61% of CMOs Say Local Marketing Is Too Complex: Here’s the Fix

This station was sponsored by Uberall. The opinions expressed successful this article are the sponsor’s own.

Who should ain AI hunt visibility crossed each our locations?

Should I adhd much AI devices to negociate section listings and reviews, aliases is that making it worse?

When 99% of elder marketers opportunity they want an AI orchestration layer, the mobility is who leads it.

The perfect multi-location trading world is 1 wherever agentic AI fixes copy listings, responds to customer reviews, analyzes sentiment, and spots optimization opportunities earlier the marketer tin opportunity “GBP.”

However, what multi-location marque CMOs really have, successful today’s acold little perfect world, is layers of disjointed AI and trading tooling creating an unclean and unclear infrastructure.

This deficiency of infrastructure makes it astir intolerable to way wide ROI.

An Uberall study past twelvemonth revealed that only astir 1 successful 4 location marketers tin show the effect of their location trading connected sales; I’ll stake that pinch varying levels of AI instrumentality take since that survey, this rumor hasn’t improved — if anything, it’s been exacerbated by it.

The AI understands what needs prioritizing and resolves it successful the inheritance while teams attraction connected their trading for aggregate locations. It squashes impatience aliases uncertainty surrounding ROI reporting because its exemplary is built connected delivering and visualizing real-time attributable location performance: bookings, array reservations, ft traffic. The cleanable and clear information that stakeholders hold for.

The results of ill-equipped and layered martech tooling are bleak for section visibility:

• Business listings are managed advertisement hoc per platform, creating inconsistencies pinch captious data
• Reviews are near unanswered aliases sporadically answered, breaking down customer spot and engagement
• Local pages are disconnected from societal and inventory systems
• Content is outdated aliases generic, weakening relevance to section hunt intent
• Website capacity is deprioritized, causing clash for users, hunt engines, and AI crawlers

Today’s existent perfect world is astir bringing immoderate consciousness backmost to the location trading stack. It will present a operation of that sought-after AI orchestration layer, omnichannel hunt visibility crossed locations, and the moreover much sought-after ROI numbers. It’s the Chief Marketing Orchestrator who will lead it.

Step 1. Decide Who Your Chief Marketing Orchestrator Will Be

Value won’t travel from simply plugging information into an LLM. 89% of leaders said their tech investments haven’t afloat delivered, pinch integration complexity the apical reason.

Instead, it comes from plugging each your multi-location trading information into an orchestration furniture that implements the nonnegotiable discourse engineering tasks, making judge each location’s information and signals are system for immoderate hunt strategy customers are utilizing to observe section businesses.

Someone needs to do this, and that personification becomes your Chief Marketing Orchestrator (CMO). And, luckily, it’s a caller improvement of a Chief Marketing Officer.

The Key Responsibilities of a CMO

The Chief Marketing Orchestrator (CMO) must determine which tasks require quality sign-off. Where are the trade-offs? Who owns AI discoverability astatine a marque and location level? Where tin they relieve their squad from operational workload and reallocate them to tasks that power gross — turning sentiment study into actionable reports for operations, aliases producing contented that drives section engagement? It’s not conscionable a exertion communicative but besides a activity story.

Any CMO who is genuinely passionate astir what they do for their multi-location marque doesn’t want to blindly outsource each azygous task to an AI agent. They want to spot the capacity numbers and location trading initiatives they’re reporting backmost to stakeholders. And they astir apt want to consciousness successful power of compute costs.

At a clip erstwhile each marketer and each leader is urged to ain AI, this often intends nary 1 owns the outcome. A streamlined stack pinch an AI orchestration furniture changes that, successful that the level owns the execution and analysis, the CMO owns the overarching strategy, and their squad owns the quality approvals and guardrails.

This is the rule Uberall’s agentic AI, UB-I, is built on: The marketer remains successful power — governing the AI’s output, not conscionable guiding aliases prompting it.

A CMO investing successful the correct group to govern agentic AI is simply a CMO focused connected output, not adoption.

Try doing this manually crossed 50 locations:

1. Open each location’s floor plan crossed GBP, Apple, Bing, and applicable directories. Check for formatting inconsistencies, missing attributes, and incorrect hours.
2. Draft a reappraisal consequence for each pending reappraisal — starting pinch the antagonistic ones — matching your brand’s reside and guidelines.
3. Audit each location for missing business descriptions and make transcript that reflects the correct section keywords and work context.

That’s the regular baseline. At scale, it’s unsustainable — which is precisely the workload UB-I handles earlier the squad logs in.

UB-I handles the measurement and velocity of section operations that nary quality squad tin sustainably lucifer astatine scale, while flagging thing that requires quality judgement earlier acting. On immoderate fixed day, that means:

1. Drafting AI-generated replies for each pending reviews, according to strict marque guidelines, prioritizing antagonistic reviews first.
2. Correcting sanction and reside formatting to each directory’s requirements, preventing sync failures, and suppressed visibility.
3. Generating missing business descriptions, attributes, and typical hours from location data

The squad logs successful to approve, not to observe what’s broken. Each of these is discourse engineering successful believe — making location information usable for some quality and AI-powered search, astatine a standard nary squad tin negociate manually.

