Retail Media Search & Keyword Strategy
Build the search and keyword bidding tactics inside a retail media plan.
Key data
Retail Media Search & Keyword Strategy is a free AI skill for shopper marketing teams in food and beverage. Build the search and keyword bidding tactics inside a retail media plan. You give it 5 inputs and it returns 6 structured outputs in about 5 minutes. It ships in 3 formats — copy-paste prompt, installable Claude Skill and Custom-GPT instructions — costs $0, and was last updated July 12, 2026.
- Role
- Trade & Shopper Marketing
- Inputs needed
- 5
- Outputs
- 6
- Price
- $0
Updated
What is the Retail Media Search & Keyword Strategy?
The Retail Media Search & Keyword Strategy skill is a free AI skill that builds the search and keyword bidding tactics inside a retail media account — the layer beneath the overall campaign plan. You give it your product, the retail media network, your objective, and your budget and margin; it returns keyword segmentation across branded, category, competitor, and long-tail terms, a match-type and bidding approach per segment, a negative-keyword approach to stop budget bleeding, a search-term harvesting workflow that promotes proven terms to exact match, a budget split across keyword tiers, and the measurement framework to judge performance. It is built for shopper and e-commerce media managers who already have a retail media budget approved and need the actual keyword-level tactics to spend it well. Because it works one layer beneath the overall media plan, it goes deeper on search and bidding than a broader plan typically covers. Grounding the keyword segmentation in live food and beverage demand data shows what shoppers are actually typing into the search bar.
Who it's for
- Shopper and e-commerce media managers running retail media search
- Retail media specialists managing keyword-level bidding
- Brand digital marketing managers funding sponsored search
- Agency retail media planners building keyword strategy for clients
What you get
- Keyword segmentation: branded, category, competitor, long-tail
- A match-type and bidding approach per segment
- A negative-keyword approach
- A search-term harvesting and graduation workflow
- A budget split across keyword tiers
- A measurement framework tied to margin-based breakeven
What you need to provide
The prompt asks for 5 inputs. Have these ready before you paste it in:
- 1Product
- 2Network — e.g. a major grocery or marketplace retail media platform
- 3Objective — grow a hero SKU, defend brand terms, launch
- 4Budget
- 5Margin
How to use it
- 1Paste the prompt into ChatGPT, Claude or Gemini.
- 2Fill the bracketed inputs (product, network, objective, budget, margin).
- 3Answer its clarifying questions about current keyword performance.
- 4Ask it to build the actual keyword list for the category segment.
See it in action
Example input
Brand: fictional 'Quill Valley Granola'. Platform: a major retail media network. Objective: grow the hero SKU and stop losing brand-term impressions to a competitor bidding on our name. Budget: a modest monthly test budget. Margin: [insert]. Problem: broad-match terms are converting poorly and eating most of the budget.
Example output
Retail media search & keyword strategy — Quill Valley Granola Keyword segmentation - Branded (defend): "Quill Valley," "Quill Valley granola," and close misspellings. Small volume, cheapest clicks, highest conversion — and currently being encroached on by a competitor bidding your name. - Category: "granola," "healthy granola," "granola clusters," "breakfast granola" — your biggest volume opportunity and the segment worth the most testing budget. - Competitor: named competitor granola terms, used cautiously — a defensive/opportunistic play, not a volume driver; expect a lower conversion rate here than on your own branded terms. - Long-tail: "gluten-free granola clusters," "low sugar granola," or whatever specific attributes your hero SKU actually carries — lower volume per term but often the cheapest, highest-intent clicks once identified. Match-type & bidding approach - Branded: exact match, aggressive bid — this is the cheapest defense against the competitor bidding on your name, and losing this auction is the highest-priority problem to fix first. - Category: a mix of phrase and exact on proven terms; start a small broad or auto component specifically to discover new converting long-tail terms, then graduate winners out of broad and into exact. - Competitor: exact match only, modest bid, monitored closely for conversion — cut fast if it's not converting within a defined test window. - Long-tail: exact match once identified through the harvesting process below; these terms usually support a lower bid for a similar or better conversion rate. Negative-keyword approach Apply negatives aggressively on the category broad/auto campaign specifically — any search term that has spent budget across a meaningful sample size without converting should be added as a negative rather than left to keep bleeding spend. Review this weekly while the discovery campaign is active, since this is where a "modest monthly test budget" gets wasted fastest if left unmanaged. Search-term harvesting workflow 1. Let the category broad/auto campaign run and report actual search terms. 2. Weekly, pull the search-term report and identify terms converting above your target rate. 3. Add winning terms to a dedicated exact-match campaign at a bid you control. 4. Add non-converting terms as negatives in the broad campaign so it stops re-learning the same lesson. Budget split (directional) Given the stated brand-term defense problem, weight budget toward branded defense first despite its low overall spend need — it's inexpensive to defend and expensive to lose. Roughly: majority to category (your growth engine), a meaningful minority to branded defense, a small test allocation to competitor terms, with long-tail folded into category once harvested. [Insert your actual monthly budget to set real dollar caps per segment.] Measurement - Primary: ROAS against a breakeven tied to your actual margin — [insert margin] to calculate this precisely. - Brand-term impression share and auction win rate — the direct measure of whether the competitor-bidding problem is resolving. - New-to-brand order share on category and long-tail terms, since branded-term conversions are largely existing buyers, not growth. - Search-term report health: declining wasted spend on non-converting broad terms over time is a sign the harvesting workflow is working. Want me to build the actual starting keyword list and bid recommendations for the category segment?
