Twopir Consulting implements Marketing Cloud Next — Growth and Advanced — as customer engagement infrastructure: unified profiles in Data 360 underneath, journey orchestration governed as one programme on top, and Agentforce deployed with review standards instead of as an experiment. So marketing, sales and finance finally read the same customer record.
Capabilities delivered across 500+ client deployments — by Twopir Consulting, a Salesforce Partner and HubSpot Partner.
Where We Operate
These are not technology problems. They are architecture, data and operational maturity problems — and they compound over time.
Records live in Salesforce CRM, the marketing platform, ERP and support tooling at the same time. There is no single unified profile to segment on, so personalisation is guesswork and nobody trusts the numbers.
Sales, service and marketing execute independently, so the customer receives fragmented and sometimes contradictory experiences. Welcome series and nurture programmes send on schedule without reflecting where the customer actually is.
Lead and contact records in Salesforce conflict with subscriber records in the marketing platform, and campaign membership drifts out of sync. Reporting cannot be trusted, so campaigns cannot be attributed.
Dozens of overlapping, undocumented journeys and automations accumulate, and nobody owns them. Customers fall into conflicting journeys simultaneously, and no one is willing to switch anything off.
Agentforce and AI-generated content get deployed with no standards behind them. Different teams produce different outputs, brand consistency deteriorates, and customer experience variance increases instead of falling.
Campaign reporting cannot answer what revenue was influenced, which lifecycle stages are breaking down, or where attribution actually sits. Leadership cannot evaluate marketing investment from open rates alone.
Marketing Cloud Next is Salesforce's AI-first customer engagement platform, built on the Salesforce platform with Data 360 (formerly Data Cloud) as its data foundation and Agentforce as its AI layer. It ships in two editions — Marketing Cloud Growth and Marketing Cloud Advanced — and it is designed to unify customer data, drive behavioural journey orchestration and apply AI-assisted personalisation across every channel a customer touches. The vendor's own product documentation lives at salesforce.com/marketing.
The difference between a Growth implementation and an Advanced one is not only feature access. It is operational maturity: how sophisticated your data model is, how your journey logic is architected, how deeply CRM data is integrated, and whether your AI capabilities are governed to produce consistency rather than noise. Growth suits organisations building their foundation; Advanced is built for complex lifecycle orchestration, multi-region compliance and mature reporting.
When an organisation treats the platform as a broadcast email tool, it uses a fraction of what the architecture can do. Organisations that buy it without an architecture foundation typically have the same problems two years later. The platform is capable. The implementation decisions — data model, lifecycle design, CRM alignment, segmentation governance — decide whether that capability ever reaches the customer.
Unified customer profiles, identity resolution and audience activation — what makes personalisation real rather than theoretical.
Behavioural triggers, lifecycle stage transitions and multi-channel journey logic, governed as one coherent programme.
Content generation, engagement prediction, segmentation assistance and agent-driven marketing operations at scale.
Sales and marketing operating on the same customer record, with lifecycle visibility shared across both teams.
Journey analytics that connect engagement activity to pipeline, retention and marketing return leadership can read.
Preference management, subscription governance and regulatory compliance built into the architecture, not managed by hand.
These are three different pieces of work bought by three different people. Most disappointing engagements are simply the wrong one of the three. Each card says where that service stops.
For organisations standing Marketing Cloud Next up for the first time, or moving off a legacy marketing platform.
We design the data model, the lifecycle framework and the CRM integration architecture before a single journey step is built — then deliver the platform against that design.
We hand over a running platform with a documented data model and a journey inventory. Day-to-day campaign production stays with your team — we train it, we do not staff it.
For teams already live on the platform whose programme is underperforming, or whose automation has grown past anyone's control.
We audit what is actually running, retire what should not be, and rebuild the parts holding the programme back — usually without starting from a blank org.
Anything achievable in setup, segmentation, journey and flow builders is configuration. The moment a requirement needs Apex, a Lightning Web Component or a custom API integration, it has crossed into build-on — and we say so before the estimate, not after.
For enterprise architects and product owners who have hit the edge of what configuration can express.
Custom development on top of the platform: the integrations, data structures and interfaces the standard product does not ship, built on supported extension points.
We do not fork the product. Everything we build sits on supported extension points, so Salesforce's own release cycle upgrades around it instead of breaking it.
Every engagement is scoped to what your organisation actually needs. These are the capability areas Twopir operates within on Marketing Cloud Next.
