Meta description

Compare creative automation platforms for display advertising and operating models to scale HTML5 banner production.

Why ad production platforms matter for in‑house teams and agencies

Ad production is now an operational bottleneck, not just a design chore.

Adobe’s 2024 State of Creativity reports that 83% of decision makers saw workload change in the past 12 months, and 75% say they’ll invest in tools or software to keep up with demand (Adobe, 2024). CHILI’s 2025 Brandwidth research found 51% of agencies cite time constraints as their biggest challenge, 56% report delayed launches, and 59% report stress or anxiety linked to production pressure (CHILI Brandwidth, 2025).

At the same time, in‑housing keeps expanding. The ANA’s 2026 benchmark shows respondents were five times more likely to say marketers are in‑housing more than pulling back, and 53% now view their in‑house agency as a strategic partner, not just a production shop (ANA, 2026).

If your team is expected to ship thousands of HTML5, GIF, and MP4 display ads across markets, you need:

• A clear operating model: centralized, decentralized, or hybrid

• A production platform that can actually support that model

• Defined roles and responsibilities so people and tools don’t collide

This guide maps how ad production platforms (including Viewst) support in‑house marketing, agencies, and performance teams running at industrial volume.

What is an ad production platform?

An ad production platform is a specialized system for creating, scaling, and exporting digital ads — especially HTML5 display banners and rich media.

It sits between design tools (Figma, Adobe) and media platforms (ad servers, DSPs like Google DV360), and focuses on the "high-friction" layer:

• Turning a master creative into dozens or hundreds of sizes and variants

• Applying motion and animation that comply with platform specs

• Managing reviews, approvals, and brand governance

• Exporting compliant HTML5 / GIF / MP4 assets, ready for trafficking

How it differs from generic design tools

General design tools (Figma, Photoshop, After Effects):

• Optimized for visual craft and concepting

• Flexible but not opinionated about specs or output formats

• Not built for governed, multi-size banner sets

Ad production platforms:

• Treat one master creative as the source of truth for every variant

• Bake in ad‑tech constraints (file size, animation length, click tags)

• Automate resizing, localization, and versioning

• Centralize approvals and export ad‑network‑ready files

Viewst, for example, is an HTML5‑native ad production platform that treats banner production as infrastructure: AI Smart Resize, AI Instant Animator, and AI Image Deflatening all work around a master creative to remove mechanical work while keeping designers in control (case study: Viewst).

Display advertising at industrial scale: why operating models matter

Display advertising is no longer a small channel. In the U.S. alone, digital ad revenue reached an estimated $258.6B in 2024 (up 14.9% year‑over‑year) and $294.6B in 2025 (up 13.9%), according to the IAB’s Internet Advertising Revenue reports (IAB, 2026 – US, FY 2024–2025).

On the creative side, AppsFlyer’s 2025 report analyzed 1.1 million creative variations and $2.4B in ad spend. For advertisers spending $7M+ per quarter, non‑gaming apps averaged 2,365 creatives per quarter, while gaming apps averaged 2,743 (AppsFlyer, 2025).

That volume forces organizations to decide:

• Where banner production lives (central team, embedded, or hybrid)

• How work moves from insight → concept → master → variants → launch

• What platform runs that pipeline end‑to‑end

Without an explicit operating model, teams end up with:

• Designers doing manual resizes in Photoshop

• Dozens of slightly different templates in Figma

• Reviews happening via email, decks, and chat threads

• Last‑minute fixes at the ad server level

Centralized vs decentralized vs hybrid ad production models

Comcast Technology Solutions (CTS) frames creative production as a choice between centralized efficiency and consistency vs decentralized flexibility and specialization (CTS, 2023). Cella’s guidance on in‑house operations similarly recommends a federated approach: a core team owns standards and process, while work happens close to the business where it makes sense (Cella, 2020).

Let’s apply those lenses specifically to banner ad production.

Centralized banner production model

Definition: One team owns most display ad production for the organization.