The prompt
This is the actual prompt, not a teaser. Read the opening below, then unlock the free bundle with your email for the full version plus the installable Claude Skill and Custom-GPT instructions.
# Role You are a retail media performance specialist who works one layer beneath the overall media plan — deep on search terms, match types, and bidding. You separate proven converters from exploration budget, and you defend brand terms as the cheapest, highest-priority spend. # Context I'll provide - Product: [PRODUCT] - Retail media network: [NETWORK — e.g. a major grocery or marketplace retail media platform] - Objective: [OBJECTIVE e.g. grow a hero SKU, defend brand terms, launch] - Budget: [BUDGET] - Margin (for breakeven ROAS): [MARGIN] - Known issues (optional): [e.g. poor-converting broad terms, competitor bidding on brand name] # Your task 1. If the product, network, objective, or budget are missing or vague, ask up to 3 clarifying questions BEFORE writing anything. 2. Segment keywords into branded, category, competitor, and long-tail, with a match-type and bidding approach for each.
Showing the first 14 of 33 lines. The free download has the full prompt, the installable Claude Skill and the Custom-GPT instructions.
$0 — unlocked with your email. Downloads instantly.
What's in the free download
| File | Format | Where you use it |
|---|---|---|
| prompt.md | Copy-paste prompt | ChatGPT, Claude, Gemini, Copilot |
| SKILL.md | Installable Claude Skill | claude.ai → Settings → Capabilities → Skills |
| gpt-instructions.md | Custom-GPT instructions | ChatGPT → Create a GPT → Instructions |
Reviewed by CPG & food retail analysts
Written and reviewed by the Tastewise F&B analyst team. Every skill is tested against real CPG briefs before publication — see our data methodology.
Frequently asked questions
- What is retail media keyword strategy?
- Retail media keyword strategy is the search-term and bidding layer inside a retail media account — deciding which branded, category, competitor, and long-tail terms to bid on, at what match type, and how much, so a retail media budget converts rather than just spending. This skill builds that keyword-level tactic set: segmentation, bidding, negatives, and a harvesting workflow that turns discovery spend into proven, controlled campaigns.
- How is this different from the Retail Media Plan Builder skill?
- The Retail Media Plan Builder covers the whole retail media campaign — objectives, overall budget split across upper- and lower-funnel, ad types, and the full measurement framework. This skill goes one layer deeper into a single piece of that plan: the actual search and keyword tactics — segmentation, match types, bidding, and negative-keyword management. Use the plan builder to set the overall campaign strategy, then this skill to build the keyword execution underneath it.
- Which AI models does this prompt work with?
- Any capable chat model — ChatGPT, Claude, or Google Gemini. It's model-agnostic, so paste it directly into a chat, save it as a Custom GPT, or store it as a reusable skill so keyword strategy stays consistent across every retail media account your team manages.
- Do I need to know my margin before running this?
- Yes, ideally — the skill ties its recommended breakeven ROAS directly to your margin, and without it, that number stays a placeholder rather than a real target. If you don't have exact margin figures on hand, provide your best estimate; the skill will not invent a target ROAS on your behalf, but a rough number is still useful for directional bidding guidance.
Related skills
Skills CPG teams pair with the Retail Media Search & Keyword Strategy.
Retail Media Plan Builder
Plan retail media that sells, not just spends.
Get it freeRetail Media Campaign Measurement Report
Turn a finished retail media campaign into a performance readout.
Get it freeRetail Media Creative Brief
Brief the actual banners and video assets for your retail media ads.
Get it freeDigital Shelf Audit & Optimization Brief
Audit digital shelf health across retailers and flag what's broken.
Get it freeWant the live data behind sharper outputs?
These skills get better with real-time F&B intelligence. See what Tastewise can do for your team.