n June 2025, Salesforce unveiled Marketing Cloud Next (MCN) at its Connections conference, a ground-up rebuild of its marketing platform. For the thousands of brands running on legacy Salesforce Marketing Cloud Engagement, it raised an immediate question: is this the upgrade you’ve been waiting for, or a signal to reevaluate your martech stack entirely?
Marketing Cloud Next represents the most significant architectural shift in Salesforce’s marketing technology since it acquired ExactTarget in 2013. It promises unified data, autonomous AI agents, and a single platform for B2B and B2C.
This guide covers what Marketing Cloud Next is, how it differs from legacy SFMC, what to evaluate when choosing a marketing platform, and how Bloomreach compares.
What Is Salesforce Marketing Cloud Next?
Marketing Cloud Next is Salesforce’s newest marketing platform, built natively on Data Cloud (recently rebranded as Data 360). Unlike legacy Marketing Cloud Engagement, which ran on ExactTarget’s separate infrastructure, MCN is integrated directly into the core Salesforce platform.
The rebuild consolidates nine of Salesforce’s previous marketing acquisitions, including ExactTarget, Pardot, Datorama, and Evergage, into a single application. At its center is Agentforce, Salesforce’s autonomous AI framework, which powers capabilities like automated campaign creation, real-time personalization decisioning, lead qualification, and segment intelligence.
What MCN does well:
- Unified data foundation: MCN’s native integration with Data 360 means customer data from Agentforce Sales, Agentforce Service, Agentforce Commerce, and Agentforce Marketing lives in one place
- Agentic AI capabilities: Agentforce agents can create campaign briefs, generate audience segments, and optimize send times autonomously, replacing Einstein’s previous bolt-on approach with native AI
- B2B and B2C unification: MCN eliminates the historical split between Marketing Cloud (B2C) and Marketing Cloud Account Engagement/Pardot (B2B), serving both from a single application
- Cross-department orchestration: Because it’s built on core Salesforce, MCN can coordinate marketing activities with Agentforce Sales, Agentforce Service, and Agentforce Commerce workflows natively.
Salesforce describes the transition from legacy SFMC to MCN as a “convergence” rather than a migration, meaning existing Marketing Cloud Engagement customers can run both systems in parallel while gradually adopting MCN capabilities. No sunset date has been announced for legacy MCE.

Marketing Cloud Next vs. Marketing Cloud Engagement: Key Differences
Understanding the practical differences between MCN and legacy MCE helps frame why Salesforce built a new platform, and why the transition is more complex than a typical upgrade.
| Aspect | Legacy MCE (SFMC) | Marketing Cloud Next |
|---|---|---|
| Architecture | ExactTarget infrastructure (2013 acquisition); separate from core Salesforce | Built natively on Salesforce core using Data 360 |
| Data model | Proprietary data extensions with batch syncs | Unified profiles using Data Model Objects and Data Graphs |
| Orchestration | Journey Builder (proprietary) | Salesforce Flow engine (Campaign Flows) |
| AI | Einstein (bolt-on features) | Agentforce (autonomous AI agents) |
| Personalization | Interaction Studio (separate product) | Native real-time decisioning on Data 360 |
| B2B/B2C | Separate platforms (MCE vs. MCAE/Pardot) | Single application for both |
| Pricing | Subscriber/seat-based licensing | Consumption-based credits (messaging, Data 360, Einstein) |
| Processing | Primarily batch-oriented | Real-time processing capabilities |
There’s definitely a big architectural shift here. MCE was effectively a standalone product bolted onto Salesforce through connectors. MCN is part of the platform itself. For organizations already deeply invested in the Salesforce ecosystem (i.e., Sales Cloud, Service Cloud, Commerce Cloud), this native integration is a clear advantage.
For organizations evaluating their marketing stack, the key question is whether MCN’s native Salesforce integration aligns with their broader platform strategy.