Typical owners:

• In‑house production studio

• Central creative operations team

• Agency production hub

Pros:

• Single source of truth for templates and brandbooks

• Easier governance over fonts, colors, and motion patterns

• Better utilization of specialized skills (HTML5, animation)

• Strong fit with a centralized ad production platform

Cons:

• Risk of becoming a bottleneck for local markets

• Can feel distant from business stakeholders

• Requires robust intake and prioritization systems

Best fit when:

• You run global or multi‑market campaigns

• Brand consistency is non‑negotiable

• You support many internal marketers or client teams

Decentralized banner production model

Definition: Individual squads, brands, or regions produce their own banners.

Typical owners:

• Regional marketing teams

• Individual product lines or business units

• Client‑specific pods in agencies

Pros:

• Faster response to local needs and tests

• Closer alignment to performance data and local insights

• Empowered teams who "own" their creative pipeline

Cons:

• High risk of brand drift and spec mistakes

• Duplication of tooling and effort

• Harder to aggregate reporting and learnings

Best fit when:

• Local differentiation matters more than global consistency

• You have strong creative leadership embedded in each unit

Hybrid / federated model (the pragmatic default)

Most enterprises end up in a hybrid model:

• A central team owns: brandbooks, templates, governance, and the production platform

• Local teams own: content, adaptations, and performance‑driven iterations

Cella’s agile in‑house guidance recommends this federated model: central standards, flexible execution where work happens (Cella, 2020). CTS echoes this by stressing that both centralized and decentralized strengths can be combined in a coordinated operating model (CTS, 2023).

An ad production platform is the shared environment that lets this hybrid model work:

• Central team defines master creatives and brandbooks

• Local teams create variants and localize within locked guardrails

• Everyone works in one system instead of exporting and emailing files

Roles and responsibilities in a banner production workflow

Cella’s operations guidance clarifies that traffic managers own status reporting and process optimization, while project managers often sit in a PMO or creative org to coordinate larger initiatives (Cella, 2022). Applied to banner production, you can map responsibilities like this:

Core roles

• Creative Director / Head of Creative
  Sets creative direction, ensures concepts align with brand and campaign goals.

• Design Director / Lead Designer
  Owns master creative quality, approves templates and brandbooks.

• Production Designer / HTML5 Designer
  Builds and maintains master banners, creates new templates, handles complex animations.

• Traffic / Studio Manager
  Manages intake, prioritization, and routing of banner requests; monitors capacity.

• Project Manager (PM)
  Coordinates multi‑market or multi‑channel campaigns; aligns timelines and dependencies.

• Performance Marketing Manager / Growth Lead
  Defines test hypotheses, manages A/B/C rotations, feeds performance data back into creative decisions.

• Brand / Compliance Reviewer
  Ensures assets adhere to legal, regulatory, and brand guidelines.

• Media / Ad Ops
  Traffics creatives into DSPs (e.g., DV360), ad servers, or retail media platforms; validates specs.

Where the ad production platform fits

A modern platform like Viewst becomes the shared environment for:

• Designers – building masters, applying motion, and using AI to remove busywork

• Traffic / PM – tracking status, ensuring all required sizes and variants are covered

• Stakeholders – reviewing and commenting directly on live, interactive banners

• Ad Ops – exporting compliant HTML5, GIF, or MP4 assets for specific platforms

Instead of eight versions of the truth (Figma, After Effects, decks, screenshots, ad server), you get one production source of truth.

Platform capabilities checklist: what to demand from an HTML5 ad production platform

This section is designed as a practical checklist you can use when comparing creative automation tools for display advertising.

1. Master creative and variant governance

A strong platform should:

• Treat one master creative as the structural source for all sizes and variants

• Let you define locked and flexible zones (e.g., logo locked, message editable)

• Sync changes from the master to all derived sizes automatically

This aligns with broader industry trends. The IAB’s New Ad Portfolio encourages aspect‑ratio and size‑range‑based units rather than dozens of bespoke sizes (IAB Tech Lab, New Ad Portfolio). Google DV360 enforces limits like a 5 MB max total download size and a 30‑second animation cap for HTML5 creatives (Google DV360 Help, accessed 2026 – global).

