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Data Reliability Insights from TDX24

Reading time: 6 min   |  By Hayley Coxon   |  Published in Articles,

The energy and excitement at TrailblazerDX 2024 about the potential of AI on the Salesforce platform was overwhelming. While AI and Data Cloud were the obvious focus, there was also an underlying theme of data reliability throughout the conference.

It’s an interesting chicken-and-egg scenario. Salesforce’s ability to sell these products is somewhat dependent on the customer’s data. But historically Salesforce (and SIs) put the full burden of data reliability on the customer. I believe we’re at a turning point, and we must acknowledge a shared responsibility for data quality.

Here are five observations on where we still have a ways to go.

Customers Don’t Understand Business Value of Data Cloud 

When Salesforce announced Data Cloud, they were careful not to call it a data lake or Customer Data Platform (CDP). Yes, Data Cloud has a lineage as a CDP (Customer 360 Audiences) and is built to process massive amounts of data. However, it also has robust data unification capabilities from Customer 360 Data Manager and the ability to put all this unified data to use beyond marketing activations.

Yet, by carefully separating Data Cloud as a hyperscale data platform Salesforce has over-indexed on technology versus business value. Our team had many conversations with consultants struggling to pitch Data Cloud to customers. Many didn’t understand how to overcome IT’s objection of “but we already have Snowflake.” Even if the data in these other technologies failed to deliver business value because they were not integrated back into business applications. Our conclusion is to focus on the tangible business use cases for Data Cloud to effectively sell it.

Salesforce also needs to broaden its talk track and customer stories for Data Cloud to overcome the perception that it’s just a marketing tool for B2C. It’s capable of more than activations. Data Cloud also supports B2B use cases and powers AI, automation, and app development within other Salesforce clouds.

Data Reliability is Essential for Data Cloud Success

Data reliability was front and center at TrailblazerDX ‘24. It’s encouraging to see a focus on improving data quality, and not surprising. Ninety-four percent of business leaders feel their organization should be getting more value from their data.


Multiple presentations included a version of the following slide. Customers need to understand their data before landing it in Data Cloud.

Every AI Conversation is a Data Quality Conversation

Data Strategies with Data Cloud: A Key to Success

Data quality is a key part of the success of Salesforce’s AI initiatives. Bad data will inevitably poison any AI project. Yet, we have a disconnect between business users who want to leverage AI to increase productivity and efficiency and the teams responsible for delivering AI projects.

As Skip Saul highlighted in the Data Strategies with Data Cloud: A Key to AI Success. “Stakeholders aren’t going to come out and say ‘We need a data strategy.’” It’s incumbent on us to educate our stakeholders on the need for data strategies that align the business.

Starting to See Misinformation Presented about Data Cloud

With how fast Data Cloud is evolving and a lack of sufficient detail about how the AI works, it’s no wonder that we’re starting to see conflicting and incorrect details emerge. What’s a bit scary is that some of this misinformation comes from Salesforce itself.
Top of the list is the claim that mapping happens auto-magically. (Truth: automapping functionality is extremely limited). While we’re on the topic, Data Cloud will not magically standardize your data either.
We’re working on debunking these and other common Data Cloud myths in a future post. Stay tuned and subscribe to our blog to receive these insights as soon as we publish.

Platform will be a Major Growth Accelerator for Data Cloud

For as much Data Cloud featured on the agenda, Salesforce is still not talking about the power of Data Cloud as a platform. For example, we spoke with some B2B companies that thought Data Cloud could not solve their use cases because of Account Name at Address matching limitations. However, extending Data Cloud with a B2B enrichment solution from the AppExchance, would meet their needs. Salesforce has also been slow to expose Einstein Copilot to partners eager to extend applications with AI functionality.

Partners are a driving force behind the Salesforce economy. The AppExchange has been a key component of the exponential growth in Salesforce’s core products. As the first data management app for Data Cloud, we’re hoping to see the platform incorporated into Data Cloud’s value proposition soon.


By Hayley Coxon

Hayley Coxon is the Head of Product Marketing, Cuneiform for Salesforce. As a career marketer who believes business data is not nearly as trustworthy as it should be, PeerNova is the perfect home. Having previously held leadership positions in marketing and RevOps at Prodly and Conga, her passion is helping companies leverage technology to automate processes, improve customer and employee experiences, and in turn generate better quality data.

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