№ 001Internal
Global Client Opportunity Agent
Finds white-space across the holding-company client base — retail media, loyalty, commerce, CRM, content, shopper, media, analytics — and routes opportunity briefs to the right practice.
A working catalogue of 120 trustworthy agentic services for ad holding companies, creative networks, media agencies, commerce shops, CRM practices, and shopper teams. Not 120 chatbots. Not 120 productivity hacks. 120 named services with visible intent, evidence, autonomy boundaries, escalation paths, memory policies, and audit trails — the trust layer that turns AI from a demo into something a global FMCG or retail client will actually sign off on.
Agents the holding groups build for themselves — to improve margin, speed, and cross-agency collaboration. The internal substrate that makes everything below it possible.
Finds white-space across the holding-company client base — retail media, loyalty, commerce, CRM, content, shopper, media, analytics — and routes opportunity briefs to the right practice.
Detects category and client conflicts across agencies before pitches, staffing, or data-sharing decisions create reputational damage.
Matches briefs to the best strategists, creatives, data scientists, retail media experts, commerce leads, and local-market specialists — wherever they sit in the group.
Searches prior decks, case studies, benchmarks, category insights, and proof points to arm new-business teams without reinventing every artefact from scratch.
A living map of what every agency, studio, practice, and market office can actually deliver — not what the slide says they deliver.
Converts campaign results into reusable, client-safe case studies with anonymisation and automated claim-checking against measurable evidence.
Monitors email sentiment, meeting notes, delivery quality, spend trends, scope creep, and relationship risks. Surfaces a churn warning weeks before the client quietly starts pitching.
Flags when client requests exceed retainer, SOW, media fee, production scope, or strategic advisory allocation — with the receipts to back the conversation.
Reviews staffing plans, production costs, pitch costs, freelance usage, and profitability leakage against historical norms and forecasted P&L.
Connects people, clients, sectors, tools, data sources, campaign results, and reusable IP into a queryable graph the whole group can actually use.
For growth, RFPs, category entry, and competitive positioning. The most expensive part of agency life — and the one most starved of structured intelligence.
Scores incoming RFPs by win probability, fit, margin, conflict risk, and required effort — so leadership stops chasing pitches the agency should never have entered.
Builds hypotheses, category tensions, client questions, proof points, and objection maps from the brief, the client's earnings calls, and the competitive landscape.
Analyses where the current agency may be weak — performance, media transparency, creativity, speed, retail capability, data maturity — and where to attack.
Predicts what the CMO, CFO, CEO, sales lead, ecommerce lead, and procurement team each privately care about — so the pitch room speaks to all of them.
Prevents generic "AI / data / creativity" pitch language and forces a sharper agency point of view by benchmarking against the network's last 24 months of decks.
Prepares teams for chemistry sessions with likely personalities, tensions, watchouts, and conversation starters drawn from open-source intelligence on the client team.
Drafts answers around fees, governance, AI usage, data privacy, sustainability, DEI, brand safety, and measurement — the parts of the RFP no creative wants to write.
Creates a fast briefing room for retail, beverages, beauty, personal care, snacks, household, pet care, or grocery clients — assembled in hours, not weeks.
Plays a sceptical CMO, CFO, procurement officer, ecommerce director, and media director against the team before the real pitch — every cliché flagged in advance.
Synthesises why the agency wins or loses by category, client type, buyer, market, and proposition — and tells leadership which patterns to break.
For creative agencies, strategy teams, brand consultancies, and integrated client teams. Where the long-term equity of the brand is either protected or quietly eroded.
Stores brand codes, tone, claims, territories, forbidden language, campaigns, competitors, and historical decisions. The institutional memory no individual planner can hold.
Finds tensions in consumer behaviour, culture, retail, pricing, occasions, and competitor messaging — the cracks where a brand can credibly position itself.
Converts consumer research, social listening, search data, reviews, and sales data into actionable needs, expressed in the customer's own language.