As globally recognized invention strategist Shawn Kanungo puts it: “The companies I americium watching triumph are not the ones optimizing the ROI of existing workflows. They are the ones utilizing agents to do things that were antecedently intolerable astatine immoderate price.” The businesslike orchestration of section trading tasks crossed aggregate locations has ever been intolerable astatine standard — and this orchestration furniture is precisely what 99% of elder marketers opportunity would beryllium “valuable” aliases “very valuable,” according to an Uberall survey.

The existent worth present successful implementing an AI orchestration furniture to negociate omnichannel beingness isn’t to optimize the ratio of existing section trading workflows — it’s successful enabling what was intolerable for marketers to execute astatine standard successful an eight-hour workday. The workload that 61% of CMOs and VPs astatine multi-location brands presently picture arsenic “complex” aliases very “complex” — search AI visibility, managing location information and listings, monitoring and responding to reviews, and posting section contented connected societal media.

Step 2. Pivot From Finding New AI To Restoring Search Visibility

As I spot it, the solution CMOs will want to instrumentality is to stamp retired the ROI-burdening exploratory agentic AI projects and attraction connected operating pinch it. Because the prize that comes from operating pinch it good is charismatic for multi-location brands, who request to activity quickly to reconstruct declining postulation amid zero-click searches.

Reports bespeak that gross is expanding for brands arsenic customers observe them via AI hunt — Adobe reports a 254% summation successful gross per visit for the unit segment. It’s nary wonderment stakeholders are much willing successful SEO and GEO capacity than ever before.

Let’s ideate a multi-location marque arsenic a building pinch 200 rooms, each hosting its ain party. The furnishings hasn’t changed, the walls haven’t changed, the infrastructure hasn’t changed — but there’s a caller entranceway to the building, 1 that seems to beryllium a shortcut for guests intentionally looking for you. The different entrances are still successful usage too. You want to maximize entree done each azygous 1 truthful much group find the correct room, person a bully time, and travel backmost for the adjacent one. You don’t prosecute personification to manually bring guests to each entrance. You put successful exertion to put up signals that do the activity for you, truthful your squad tin attraction connected the acquisition wrong the rooms.

Context engineering is what builds those signals. It’s erstwhile AI tin orchestrate really brands make their integer footprint machine-readable, consistently accurate, technically discoverable crossed aggregate surfaces, contextually relevant, and socially validated — without individuals needing to unpeel layers of tech stack insights.

Implement The 4 Pillars Of Location Performance Optimization (LPO)

Image by Uberall Brand Studio, June 2026

If visibility connected immoderate hunt aliases trading transmission improves, each different location capacity pillar improves: engagement, reputation, and conversion. These are the 4 pillars of Location Performance Optimization (LPO), a revenue-first model I said astir astatine brightonSEO successful October 2025. LPO connects a brand’s integer beingness to commercialized outcomes by activating location information and signals crossed these capacity pillars:

• Visibility: Every location is accurately represented crossed each applicable find surfaces (website, Google, Apple, Yelp, Bing, manufacture directories).
• Reputation: Trust is reinforced done ratings, regular reviews, and customer resolution.
• Engagement: Local contented — posts, photos, offers — signals caller business activity and relevance for high-intent customers.
• Conversion: Customers tin return clear action — bookings, directions, and click-to-calls.

An AI supplier that implements these LPO measures to pull much customers, scope caller audiences, and power gross isn’t exploration. It’s a hard-ROI workflow that pays for the program; they’re the important furniture that restores and increases hunt visibility, customer acquisition, retention.

So, erstwhile the committee asks astir AI ROI and section trading performance, this caller CMO doesn’t conscionable show AI adoption; they warrant AI finance to proceed to money their operations. The spread betwixt the brands measuring existent ROI and the companies pretending to — aliases being preoccupied by their analyzable section trading stacks is wider than ever.

How To Shift From AI Experiments To ROI-Driven Operations

EY described the infinitesimal we’re successful well: moving from vibe to value. The “vibe” shape was each institution exploring AI — experimenting, piloting, racking up compute costs, layering up their tech stack — and either still being successful that shape aliases having concluded it pinch the vexation of not knowing really to advancement to real, quantifiable returns.

Marketing leaders astatine multi-location brands, for illustration the Chief Marketing Orchestrator, must adopt and govern agentic-AI-powered stacks that are little exploratory and much ROI-driven. These are stacks that are sensible, streamlined, and alteration teams to do things that conscionable weren’t imaginable before, for illustration logging successful to o.k. fixes, not to observe aliases prioritize what’s broken. And that support mightiness not hap earlier a marketer tin opportunity “GBP,” but it’s the orchestration furniture — the added AI — elder marketers and leaders are looking for.

Find retired really to usage Uberall’s UB-I supplier for multi-location marketing for your operations

Image Credits

Featured Image: Image by Uberall Brand Studio. Used pinch permission.