Recommendation roadmap
A weekly roadmap for winning AI search.
Every Monday, Wildcard prioritizes seven kinds of work that move the answer, with evidence, effort, and next steps attached to every recommendation.
Weekly roadmap
Illustrative queue · sunscreen brand
- 30 minBlogHigh impact
How to layer sunscreen under makeup
Closes 4 gap prompts · absent on ChatGPT + Gemini
- 20 minPDPPriority
Add SPF and PA rating to Daily Fluid SPF 50
3 attributes missing · schema gap on FAQPage
- 15 minRefreshDefense
Refresh: best mineral sunscreens roundup
Competitor took position on 2 tracked prompts
- 10 minRedditCited thread
r/SkincareAddiction · zinc vs chemical SPF
Cited on 2 gap prompts · thread age 4d
- 25 minOutreachEditorial
Wirecutter · sunscreen roundup update
Author: Rachel Wharton · preflighted
7
rec types
5
this week
1
defense play
The seven kinds of work
One prioritized queue. Seven proven plays.
Every recommendation Wildcard makes falls into one of seven types. Each type has a dedicated workflow, evidence model, and product surface. Follow any card to see how the work moves from recommendation to review.
On-site content
Pages you own. Wildcard writes new posts, builds category pages, and refreshes stale ones.
Blog
A new blog post targeting a cluster of prompts where the brand is absent or ranked below cited competitors.
- One post per topic cluster
- Eight source formats supported
- Bound to a real page
Collection page
Build a new shoppable category or use-case page that pairs SKUs with citation-ready guidance.
- Not a blog post
- Shoppable + citable
- Query-driven
Content refresh
Refresh an existing blog or collection page that is declining, stale, or losing ground to competitors.
- Never PDPs (those become optimizations)
- Stakes: page age + position drop
Product data
The catalog itself. Attributes, FAQs, descriptions, and structured data AI can actually cite.
Off-site presence
Third-party surfaces AI already cites. Editorial pitches, cited-thread engagement, competing video.
Reddit engagement
Engage in a specific Reddit thread AI models already cite for the brand's gap prompts.
- One rec per thread URL
- Cited-on evidence attached
- Community-safe drafts
Source outreach
Pitch editorial, review, and news publications AI already cites. Preflighted against a real article and author.
- Editorial only, never competitors
- Article + author verified
- Prompt evidence bundled
YouTube video
Plan a branded video that competes with the videos AI cites for the brand's gap prompts today.
- Scratchpad + brief
- Never auto-published
- 30-day cooldown per target
Modifier
Defense.
When competitors take an answer, any on-site type above can carry a Defense chip. The recommendation keeps its primary badge (Blog, PDP, Collection, or Refresh) and adds the competitive counter-move behind it.
Anatomy of a recommendation
Every card carries its own evidence.
Wildcard never asks your team to trust a headline. Each recommendation ships with the measured facts behind it, the exact prompts it addresses, and imperative subtasks with per-step effort.
TL;DR
Add SPF and PA rating attributes plus FAQ schema to Daily Fluid SPF 50.
Why this matters
ChatGPT and Gemini cite competitors on 4 tracked prompts because their PDPs expose the same attributes the brand is missing.
Prompts affected
4
Competitors ahead
3
Missing attributes
3
Schema gaps
FAQPage
Subtasks
- Confirm SPF + PA rating from formulation sheet5 min
- Add attributes to Shopify variant metafields8 min
- Publish FAQPage JSON-LD via theme block7 min
Why this matters
A merchant-readable distillation of the gap and the opportunity.
Stakes
Measured chips: prompts lost, citation count, search volume, position drops.
Target prompts
The exact queries the recommendation is meant to move.
Effort estimate
Time to complete, calibrated per action type.
Subtasks
1 to 5 imperative steps with per-step minutes.
Expected outcome
What success looks like once the work ships.
Priorities you control
Ordered for the way your team ships.
Wildcard sorts the queue by prompt-gap severity, position, search volume, and page age. Your catalog mode adjusts scope weighting. Your per-type priorities decide which work rises first.
Catalog mode
Set once in workspace settings. Wildcard weights recommendations to match how your catalog behaves.
Single product
Boost brand-level and single-SKU recs. Deprioritize sprawling collections.
Stable catalog
Balanced weighting across categories, SKUs, and prompts. Default for most catalogs.
Rotating inventory
Boost collection scope and prompt coverage. Deprioritize per-SKU PDP work.
Per-type priority
Turn any of the seven types Off, keep it Default, or promote it to Priority. Off means Wildcard stops generating it.
Recommendation priorities
Illustrative settings
- Off0.0×Skip this type entirely.
- Default1.0×Normal weighting.
- Priority1.5×Surface first in the queue.
FAQ
Roadmap questions.
What kinds of recommendations does Wildcard make?
Seven actionable types: Blog, PDP optimization, Collection page, Content refresh, Reddit engagement, Source outreach, and YouTube video. Any of the four on-site or catalog types can also carry a competitive Defense modifier when a competitor is gaining ground.
How does Wildcard decide what to recommend first?
Each recommendation carries a priority score built from prompt gap severity, citation position, search volume, and page age. Your catalog mode adjusts scope weighting, and you can set each type to Off, Default, or Priority to override the order.
Can I turn off a recommendation type?
Yes. If your team does not run YouTube, does not participate on Reddit, or has no bandwidth for outreach, set that type to Off in workspace priorities. The queue stops surfacing it until you re-enable it.
What evidence sits behind every recommendation?
A TL;DR, why it matters, expected outcome, measured stakes, target prompts, target SKUs or domains, 1 to 5 subtasks with per-step effort, and the strategist agent that authored it. Prose is canaried so numbers are never invented.
How often are new recommendations generated?
Wildcard runs a fresh weekly pass so each team has a Monday-ready roadmap. Defense recommendations can also appear mid-week when a competitor takes ground on tracked prompts.