ChatGPT Plugin

Sweet Analytics

Ask your data anything.

Brand: Sweet Analytics

Category: Data & Analytics
Primary Subcategory: Self-Serve BI & Conversational Analytics

Integration details

Description

Sweet helps ecommerce teams understand sales, marketing, customer, product, discount, refund, and profit performance using their connected Sweet data. Ask questions in plain language, such as what drove sales growth, which marketing channels are most efficient, how customer retention is changing, which products or discounts are affecting margin, or where refunds are impacting profitability. Sweet returns clear summaries, KPI comparisons, segment breakdowns, and practical insights so teams can make faster trading, marketing, and retention decisions from the data they already use.

Integration type: Plugin
Verification status: Not applicable
Platform: ChatGPT
Category: Data & Analytics
Primary Subcategory: Self-Serve BI & Conversational Analytics
Secondary Subcategories: None listed
Brand: Sweet Analytics
Access: Account required
First tracked: 2026-07-04
Tool count: 88
Market: US

Agent DiscoverabilityChatGPT Plugin Discovery Score

ChatGPT organic discovery is live

Your score is coming

ChatGPT now suggests Plugins on its own when they match a user's request.Your Plugin Discovery Score measures how often yours appears, and it will show here as soon as it’s ready.

ChatGPT recommends Airtable when a user asks it to update a CRM. — ChatGPT surfaces Airtable because it matches the user's request.