Data 360 identity resolution and profile unification, so a customer becomes one actionable record instead of duplicate rows across disconnected systems.
Lifecycle journeys governed by customer behaviour rather than the campaign calendar — onboarding, adoption, retention and re-engagement built to run and improve continuously.
Agentforce capabilities and AI content generation deployed with governance — personalisation that improves engagement because it is grounded in real customer data, not assumptions.
Segments built on behavioural, demographic and lifecycle data rather than static lists — audience logic that scales without a manual rebuild every campaign cycle.
Email, SMS, push and advertising orchestrated as a single customer experience — not operated as separate campaign programmes by separate teams.
Reporting infrastructure that connects campaign activity to pipeline and revenue outcomes, so leadership stops asking whether marketing is working.
Most reporting discrepancies between Marketing Cloud and Salesforce trace back to synchronisation that was deployed quickly rather than designed. These are the four flows we architect first.
The alignment flow. Sales and marketing operate on one customer record, and campaign engagement reaches pipeline reporting instead of dying inside the marketing platform.
The foundation flow. Without it the platform segments on subscriber data that reflects how a record entered the system rather than who the customer is.
The behaviour flow. Purchase history, support interactions and product usage are the signals that separate a real lifecycle model from a demographic one.
The compliance flow. Global programmes need regional preference management that is systematic, not a spreadsheet maintained by whichever regional team remembered.
Each phase builds on the last. Implementations that skip the foundational work create the same problems two years after go-live that they had before it.
We assess the current state before proposing anything — including whether you need an implementation at all, or a configuration engagement on what you already own.
The foundation phase, and the one most often skipped. Nothing is built until the data model and the lifecycle stages are agreed on paper.
Configuration and development against the agreed design — journeys, automations, the CRM synchronisation layer and the Agentforce setup with its governance already defined.
Where the programme becomes something your team can operate. Attribution reporting goes live, and the governance model gets documented and handed over.
Two engagements where the marketing platform was rebuilt around the data model rather than the campaign calendar — and the scenarios these programmes were built to resolve.
Consolidating email, social, web and mobile into one engagement environment with individualised journeys.
Resolving sync failures between marketing automation and Salesforce so campaign reporting could be trusted again.
Salesforce CRM, the marketing platform, ERP and support tooling each hold a version of the customer, with no unified identity layer. Segmentation is unreliable, personalisation is guesswork, and nobody trusts the numbers.
What resolves it: Data 360 unification, identity resolution and a governed customer profile architecture — at the foundation, before any journey is rebuilt.
Welcome series, onboarding sequences and nurture programmes all exist and all deliver. They drive no meaningful engagement and no measurable pipeline contribution. The automation exists; the architecture does not.
What resolves it: journey redesign on behavioural logic, lifecycle stage mapping, and exit criteria that reflect real conversion intent rather than a send schedule.
Lead records in Salesforce do not match subscriber records in the marketing platform, and campaign membership is out of sync. Attribution cannot be established because the data foundation does not support it.
What resolves it: synchronisation architecture re-alignment, sync governance, and a shared data model that both platforms genuinely operate from.
Agentforce and AI content generation are in use with no governance framework behind them. Different teams produce different outputs, brand consistency deteriorates, and customer experience variance goes up rather than down.
What resolves it: AI governance design, content review workflows and prompt standards that make Agentforce a systematic asset rather than a creative wildcard.
Leadership asks what marketing contributed to pipeline. Answering takes hours of manual extraction across systems that do not agree with each other, and the result is an estimate rather than a measurement.
What resolves it: a revenue attribution framework, journey analytics reporting, and marketing-to-CRM pipeline visibility built into the platform architecture.
Investment concentrates on demand generation while existing-customer engagement gets minimal operational attention. Retention programmes exist in name but not in systematic execution.
What resolves it: customer health scoring, churn signal detection, and automated retention journeys that intervene on behaviour instead of waiting for a quarterly review to notice.
The distinction matters more on this platform than on most. Marketing Cloud Next rewards teams who understand data models and CRM integration architecture, and punishes teams who only understand campaigns.
We are marketing operations architects, Data 360 consultants and Agentforce specialists who work inside enterprise Salesforce ecosystems — not an email production team with a platform certification attached.
Identity resolution, unified profile architecture and audience activation strategy are designed before journey logic is built. Reversing that order is the single most common reason these programmes stall.
Marketing and sales operate from a shared customer lifecycle view, with attribution that reaches pipeline and revenue reporting. No more two datasets and an argument about which one is right.
