HubSpot and Salesforce Advisory

Before making decisions about a platform, you need a clear picture of where things stand. We conduct structured assessments of existing HubSpot and Salesforce implementations covering data model health, data sources and integration quality, segmentation architecture, workflow effectiveness, consent management, and overall platform readiness.

The output is a prioritized findings document that tells you what is working, where the gaps are, and what needs to be addressed before you build further or migrate away. For clients heading into a migration, this work comes first. Carrying a poorly structured data model into a new platform recreates the same problems in a new environment.

The decisions made before a migration begins determine whether the outcome is clean. Data model issues carry over. Lifecycle stage misclassifications carry over. Consent logic distributed across workflows becomes harder to untangle in the new platform.

We support migrations in both directions: HubSpot to Salesforce, Salesforce to HubSpot, and from other CRM platforms into either. That covers pre-migration remediation, migration planning and sequencing, field mapping, data transformation, and post-migration validation. The assessment work typically comes first, giving us a clear view of what needs to be resolved before data moves.

The CRM is the foundation everything else depends on. Getting the data model right from the start, before workflows are built and campaigns are running, is the most important architectural decision in either ecosystem.

For HubSpot, that means designing the CRM layer properly: object architecture, custom objects, properties, relationships, and lifecycle stage strategy. Sales Hub and Marketing Hub sit on top of that foundation. If the CRM layer is poorly structured, everything built on it inherits those problems.

For Salesforce, the same principle applies. We design the full object architecture including Contact, custom objects, consent and subscription modeling, and product and transaction data structures. We make deliberate decisions about what belongs on the Contact record and what belongs on related objects.

In both platforms, segmentation strategy is built into the data model from the start. Lifecycle stage definitions, audience attributes, and the signals that drive targeting are architectural decisions, not something added after the fact.

Marketing execution lives on top of the CRM layer. How well it works depends directly on how well the CRM is structured.

On the HubSpot side that means Marketing Hub Pro: campaign architecture, marketing email setup and governance, segmentation strategy, consent management, forms and landing pages, and ad retargeting using CRM audiences. Segmentation in HubSpot is most effective when it draws on well-defined lifecycle stages and audience attributes built into the CRM, rather than one-off lists created for individual sends.

On the Salesforce side that means SFMC: Journey Builder, Email Studio, subscription list management, and the connector between Salesforce CRM and SFMC. Consent architecture, audience strategy, and how behavioral data flows from the CRM into activation decisions are all part of this work, not separate considerations.

Data Cloud sits above the CRM layer. It unifies Salesforce CRM data with behavioral signals from web, email, and other channels to enable identity resolution, advanced segmentation, and cross-channel activation that is not possible within the CRM alone.

We design the CRM data model to be Data Cloud-compatible from the start, define how behavioral data flows in and joins with CRM records, and architect the segmentation and activation approach including SFMC journeys and paid media audiences. Data Cloud is also what makes Einstein work well. Predictive scores, next best action, and personalization all depend on unified, enriched data. Without that foundation, Einstein has limited signal to work with.

This is also where CRM and DXP strategy connect. Customer data platform capability is a core component of a modern digital experience stack, and Data Cloud is Salesforce's answer to that layer.

CRM implementations rarely exist in isolation. Most organizations have surrounding systems that own critical data, and getting the CRM to reflect an accurate, current view of that data requires more than platform configuration.

We advise on how the CRM connects to external systems: where the source of truth lives for different data types, how changes in upstream systems propagate to the CRM, and what the integration architecture needs to keep data in sync reliably. That includes working alongside development teams building custom integration layers, coordinating between CRM implementation work and the broader technical architecture, and advising on patterns like event-driven sync when a proprietary system owns data that the CRM needs to reflect.

• HubSpot: CRM, Sales Hub, Marketing Hub Pro
• Salesforce: CRM, Sales Cloud, SFMC, Data Cloud, Einstein

Some clients come with a greenfield implementation and need the CRM designed from scratch. Some have an existing platform they want assessed before building further or migrating away. Some are mid-migration and need advisory support on specific decisions. Engagements are shaped around the situation, not a fixed-scope package.