Has Salesforce Admitted Defeat to Snowflake in the Battle for Customer 360?

Salesforce, the CRM platform, recently unveiled Genie. It was a groundbreaking addition to the Salesforce products lineup. Genie is described as an advanced Customer Data Platform, a hyperscale real-time data platform that powers the entire Salesforce Customer 360 platform. This announcement is arguably among the most significant developments from this tech giant, especially for those keen on optimizing the customer relationship management processes.

Diving deeper into Genie's functionality, I found something interesting. The key to Genie’s ability to help companies “turn data into customer magic” is a bi-directional data sync between Salesforce and Snowflake. In a way, this is a concession to the overwhelming tide of the warehouse-first paradigm. Salesforce is no longer trying to own all of the data required to build a comprehensive customer source of truth, the coveted Customer 360.

Before we dive into the latest products, let’s briefly understand how Salesforce products have evolved over the years.

The history of Salesforce and its products

From a fledgling idea in a San Francisco apartment to becoming the world's premier customer relationship management (CRM platform), Salesforce's growth is nothing short of a tech revolution. Let's embark on a journey tracing the origins and evolution of Salesforce's product suite.

A game-changing start: Sales Cloud

In the waning days of the 20th century, when the digital realm was just taking shape, a transformative change was on the horizon in the CRM world. Salesforce introduced its Sales Cloud. No longer did sales reps need cumbersome on-premise solutions to manage their leads and customer data. The cloud was the future, and Sales Cloud was its herald. With real-time access to data and streamlined workflows, Salesforce redefined the sales process, offering a more efficient way for sales teams to operate.

Extending the reach: Service and Marketing Clouds

Salesforce's ambitions soon grew beyond sales. The Service Cloud came as a boon to customer service professionals, empowering them with tools to provide immediate and personal customer interactions, setting a gold standard in enhancing customer satisfaction.

The Marketing Cloud was the answer to the evolving demands of modern marketing. Salesforce recognized that today's marketing dynamics needed sophisticated tools. With the Marketing Cloud, businesses had a suite of marketing automation tools at their fingertips, ensuring that their marketing campaigns were precise. Effective audience segmentation, tailored messaging, and a host of other features allowed marketers to create and nurture more meaningful customer relationships.

The latest: Genie

By consolidating data and dismantling silos, Genie indicates a trend into the need of businesses for a singular, unified view of the customer, enabling more tailored and impactful engagements. This one is different from the past Salesforce products, not just in terms of functionality but the approach as well.

Let’s dive into what this new approach hints towards.

If you can’t beat the warehouse, strategically partner with the warehouse

Genie is enabled by a number of what Salesforce calls strategic partnership innovations. But it’s the open data sharing between Salesforce and Snowflake that really powers the product. Genie is all about creating and using a customer 360, and Salesforce is relying on Snowflake for this data. Like a Genie, the details of this open data sharing aren’t very clear, but one can guess that this will support pulling data from Snowflake into Salesforce as well as syncing Salesforce’s copy of customer data (or parts of it) into Snowflake.

Part 1: Syncing data from Snowflake to Salesforce

In the realm of CRM software optimization and data management, syncing data from Snowflake to Salesforce stands out as a crucial functionality. Primarily, the endeavor to integrate data into Salesforce CRM aligns perfectly with the enterprise needs. Considering the vast amounts of customer data stored by businesses in their respective warehouses, it's understandable why SaaS vendors, especially those focusing on apps for small businesses, aim to replicate this data for streamlined business processes.

Salesforce recognizes the importance of warehouse integration. It is crucial for automation, real-time data syncing, and enhancing the overall customer relationship management experience. Alongside Salesforce, other tools like Segment's SQL traits, Amplitude, and Braze are also capitalizing on warehouse integrations. This also has led to the creation of a category called reverseETL with vendors like Census, Hightouch, and of course RudderStack, who enable this data movement into SaaS tools that don’t natively support it.

Part 2: Syncing data from Salesforce to Snowflake

The other part of the sync to enable data movement from Salesforce into Snowflake is a lot more interesting. Traditionally, SaaS vendors want to hold their customer’s data to keep the customers locked-in to their platforms. They make it extremely hard to get that data out. Often SaaS tools only expose data through difficult to use and severely rate-limited APIs.

ETL tools like FiveTran and Matillion built big businesses by automating this complexity and making it easier to extract data from SaaS tools, but they only go so far. There are a number of limitations to these cloud ETL tools:

• Getting anything close to a real-time copy of the data is impossible. You only get point in time copies without the change-log, and hence all updates in between are not captured.
• There are no database style consistency guarantees (e.g. foreign key constraints across tables) on the data.
• The data models of the SaaS tool and what is available over API are often different.

That list is far from exhaustive, and if the new Salesforce to Snowflake sync works as promised, it will eliminate a number of these challenges. But a major question remains: Why is Salesforce okay with giving away the keys to its kingdom by making it easy to take the data out? I think the answer is simple: there are fundamental and far reaching problems with storing your customer master in Salesforce or any other walled SaaS garden for that matter. 

The evolving landscape of Salesforce products hints at a paradigm shift. Salesforce's advanced offerings with Snowflake integration, is just one of the proof.

