Andy Mullings

They point to a 300% rise in requests to clean and deduplicate Marketo Engage databases, driven by renewal costs, the need for sound foundations before AI can work, and databases merged through acquisitions. Dirty data does more than distort reporting: it corrupts the inputs AI uses to judge intent, personalise and recommend actions.

Duplicate records split engagement history, so AI can treat an active person as cold or overstate their interest.

• Bad job titles, old company names, incorrect lifecycle stages and poor consent data lead to irrelevant personalisation.
• Unreliable AI summaries, lead scores and next-best actions then reach sales teams.
• Mullings names three deduplication offerings built on Marketo with Salesforce, Microsoft Dynamics or custom environments, and offers an audit walkthrough to show where the issues sit.

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They object to HubSpot's default opt-in change, which pooled customer enrichment data across its customer base and fed a shared dataset and AI models.

• They draw on earlier marketing operations work at Bank of New York, where Americas, EMEA and APAC data was never visible across regions.
• They also argue that email permission is not the same as tracking permission, and that rules vary by market, so compliance must be operationalised rather than treated as one global checklist.

The HubSpot post describes a hard-bounce signal feeding a shared dataset that competitors could draw from.

• It lists questions for the next contract review: Is our data ever pooled?
• Is it used to train models?
• How many settings govern consent?
• How far in advance would we hear about a change?
• Mullings notes HubSpot reversed the change within days and that Duncan Lennox said the company had made a mistake and committed to transparent opt-in.
• A separate post covers France, Italy, Germany, Austria, Canada, California and wider EMEA requirements for consent, legitimate interest, tracking pixels, retention and evidence of permission.

Mullings calls the HubSpot post a rare negative one, saying their default is to share what is working. The exception makes clear that governance is an issue they will publicly criticise a platform over.

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They describe Adobe Workfront as more than project management: it covers planning, resourcing, approvals, workflows, dashboards, reporting and request queues, alongside Workfront Proof, Workfront Fusion middleware, automated content delivery and AI brand review. They extend that approach to Adobe Experience Manager Assets and GenStudio, and to a Workfront-to-Marketo connection where approval triggers campaign launch.

For a client in the north of England marketing in five languages across Europe, an English content brief clones and translates into five other languages in about three seconds using Workfront and AI translation.

• The AI is trained to match tone, terminology and industry style.
• In the Workfront-Marketo setup, assets, copy and metadata flow into Marketo; nurture emails and landing pages go live; leads are scored and routed to sales; and both teams see which content drives revenue.
• A separate migration post describes moving a financial services client from WebDAM to AEM Assets while preserving asset history, metadata, permissions and version control, with a focus on compliance, audit trails and faster access to approved materials.

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They prioritise integration as a pipeline and reporting advantage, not tool collection, grouping the stack into CRM, BI and analytics, web and events, social and account-based marketing, and collaboration.

The systems named include Salesforce or Microsoft Dynamics for lead and pipeline visibility; Power BI, Tableau and Domo for executive dashboards; ON24, Zoom and personalised websites for journeys; LinkedIn, Oktopost and Demandbase for targeting and lead scoring; and Microsoft Teams, Slack and Adobe Workfront for everyday workflows. The stated outcomes are faster pipeline creation, better customer experiences and measurable business outcomes.

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In the demonstration, a marketing manager, not a developer, built one webinar campaign end to end on screen in about three minutes.

• Mullings uses this to argue that the approach is already used by the ops team, not just tested in a lab.
• The room then focused on red tape, compliance sign-off, risk ownership and the foundations needed before an agent touches a live instance.

The post reports that Shane O., JTF's marketing manager and not a developer, ran the live demonstration.

• Jack McClean and Nicholas Oleshko from Adobe supported the roundtable.
• The discussion focused not on whether agentic AI can work, but on how to adopt it without breaking anything.

Once the demo ends, compliance sign-off and sound instance foundations become the decisive adoption challenges.

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They also present public partner participation as evidence of capability, not just marketing. This is a platform-aligned perspective, not a neutral vendor comparison.

One post lists six criteria leaders should expect from an investment: proven stability and enterprise security; market-leading tools with strong references; AI already delivering value; technology that reduces effort and increases clarity; better customer experiences across touchpoints; and measurable demand generation impact.

