Article

Salesforce’s Roadmap Reveals Evolving Support of Converged Growth Models

Salesforce is actively building a comprehensive Converged Growth tech stack, decoupling marketing technology from pre-sales focus and embracing full-cycle nurture and growth enablement, with a focus on real-time data, automated engagement across channels, and cost optimization to support a perpetual growth engine and orchestrate engagement throughout the customer journey.

Martin Schneider
6 min read
ANNUITAS Research Brief

I recently had a few deep dive briefings with Salesforce to dig into their Marketing Cloud and related technologies. I wanted to get an understanding of their vision and see how the overall portfolio was aligning with its go‑to‑market tool set to help support a Converged Growth model for enterprise users.

What I discovered, not to my surprise, is that Salesforce has been very busy building what looks like a top-down Converged Growth tech stack to support the orchestration of engagement across the entire customer journey. It has philosophically decoupled its “marketing” technology from a traditionally pre-sales focus and seems to have fully embraced the idea of full-cycle nurture and growth enablement.

The recent and upcoming additions to the Marketing Cloud (I hesitate to even call it that anymore, as it has grown so far beyond the Pardot/ExactTarget core – with new innovations like Data Cloud and new acquisitions like Datorama, Evergage, etc.) focus on three key themes:

  • Personalize Every Moment with Real Time Data
  • Automate Engagement Across Every Channel
  • Optimize Spend and Performance

When you think about the tenets of what we at ANNUITAS|research call Converged Growth, these themes are in lockstep with how enterprises can build a perpetual growth engine that orchestrates engagement for the right stakeholders, across all critical channels, at every stage of the customer journey. Let’s dig into these elements in more detail:

Real Time Data – Supporting the Customer Value Chain

Salesforce has been busy creating connectors between its various CRM and related products to the Marketing Cloud, but also has been making it easier to plug nearly any data set into your marketing processes for faster, more effective segmentation, targeting and analysis. This is in addition to its existing Data Cloud for Marketing, which allows for segmentation and unifying data from various sources within an organization’s tech stack. Additionally, Marketing Cloud Personalization allows for marketers to deliver personalized content and experiences and is able to deliver a seamless experience by combining touchpoints from various channels by creating unified profiles for traditional and ABM marketing.

The company has been adding connectors to all the key data sources that feed a data-driven marketing initiative. These include the full MuleSoft library of connectors and enrichment pipes like Acxiom, LiveIntent and also key cloud platforms from Amazon, Google, and Microsoft. The result is a far richer set of data around every prospect, lead, contact, account, etc.

In the past, a major complaint I’ve heard from marketers about Salesforce was the fact that creating a data lake “inside” Salesforce can be a tricky, if not expensive, endeavor. You usually have to extract and mirror the data, causing a “doubling up” effect on storage costs. But Salesforce is solving this in an innovative way. The company is using its partnership with Snowflake as a starting place for what it is calling its “Zero-copy ‘bring your own lake’ model. Without getting too deep into the technical aspects, essentially this allows users to access data where it lies (no data copy needed) for segmentation and other analysis – making for faster segmentation as well as less storage impact inside Marketing Cloud. The company plans to expand this to multiple data services in the near future. The company is also expanding this approach to insights with “bring your own AI” where data science teams can train and deploy AI and machine learning models on Salesforce data using popular tools like Amazon Sagemaker – again without having to copy any data.

In short, this allows users to better aggregate data around customers, perform segmentation and analysis, with far less complexity and data storage overhead. When combined with the actual go‑to‑market features, this more inclusive customer data value chain can unlock more efficient, highly personalized marketing efforts in theory.

Automating Engagement Along the Customer Journey

In addition to adding more data enrichment capabilities, Marketing Cloud now includes more tools for faster segmentation, using even more attributes – to better identify and reach out to both prospects and more important, existing customers who might be behaving or otherwise prime targets for cross and upsell actions. The additions align well with a full journey engagement mindset.

Marketing Cloud now offers native WhatsApp integration. This again is key for full journey engagement, as it allows users to create more seamless dialogs that span beyond the normal lead/acquisition phases of customer journeys.

Additionally, with Data Cloud powering sales and service, the moments beyond marketing can be natively personalized as the customer moves to Data Cloud-powered commerce and CRM experiences.

Here we can see how Salesforce components can support a full journey engagement approach – in this case for Grammarly.

Optimizing Costs & the Full Customer Journey

Salesforce has done significant work integrating analytics acquisitions like Datorama (now “Intelligence”) and Tableau into the Marketing Cloud. Users can now aggregate data from various stages of the journey – from marketing activities, sales engagements and even ecommerce transaction behaviors, to better understand the full journey.

Also, now more business users can take advantage of code-free access to the data inside both Tableau and Marketing Cloud to better understand customer movement along the journey and make decisive impact without the need for business analysts or programming skills. To make things even easier the company has added more pre-built dashboards or faster insights on customers, segments, identities, products, campaigns, content, channels, etc.

The Takeaway

Salesforce is doing all the right things to de-silo the data points that can unlock a Converged Growth strategy. Not only is it making lots of data enrichment services more easily accessible to better target and segment; it is making it easier to leverage data from latter portions of the customer journey to better create a perpetual marketing model, rather than one solely focused on net new acquisition.

The company’s multi-channel engagement improvements also support a Converged Growth mindset. Adding more native integration to WhatsApp allows for a continuous engagement model. Also, improving the customer insights inside the CRM itself allow more stakeholders to make more informed engagement decisions further along the journey outside of traditional “marketing” stages.

Supporting all this with a data lake concept that reduces complexity and storage overhead is the icing on the cake. Marketing Cloud users now have the ability to unlock more insights and drive a data-driven full journey engagement model. In short, Salesforce is adding all the pieces of the puzzle, it is up to users to take advantage of these new capabilities in building perpetual growth engines in their organizations.