What To Look for in a Marketing Automation Platform
Whether you’re evaluating MCN or exploring the broader market, these are the criteria that matter most when choosing a marketing automation platform in 2026.
- Real-time data activation. The marketing automation market is growing at 12% CAGR and is projected to reach $20 billion by 2034. As customer expectations rise, batch-oriented processing is giving way to real-time activation. Look for platforms that can act on customer signals within milliseconds, not hours.
- Total cost of ownership. Platform pricing extends beyond licensing. Factor in implementation consulting, data infrastructure requirements, team training, and any credit-based consumption models that make costs harder to forecast. Understand the full picture before committing.
- Cross-channel reach. Modern marketing requires coordination across email, SMS, web, mobile app, ads, and more. Evaluate whether a platform handles this natively or requires middleware and integrations to connect channels, as additional tools add complexity and cost.
- AI accessibility. AI-powered features are only valuable if your team can use them. Consider whether a platform’s AI requires specialized technical skills (SQL, data science, custom model configuration) or whether it’s accessible to the marketers running day-to-day campaigns.
- Flexibility and modularity. Some platforms require full commitment upfront. Others let you start with one capability (like email marketing automation) and expand over time. Consider your roadmap and whether the platform grows with you without forcing a major replatform.
- Data governance and compliance. For regulated industries like financial services, visibility into how AI makes decisions is a real consideration. Evaluate whether the platform gives your team enough transparency to meet governance requirements under GDPR and emerging AI frameworks.
How Bloomreach Compares
At Bloomreach, we approach marketing automation from a different starting point. Loomi AI, our agentic platform, powers every Bloomreach application and connects to every touchpoint, from email and marketing automation to search and conversational shopping.
Here’s where the differences are most relevant for teams evaluating their options:
Real-Time Personalization From Day One
Our platform processes customer signals and activates personalization in actual real time (between 5 milliseconds and 2 seconds), from data ingestion to campaign activation. When a customer abandons a cart, browses a product category, or triggers an intent signal, Loomi AI responds immediately across channels. This is especially useful for campaigns like personalized reengagement journeys.
When Motorpoint, a UK automotive retailer that previously ran on Salesforce Marketing Cloud, switched to Bloomreach, the team saved 40% of their time on email operations per week and saw a 50% uplift in email performance. The migration addressed what they described as limited automation capacity and shallow customer tracking under SFMC.
Cross-Channel Orchestration Without Middleware
We natively support 13+ channels, including email, SMS, WhatsApp, web, mobile app, ads, and more — all from a single platform. There are no API call limits forcing you into middleware solutions, and no separate credit types for different channel activities. Teams can build personalized welcome flows, abandoned cart sequences, and lifecycle campaigns that span every channel without stitching together separate tools.
Woolacombe Bay Holiday Parks used this cross-channel capability to double its conversions, achieving a 49.39% abandoned cart conversion rate and generating £270K in revenue from automated campaigns alone. The key was real-time orchestration: When a guest abandoned a booking on the website, Loomi AI coordinated campaigns across email, direct mail, and web personalization — all from one platform and all informed by the same customer data.
AI That’s Transparent and Accessible
Loomi AI powers predictive analytics, autonomous marketing, and real-time decisioning across every application. Unlike credit-based AI consumption, Loomi AI is built into the platform. You don’t pay per AI interaction or face trade-offs between AI usage and cost control. And because Loomi AI operates on first-party customer and product data within a single platform, there’s no data quality gap between ingestion and activation.
Loomi AI also puts marketing intelligence directly in marketers’ hands without requiring SQL fluency. Teams can use natural language to build audience segments, generate campaign copy variants, and analyze performance, making AI accessible to the marketers who actually run campaigns, not just the technical teams who configure them.