• Another reports from Adobe Summit EMEA in London on Marketo with AI and Adobe Brand Visibility for GEO, AEO and AI search.
• A third announces that Mullings reached the final of Adobe's Beat the Buzzer competition in the Customer Engagement category with the JTF Campaign Builder, arguing that scale is not the only measure of capability.

These are partner-facing advocacy posts, not an independent vendor comparison. Ask for independent evidence before using them to compare platforms.

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In a rare critical post, Andy Mullings describes HubSpot's default opt-in change, which pooled customer enrichment data across its customer base and fed a shared dataset and AI models.

• They contrast it with prior marketing operations work at Bank of New York, where Americas, EMEA, and APAC data was never visible across regions; only approved system administrators could operate across the full dataset, and access required formal training and compliance clearance.
• They also flag a deliverability risk: a hard bounce on one list would feed a shared dataset competitors could use.
• HubSpot reversed the change within days, and Duncan Lennox said the company 'made a mistake' and committed to fully transparent opt-in.
• The post closes with contract-review questions: is our data ever pooled, is it used to train models, how many settings govern consent, and how far in advance would we hear about a change?

For brands planning a campaign

For a partnership, this points to a governance-first approach. A B2B marketing automation agency should review data pooling and model training, audit consent settings, and agree clear change-notification terms before scaling campaigns.

Andy Mullings reports a 300% increase in requests to clean and deduplicate data in Marketo Engage.

• The post gives three business reasons: avoiding higher renewal costs, building foundations for AI, and merging multiple databases after acquisitions.
• It names three deduplication solutions: Marketo plus Salesforce, Marketo plus Microsoft Dynamics, and Marketo custom-environment deduplication.
• All are designed to clean, standardise, and protect the database at scale.
• They offer to walk through an audit report showing where the issues are.

For brands planning a campaign

An agency evaluating a partner can start with a data-health audit and deduplication roadmap, making the case around renewal-cost risk and AI readiness.

The post lists three mistakes Andy Mullings has seen AI make because of dirty data.

• First, duplicate records split engagement history, so AI treats an active person as cold or overstates their interest.
• Second, bad job titles, old company names, incorrect lifecycle stages, and poor consent data lead to personalisation based on the wrong context.
• Third, AI summaries, lead scores, and next-best actions become unreliable when the underlying data is incomplete or duplicated.
• Deduplication, they argue, is no longer just data hygiene; it is a foundation for AI performance.

For brands planning a campaign

For AI-driven campaign delivery, a partner should set data-quality gates before deploying models or automation, especially for identity resolution, lifecycle stages, and consent.

The post asks why teams with Adobe Workfront and Marketo are not connecting them.

• In the described setup, content approval triggers campaign launch; assets, copy, and metadata flow into Marketo; nurture emails and landing pages go live instantly; leads are scored and routed to sales within minutes; and both teams can see which content drives revenue.
• The result: no manual uploads, copy and paste, or delays.

For brands planning a campaign

A partnership can start with an approval-to-launch integration map, named handoffs, metadata requirements, and reporting on content-attributed revenue.

Andy Mullings describes helping a major financial services client migrate from WebDAM to Adobe Experience Manager Assets while preserving 100% of asset history, metadata, permissions, and version control.

• The post presents the project as more than a tech migration: it enabled marketing and compliance teams to work with speed, trust, and control.
• Listed benefits include tighter compliance through audit trails and content governance, faster access to approved brand-compliant materials, better collaboration across global teams and partner networks, and scalable content operations for campaigns, client onboarding, and reporting.
• They invite financial services and asset management firms wrestling with content management to talk.

For brands planning a campaign

For agencies targeting regulated B2B clients, this is a concrete example of DAM migration and governance work to anchor a partnership conversation.

The post argues that Marketo's real power lies not only in the campaigns it runs but in how it connects to the rest of the stack.

• It lists CRM sync with Salesforce or Microsoft Dynamics for lead and pipeline visibility; BI and analytics tools such as Power BI, Tableau, and Domo; web and events tools including ON24, Zoom, and personalised websites; social and ABM tools including LinkedIn, Oktopost, and Demandbase; and collaboration tools including Microsoft Teams, Slack, and Adobe Workfront.
• The stated outcomes are faster pipeline creation, better customer experiences, and measurable business outcomes.