Primary Subcategory

Competing in ChatGPT Self-Serve BI & Conversational Analytics

View Category

Listed in alphabetical order

Primary Subcategory

ADECIComing soonGet notified

Adzviser Google AnalyticsComing soonGet notified

Adzviser ShopifyComing soonGet notified

AI for DatabaseComing soonGet notified

AI2SQLComing soonGet notified

Sweet AnalyticsComing soonGet notified

Tools

88 tools agents can invoke

Get an over time (time series) chart for orders, sales and customers for each marketing channel for a given attribution model across a date range.
Get a side-by-side marketing channel attribution table comparing channel performance between either two attribution models or same model between two date ranges.
Get attributed marketing channels for each Growth Model segment cohort broken down by primary vs secondary orders
This analysis shows the number of customers who placed both primary (i.e a first time order) and at least one secondary order (any subsequent orders) in the period of time selected. The primary order is attributed based on the selected attribution model. In terms of secondary orders, the table shows the touchpoints customers are using to repurchase (secondary orders). Use this tool to understand whether customers are returning via the same marketing channels; and particularly whether they are moving to more cost effective channels - eg organic search, direct or email - or they continue in more expensive paid channels, such as paid search.
Get the top 5 channels by attributed orders and sales, and customer acquisition.
Get the total number of audiences configured for the workspace.
List accessible clients/brands/accounts for the current user. Use this before analytics calls when the user mentions a brand, client, account, or customer by name and you need to resolve it to a clientScope client id or exact client name. For example, if the user asks "What were sales for Aspiga last week?", treat Aspiga as a possible brand/client name, call this tool to resolve it, then run the analytics tool with clientScope set to the resolved client. Only partner users can use this tool.
List the shops/stores available to the current user. Use this before analytics calls when the user asks about a specific store, shop, country, region, market, or location (for example US, USA, United States, UK) and you need to resolve that wording to a storeScope shop id or exact shop name.
Get channel-level reporting matrix data for a date range and grouping.
Get sales metrics chart data (ROAS, CAC, CPO and cost %) for cost reporting.
Get summary metrics for cost reporting in the selected date range.
Get total discount usage metrics with comparison to a prior period. Use this tool to understand the total discount usage and its impact on your revenue.
Get a time-series of total discount activity with comparison values for the prior period. Use this tool to understand the impact of discounts on your revenue over time.
Get a time-series of shipping discount metrics with comparison to a prior period. Use this tool to understand the impact of shipping discounts on your revenue over time.
Get shipping discount KPIs (average and lost shipping revenue) with comparison to a prior period. Use this tool to understand the impact of shipping discounts on your revenue.
Get a paginated leaderboard of the top discount codes ranked by usage and value, with prior-period comparison. Use this tool to understand the most used discount codes and their impact on your revenue.
Filter the supplied channels list down to those with non-zero cost-manager rows in the rolling window.
Get day by day sales, marketing costs, ROAS and CAC metrics. Use this tool to ensure that marketing investment is delivering the required ROAS.
Get available dashboard filters such as audiences, coupon codes, channels, channel groups, and RFM segments. Use this tool if you need to apply filters to other dashboards, specifically sales, insights, discounts, and refunds tools.
Analyzes the impact of key sales metric (new customers in FY, AOC, AOV) for new customers in the financial year and how each metrics impacts total sales.
Provides a breakdown of metrics for each Growth Model cohort/segment. GM segment definitions: NEW - new customers in the current financial year PYNEW - new customers from the previous financial year PYNON - customers who purchased in previous financial year and in any prior year(s). Customers not newly acquired in the previous year PY1INACT - customers who did not purchase in previous financial year but rather 1 year prior PY2INACT - customers who did not purchase in previous financial year but rather 2 years prior PY3INACT - customers who did not purchase in previous financial year but rather 3 years prior or more Use this tool when you need to understand the performance of each Growth Model cohort/segment to understand customer retention and acquisition patterns.
Analyzes the impact of growth model metric (opening customers in FY, retained percentage in FY, productivity). Opening customers are number of customers are the beginnign of the period/FY. Retained percentage is the percentage of opening customers that purchased during the period. Productivity is the average revenue per retained customer.
Provides Growth Model metrics per segment for the selected fiscal year. Use this tool when you need the raw data to build your own custom growth model
Get Microsoft (Bing) Ads KPIs for each metric with their corresponding targets. Use this tool to understand whether Microsoft (Bing) Ads performance is meeting or exceeding targets.
Get email marketing KPIs for each metric with their corresponding targets. Use this tool to understand whether email marketing performance is meeting or exceeding targets.
Get Google Analytics-attributed KPIs for each metric with their corresponding targets. Use this tool to understand whether Google Analytics performance is meeting or exceeding targets.
Get Google Ads KPIs for each metric with their corresponding targets. Use this tool to understand whether Google Ads performance is meeting or exceeding targets.
Get marketing KPIs for each metric with their corresponding targets. Use this tool to understand whether marketing performance is meeting or exceeding targets.
Get Meta Ads KPIs for each metric with their corresponding targets. Use this tool to understand whether Meta Ads performance is meeting or exceeding targets.
Get sales performance KPIs for each metric with their corresponding targets. Use this tool to understand whether sales performance is meeting or exceeding targets.
Get sales metrics broken down by a given dimension such as channel, country, province, city, shipping city, frequency of units, frequency of products, channel, channel group, payment method, and shipping method.
Analyzes the average time between repeat purchases across the requested window breaking the data by primary and secondary orders (including a breakdown by the order number). Use this tool when you need to understand the average time between repeat purchases for first order to second order, second order to third order, etc. within the selected and compare periods.
Get a detailed metric breakdown comparing the current period to the comparison period broken down by new and existing customers. Use this tool when you need a complete view of key sales metrics vs the compare period.
Get a time-series of sales metrics split by new and existing customers and total.
Get a heatmap dataset comparing the day of the week and time of day that customer cohorts purchase. Can be looked at by number of orders or value of orders.
Analyzes the impact of product-level metrics (orders, average selling price, units per order) on sales performance by measuring the impact of each individual metric on total sales compared to the comparison period broken down by new and existing customers. Use this tool when needing to understand the value impact of order-level metrics to understand what drove higher or lower sales vs the compare period.
Get purchase-gap distribution metrics describing the average time between repeat purchases.
Analyzes the impact of sales metrics (customers, AOV, AOC) on sales performance by measuring the impact of each individual metric on total sales compared to the comparison period broken down by new and existing customers. Use this tool when needing to understand the value impact of customer-level metrics to understand what drove higher or lower sales vs the compare period.
Get customer lifetime value for cohorts grouped by the month that each customer made their first order (can also we looked as weekly or yearly cohorts). Use this tool to understand the customer lifetime value for each cohort and how it changes over time. Analysis can be run for a given audience or comparing two audiences
Analyze customer lifetime value by order sequence. Rather than time based, we look at second, third, fourth, etc orders, regardless of when they were placed. Use this tool to understand the customer lifetime value by orders removing the time aspect. Analysis can be run for a given audience or comparing two audiences
The Margin Calculator is your key tool to calculate the Return on Advertising Spend (ROAS) that is required to deliver the profitability for your business. Use the get_margin_calculator_syncable_values` tool in case the inputs have not been provided by the user to set defaults based on their data.
Get default margin calculator inputs derived from orders and costs data. Use this tool for defaults to the inputs required for the `get_margin_calculator` tool.
Get the marketing summary comparing ecommerce conversions vs synced marketing conversions. Use this tool to get a top-level view of how marketing platforms are reporting conversions/value compared to your actual sales.
Summarises and blends the impact of marketing data with your actual sales data to show the impact of marketing spend. Use this tool to understand the impact of marketing spend on your sales beyond what the marketing platforms tell you.
Analyzes each marketing platform and provides a detailed breakdown of Conversions, Conversion Value, Cost, CPA, and ROAS. Use this tool to get a detailed view of how each marketing platform is performing.
Get a paginated list of orders with optional filtering by channel, attribution, audience, and free-text search. Use this tool to get a list of orders and their details or search for a particular order by customer or ID.
Get a time-series PPC chart broken down by a specific dimension.
Get a paginated table of PPC media performance broken down by dimension.
Get the SKU/product margin breakdown compared to a prior period.
Get return rate metrics derived from refunds and order indexes.

FAQs

Sweet Analytics ChatGPT Plugin FAQ

How the directory, categories and Discoverability Score work.

Read the methodology

How do I improve Sweet Analytics's ChatGPT Plugin discoverability?

The levers are the listing surface agents actually read: names, descriptions, keywords, tool metadata, and registry health. Which lever matters depends on where discovery breaks, which is what continuous measurement shows.

What are Sweet Analytics alternatives on ChatGPT?

As of 2026-11-02, Sweet Analytics competes with ADECI, Adzviser Google Analytics, Adzviser Shopify, AI for Database, AI2SQL, Alteryx Insights, AnalyticsLog, Anomaly AI and 81 more in ChatGPT Self-Serve BI & Conversational Analytics, ranked by public Discoverability Score.

Where is this profile measured?

This profile uses the geography attached to the latest public registry snapshot: US. Locale tags are intentionally omitted.