What is Shopping?

Shopping is the GetMint workspace that tells you whether (and how) your products show up when shoppers ask AI assistants for buying recommendations. It monitors five AI surfaces — ChatGPT, Google AI Overview, Google AI Mode, Microsoft Copilot, and Amazon Alexa Shopping — and tracks how every prompt that matters to your brand performs, daily, in every market you care about.

When someone types "What are the best running shoes for marathon training?" into any of these surfaces, the assistant answers with a shortlist of products, brands, and sources. Shopping captures those answers and turns them into analytics.

The four tabs

Filters at the top (date range, market, group, models, granularity) apply across every tab and persist as you switch between them.

Step 1: Set up a group (4-step wizard)

Creating data in Shopping starts with a group. Groups gather prompts that share the same market, competitors, and AI surfaces. The wizard guides you through:

Step 1 — Group

Give the group a name (e.g. "Marathon Shoes"), an optional description, and pick the market (country + language are inferred from the country choice).

Step 2 — Prompts

Add the buying questions you want to monitor. Type them one per line, or upload a CSV to bulk-import.

Step 3 — Competitors

Declare the competitor brands you want to track against. They become the "vs" reference in every chart and table downstream. GetMint can pre-suggest competitors based on your domain.

Step 4 — AI surfaces

Pick the AI assistants the prompts should be run against. You can select several at once. Each surface counts against your organization's prompt limits.

Step 2: Read the Overview

The Overview tab is the first thing you'll open every Monday morning. It's organized as a single scrolling dashboard.

• KPI row — top of the page. A handful of headline numbers with trend indicators (up/down/stable vs previous period).
• Share of Shelf — a donut showing how the category is split between your brand and the competitors you declared. Toggle to a trend chart to see how that share moves over time.
• Top Merchants chart — retailer share. Which marketplaces and shops show up most often in AI answers (Amazon, Best Buy, Wayfair, niche e-commerce, etc.).
• Top Offer Merchants table — a full-width table ranking the merchants that hosted offers cited by the AI, with the number of products and offers.
• Your Top Products / Competitor Products — two side-by-side tables. On the left, your most-surfaced products with average rank, rating (and rating trend), and price. On the right, the same view for competitor products.
• Competitive Landscape chart — a trend chart plotting your brand and your competitors over time on the same axis. Lets you see who's gaining or losing share at a glance.

Every table on Overview has a CSV export button so you can ship the data into your own reporting tools.

Step 3: Drill into Prompts (analytics)

The Prompts tab is a per-prompt × per-model analytics table. Each row shows one prompt running on one AI surface. Key metrics:

• Product Yield — share of responses where the AI actually returned a shopping carousel (vs a text-only answer with no products). High Product Yield = the AI takes this prompt seriously as a buying question.
• Mentions — how often your brand is mentioned in the response.
• Responses — total runs in the selected period.

A model column with model icons makes it easy to compare ChatGPT vs Google AI Overview vs Copilot on the same prompt.

Step 4: Track the Sources

The Sources tab tells you where the AI got its information. It has two angles:

• Websites — third-party domains the AI cited, ranked by frequency.
• Searches — the actual sub-queries the AI issued to the web before answering (web fan-out). These are gold for SEO: if ChatGPT searches "best marathon running shoes 2025 review" before answering, you want to rank for that query on Google too.

Step 5: Manage everything in Setup

The Setup tab is the day-to-day cockpit for groups and prompts. From Setup you can:

• See all your groups with their key metadata (market, models, prompt count).
• Edit a group (rename, change description, update market, change AI surfaces, edit competitors).
• Add a prompt inline to an existing group — without going back through the full wizard.
• Run a prompt manually to refresh data on demand.

Filters available everywhere

A persistent filter bar sits at the top of every tab:

• Date range — last 7 days, last 30 days, custom range.
• Market — narrow to one country.
• Group — focus on one prompt group.
• AI surfaces (models) — show one, several, or all assistants.
• Granularity — daily, weekly, or monthly buckets (Overview trend charts).

Filter selections are preserved as you switch tabs, so you set them once and read across the whole product.

Reading the raw AI answer

Every row in every table links back to a Raw Results dialog — the exact AI answer GetMint captured for that prompt × model × date, with full text, products mentioned, and citations.

Key takeaways

• Shopping monitors 5 AI surfaces: ChatGPT, Google AI Overview, Google AI Mode, Microsoft Copilot, Amazon Alexa Shopping.
• Setup flow: Add Group wizard (Group → Prompts → Competitors → AI surfaces).
• Four tabs: Overview, Prompts, Sources, Setup.
• Competitors are first-class — declared once per group, surfaced everywhere downstream.
• Key metrics: Share of Shelf, Product Yield, Top Merchants, Competitive Landscape.
• Filters apply across every tab and persist between sessions.
• Everything is read-only analytics.