Use case
Seed AI brand queries
Seed AI Presence with brand, domain, aliases, and shopper-style queries so ChatGPT, Gemini, Perplexity, and AI Overviews have signals on day one—10 to 100 keywords by plan.
Highlights
What you get out of this flow
Outcomes you can expect when you run this playbook inside EShopSet on Shopify.
- Brand + aliases + domain so models recognize you consistently
- 10 / 50 / 100 AI keywords on Starter / Growth / Pro
- Shopper prompts beat jargon on day-one citation reads
Why seeding is a pillar step
If you only track your exact brand string, you miss category and comparison prompts where AI answers already recommend competitors. Seeding a balanced set—brand, aliases, category, and “best X for Y”—creates a measurable citation baseline across four answer surfaces.
How it works in EShopSet
In AI Presence Settings, add brand name, domain, aliases (DBA, misspellings), and starter keywords up to your plan limit. Overview then tracks mentions and citations by model for that set.
Example: coffee brand seed set
A specialty coffee Shopify store on Starter (10 AI keywords) seeded:
- 2 brand variants + domain
- 3 category prompts (“best single origin coffee subscription”)
- 3 comparison prompts (“Brand vs Competitor for espresso”)
- 2 problem prompts (“coffee beans for dark roast at home”)
First sync showed mentions on 2/4 models for brand queries but 0/4 for category—clear content brief for comparison pages.
Playbook
- List official brand, legal entity, and common misspellings.
- Add 5 shopper questions from support tickets or search console.
- Add 3 competitor comparison prompts.
- Stay within plan limits; expand later with Expand your AI query set.
- Run first sync; save day-0 citation rates by model.
What to measure
- Mention rate by model on brand vs category queries
- % of seeded keywords with ≥1 citation
- Aliases that never appear (clean up or reinforce elsewhere)