For brands planning a campaign

A partner can map the client's stack, prioritise integrations with the clearest pipeline or reporting payoff, and avoid treating Marketo as a standalone platform.

Andy Mullings describes a JTF agentic marketing operations roundtable at Adobe EMEA HQ in London.

• Shane O., JTF's marketing manager and not a developer, ran a live demonstration, building one webinar campaign end to end in three minutes.
• The point, the post says, is that the ops team uses this process every day; it is not a lab experiment run by engineers.
• The room then discussed red tape, compliance sign-off, where risk sits and the foundations needed before any agent touches an instance.
• Jack McClean and Nicholas Oleshko from Adobe supported the roundtable.

For brands planning a campaign

A partnership around agentic AI should cover the unglamorous but decisive parts: compliance sign-off, risk ownership, and instance foundations before agents can act.

Andy Mullings describes helping a client in the North of England that markets in five languages across Europe.

• Using Adobe Workfront and AI translation, English campaign content is cloned and translated into five other languages in three seconds.
• The post says this cuts turnaround from days to seconds without waiting on agencies, creates one process for six languages, maintains a consistent brand voice with AI trained to match tone, terminology and industry style, frees hundreds of hours for higher-value work, and prepares content for email, web, social, blogs and events.
• The approach automates localisation at the point of creation.

For brands planning a campaign

For B2B brands with European or multilingual campaigns, a partner can propose a creation-stage localisation process with brand-voice controls and multilingual campaign operations.

One post reports a 300% rise in requests to clean and deduplicate Marketo Engage databases, driven by renewal cost pressure, the need for sound foundations before AI works properly, and databases merged through acquisitions.

• A companion post names three failure modes when AI runs on dirty data: it misreads intent because duplicate records split engagement history and make an active person look cold; it personalises from stale job titles, old company names or weak consent data; and it gives sales unreliable summaries, lead scores and next-best actions.
• They list three deduplication offerings built around Marketo with Salesforce, Marketo with Microsoft Dynamics, and custom Marketo environments, and offer to walk clients through an audit report showing where the issues sit.

Opens with a counter-intuitive claim ("It isn't AI. It's data."), then moves to a numbered breakdown and a named list of solutions, ending with an audit walkthrough as the next step.

For brands planning a campaign

A brand evaluating Mullings gets a specific, testable position: data cleanup is a prerequisite for AI, not a parallel workstream.

• They also name solution areas to probe.
• This gives marketers a useful starting point for content aimed at marketing operations leaders facing renewal cost pressure, acquisition-driven database sprawl or stalled AI programmes.

Examples: Source 1 · Source 2

One post criticises HubSpot’s move to pool customer enrichment data across its customer base with everyone opted in by default.

• They draw on earlier marketing operations work at Bank of New York, where Americas, EMEA and APAC data was never visible across regions and cross-region access required formal training and compliance approval.
• The post notes that HubSpot reversed the change within days and committed to fully transparent opt-in, then poses contract-review questions: Is data ever pooled?
• Is it used to train models?
• How many settings govern that consent, and how much notice would a change receive?
• A second post covers how email compliance varies by market across France, Italy, Germany, Austria, Canada, California and the wider EMEA region.
• It stresses that permission to send an email does not always include permission to track opens and clicks, and frames the work as turning regulatory requirements into scalable operations.

The HubSpot post is explicitly framed as unusual: Mullings says they usually share what works and calls this the rare negative post.

For brands planning a campaign

Relevant for brands in regulated industries or with international lists. Mullings raises consent-versus-tracking distinctions and data-pooling risk in vendor or contract reviews, making this a fit for governance, privacy and consent-management topics rather than purely demand-generation pitches.

Examples: Source 1 · Source 2

One post breaks Workfront into its parts: core planning, resourcing, approvals, workflows, dashboards, reporting and request queues; Workfront Proof with version control, annotations, audit trails and e-signatures; Workfront Fusion as middleware linking CRM, DAM, marketing automation, CMS, BI and collaboration tools; automated content delivery from request to approval to creation; and AI brand review that scores assets against guidelines before publication.