Checks whether new campaigns preserve distinctive assets, codes, tone, rituals, packaging cues, and category entry points — or quietly trade them for novelty.
Maps FMCG consumption occasions — breakfast, commute, gym, lunchbox, snacking, hosting, gifting, cleaning, self-care — to portfolio strategy and creative briefs.
Clarifies the role of each SKU, sub-brand, pack size, price tier, and channel-specific variant. Stops the portfolio from quietly cannibalising itself.
Suggests new product, flavour, format, packaging, and bundle territories based on category signals, white-space, and consumer language gaps.
Helps large CPG groups rationalise master brands, sub-brands, claims, benefits, and shopper navigation across markets, retailers, and channels.
Identifies moments, memes, rituals, communities, and events that a brand can credibly enter — and the ones it absolutely cannot.
Checks whether creative briefs, media briefs, retail plans, influencer briefs, and ecommerce plans all ladder up to the same strategy — or quietly tell different stories.
For creative networks, content studios, design agencies, production shops, and social agencies. Where AI is most tempting — and most likely to flatten everything that makes a brand interesting.
Generates campaign territories with rationale, brand fit, audience fit, risks, and rejection reasons. Not endless variations — judged options.
Pressure-tests creative briefs for weak insight, vague audience, unclear behaviour change, missing proof, and unrealistic mandatories — before they reach the creative team.
Drafts and reviews copy against tone, vocabulary, humour, formality, claims, and compliance rules. Trained on the brand's last decade, not a generic LLM voice.
Checks layouts, colour, typography, photography style, packaging presence, and brand asset usage against the codified visual system.
Flags risky product claims, sustainability claims, health claims, price claims, and comparative claims — referenced against approved evidence libraries.
Turns a big idea into platform-specific assets for TikTok, Meta, YouTube, Amazon, retail media, DOOH, CRM, in-store, and ecommerce — without diluting the core idea.
Converts campaign strategy into creator-native briefs with dos, don'ts, hooks, formats, and disclosure rules — so creators stay creators, not actors.
Spots real-time social opportunities and drafts brand-safe responses requiring human approval. Speed without the 2am tweet that ends a career.
Detects when assets are wearing out by audience, market, channel, format, and message — before performance collapses and the client notices first.
Converts TVCs, long-form video, influencer content, UGC, shopper assets, and product pages into modular content systems — without producing the same thing six times.
For media agencies, trading desks, analytics teams, and integrated account teams. Where transparency and judgement have to coexist with scale and automation.
Reviews a media plan before the client does — assumptions, risks, missing audiences, weak channel logic, budget tension. The internal stress test no one wants to run manually.
Simulates alternative allocations across TV, OLV, social, retail media, search, programmatic, DOOH, audio, influencer, and CRM — with explainable trade-offs.
Monitors budget pacing, overspend, underspend, thresholds, and approval requirements — across every platform feeding the plan.
Recommends spend distribution across Amazon, Walmart, Tesco, Carrefour, Allegro, Instacart, Kroger, Target, Mercado Libre, and local networks — with retailer-specific reasoning.
Flags when short-term ROAS optimisation is damaging reach, penetration, salience, or long-term brand growth. The voice in the room everyone agrees with but ignores.
Explains fees, tech costs, platform costs, data costs, inventory sources, and optimisation logic in language a CFO can verify and a CMO can defend.
Detects waste and duplication across media platforms, retailer audiences, CRM segments, and lookalikes — and quantifies what the agency is paying to reach the same person five times.
Monitors placements, contexts, exclusions, sensitive topics, and retailer / platform suitability rules in real time.
Recommends burst, always-on, pulsing, seasonal, and promotion-led flighting patterns matched to category buying cycles and retail calendars.
Defines testable hypotheses for each campaign — channel, creative, audience, offer, geography, frequency, format — so every quarter compounds into knowledge.
