By Ribeye VP of Product & Engineering Martin Lasarga
Local media sellers are working harder than ever. As local TV revenue fragments across channels and competition for advertising dollars intensifies, many organizations no longer have the staffing models that once supported dedicated planners, traffickers, analysts, and account managers. The work still needs to get done. Increasingly, all of it falls to the seller.
If local media sellers do five jobs at once, national advertising tools were built for workflows where five different people each do one of them. This mismatch is one of the biggest drags on the economics of local digital advertising. It’s also why many local sellers spend more time on operational overhead than on the advertiser conversations that drive renewals.
Local-first design addresses this by building the tool around the seller as the primary use. And now, AI is making this design principle executable at scale.
Why national tools fail local sellers
In a national agency workflow, a planner builds the media plan, a trafficker handles activation, an ops analyst monitors performance, a reporting specialist assembles the deliverable, and account management owns the client. Because of this, the tools that platforms like national DSPs ship are designed for that division of labor.
In local media, one person does all five jobs, often across 40 active accounts. The seller who took the discovery call is building the plan, activating the campaign, monitoring pacing, pulling the report, and walking the advertiser through results. The workflow is the same, but the economics are fundamentally different.
Still, national tools impose roughly the same overhead per campaign, regardless of budget size. On a $500,000 buy, that overhead is acceptable. The campaign is large enough to justify the time, and specialists handle each piece anyway.
Consider a $5,000 monthly buy for a local HVAC company. A seller can’t spend three hours building the plan, two hours activating it, and four hours assembling the report while managing dozens of similar accounts. As a result, sellers build simpler plans, activate fewer channels, and report on what’s easiest rather than what’s most useful. Campaign quality suffers in ways that don’t show up until renewal.
Local sellers are expected to manage more accounts, more channels, and higher advertiser expectations than ever before. The right tools should help new sellers operate with confidence from day one while allowing experienced sellers to spend more time on strategy and less on administration.
What local-first design actually means — and where AI fits in
Local-first design fixes this by building the tool around the seller as the primary user. This enables sellers to become sophisticated operators by empowering them with a technological companion.
From prospecting and media planning to activation, optimization, and renewals, the platform should proactively guide the seller while keeping them in control. That’s where AI comes in, providing leverage that makes one seller operate at the sophistication level a national agency deploys a team for.
A planning layer that compresses two hours of assembly into 90 seconds means the seller can present a thoughtful plan in a $5K conversation. An activation workflow that handles cross-channel setup without specialist intervention means the seller can launch the campaign they actually planned. A reporting layer that assembles the advertiser story automatically means the seller spends the meeting having the conversation instead of preparing for it.
AI makes this design scalable by creating a proactive system that surfaces opportunities, recommends actions, identifies optimization paths, supports upsells, and helps drive renewals throughout the account lifecycle. The system should guide and assist while always keeping the human in the loop and the final decision with the seller.
Why this matters for local media
Local media organizations are competing for SMB digital spend against national platforms selling directly to those same businesses. Yet many of the tools available to local media were designed for workflows with specialized teams handling planning, activation, optimization, reporting, and client management separately.
Local sellers manage those responsibilities simultaneously, often across dozens of accounts.
As AI becomes more deeply embedded into advertising, better information, faster execution, and connected workflows can give sellers more time to focus on the relationships and market knowledge that have always been at the center of local advertising.
