Generate custom catalog creative for every customer
Generic, one-size-fits-all creatives rarely perform. Bestever uses AI to generate personalized, on-brand variations directly from your catalog—at scale. Every customer gets a creative that matches your products and their interests.
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How Bestever Works
1
Connect your catalog & set your brand kit
Use a product feed, PIM, or API—map attributes like price, badges, promos, seasons, and inventory.
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2
Define experiments
Pick hypotheses across copy, offer, layout, background, model use, price framing, and more. Choose your variant count and daily cadence.
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3
Generate in bulk
Bestever spins up creative cuts from the same concept pack. SKU, audience, and channel organize variants.
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Make more. Guess less. Launch Daily
Value Prop Strip
Bestever is your AI force multiplier for high SKU counts. We handle the production grind so your teams can focus on ideas and outcomes.
Daily generation
Fresh variations for every priority SKU set, every day.
Built for scale
Templates and prompts that adapt across channels and aspect ratios.
Brand‑safe by design
Guardrails, locked elements, and approvals keep everything on brand.
Experiment native
Creative is produced with test design baked in, not bolted on.
No new headcount
Multiply output without growing the team
SKU‑aware prompts
Designs and copy adapt to attributes like colorway, price, rating, and stock
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Collections and moments
Rules handle seasonal drops, regional promos, weather triggers, and flash sales.
Collections and moments
Region and language
Locale packs for copy, currency, and compliance lines.
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Roles and workflow
Workspaces for brand, region, and partner teams with approvals.
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Work The Way Creative And Performance Already Work
For Creative Teams
Start with your idea, not a blank page
Flexible templates that do not break when you switch aspect ratios
Comments in context and version history that is actually useful
For Performance Teams
Variant matrices created with test design in mind
Creative scorecards that tie outcomes back to elements like CTA, layout, and offer
Faster refresh cycles to fight fatigue
Experiment OS
Turn every drop into a learning loop.
Plan build a simple test plan with hypotheses, sample sizes, and guardrails
Generate variants that map to that plan
Launch to your channels from the same pack
Read lift by element to spot what really moved results
Repeat push the next wave tomorrow without a rebuild
Plan build a simple test plan with hypotheses, sample sizes, and guardrails
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