Especially valuable for FMCG / CPG, grocery, beauty, consumer electronics, pet care, and household brands. The fastest-growing media channel — and the messiest operationally.
Turns brand objectives into retailer-specific media briefs, audiences, placements, keywords, offers, and measurement plans — not a single generic doc copy-pasted across 12 retailers.
Audits product detail pages for title, bullets, images, A+ content, reviews, keywords, claims, and conversion blockers — across the entire portfolio at once.
Manages keyword opportunities across retailer search environments with human-approved bid recommendations and category-share context.
Monitors digital shelf visibility versus competitors across priority retailers — by category, search term, day part, and promotional window.
Aligns retailer promotions, media bursts, trade plans, seasonal moments, and content needs across markets — the single calendar everyone secretly wishes existed.
Identifies missing SKUs, pack sizes, bundles, variants, and channel-specific portfolio opportunities by retailer and market.
Prepares sales and shopper teams for joint business planning with retailers — past performance, category context, competitive shifts, and credible asks.
Flags out-of-stock, image errors, wrong prices, bad descriptions, poor ratings, lost buy box, or competitor hijacking — within the hour, not the quarter.
Adapts product content for retailer, market, language, pack format, and legal requirements — without producing 47 conflicting versions of the same page.
Finds products commonly bought together and suggests bundles, cross-sell media, and in-store / ecommerce activations grounded in real basket data.
For shopper agencies, retail activation teams, field marketing, and trade marketing clients. Where strategy meets concrete: the last metre of the funnel.
Maps shopper missions — stock-up, top-up, impulse, meal solution, gifting, wellness, cleaning, beauty routine — and matches activation to actual moments of decision.
Suggests displays, POS, shelf talkers, sampling, endcaps, QR experiences, and retailer-specific mechanics with rationale tied to mission and category.
Reads planogram data and flags visibility, adjacency, category flow, and conversion opportunities — for the brand and for the retailer.
Reviews packaging for shelf impact, claims hierarchy, navigation, benefit clarity, and occasion relevance under realistic shelf conditions.
Analyses which discounts, bundles, multi-buys, coupons, and loyalty mechanics drive incremental sales — and which just discount the loyal.
Builds shopper playbooks for Walmart, Target, Amazon, Carrefour, Tesco, Żabka, Biedronka, Lidl, Allegro, or local chains — not a universal template.
Chooses where, when, and to whom sampling should happen based on audience, location, product, trial barrier, and incremental sales potential.
Turns brand strategy into retailer-facing sell-in narratives that lead with category growth, not brand ego.
Helps CPG clients prepare category growth stories for retailers — not just brand-first sell-in decks dressed up as category logic.
Generates shopper activation ideas for launches, seasonal campaigns, and promotional peaks — engineered to break the daily shelf scan.
For CRM agencies, data practices, loyalty consultancies, and owned-channel teams. The most valuable inventory the brand actually controls — and the easiest to ruin with bad personalisation.
Builds and explains customer segments based on purchase frequency, value, category behaviour, channel, and lifecycle — segments a marketer can act on, not just admire.
Recommends offers, content, reminders, replenishment nudges, or education journeys — with reasoning attached to every recommendation.
Designs points, perks, challenges, subscriptions, surprise-and-delight, and tier mechanics matched to category economics and customer behaviour.
Drafts lifecycle journeys — welcome, replenishment, win-back, post-purchase, cross-sell, loyalty upgrade — under brand voice and compliance controls.
Checks whether personalisation logic is useful, creepy, compliant, and explainable — the line between relevance and surveillance.
Detects duplicate records, consent gaps, missing fields, broken events, and poor taxonomy across the CDP and downstream tools.
Flags customers receiving too many promotions, discounts, or irrelevant messages — before the unsubscribe.
Explains why a customer or segment is at risk and which interventions are allowed under brand, legal, and privacy constraints.
Designs quizzes, preference centres, surveys, and interactive experiences that collect useful data with consent — and a clear value exchange.