• A client case describes an English content brief cloning and translating into five other languages in about three seconds, with AI trained to match tone, terminology and industry style.
• The process cuts translation from days to seconds and frees hundreds of hours.
• Another post groups Workfront, AEM Assets and GenStudio around content reuse, speed to market, end-to-end visibility and personalisation, and says the team delivers all five pillars of the content supply chain.
• A fourth shows Workfront connected to Marketo so approved assets, copy and metadata flow in, campaigns launch automatically, and leads are scored and routed.

Posts commonly use a component list or a client outcome with numbers, followed by a concise takeaway for marketing leaders.

For brands planning a campaign

For a brand assessing a Workfront or content-operations partner, the posts show a workflow-level view—proofing, middleware, translation and campaign hand-off—rather than a single-tool pitch. The multilingual translation example and the Workfront-to-Marketo hand-off are concrete starting points for a joint use case.

Examples: Source 1 · Source 2 · Source 3 · Source 4

It names CRM sync with Salesforce or Microsoft Dynamics for lead and pipeline visibility; BI and analytics tools such as Power BI, Tableau and Domo for executive dashboards; web and event platforms including ON24 and Zoom for personalised journeys; social and account-based tools including LinkedIn, Oktopost and Demandbase for aligning targeting with lead scoring; and collaboration tools including Microsoft Teams, Slack and Adobe Workfront for embedding marketing operations in everyday work. The stated result is faster pipeline creation, better customer experiences and measurable business outcomes, with Marketo positioned as the centre of an integrated ecosystem.

For brands planning a campaign

Useful when a brand wants integration-led positioning content. The post provides a map of integration categories Mullings considers, which can anchor a co-marketing piece on connecting marketing automation to CRM, BI and events.

Examples: Source 1

One post argues that investing in Adobe technology in 2026 is among the safest and smartest moves available.

• It covers marketing automation, work management, customer data platform, content supply chain, personalisation and AI, and lists six criteria leaders should expect: proven stability and enterprise security; market-leading tools with strong references; AI already live and delivering value; technology that reduces effort and increases clarity; better customer experiences across touchpoints; and measurable demand generation impact.
• A second post reports from Adobe Summit EMEA in London, highlighting Marketo with AI and the Adobe Brand Visibility tool for generative engine optimisation, answer engine optimisation and AI search.
• It argues that AI, visibility and trusted data are becoming central to how brands are discovered.

This is partner-facing platform advocacy, not an independent comparison. Treat it as the perspective of an Adobe specialist, not a neutral vendor assessment.

For brands planning a campaign

Suitable for an Adobe-aligned campaign, partner event coverage or a thought-leadership piece on AI search visibility. The content favours Adobe, so plan a partner-led brief.

Examples: Source 1 · Source 2

A marketing manager—explicitly not a developer—built a single webinar campaign end to end on screen in about three minutes.

• Mullings uses this detail to argue that agentic AI is a daily workflow, not an engineering experiment.
• The post reports that the room’s discussion moved past whether the technology works to red tape: compliance sign-off, where risk genuinely sits, and the foundations a team must get right before an agent touches a live instance.
• Adobe staff are credited with supporting the session.

For brands planning a campaign

Gives a brand a concrete demonstration format—a live build by a non-developer—and a candid view that governance readiness, not capability, is the sticking point. This is a natural hook for content or events about agentic AI in marketing operations and the controls needed before deployment.

Examples: Source 1

Mullings frames the work as more than a technology project: it enables marketing and compliance teams to operate with speed, trust and control.

• The stated benefits for asset managers and financial services firms are tighter compliance through audit trails and content governance, faster access to approved brand-compliant materials, better collaboration across global teams and partner networks, and scalable content operations for campaigns, client onboarding and reporting.
• The post invites financial services and asset management contacts with content management problems to get in touch.

For brands planning a campaign

Demonstrates a regulated-industry migration story a brand can evaluate, with compliance and governance—not cost—as the headline benefit. Useful evidence for briefs involving financial services, digital asset management or content governance.

Examples: Source 1

One announces reaching the final of Adobe's Beat the Buzzer competition in the Customer Engagement category with the JTF Campaign Builder solution.

• It notes that competitors included much larger systems integrators and professional services firms, and argues that scale is not the only measure of capability.
• Another covers Adobe Summit EMEA in London and the value of the community and Adobe's technology evolution.
• A third describes a London roundtable supported by Adobe staff.

