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Customer decisions are increasingly made in the moment, but many brands still rely on fragmented signals, disconnected identities and data that arrives too late to influence the outcome.

In this episode of The First Mile, Dom Burch speaks with Mike Danley, Vice President of Solution Consulting and Strategy at Acxiom, about how customer data has evolved from batch files and offline databases to real-time, cloud-native infrastructure.

Drawing on more than 23 years at Acxiom, Mike explains why first-party data has become one of a brand’s most important assets, why establishing an identity is easier than maintaining it, and why businesses need greater control over the signals generated across their websites and apps.

They also explore how AI agents are changing customer discovery and commerce, why the marketing technology landscape may be heading for consolidation, and how Acxiom and MetaRouter work together to help brands create “winnable moments” while customer intent is still live.

In this episode

• How Acxiom has evolved from direct mail and batch processing to cloud-native, real-time customer intelligence
• Why brands are taking greater ownership of their first-party data and identity infrastructure
• The risks created by fragmented tags, duplicated data and unnecessary data movement
• Why real-time customer context is now a commercial priority, not simply a technical consideration
• How Acxiom and MetaRouter combine behavioural signals with identity and people intelligence
• Why building an identity is relatively easy, but keeping it accurate and actionable is much harder
• How AI agents could reshape customer acquisition, discovery and transactions
• Why more marketing applications may collapse into the underlying data and intelligence layer
• What it takes to create winnable customer moments at the speed of now

About Mike Danley

Mike Danley is Vice President of Solution Consulting and Strategy at Acxiom. During more than two decades with the company, he has worked across architecture, product, client services, delivery and sales strategy, giving him a broad perspective on how enterprise customer data has changed and where the market is heading next.

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Modern data collaboration promises to help organisations work together without repeatedly copying, moving or exposing sensitive information. But while the technology has advanced quickly, trust, commercial incentives and internal processes have not always kept pace.

In Episode 6 of The First Mile, Dom Burch speaks with Adrian Bolosan, Head of ISV GTM Strategy for Enterprise and Emerging Business in the Americas at Databricks.

Adrian explains how Databricks is expanding its focus beyond the core platform to the wider ecosystem of data providers, connected technologies and software companies building on Databricks. The ambition is to make “Databricks plus partner” a force multiplier for customers, helping them solve specific business problems without assembling everything themselves.

The conversation explores how OpenSharing and clean rooms allow organisations to collaborate without surrendering control of their underlying data. Adrian shares examples from identity resolution, supply-chain data and retail media, including one retailer and CPG collaboration that took almost a year to complete. The technology worked, but lengthy approvals, misaligned incentives and excessive aggregation left the resulting insights too diluted to be useful.

Dom and Adrian also discuss the less glamorous middle of data collaboration: legal agreements, procurement, security reviews, data engineering and seller incentives. In many cases, the biggest obstacle is no longer technical. It is persuading people and commercial models to move away from established ways of working.

The final part of the episode turns to AI. Adrian argues that organisations cannot jump straight to sophisticated agents without first addressing the quality, identity, consent and governance of their underlying data. They also discuss real agentic media-buying pilots between publishers and agency holding companies, where agents are already buying media, receiving signals and deciding what to do next.

In this episode

• What data collaboration means in practical terms
• Why zero-copy sharing is replacing legacy files, APIs and duplicated pipelines
• How clean rooms support identity resolution without exposing raw customer data
• Why a technically successful retail-media collaboration still failed to create value
• Where Databricks chooses to build and where it relies on specialist partners
• What Databricks looks for in a Built-On partner
• How commercial incentives can slow adoption of better technology
• Whether clean rooms reduce costs or create another cost centre
• Why AI adoption depends on reliable and governed source data
• How MCP servers are connecting agents to external data and tools
• What is already happening in agentic media buying
• How businesses should identify the right place to begin

Chapters

00:00 Introduction
02:01 Adrian’s expanded role and the Databricks partner ecosystem
03:16 What has changed in data collaboration
04:47 Identity resolution and zero-copy sharing
06:37 A retail-media collaboration that underdelivered
09:28 Why trust still comes first
10:09 Where Databricks stops building and partners begin
12:35 The Partner Well-Architected Framework
15:44 Legal, procurement and the boring middle
18:22 Who pays for data collaboration?
20:21 Why poor data undermines AI
23:13 MCP adoption and AI-ready data
24:03 Agentic media buying across company boundaries
26:18 Governing what agents can access and do
27:50 Adrian’s advice for getting started

About Adrian Bolosan

Adrian Bolosan leads ISV go-to-market strategy for Databricks’ Enterprise and Emerging Business across the Americas. His work spans data collaboration, partner adoption and the ecosystem of specialist companies that connect to or build their products on Databricks.

Before taking on his expanded role, Adrian helped develop Databricks’ go-to-market approach around data collaboration, including OpenSharing and clean rooms.

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AI doesn’t start with algorithms. It starts with data flow.

In this episode of the First-Mile Podcast, we sit down with Patrick Harrington, Head of AI & Machine Learning at MetaRouter, to cut through the noise and talk about where real AI capability is actually being built.

Patrick explains why most AI systems today still operate like archaeology—analyzing the past instead of shaping outcomes in the moment—and why the real breakthrough happens in the first mile, where data is created, identity is resolved, and intent is revealed in real time.

We explore what it means to hold a privileged position in the data flow, why bot detection is fundamentally a data quality and behavior problem, and how AI becomes powerful only when learning compounds across use cases—not when it’s treated as a feature.

If you’re tired of AI hype and want a grounded conversation about real-time intelligence, server-side infrastructure, and how AI actually drives commercial outcomes, this episode is for yo