Helps brands activate through retailer loyalty data without overstepping privacy or platform limits — the difference between partnership and overreach.
For insight teams, social listening units, data agencies, innovation teams, and brand planners. Where most of the agency's so-called "insight" is actually observation in nicer typography.
Analyses Amazon, retailer, app store, social, and review data for complaints, praise, unmet needs, and language patterns the brand isn't using.
Extracts the actual words people use to describe problems, benefits, rituals, and frustrations — not the words the brand wishes they used.
Separates real category-relevant signals from generic "trend reports." Filters the noise before it ends up in a planning deck.
Simulates responses from defined consumer personas — clearly labelled as synthetic and never sold as a substitute for real research.
Scores whether an "insight" is actually an observation, fact, tension, cliché, or usable human truth. Stops bad insights at the door.
Tracks competitor claims, promotions, creative territories, influencer usage, media bursts, and retail content — a single, current view of the battlefield.
Detects early signals from search, social, reviews, forums, retail data, and cultural conversation — before they become trend report fodder.
Analyses reactions to price increases, shrinkflation, private label competition, and value messaging across markets and categories.
Maps which benefit claims competitors own and where the brand can credibly differentiate — with evidence, not opinion.
Identifies buying triggers and mental availability cues for FMCG categories — and where the brand is or isn't showing up at them.
For media agencies, data science teams, performance marketing teams, and client leadership. Where most reporting is theatre — and where agents can finally make it accountability.
Turns performance data into facts, interpretations, possible causes, confidence levels, and recommended actions — separated explicitly, not blended into one paragraph.
Detects abnormal changes in sales, ROAS, traffic, CPC, CPM, conversion, stock, price, or review volume — and proposes the three most likely causes.
Checks whether data quality, taxonomy, spend history, promotions, seasonality, and sales data are ready for marketing mix modelling — before the consultants arrive.
Designs geo tests, holdouts, matched markets, audience splits, and retail media incrementality tests with realistic statistical power.
Flags vanity metrics, conflicting KPIs, unclear attribution windows, and platform-biased reporting — the slow corruption of every dashboard.
Creates CMO and CFO-ready summaries of what happened, why it matters, what to do next, and what not to overclaim.
Reconciles conflicting numbers from platform reports, analytics tools, ecommerce data, CRM, and retailer dashboards — and names the most likely source of truth.
Converts every campaign into structured learnings by audience, creative, channel, retailer, product, market, and objective — so the next campaign starts smarter, not from zero.
Ranks experiments by expected impact, cost, confidence, and operational complexity — so the testing roadmap stops being whoever shouted loudest in the QBR.
Shows the confidence level and assumptions behind every media, sales, traffic, or conversion forecast. No more single-number certainty theatre.
For production studios, transcreation hubs, design ops, content supply-chain teams, and global brands. The unglamorous backbone where margin and brand consistency are won or lost.
Tracks what assets are needed, created, approved, localised, distributed, expired, or reused — across every market, channel, and campaign.
Adapts campaign ideas for market, culture, language, regulation, retailer, and channel — without 27 markets each rewriting the same brief from scratch.
Checks whether final assets match legal, brand, platform, retailer, accessibility, and usage-rights requirements before delivery.
Monitors talent rights, music rights, image rights, territories, expiration dates, media types, and renewal risks — the lawsuit that hasn't happened yet.
Produces cost scenarios for shoots, CGI, creator content, dynamic content, localisation, and post-production grounded in real historical project data.
Creates controlled variants by SKU, offer, market, channel, retailer, audience, and season — with full lineage on every cut.
Helps teams find existing assets and prevents unnecessary reshoots or duplicate production — the cheapest cost saving most agencies refuse to make.
Routes assets to brand, legal, medical, regulatory, sales, ecommerce, retailer, and market approvers — and knows where they're stuck.
Checks captions, contrast, alt text, readability, language simplicity, and inclusive design as a default, not an afterthought.
