Marketing is generating leads. Sales can't trace them to revenue.

Marketing Cloud is a family of products rather than a single application, which is the most common source of confusion on this topic. The main members are Marketing Cloud Engagement (formerly ExactTarget) for high-volume multichannel campaigns and journey orchestration; Marketing Cloud Account Engagement (formerly Pardot) for B2B lead nurturing, scoring and native Sales Cloud alignment; Marketing Cloud Intelligence (formerly Datorama) for cross-channel reporting and attribution; and Data Cloud beneath them as the unified customer data layer. They have different data models, different integration paths into Sales Cloud, and different buyers — so "we need Marketing Cloud" is not yet a scope.

Engagement is built for high-volume, multichannel campaigns — email, SMS, push, advertising and complex journey orchestration across large contact databases. Account Engagement is purpose-built for B2B pipeline marketing: nurture programmes, behaviour-based lead scoring, native Sales Cloud alignment and closed-loop campaign reporting. The quickest way to tell which you need is to ask whether your revenue depends on a defined MQL-to-SQL handoff or on messaging a large base across a long lifecycle. Many organisations legitimately run both — Account Engagement to qualify pipeline, Engagement for lifecycle and retention — and in that case the real work is architecting the join between them.

Usually no. Marketing Cloud Next, also marketed as Agentforce Marketing, is Salesforce's rebuild of marketing directly on the core platform with Data Cloud and Agentforce at the centre — genuinely significant, because it removes the connector that has always sat between marketing and CRM data. But there is no forced migration: Email Studio, Journey Builder, Content Builder and Automation Studio have no published end-of-life and no mandatory cutover date, and existing Engagement and Account Engagement customers can adopt Next capabilities inside the orgs they already run through the Engagement+ and Account Engagement+ routes. More importantly, the work that makes Next valuable is the same work that makes your current platform valuable — a clean contact data model and a properly designed Sales Cloud connection. Waiting does not build either of those, so the sensible answer for most teams is to build the foundation now.

A focused Engagement implementation covering journeys, segmentation and the Sales Cloud integration typically runs 8 to 14 weeks. A full build adding Data Cloud unification, cross-channel orchestration, AI activation and Intelligence reporting typically runs 16 to 24 weeks. Standard B2B Account Engagement setups run 6 to 10 weeks. Rescue engagements vary entirely with what is already in place, which is why they start with an audit rather than a timeline. We define scope and milestones before any build begins.

Configuration covers the contact and data extension model, segmentation, journeys and automations, scoring and grading, templates and dynamic content, forms and landing pages, the Sales Cloud connection and its field mappings, and reporting — which is the large majority of what a marketing team needs. Custom development starts when you need a preference or subscription experience the standard tools cannot render, when sends must be triggered in real time by product events through the API, when logic on the Sales Cloud side needs Apex or a Lightning Web Component, or when an integration needs genuine error handling and retry. We hold that line carefully here because custom code in a sending platform has to survive every release and every deliverability change, and that maintenance cost lands on you.

We do both, and we will tell you which we think is right. Migrations from HubSpot Marketing Hub, Marketo, standalone Pardot, Mailchimp and ActiveCampaign cover contact and list transfer, workflow and journey recreation, template rebuilding, suppression list migration and historical engagement preservation where the source platform allows it. But migrating is not automatically the right answer: if HubSpot is working for your marketing team and the real problem is the Salesforce integration, the cheaper and lower-risk fix is to keep HubSpot and architect that connection properly. Twopir Consulting holds credentials on both platforms, so we have no commercial reason to push you one way.

Almost always because the data underneath cannot support it. Einstein Engagement Scoring, Send Time Optimization and Content Selection learn from your historical send and response data, so if the contact model is fragmented, segmentation is coarse, or engagement history is incomplete, the models train on noise and return it confidently. Switching the features on is a five-minute job; making them useful is a data modelling job. We assess that readiness during the architecture phase and will say plainly when the right sequence is to fix the data model first and activate AI in a second phase — which is a less exciting answer than turning everything on at go-live, but it is the one that produces a measurable difference.