Start With What You Need, Expand When You’re Ready
Our platform is modular by design. You can start with email and marketing automation, then expand to search, categories, web personalization, or conversational shopping as your needs grow, without needing to replatform. This matters because many organizations don’t need a full platform replacement on day one. A team currently using MCE for email can adopt Bloomreach for email personalization first, then layer on additional channels as business needs evolve.
Each additional channel enhances the others through Loomi AI: data from one touchpoint makes every other touchpoint smarter. A customer’s search behavior on your website informs the email recommendations they receive, which informs the ad audiences they’re placed in, which informs their next on-site experience. This compounding effect is only possible when all channels operate on the same intelligence platform, not stitched together through integrations.
Beauty retailer Notino used this expansion strategy to great success. Having already used Bloomreach for email marketing and weblayers, Notino wanted to add more channels into the mix. Thanks to Loomi AI’s single customer view, the brand was able to create holistically personalized experiences, leading to a 63% increase in conversion rates in its remarketing efforts. Additionally, Notino also drove 11% of all Black Friday orders via the newly adopted SMS channel, highlighting how powerful a unified platform can be to an omnichannel strategy.
See What You Can Achieve With Loomi AI-Powered Marketing Automation
If you’re evaluating Marketing Cloud Next or questioning whether the convergence effort is worth it, see how our marketing automation delivers real-time personalization without the complexity. You can also see how other brands have made the switch in our SFMC to Bloomreach migration guide, or compare us directly against Salesforce Marketing Cloud.
*All trademarks, including Salesforce, Marketing Cloud, Marketing Cloud Engagement, Agentforce, Einstein, Pardot, ExactTarget, Data Cloud, and Data 360, are the property of their respective owners.
FAQ: Marketing Cloud Next
What is Salesforce Marketing Cloud Next?
Marketing Cloud Next is Salesforce’s new marketing platform, announced at its Connections event in June 2025. Built natively on Data 360, it consolidates nine previous Salesforce marketing acquisitions into a single application powered by Agentforce AI agents. It supports both B2B and B2C marketing from one platform and introduces agentic capabilities for campaign creation, personalization, lead management, and audience intelligence.
What is the difference between Marketing Cloud and Marketing Cloud Next?
The main differences are architectural. Legacy Marketing Cloud Engagement runs on ExactTarget’s separate infrastructure with batch data syncing and Journey Builder for orchestration. Marketing Cloud Next is built on Salesforce’s core platform using Data 360, with real-time data processing, flow-based orchestration, and native Agentforce AI agents. MCN also unifies B2B and B2C marketing in a single application, whereas legacy SFMC required separate platforms.
Is Salesforce sunsetting Marketing Cloud?
Salesforce has not announced a sunset date for Marketing Cloud Engagement (MCE) or Marketing Cloud Account Engagement (MCAE). The company frames the transition as a “convergence,” meaning customers can run both systems in parallel through MCE+ while gradually adopting MCN capabilities.
Does Marketing Cloud Next require Data 360?
Yes. Marketing Cloud Next is built natively on Data 360 (formerly Data Cloud), which serves as its data foundation. Organizations implementing MCN must provision Data 360 and purchase associated Data 360 credits. Data 360 enables the unified customer profiles, real-time audience activation, and AI capabilities that define MCN.
What is Salesforce Marketing Cloud called now?
Salesforce’s marketing product naming has evolved significantly. The current lineup includes: Marketing Cloud Next (MCN), the latest platform; Marketing Cloud Engagement (MCE), the legacy platform formerly known as “SFMC” or ExactTarget; Marketing Cloud Account Engagement (MCAE), formerly Pardot, for B2B; and Marketing Cloud Growth (MCG) and Marketing Cloud Advanced (MCA), stepping-stone editions toward MCN.
How does Marketing Cloud Next pricing work?
Marketing Cloud Next uses a consumption-based credit model. This replaces the subscriber/seat-based licensing used by legacy MCE. Organizations evaluating MCN should factor in implementation consulting, Data 260 provisioning, and team training alongside licensing costs to understand the full investment.
