Exploring how Salesforce's next-generation marketing technology could address familiar challenges with Marketing Cloud Account Engagement (formerly Pardot).
Having worked extensively with Pardot (now Marketing Cloud Account Engagement), I've become familiar with some of the challenges marketing teams face when managing customer data, email engagement and automation.
With Salesforce Marketing Cloud Next introducing new capabilities, particularly around AI, predictive engagement and data management, I wanted to explore how some of these familiar challenges could be addressed.
This article looks at six areas where Marketing Cloud Next presents opportunities to rethink existing marketing processes and make better use of Salesforce's evolving marketing technology.
These observations are based on my knowledge gained through hands-on sessions and the extensive exam study I undertook to achieve my recent Salesforce Marketing Cloud Next Consultant certification.
1. Identifying and Filtering Automated Email Clicks
The current situation / challenge
Currently, the only way to identify automated bot clicks in Pardot is to set up a honeypot link associated with a campaign and embed it as a hidden link within an email template. This link is designed to be triggered by a bot click, helping to distinguish automated activity from genuine customer engagement.
However, this approach is not ideal, as it relies on a template-level workaround, requires ongoing maintenance and may not capture all automated activity. It also introduces a dependency on email template configuration, making it harder to manage consistently and reliably across campaigns.
This can impact the accuracy of email engagement reporting and campaign performance metrics.
The Marketing Cloud Next opportunity
Marketing Cloud Next offers an opportunity to move away from manual honeypot solutions through Einstein Metrics Guard, which helps identify and filter bot-generated email engagement activity.
This provides a more integrated approach to improving the accuracy of email metrics, reducing reliance on template-level workarounds and giving the Marketing team greater confidence in campaign engagement reporting and performance analysis.
2. Moving Beyond Fixed Email Send Times
The current situation / challenge
The current Pardot setup relies on the Marketing team selecting and scheduling email send times, typically based on campaign experience and assumptions about when customers are most likely to engage. This means send times are largely predetermined rather than tailored to individual customer behaviour, potentially missing opportunities to maximise email open rates and overall engagement.
The Marketing Cloud Next opportunity
Marketing Cloud Next presents an opportunity to use Einstein Send Time Optimisation to analyse individual engagement patterns and identify when each customer is most likely to engage with an email. Rather than relying on fixed send times, this enables more intelligent, data-led delivery, helping to improve engagement and maximise the effectiveness of marketing campaigns, while reducing the need for manual optimisation by the Marketing team.
3. Predicting Customer Engagement
The current situation / challenge
The current Pardot setup provides engagement reporting based on historical activity, such as email opens, clicks and interactions. While this helps the Marketing team understand past campaign performance, it offers limited predictive insight into how likely individual customers are to engage with future communications.
Identifying customers whose engagement is declining or who may be at risk of becoming inactive therefore relies largely on manual analysis and segmentation.
The Marketing Cloud Next opportunity
Marketing Cloud Next presents an opportunity to use Einstein Engagement Scoring to predict how likely individual customers are to engage with future marketing communications.
This would give the Marketing team greater visibility of highly engaged, declining and less engaged audiences, enabling more targeted segmentation, tailored campaigns and proactive interventions to improve customer engagement.
4. Managing Customer Communication Frequency
The current situation / challenge
The current Pardot setup provides limited automated insight into whether customers are receiving too many marketing communications across campaigns and channels. Managing communication frequency relies largely on Marketing team oversight, suppression rules and manual segmentation.
This creates a risk of over-communicating with customers, potentially contributing to email fatigue, reduced engagement and increased unsubscribes.
The Marketing Cloud Next opportunity
Building on the predictive engagement insights outlined in point 3, Marketing Cloud Next presents an opportunity to use Einstein Engagement Frequency to better understand individual customer engagement and communication volumes.
This can help identify customers who may be receiving too many communications and support more intelligent decisions around send frequency. The result is a more considered approach to customer contact, reducing communication fatigue while helping to maintain long-term engagement.
5. AI-Powered Marketing and MQL Management
The current situation / challenge
The current Pardot setup offers limited embedded AI capability to analyse campaign performance, identify customer behaviour patterns or support marketing optimisation. Lead qualification and follow-up also rely heavily on manually built automations and manual processes, requiring ongoing Marketing team input to manage and maintain.
Lower-priority MQLs, which may not justify direct Sales engagement, ultimately fall back to the Marketing team to manage and nurture. This creates additional manual workload and limits the team's capacity to focus on more strategic marketing activity.
The Marketing Cloud Next opportunity
Marketing Cloud Next presents an opportunity to embed AI more deeply into marketing and lead management through Salesforce Einstein and Agentforce capabilities.
Beyond providing customer insights and supporting campaign optimisation, AI agents could potentially engage, qualify and nurture lower-priority MQLs that do not warrant immediate Sales intervention.
With Salesforce's AI governance, security controls and configurable guardrails, these interactions can operate within defined business rules and appropriate oversight.
This would help reduce manual workload, improve lead management and allow Sales teams to focus on higher-value opportunities.
6. Managing Multiple Email Addresses Against a Single Customer Record
The current situation / challenge
The current Salesforce and Pardot architecture is centred around a single email address field on each Lead, Contact or Prospect record. This creates a limitation where customers may have multiple valid email addresses, such as a work and personal email address, but only one can be managed as the primary email address within the standard record structure.
Additional email addresses may need to be stored in custom fields or managed through workarounds, making it harder to maintain a complete and consistent view of customer contact details. It also limits the flexibility to determine which email address should be used for different types of customer communications.
The Marketing Cloud Next opportunity
Marketing Cloud Next, supported by Salesforce Data Cloud (Data 360) and its identity resolution capabilities, provides an opportunity to move towards a more flexible approach to managing customer email addresses.
Rather than relying solely on a single email field, multiple email addresses can be associated with a unified individual profile through Contact Point Email records. These can distinguish between different email types, such as work and personal, while also identifying a primary email address.
This provides the ability to maintain a more complete view of each customer while ensuring that marketing communications and associated processes recognise the individual as one customer, rather than treating each email address as a separate person.
With appropriate configuration of identity resolution, primary email selection, activation and sending rules, this could enable Marketing to manage multiple contact addresses while maintaining a single customer identity and avoiding duplicate communications.
As Marketing Cloud Next continues to evolve, it's exciting to see how these capabilities could change the way we approach marketing automation. It's not just about introducing new features, but looking at how we can rethink existing processes, overcome some of the limitations we've worked around for years and make better use of the data and technology available to us.
There is plenty to explore, and I'm particularly interested in how capabilities such as Einstein, Agentforce and Data Cloud will work together to create smarter, more connected marketing experiences.
As I continue exploring Marketing Cloud Next, I'll be sharing my findings, practical insights and thoughts along the way. There's a lot to unpack, and I'm looking forward to discovering what's possible!