Why it matters:

• Production can scale from one master asset

• Updates roll out predictably and safely

• Brand risk is reduced when local teams can’t break core layout rules

2. AI tools for production (not just generation)

A modern ad production platform should include AI that handles mechanical work rather than replacing creative judgment.

Look for features like:

• Smart Resize – generates required sizes from a master while respecting hierarchy

• Image deflatening – converts flat image assets (e.g., from legacy PSDs or exports) into structured, editable banners

• AI‑assisted layout – suggests placements that preserve legibility and visual balance

• Instant animation – applies motion patterns to multiple layers in one click

Example – Viewst: AI Smart Resize, AI Image Deflatening, AI Designer, and AI Instant Animator are vendor‑specific features that use AI to convert one master into a governed banner set while keeping exports as editable HTML5 (case study: Viewst).

Keep in mind that there is an AI proficiency gap: Cella’s 2025 Intelligence Report found 63% of creative professionals see AI as a productivity tool, but only 5% feel strongly proficient (Cella, 2025). Platforms should therefore prioritize clarity and control in AI workflows.

3. Native HTML5 and export capabilities

Your platform should be an HTML5 ad production platform by design, not an image editor with an HTML5 plugin.

Key questions:

• Does the editor work on actual HTML5 layers, not flat images?

• Can you export HTML5, GIF, and MP4 from the same master?

• Are exports compliant with major platforms (e.g., DV360, Google Ads, retail media specs)?

Look for:

• Inline clickTag support

• Animation timeline controls and easing presets

• Preset profiles for major media platforms (e.g., DV360 5 MB / 30‑second defaults)

Why it matters:

• You avoid hand‑coding fixes in HTML packages

• Designers don’t have to think in code but still ship clean files

• Media teams gain predictable, spec‑compliant deliveries

4. Integrations with design and media tools

Creative automation software for display advertising should bridge the gap between where concepts start and where campaigns run.

Must‑have integrations:

• Design tools – Figma and Adobe imports (e.g., PSD, XD, Illustrator) into editable banners

• DAM/asset libraries – to reuse photography, logos, and brand elements

• Media / ad platforms – export presets or direct connections for DSPs, ad servers, and retail media

Example – Viewst: Figma and Adobe import plus export to HTML5 / GIF / MP4 as production‑ready files. This is an example of how one platform supports both design and media sides (case study: Viewst).

5. Brandbooks and governance

Brand control in the AI era is non‑negotiable. Cella notes that AI governance in marketing should be owned by creative/marketing leadership because non‑creative "on‑brand" interpretations can still dilute brand trust (Cella, 2024).

Your platform should allow:

• Brandbooks – defined typography systems, color tokens, and logo rules

• Locked components – non‑editable zones for core brand elements

• Role‑based permissions – restrict who can edit templates vs who can create variants

Why it matters:

• Automation scales within guardrails rather than around them

• Local teams can work faster without jeopardizing brand standards

6. Collaboration and approvals inside the platform

Bannerflow’s 2026 survey of 300 marketers found nearly 80% regularly review performance metrics in shaping creative, and 93% track multiple creative performance metrics (Bannerflow, 2026). But they also found that the bottleneck is turning data into action, not collecting it.

Creative automation platforms can help by:

• Centralizing comments and visual feedback on live banners

• Providing shareable previews for stakeholders without requiring logins

• Tracking approval status per creative, size, or variant set

This keeps collaboration where the work lives, rather than in screenshots and deck exports.

Creative automation platforms comparison — Viewst and alternatives

This section compares several creative automation tools for display advertising against the checklist above. It is high‑level and based on published positioning as of 2026; always confirm details with vendors.

1. Viewst (case study: HTML5‑native production infrastructure)

Positioning: HTML5‑native ad production platform focused on banner production as infrastructure for creative and advertising teams.