Content standards, review workflow, prompt standards and named ownership ship with the AI capability rather than following it a year later. Governance does not slow adoption down; it makes the output trustworthy enough to scale.
We say where configuration ends and custom development begins before the estimate. We hand over documentation your team can operate from. And we will tell you when the answer is optimising what you already own rather than a new implementation.
Growth is the entry and mid-market edition of Marketing Cloud Next, providing core Data 360 usage, standard journey orchestration and basic Agentforce capabilities. Advanced is the enterprise tier: expanded data unification and activation, more complex journey orchestration, deeper AI and Agentforce integration, and advanced analytics and attribution. The distinction that matters operationally is scale and governance — Growth works well for organisations building their foundation, while Advanced is designed for programmes with complex lifecycle orchestration, multi-region compliance requirements and mature reporting needs.
Data 360 — renamed from Data Cloud in 2025 — is the foundational infrastructure that makes Marketing Cloud Next meaningful at scale. Without it the platform operates on subscriber data that reflects how a record entered the system rather than who the customer actually is. Data 360 performs identity resolution across source systems — CRM, support, commerce, product usage — and produces a unified customer profile. That profile is what drives accurate segmentation, behavioural journey triggers and AI personalisation grounded in real context. Organisations that deploy Marketing Cloud Next without that architecture usually find their personalisation is shallow and their journey logic fires on incomplete signals.
Agentforce delivers value once the data foundation is mature enough to give the AI meaningful signals to act on. Organisations that adopt it before their customer data is unified typically generate outputs that are inconsistent, off-brand or irrelevant, because the model is working from incomplete context. The right sequence is unified customer profiles first, then governed AI deployment. Agentforce is most effective for content generation at scale, intelligent segmentation assistance, predictive engagement scoring and automating repetitive marketing operations decisions — and it should ship with governance standards, meaning prompt guidelines, review workflows and output validation, so it produces consistency rather than variance.
The synchronisation layer between the marketing platform and Salesforce CRM requires deliberate architecture to work at enterprise scale. The critical design decisions are which object types synchronise — lead, contact, campaign member — the direction and frequency of that sync, how duplicate records across platforms are handled, and how campaign engagement data flows back into Salesforce for reporting. Most reporting discrepancies between the two trace back to sync configuration that was deployed quickly rather than architecturally designed. With Data 360 as the foundation, the integration can move beyond record-level sync toward a shared unified customer profile that both platforms operate from.
Anything achievable inside setup, the segmentation tools and the journey and flow builders is configuration: lifecycle stages, entry and exit criteria, dynamic segments, channel logic, preference settings and reporting on standard objects. It crosses into custom development the moment a requirement needs Apex, a Lightning Web Component, a custom API integration to a system outside the Salesforce stack, or a data model extension the standard product does not express.
The practical reason to draw the line early is cost and risk, not pedantry. Configuration is quicker to change and survives platform releases untouched; custom development needs a maintenance owner and regression testing against each release. We identify which side of the line a requirement sits on before the estimate rather than after, and we build on supported extension points so Salesforce's own release cycle upgrades around our work instead of breaking it.
Journey failures fall into three operational categories. First, data quality — journeys are triggered by data events, so if the underlying data model is unreliable, entry logic fires incorrectly or not at all. Second, design — journeys built around campaign logic rather than customer behaviour, with exit criteria that do not reflect real conversion signals and no consideration for customers sitting in several active journeys simultaneously. Third, governance — journeys that were built and launched but never reviewed, optimised or decommissioned, so over time overlapping journeys create contradictory customer experiences. Effective governance requires named ownership, documentation, performance monitoring and a defined lifecycle for retiring journeys that are no longer relevant.
Reporting should operate at three levels. Tactical reporting covers individual campaign and journey performance — opens, clicks, conversions, deliverability. Operational reporting covers lifecycle health: what proportion of the base is engaged, where customers break down in key journeys, and whether audience quality is improving or degrading. Strategic reporting covers revenue attribution — which programmes influenced pipeline, what the retention rate is, and what the demonstrable marketing return is across the business. The common failure mode is an organisation with strong tactical reporting and no operational or strategic layer at all. Leadership cannot evaluate marketing investment from open rates alone.
Talk to a Twopir Marketing Cloud Next architect. We will assess your current platform state, identify the gaps limiting performance, and outline what a properly architected implementation would deliver — including whether you need one at all.
Marketing Cloud Next (Growth & Advanced) · Data 360 · Agentforce · Journey Consulting