Reviews environmental claims, packaging claims, recycling language, and substantiation requirements against current regulatory standards — the greenwashing fine that doesn't happen.
These become sellable products or premium service layers for agencies. Not productivity tools — strategic assets clients pay for, name, and depend on.
Audits a client's marketing workflows and recommends where agents can safely create value — and where they absolutely cannot yet.
Designs the agent spec, autonomy map, memory policy, escalation logic, and scorecard for a client workflow. The artefact AUX exists to produce.
Recommends which tasks stay with humans, agencies, in-house teams, platforms, and agents — and what each tier costs to run.
Helps CPG clients build a roadmap for retailer media governance, measurement, content, data, and investment — across a multi-retailer portfolio.
Diagnoses ecommerce growth blockers across traffic, conversion, content, price, assortment, stock, reviews, and media — one diagnosis, one plan.
An always-on guardian for brand consistency across agencies, markets, platforms, and retailers — the role no one in-house has time to do well.
Helps clients evaluate agency work based on outcomes, speed, quality, collaboration, innovation, and business impact — with real evidence, not perception surveys.
Connects product launches, media plans, shopper activations, promotions, CRM, retail moments, and cultural events into one navigable plan.
Builds quarterly business reviews with progress, insights, financials, decisions, risks, and next-quarter recommendations — the QBR no one dreads.
A boardroom-facing agent that summarises brand, media, commerce, consumer, competitive, and financial signals into clearly framed decision options.
For ad holdings and agencies serving retail / FMCG brands, these are the agents to build first — because they deliver clear value without requiring dangerous autonomy. They research, challenge, draft, explain, monitor, and recommend. They do not autonomously publish ads, change budgets, approve claims, or alter live campaigns. This is what makes them shippable to a global client in 2026 — not 2030.
Individual agents are interesting. Packaged, named, governed services are sellable. These are how holding companies and their agencies can turn the index into client-facing products — each with a clear remit, a defined audience, and a measurable promise.
One operating layer for retail media decisions — allocation, alerts, narratives, and incrementality — across every retailer the brand spends with.
An always-on guardian of brand codes, claims, and distinctiveness across markets, agencies, and channels — so global brand integrity doesn't depend on a single overworked global brand lead.
A diagnostic-to-action environment for the digital shelf — PDPs, search, share, assortment, and reviews — turned into a single growth narrative the team can actually run on.
An idea-to-asset pipeline that challenges briefs, generates territories, detects fatigue, and modularises ideas across channels — without flattening the work into AI sludge.
A live competitive and category radar — messaging, claims, trends, price moves — for strategists and planners who can no longer pretend a quarterly report is enough.
The retention layer agencies usually run on intuition and weekly check-ins — health signals, opportunity surfacing, structured QBRs, and a real learning archive.
A pitch operation that triages opportunities, attacks incumbent weakness, sharpens the strategy, and rehearses against a believable client room — before money is spent on a pitch the agency shouldn't enter.
A governance backbone for global production — compliance, versioning, localisation, and rights — so growth in asset volume doesn't quietly become growth in legal exposure.
Every agent in this index sits inside the same trust frame. The difference between a cool AI demo and an agentic service a global FMCG or retail client will actually approve is knowing exactly which of these three tiers the agent operates in — and being able to show it.
The agent can act without human approval on each instance. Outputs are reviewable, reversible, and shaped to inform — not to commit the brand.
The agent proposes — the human commits. Every action is logged, justified, and tied to a named approver with the authority to make that decision.
No agent in this index does any of the following without explicit human action. Hard-coded refusals, not policy nudges. This is the line the trust layer enforces.
auxfirst is an agentic experience design agency. We don't sell agent licences and we don't sell platforms. We design the trust layer — the visible intent, the evidence, the autonomy boundaries, the escalation paths, the memory policies, the audit trails — that turns one of these 120 ideas into a service a holding company can actually put in front of a global FMCG or retail CMO.