Strengths:

• AI Smart Resize, AI Image Deflatening, AI Designer, AI Instant Animator (example of AI built for production, not just generation)

• True WYSIWYG editor where output matches editor exactly

• Strong focus on master creative governance and brandbooks

• Figma / Adobe import, production‑ready HTML5 / GIF / MP4 export

Best for:

• In‑house studios and agencies producing high volumes of HTML5 banners

• Teams that want production infrastructure without replacing core design tools

2. Celtra

Positioning: Enterprise creative automation platform linking creative generation, review, approval, activation, and performance tracking in one system (Celtra, Product Overview).

Strengths:

• End‑to‑end workflow: templates, automation, localization, and activation

• Strong ties into media activation and dynamic creative optimization (DCO)

• Suitable for global enterprise advertisers and complex organizations

Best for:

• Enterprises seeking one system to connect creative automation with activation

• Brands running large‑scale DCO and omnichannel automation

3. Bannerflow

Positioning: Creative automation platform focusing on design, automation, localization, data, and DCO for display and video (Bannerflow, 2026).

Strengths:

• Strong data and performance feedback loops

• Localization and multi‑language campaign support

• Focus on connecting performance metrics with creative iterations

Best for:

• Teams already data‑mature that need to accelerate test/learn cycles

• Media and performance teams working closely with creative

4. Hunch

Positioning: Creative automation platform extending from template creation into campaign launch and optimization (Hunch, Product Overview).

Strengths:

• Strong integration with social and dynamic campaigns

• Focus on automating creative + campaign setup end‑to‑end

Best for:

• Performance‑driven teams focusing on dynamic social and display campaigns

5. Generic design tools (Figma, Adobe) as partial solutions

Many teams still rely on Figma, Photoshop, and After Effects as their main “platforms for banner ad production.” While these are essential design tools, they lack:

• Master‑creative‑driven HTML5 automation

• Built‑in spec and ad‑platform compliance

• Integrated approvals and exports tailored for DSPs

They remain critical for concept development, but are not a substitute for a dedicated HTML5 ad production platform if you operate at scale.

Best software for creating and managing display ads (by use case)

This section summarizes which types of tools fit common scenarios.

Best for high‑volume HTML5 banner production

• Viewst (case study): HTML5‑native, AI‑assisted production infrastructure that sits between design and media. Strong fit for agencies and in‑house studios juggling high volume, multiple markets, and strict brand control.

Best for enterprise‑wide creative automation and activation

• Celtra: Deep integration into activation and DCO. Suited for organizations that want a single system across display, rich media, and sometimes video.

Best for data‑driven creative optimization loops

• Bannerflow: Focus on connecting data insights with creative updates for display automation, localization, and DCO.

Best for dynamic social + display campaigns

• Hunch: Particularly strong for social and cross‑channel dynamic campaigns where templates, feeds, and launch automation are tightly coupled.

Essential design stack (but not full production platforms)

• Figma + Adobe suite: Still the best software for creative concepting and high‑craft design work; pair them with an ad production platform to handle scaling, governance, and exports.

Ethical AI tools for creating display ads

AI is moving from "create" to "operate." The IAB’s 2025/2026 revenue report notes that generative AI is lowering creative‑production costs and that agentic systems are reshaping how companies buy, plan, and execute media (IAB/PwC Internet Ad Revenue Report 2025, published 2026).

That makes ethical AI and governance critical for ad production platforms.

Key ethical considerations

1. Brand safety and governance

   • AI should operate within locked brand systems (brandbooks, templates)

   • Creative leadership must define what "on‑brand" means in AI prompts and outputs

   • Cella argues AI governance should sit with creative/marketing leaders, not IT, to avoid brand dilution (Cella, 2024)

2. Data privacy and security

   • Training data and prompts should be handled according to privacy regulations

   • Platforms should clearly disclose how they use uploaded assets for model training (or not)

3. Transparency and controllability

   • Designers should understand what AI is doing: when it resizes, reflows, or animates

   • Platforms should provide human‑readable logs or versions so changes are auditable

4. Role clarity

   • AI should augment production work (resizes, exports, base animations), not replace human creative judgment

   • Clear roles and responsibilities (who approves AI output, who locks templates) reduce risk

How platforms support ethical AI in advertising creative tools

Ethical AI in ad production platforms should show up as:

• Guardrails – brandbooks, locked elements, and approval workflows

• Limited scope – AI focuses on layout, scaling, and animation, not brand strategy

• Human‑in‑the‑loop – designers can override, tweak, or reject AI suggestions

Platforms like Viewst position AI as a collaborator that reduces non‑creative suffering (manual resizes, repetitive motion work) so designers can focus on concept and craft.

