Best of LinkedIn: MarTech Insights CW 24/ 25

MarTech is moving from tool accumulation toward governed, data-native execution layers. The strongest signals are Databricks CustomerLake, Snowflake and Hightouch activation models, Salesforce and Adobe platform moves, and AI workflows that depend on clean data, clear ownership and measurable outcomes. The market narrative is shifting from buying more software to designing better architecture, orchestration and operating models.

Date

June 26, 2026

MarTech Insights

Thomas Allgeyer

Methodology: Every two weeks we collect most relevant posts on LinkedIn for selected topics and create an overall summary only based on these posts. If you´re interested in the single posts behind, you can find them here: https://linktr.ee/thomasallgeyer. Have a great read!

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If you prefer listening, check out our podcast summarizing the most relevant insights from MarTech Insights CW 24/ 25:

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Data Layer and CDP Architecture

Databricks CustomerLake shifted the CDP debate toward lakehouse-native customer activation
Snowflake and Databricks were positioned as stronger data foundations, not Salesforce or HubSpot replacements
CDPs were reframed as orchestration capabilities rather than only standalone customer databases
Databricks CustomerLake was described as making the data platform behave like the marketing platform
Warehouses still need operational context layers for real-time activation and customer action
Salesforce, Informatica, Snowflake and Databricks were linked to a more headless customer data layer

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Identity and Activation

Acxiom Real ID became natively available in Databricks CustomerLake for identity resolution
Iterable appeared as a Databricks CustomerLake launch partner for data-to-campaign activation
Hightouch’s reported 1.2 billion dollar offer for LiveRamp ID assets signaled intensifying identity competition
Hightouch and Snowflake enabled Salomon marketing teams to build self-service audience activation
First-party data activation was positioned closer to the platforms where customer data already lives
Identity, activation and data ownership emerged as connected battlegrounds across the MarTech stack

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Agentic Marketing and AI Workflows

Agentic marketing was framed as an open B2B category while sales AI receives more attention
Adobe Experience Cloud was positioned as an AI workforce rather than a passive login environment
MCP Studio showed AI agents connecting workflows across multiple MarTech systems
The unofficial Marketo MCP showed how Marketing Ops can enter agentic workflows
Hightouch’s agent harness was described as helping marketers prioritise ranked customer opportunities
SignalLoom InvoiceOps demonstrated human-gated AI automation for invoice review and approval

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Marketing Operations and RevOps

Clay was positioned as a Marketing Ops enrichment layer before lead scoring and routing
RevOps hiring was challenged unless the specific revenue problem is clearly defined first
Real RevOps was described as owning end-to-end revenue movement, risk visibility and execution gaps
CRM cleanup advice focused on marking unused fields as “OLD DO NOT USE” before deletion
HubSpot custom objects were challenged when standard objects and properties can handle the use case
Marketing Ops hiring was linked to clarity, alignment and leadership skills, not only platform experience

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Marketing Automation Platforms

Marketo AI was positioned as a shift from manual clicking to intelligent operational orchestration
Marketo Validate Programs introduced AI-based QA against rules, test plans and campaign briefs
Adobe Marketo Engage received a new UI after a long-awaited interface update
Marketing Cloud Next Summer 26 added AMPscript and Marketing Objects for dynamic personalisation
A new lean marketing automation platform was described as being built solo with AI support
MAP selection was framed around business value and fit, not premium price or feature volume

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Personalisation and Measurement

1:1 personalisation was defined across offer, channel, timing and message, not only wording
Customer Brain was separated from personalisation as a decisioning and learning capability
Customer intelligence was positioned as the next ESP battleground beyond campaign execution
CRM performance measurement was pushed from attribution toward causality and incrementality
Less attributable marketing was used to argue for renewed focus on customer value
AI decisioning was linked to next-best-action orchestration across customer journeys

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Governance, Security and Data Quality

EU-based AI tools were recommended where marketing data sensitivity and validation matter
Public AI tools were challenged for sensitive marketing data and uncontrolled answer generation
AI-generated fraud and fake leads were highlighted as risks for MarTech data quality
Snowflake’s Modern Marketing Data Stack report emphasized governance, collaboration and AI readiness
A neutral governance layer was proposed above Snowflake, Databricks and enterprise applications
AI scaling was tied to clean data, ownership, governance, workflow integration and change management

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Data + AI Summit 2026

Databricks CustomerLake positioned the lakehouse as a customer activation and agentic CDP layer
CustomerLake reframed MarTech architecture around governed customer data, identity, decisioning and activation
Profile Agents and Campaign Agents pointed toward self-service customer intelligence for marketing teams
Acxiom, Iterable and Slalom partnerships strengthened the bridge between identity resolution and campaign execution
Genie, Agent Bricks, Lakebase, Lakewatch, Omnigent and Unity AI Gateway reinforced the enterprise AI platform narrative
The main MarTech implication was clear: activation is moving closer to governed data platforms

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