Journeys, segmentation, consent and data extensions designed before the first send. We also help you choose between Marketing Cloud Engagement and Account Engagement without a sales pitch.
Marketing Cloud projects go wrong in the data layer, not the journey canvas. Lists are imported ad hoc, consent lives in three places, and the first send goes to people who opted out.
We are Salesforce implementation specialists inside an AI-first engineering firm, so the platform choice, the data design and the AI features are decided together.
Salesforce sells two marketing products under similar names. They differ in data model, channels and the skills needed to run them. Neither is better; they fit different programmes.
| Criteria | Marketing Cloud Engagement | Account Engagement (formerly Pardot) |
|---|---|---|
| Typical fit | High-volume, multi-channel programmes, often consumer-facing | B2B lead nurture closely tied to sales activity |
| Data model | Its own: contacts, data extensions, SQL queries, a contact key you must design | Prospects synced one-to-one with leads and contacts in the CRM |
| Channels | Email, SMS, push, in-app, advertising audiences | Email, forms and landing pages |
| Journey tooling | Journey Builder with decision splits, waits and API entry | Engagement Studio with branching nurture programmes |
| Scoring | Engagement scoring and predictive models on Marketing Cloud data | Prospect score and grade feeding lead assignment |
| Skills to run it | Data architecture, SQL, AMPscript; usually a dedicated specialist | Admin-level configuration plus CRM knowledge |
| Common failure | Data extension sprawl and consent that differs by channel | Sync rules and duplicate prospects when CRM data is untidy |
Week one of discovery lists your channels, volumes, data sources and who will run the platform. The product recommendation follows from that list, and we write down why.
A documented contact key, sendable and reference data extensions designed from your segments, and the CRM connector configured with explicit sync rules.
Consent by channel and purpose captured at the point of entry, stored in the CRM, synced and enforced by suppression. A preference centre customers can actually use.
Data privacy principlesSegments defined once as SQL queries or filters against designed data, refreshed on a schedule, with counts that marketing and sales both recognise.
Welcome, nurture, win-back and event journeys with explicit entry criteria, exit rules and goals. Each journey has an owner and a date to review it.
Responsive templates, personalisation through AMPscript or merge fields, and AI-assisted copy variants that a human approves before they ship.
Email marketing AIEngagement written back to the CRM as activity, campaign influence configured, and dashboards that show journey performance next to pipeline.
Every send depends on four things lining up. The source data, the data extension it lands in, the consent that permits the channel, and the journey that decides timing. The diagram shows the order and the loop back.
Channels, volumes, data sources, consent today and who will run the platform. Product recommendation written down.
Contact model, data extensions, consent rules, journey map and connector sync rules, signed off before build.
Platform configured, connector live in a sandbox, templates and the first journeys built with weekly demos.
Lists, suppression files and engagement history cleansed, consent reconciled and loaded.
Seed sends across every channel and device, journey logic walked through with real records.
Sender authentication confirmed, IP or domain warmed where needed, first journey switched on.
Two to four weeks watching deliverability, sync errors and consent exceptions.
Marketing data is only useful when sales can see it and the law allows it. These pages cover both sides. Browse all Salesforce services.
Lead scoring, nurture design and hand-off rules that work across whichever platform you choose.
ReadSubject lines, copy variants and send-time optimisation with a human in the approval loop.
ReadMoving lists, consent and history from another platform without losing opt-outs on the way.
ReadLawful basis, minimisation and retention for customer data used by marketing and AI features alike.
ReadWhere marketing-qualified leads land, get routed and turn into forecast.
ReadConnector patterns, event-driven sync and what to do when the CRM is not the only source of truth.
ReadMarketing Cloud Engagement suits high-volume, multi-channel programmes, often consumer-facing, with its own data model. Account Engagement (formerly Pardot) suits B2B nurture that stays close to leads, contacts and sales. Some organisations run both. We map your use cases to each before anyone talks about licences.
Account Engagement with forms, scoring and a few nurture journeys typically takes 6–10 weeks. Marketing Cloud Engagement with data design, the CRM connector, consent and the first journeys takes 10–16 weeks. Several business units or many source systems extend both ranges.
Consent is captured per channel and per purpose, stored against the CRM record, synced to the marketing platform and enforced through suppression before every send. A preference centre lets customers change it. Our AI data privacy page covers the same principles for AI features.
Yes. Lists, suppression files, templates and engagement history are profiled, cleansed and loaded using our Salesforce data migration method. A dual-running period follows before the old tool is switched off.
Subject-line and copy variants, send-time optimisation, segment discovery and attribution. We cover the practical options in email marketing AI and marketing automation.
Tell us about your systems, your data and your constraints. We reply within one business day with a straight answer and a suggested next step.