Turning data into creative action: closing the execution gap

Bannerflow’s 2026 report shows 93% of teams track multiple creative performance metrics, and 74.3% track more than two (Bannerflow, 2026). Yet the bottleneck remains: translating data into new creative quickly enough.

Ad production platforms can help close this gap by:

• Making variant creation cheap – new copy, offers, or CTAs can be tested without manual rebuilds

• Keeping master creatives synced – winning elements can be rolled out across markets

• Enabling fast approvals – stakeholders review and approve in one environment

For teams managing thousands of creatives per quarter (AppsFlyer reports 2,365–2,743 per quarter for high‑spend apps, AppsFlyer, 2025), this operational layer can be the difference between a test‑and‑learn culture and a backlog of "ideas we never shipped."

Q&A: common decisions about ad production platforms and operating models

1. Should we centralize banner production or keep it in each team?

Start with a hybrid model.

• Centralize: brandbooks, templates, production platform ownership, and governance

• Decentralize: campaign‑level variants, localization, and performance‑driven tweaks

This follows CTS’s recommendation to blend centralized consistency with decentralized flexibility (CTS, 2023) and Cella’s federated model for in‑house agencies (Cella, 2020).

2. How do we know we’re ready for a dedicated ad production platform?

Signals you’re ready:

• Designers spend more time resizing than designing

• Launches are delayed due to production bottlenecks (56% of agencies report this, CHILI Brandwidth, 2025)

• You run multi‑market campaigns and see inconsistent brand execution

• Your team is tracking performance metrics but struggles to translate them into creative updates

If you’re producing hundreds or thousands of variants per quarter, a specialized platform usually pays for itself in time saved and reduced rework.

3. What’s the minimum team size for centralizing on a platform like Viewst?

There’s no universal number, but as a rule of thumb:

• In‑house teams – once you have a 20+ person marketing or creative organization and a dedicated production/traffic function, centralizing banner production becomes beneficial.

• Agencies – if multiple client accounts rely on display ads and you frequently build multi‑size sets, a central platform is valuable even with a smaller core team.

4. How do we keep AI from going off‑brand in our banners?

• Lock brandbooks and templates in your platform

• Route all AI‑generated or AI‑modified banners through the same approval workflow as human‑made ones

• Ensure creative leadership owns AI governance policies (per Cella’s recommendation, Cella, 2024)

5. How do we evaluate platforms quickly?

Use this short checklist:

• Master creative → many governed variants?

• AI focused on production (resize/animate) vs full creative generation?

• Native HTML5 editing and export with DV360‑compliant presets?

• Brandbooks, locked components, and role‑based permissions?

• Integrated review and approvals inside the platform?

• Figma/Adobe import and export to HTML5 / GIF / MP4?

If a candidate platform cannot answer "yes" to most of these for your use case, it’s likely not a fit for high‑volume, multi‑market banner production.

How Viewst fits as your banner production infrastructure (case study)

Within this landscape, Viewst is an example of an HTML5 ad production platform designed as infrastructure rather than a generic design tool.

For Heads of Creative, Design Directors, and Creative Operations leads:

• It centralizes banner production on one system between Figma/Adobe and your DSPs/ad servers

• It uses AI to remove non‑creative suffering (resizes, basic animations, deflatening flat assets) while keeping designers in control

• It reinforces brandbooks and governance rather than bypassing them

Whether you choose Viewst or another platform, the principle holds: treat banner production as an infrastructure problem. Once you have a clear operating model and a platform that supports it, your team can spend more time on bold creative work — and less on wrestling with formats, specs, and scattered approvals.