The traditional SaaS model is incompatible with today’s data use cases

While the traditional SaaS model of delivering software has tons of benefits, for example leaner IT teams, cost savings, and faster time to value, these tools also severely limit flexibility of usage. You’re fundamentally limited to the use cases that the SaaS vendor offers. Nowhere does this show up more prominently than customer information locked in Salesforce. Let’s consider a few questions to parse this out:

• If the selected database by Salesforce platform (Oracle) does not adequately meet your needs for storing large amounts of data (such as first-party events or other application data) in terms of data volume and performance, what options are available?
• What if you want to build BI and analytics dashboards on top of your customer data in Salesforce?
• What if your data science team is looking to build advanced ML use cases on top of that data?
• What if you want to send customer data from your production database into Salesforce?

Over the years, Salesforce has tried to address each one of these by buying (e.g. Tableau) or building (e.g Einstein), but these vertically integrated solutions have their limitations. At the end of the day, you’re still caged by what Salesforce provides. This is where the data warehouse comes in as a magic bullet to address all these challenges.

The data warehouse takes over

While data warehouses have been around for almost three decades, they didn’t become prominent until Amazon launched a data-warehouse in the cloud (Redshift) in 2012, and then Snowflake came along. The cloud data warehouse immediately made storing and processing data at scale much easier and gained rapid adoption. Now companies could affordably and efficiently store all of their customer data in a central location, and creating customer records in these cloud data warehouses was the avenue to address all the challenges mentioned above. Want advanced analytics? Want to build ML use cases? Want to store customer data that you cannot store in Salesforce (e.g. events)? Just copy everything into a CDW and build on-top.

Yes, with a CDW you still have to figure out the painful process of getting data out of Salesforce, but that’s a small cost (not that FiveTran is exactly cheap) to pay for the benefits delivered by aggregating customer data in a central storage layer. With the widespread adoption of the cloud data warehouse, companies, knowingly or unknowingly, made the warehouse the single source of truth for customer data. These warehouses now had the data to create a more complete customer profile than Salesforce or any other SaaS vendor ever could. The paradigm had shifted. Constructing robust customer profiles in these cloud data repositories is the evident solution to a multitude of challenges of the CRM era. Yearning for advanced analytics? Keen on forging machine learning applications? Need to archive customer data points that don't seamlessly integrate with Salesforce, like event-driven data? The strategy usually is to migrate everything into a Cloud Data Warehouse (CDW) and build from there.

Recognizing the warehouse-first paradigm

The Genie announcement, with its open data sharing between Salesforce and Snowflake, is evidence that Salesforce has recognized this paradigm shift—which is significant. The company has observed this irreversible change over the last few years, and instead of building higher walls, they’ve finally decided to embrace it. Giving up control and actively working to make it easy to get data out of their platform is the first step!

Salesforce’s place in the new world

So, will we still need Salesforce in a warehouse-first world? Absolutely. But its place is as an engagement layer that doesn’t keep the full customer profile, but only the data needed to enable that engagement. Salesforce users, whether they be sales, marketing, or support, still want to work on top of Salesforce. They prefer its user experience and the ecosystem of tools that comes with it. But Salesforce won’t have the golden customer master, and it won’t need it, because that will be in Snowflake or its equivalent. Salesforce will only have the relevant data needed to enable its users. If they really do deliver a seamless way to sync this data back and forth, it will be something special.

So, will there be a Salesforce in 20 years? In all likelihood, yes. But if a startup can replicate a Salesforce like experience on Snowflake, and if Snowflake can deliver on its promise of enabling transactional use cases, things will get interesting for sure!

Taming architectural complexity

Even in the midst of this massive shift towards the warehouse, creating and actually using a customer 360 is no small task, but the reward is undeniable. It’s why so many companies are emerging with “solutions” aimed at delivering on this promise. It’s encouraging to see movement away from black box solutions towards more open systems centered on the data warehouse. But this comes with its own challenges.

With the customer source of truth in a warehouse, data architectures are becoming increasingly complex. This is partly because data-warehouses are still not suited for real-time use cases and aren’t purpose-built for customer data. As a result, you may end up building a number of pipelines:

• A real-time integration via one tool to get data into Salesforce
• A separate ETL pipeline from another vendor to get data from Salesforce to Snowflake
• Another homegrown script or rETL tool to get data back into salesforce

Imagine the exponential growth of complexity in your infrastructure due to the presence of customer data not only in Salesforce but also in multiple other systems. Additionally, achieving a comprehensive customer 360 degree view involves various crucial steps such as identity stitching and the creation of user profiles. However, this is just the beginning as the activation of this data, along with the implementation of advanced analytics and artificial intelligence use cases, presents significant challenges that cannot be overlooked.

Taming this complexity is exactly the reason we started RudderStack. Our product enables brands to collect customer data from all the sources including first-party and third-party ones; model it in a data-warehouse to create that golden customer 360; and activate it into downstream sales, marketing, support, and analytics tools. In order to understand how this approach has helped businesses in making more informed decisions, building personalized customer experiences, and increasing customer engagement, check out real-life case studies of RudderStack customers. This digital transformation is usually led by data engineers or marketing teams.