Executive movement
What improved, declined, or remained stable since the previous reporting period.
For agencies
Make AI shopping visibility a measurable client service
Give ecommerce clients a recurring view of product recommendations, competitor wins, citations, and the actions most likely to close meaningful visibility gaps.
Report architecture
A report clients can understand and act on
Avoid a dashboard dump. Lead with movement and decisions, then preserve the prompt-level evidence for specialists who need to investigate.
Product visibility
Products recommended, shortlisted, missing, replaced, or described inaccurately.
Competitive shelf
Brands and products occupying the same high-intent recommendation sets.
Source landscape
Citations, retailers, and external pages influencing how products are framed.
Opportunity queue
Prioritized page, content, and product-information improvements with clear owners.
Recurring delivery model
Separate setup, monitoring, analysis, and execution
1. Establish
Define client products, competitors, markets, prompt clusters, and baseline classifications.
2. Monitor
Run the agreed prompt set on its recurring schedule and preserve historical outcomes.
3. Interpret
Explain recommendation movement, source patterns, inaccuracies, and competitor replacement.
4. Execute
Turn validated gaps into client-approved product, comparison, and content improvements.
Sell decisions, not a vanity score
The strongest agency deliverable ties every recommendation trend to evidence, business relevance, a responsible owner, and a measurable follow-up run.
Client setup standard
Make every account comparable without making every strategy identical
Standardize the measurement frame, not the client’s market. Each account needs an explicit product scope, prompt taxonomy, competitive set, languages, countries, merchant aliases, and reporting definitions before the first benchmark is presented.
- 1
Define scope
Brands, product families, priority SKUs, retailers, markets, and languages.
- 2
Build prompt cohorts
Category, problem, comparison, audience, budget, and branded shopping questions.
- 3
Set outcome definitions
Agree what counts as mentioned, shortlisted, recommended, linked, inaccurate, or replaced.
- 4
Capture the baseline
Archive answers and explain what the initial metrics do and do not prove.
- 5
Create the action register
Connect each recurring loss to an owner, evidence, deadline, and verification run.
A client report should explain what changed and what happens next
Visibility movement
Recommendation, shortlist, and merchant-link rates by prompt cohort and market.
Product winners and losses
The SKUs gaining visibility and the competitors replacing priority products.
Accuracy and risk
Incorrect specifications, positioning, price, availability, or seller information found in answers.
Source landscape
Domains and page types repeatedly cited around the client and competing products.
Completed work
Catalog, PDP, feed, content, and evidence changes shipped during the period.
Next actions
Prioritized work with an owner, expected evidence, and a future verification date.
Reporting guardrail
Do not imply that one content change caused an answer movement or that a tracked prompt represents all customer behavior. Use controlled cohorts, recurring runs, transparent definitions, and trend language.
Related intelligence
Continue through the AI shopping stack
Common questions
What teams ask about AI shopping
How can agencies package AI shopping intelligence?+
Agencies can build recurring services around prompt coverage, product and competitor visibility, citation analysis, content gaps, and prioritized recommendations.
Can reports be segmented by client market?+
Market and language-specific prompts should be separated so reports reflect the client’s actual operating context rather than blending unrelated answers.
What should an executive report contain?+
Include coverage, recommendation share, notable product gains and losses, competitor movement, source patterns, accuracy issues, and the next actions tied to evidence.
How should agencies prove progress?+
Use recurring prompt sets and consistent classifications. Compare recommendation outcomes before and after meaningful changes without presenting correlation as guaranteed causation.
Move from assumptions to recurring evidence
See where your products appear in AI shopping answers
Monitor buyer prompts, product recommendations, competitors, citations, and shopping visibility across supported AI platforms.