Here’s the truth - by 2030, Ad Ops will no longer be a back-end execution function. It will be the intelligence layer responsible for customer-level personalisation and revenue growth for modern media companies. Platforms like Salesforce will be leading this shift by unifying measurement, identity, campaign data, and personalisation capabilities into one scalable MediaOps framework. But this transition towards intelligence-driven Ad Ops will not be without obstacles. After all, most media organisations are still operating on legacy stacks that are stalling transformation before it even begins.
The Legacy Ad Tech Burden: Why Old Tools Fail Modern Marketing?
Today, many media organisations are working with fragmented, legacy systems that were never designed for real-time decisioning or customer-level insight. These systems were built for a world of siloed channels and manual workflows.
But the dynamic media environment of today, predominantly consisting of programmatic OOH advertising, requires unified data and a single view of Ad Ops. This is something legacy systems simply can’t deliver. Teams are left juggling disconnected tools and slow turnaround times. Apart from this, there are two other main issues with legacy systems that are preventing the modernisation of your media stack:
Multi-Touch Attribution
With customer journeys now spanning dozens of touchpoints, last-click models offer a dangerously incomplete view of performance. But most existing stacks weren’t architected for multi-touch attribution or real-time incrementality modelling. As a result, marketers can’t accurately measure influence and struggle to justify spend in an increasingly accountable ecosystem.
Cookieless World
With third-party cookies disappearing and privacy regulations tightening, media companies are forced to shift to first-party data strategies. There is also the need to embrace contextual intelligence and consent-driven personalisation. Legacy stacks aren’t built for this new world. They lack durable IDs, clean rooms, and advanced modelling. This leaves teams exposed and unable to future-proof their Ad Ops.
Before you map your automation strategy, don’t miss this guide: What Every Media Business Owner Should Know Before Investing in Automation.
Ad Ops 2030: What Best-in-Class Media Operations Will Look Like?
In 2030, best-in-class media operations will revolve around using advanced AI and automation for hyper-personalisation. The operations will be executed within a consolidated and transparent ad tech ecosystem. Here are some key characteristics of media operations in 2030:
Planning to invest in automation? Check out this guide first - What We Wish Every Media Business Owner Knew Before Investing in Automation?
Salesforce as the Foundation for Your Modern Media Stack
Salesforce is not just a CRM. It will become the foundation for shaping Ad Ops 2030. As media teams move into a cookieless, AI-driven decade, Salesforce provides the unified, future-ready backbone legacy ad-tech stacks can’t deliver. Instead of scattered tools and siloed reporting, it will centralise identity and personalisation into a single source of truth. With real-time intelligence and built-in AI, Salesforce will act as your business’s operating system that powers modern Ad Ops.
Where legacy ad-tech platforms optimise media in isolation, Salesforce looks at the entire customer lifecycle. By integrating sales, marketing, service, commerce, and ad operations, it provides end-to-end visibility and eliminates the data silos that slow decision-making and limit performance.
At the core of this ecosystem, Salesforce Data 360 unifies customer data from CRM, web, media, and offline sources into actionable, real-time profiles, enabling stronger attribution, smarter audience building, and more accurate measurement than traditional DSPs or analytics tools. Layered on top, Einstein AI brings predictive intelligence that automates bidding, audience expansion, personalisation, and next-best-action decisions so every campaign gets smarter with time and reduces manual busywork. And rounding out th
n management platform. This eliminated manual data transfers, enabled real-time inventory visibility, and allowed campaigns to be managed entirely within Salesforce, resulting in a 40% boost in operational efficiency and a future-ready stack designed for the next era of digital OOH.
Read the full i-media case study.
Ad Ops 2030 Readiness Checklist
Before you can modernise for 2030, you need to know exactly where your Ad Ops stands today. This checklist helps you assess your stack, your data maturity, and your readiness for AI-driven personalisation.
Key Questions to Assess Your Current Stack
- Do we have a single source of truth for audience, campaign, and revenue data?
- Are our media, CRM, and analytics systems integrated or are we still exporting spreadsheets?
- Can we personalise campaigns in real time across channels (not just batch updates)?
- Is our attribution model modern (multi-touch, incrementality) or stuck on last-click?
- Are optimisation decisions still manual, or do we leverage predictive/automated tools?
- Can our teams access cross-channel performance insights without engineering support?
- Do we have a unified view of the customer lifecycle across sales, marketing, and Ad Ops?
Metrics & Benchmarks to Measure Readiness
- Data freshness: Are we operating on real-time or near-real-time data (sub 5 mins)?
- Audience match rates: Are platform match rates consistently above 60–70%?
- Automation coverage: What % of campaign tasks (bidding, pacing, QA, reporting) are automated?
- Attribution accuracy: Do we measure incremental impact across channels?
- Time-to-launch: How long does it take to go from brief → live campaign (target: <24 hours)?
- Operational efficiency: Are we reducing manual tasks year over year by at least 20–30%?
- Personalisation depth: How many segments/journeys run on dynamic, behaviour-driven logic?
Quick Wins & Long-Term Priorities
Quick Wins (0–90 days)
- Connect CRM and media platforms to unify audience activation
- Automate basic reporting and QA workflows
- Introduce standardised naming conventions and taxonomies
- Enable real-time behavioural triggers for high-value segments
Long-Term Priorities (6–24 months)
- Build a unified data layer with identity resolution and persistent customer profiles
- Move from rules-based to predictive, AI-driven personalisation
- Implement full-funnel, multi-touch attribution
- Consolidate legacy ad-tech tools into a single, integrated media stack
- Scale cross-channel optimisation with AI-driven bidding and journey orchestration
The Brysa Approach: Modernising Media Stacks for Performance
At Brysa, we help media businesses shift from fragmented, outdated ad-tech setups to modern, Salesforce-powered media stacks built for precision and scale. Our methodology ensures every transformation is structured, measurable, and aligned to your commercial goals. Here’s how we modernise media stacks for performance:
Phase 1: Discovery & Audit: Understanding Your Current Technology and Processes
We start by mapping your full media operations ecosystem, including tools, workflows, data flows, bottlenecks, attribution gaps, and personalisation limitations. This gives us a clear baseline of what’s working and where you’re losing performance due to fragmentation or manual work.
Phase 2: Architecture Design: Building Your Salesforce-Powered Media Stack
Using these insights, we design a unified architecture anchored in Salesforce Data 360 Marketing Cloud and Einstein AI. The goal is to create a single, connected system where customer data, media activation, measurement, and optimisation operate seamlessly.
Phase 3: Implementation: Connecting Data, Tools, and Teams Seamlessly
Through our implementation services, we integrate your CRM, web analytics, ad platforms, and media tools into Salesforce to create one operational engine. We automate data syncs, eliminate manual workflows, connect campaign planning to activation tools, and give teams real-time visibility across channels.
Phase 4: Optimisation: Continuous Improvement with AI-Driven Insights
Once live, we shift to continuous optimisation using AI-led recommendations and real-time performance data to refine targeting, improve attribution accuracy, and unlock new revenue opportunities. Your media stack becomes smarter, faster, and more efficient with every cycle.
Want to know what a Salesforce-powered future would look like for your business? Let’s talk.