For brands planning a campaign

Signals an active partner-community presence and willingness to appear at Adobe events and competitions, supporting co-marketing around launches, awards and event-based content. The Beat the Buzzer final is a specific credential brands can reference when assessing partner visibility.

Examples: Source 1 · Source 2 · Source 3

The posts describe the work and team but do not state a job title; ask for their exact role.

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They draw on that experience to explain why region-separated data architecture — with Americas, EMEA and APAC data never visible across regions — is the standard they use to judge vendor data policy. The post describes it as a past role.

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The posts document joint work across Adobe's stack: Marketo Engage campaign and data projects, Workfront planning, proofing and Fusion integration, AEM Assets migration, GenStudio content supply chain, and Workfront-to-Marketo campaign launch automation.

• Adobe staff supported a JTF roundtable at Adobe EMEA HQ in London, and a JTF solution reached the final of Adobe's Beat the Buzzer partner competition.
• Confirm whether the relationship includes paid sponsorship or a client contract.

Original disclosure

As a specialist B2B Adobe partner, our strength is the depth of our expertise, our understanding of B2B marketing, our ability to drive performance for customers, and our ability to solve complex challenges with Adobe technology.

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Ask how Mullings or JTF relates to Bluprintx.

Original disclosure

At Bluprintx, we're one of the few partners delivering all five pillars of the content supply chain.

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The post says HubSpot reversed the change within days.

View example

Both treat Marketo plumbing — API changes, list limits and sync failures — as the practical core of the job.

Rizzo covers the MOps and RevOps field as a weekly news-and-analysis voice, including Salesforce, HubSpot and EU AI Act developments, and writes about who should own the system. Mullings writes as an Adobe partner about delivery inside Adobe products and makes the case for Adobe directly.

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Hove's analytical, process-oriented and collaborative habits sit close to Mullings's insistence on foundations before AI or automation can be trusted.

Hove's posts are practitioner- and career-facing: a notes series on the habits that make a good operations professional, and a recommendation for a recruiting contact who places marketing ops and automation roles.

• Mullings writes about implementing and governing specific Adobe platforms for clients.
• Their posts date from a different period, so the comparison is about subject and format rather than matched currency.

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Both prefer a concrete story that ends in a fix over an abstract best-practice list.

Abiose A. writes for creators, freelancers and small e-commerce brands about welcome emails, lead magnets and scarcity tactics, focusing on basic follow-through. Mullings writes for enterprise marketing and operations teams working inside Adobe Marketo Engage, Workfront and AEM Assets, on data architecture and governance rather than list-building courtesy.

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One post argues for a named owner with decision rights and proposes asking the CMO and CRO separately who owns the stack.

• Another connects AI interfaces to the importance of permissions, business rules, data governance and CRM/marketing-automation structures.
• Those ideas could sharpen the leadership and governance angle of a joint campaign.

The posts do not demonstrate Marketo database-cleanup services, a deduplication method or a delivery example comparable to Mullings’s stated Marketo work.

• Rizzo could contribute thought leadership on the ownership question, but the posts do not establish a fit for co-delivering the technical audit.
• Before considering Rizzo as an alternative, ask for confirmation of identity and relevant delivery experience.

Examples: Source 1 · Source 2

One post lays out analytical, process-oriented and collaborative approaches, including using data to find process improvements and guiding a team without direct reports. That could support a people-and-process perspective alongside a technical data-quality campaign.

The two posts do not show Marketo data governance, AI-readiness work or a technical campaign-delivery example.

• One is a general marketing-operations advice post; the other recommends a recruiter for marketing-operations and marketing-automation roles.
• Together, they support a practitioner perspective, not co-delivery of the proposed technical engagement.
• Before selecting Hove, ask for confirmation of identity and relevant project experience.

Examples: Source 1 · Source 2

The posts explain those customer-facing automation scenarios in practical terms and could add a useful email-journey component to a broader partnership campaign.

The examples concern email welcome flows and ecommerce waitlists, not Marketo database cleanup, data governance or AI readiness.

• They support a narrower lifecycle-marketing contribution, not the proposed technical audit or its data-quality point of view.
• Before considering Abiose for the full partnership, ask for confirmation of identity and relevant Marketo project experience.

Examples: Source 1 · Source 2