect data security firewalls, delivering contextual and compliant insights
- Power not only Activation, but also AI, Automation, and Analytics solutions across every customer engagement touchpoint, further empowering Sales & Service users through a unified architecture
backed by a trusted, scalable, reliable data platform, so organizations can achieve faster time to business value and realize operational cost savings.
Skeptical? Post a comment or send a message, and I’ll do my best to share my experience-driven views or learn about other challenges to see if we can tackle them better, together.
