Trendata Market Intelligence

Retrieves all available filter columns the current user has access to, contextualized by location and product. **Required Tool Calling Order:** 1. `get_locations_and_products_overview`: Discover high-level category names. 2. `lookup_location_and_product_ids`: Get the exact numeric `location_ids` and `product_ids`. 3. **`get_available_filters` (THIS TOOL)**: Pass the discovered IDs here to see which dynamic filters (e.g., Brand, Retailer) apply to this specific product/location combination. 4. `get_filter_options`: Discover valid exact string values for the columns returned here. 5. `get_filtered_data`: Finally, fetch the actual volume/time-series data. **LLM Usage Instructions:** The column names returned by this tool MUST be used as the exact 'keys' in the `applied_filters` dictionary when calling `get_filtered_data`.

Retrieves the available, specific filter values for up to 5 filter columns, scoped to the given location and product. **Required Tool Calling Order:** 1. `get_locations_and_products_overview`: Discover high-level category names. 2. `lookup_location_and_product_ids`: Get the exact numeric `product_ids`. 3. `get_available_filters`: Discover valid filter columns for these IDs. 4. **`get_filter_options` (THIS TOOL)**: Pass up filter column names, PLUS the same `product_ids`, to see what values you can filter by. 5. `get_filtered_data`: Finally, fetch the actual volume/time-series data using these options. **LLM Usage Instructions:** The string values returned by this tool MUST be used as the exact 'values' in the `applied_filters` dictionary when calling `get_filtered_data`.

Fetches time-series volume data with support for dynamic filtering across multiple strategic datasets. **Dataset Descriptions (`datasets` argument):** - "Strategische Dataset - Total": Baseline dataset for high-level, unsegmented overall trends. - "Strategische Dataset - Merk": Use for brand-specific data (e.g., Nike, Samsung). - "Strategische Dataset - Retailer": Use for store/vendor-specific data (e.g., Bol.com, Amazon). - "Strategische Dataset - Specifications": Use for product features, sizes, colors, or technical specs. - "Strategische Dataset - Customer Segment": Use for audience demographics or user segments (e.g., children, women). - "Strategische Dataset - Purpose": Identifies the specific use-case, environment, or gifting occasion driving the purchase. - "Strategische Dataset - Information": Use for analyzing what information needs consumers have. - "Strategische Dataset - Purchase Intention": Use for commercial intent signals and buying readiness. **LLM Usage Instructions:** 1. **Overviews & Comparisons (CHOOSE A DATASET):** In order to get an overview or compare different dimensions, you MUST explicitly choose the exact string names from the list above and pass them via the `datasets` argument. 2. **Optional Specific Filtering (USE APPLIED FILTERS):** In order to filter the dataset on specific dimensions (e.g., isolating the data to only show "Nike" or only "Sneakers"), you MUST use the `applied_filters` argument. - Use `get_available_filters` and `get_filter_options` to discover appropriate filters. - Example `applied_filters` payload: { "brand": ["nike", "adidas"], "category": ["sneakers"] } 3. **Optional Location & Product Context:** Use `get_locations_and_products_overview` and `lookup_location_and_product_ids` to find relevant `location_ids` and `product_ids`. 4. **State-level Data (HIGHER TOKEN COST):** Only set `group_by_state=True` if the user explicitly asks for state-level or regional breakdowns. Because this exponentially increases the size of the returned data, default to False for all general market queries to conserve tokens. 5. **Defaults:** All filters (location, product, applied_filters) and datasets are OPTIONAL. If no dataset is explicitly provided, the tool defaults to "Total".

Retrieves a top-level overview of the master hierarchy for Locations and Products (Categories). **LLM Usage Instructions:** 1. Call this tool FIRST to understand the available categories without cluttering the context with IDs. 2. Extract the exact string 'value' (names) from this response. 3. Pass those exact strings into the `lookup_location_and_product_ids` tool to fetch the actual integer IDs.

Retrieves specific IDs from categories using lookup terms. **LLM Usage Instructions:** 1. Call this AFTER using `get_locations_and_products_overview`. 2. Provide an exact string match for `location_lookup` or `product_lookup` based on the overview. 3. Traverse `subOptions` in the response to find specific subcategories or states. 4. CRITICAL: Extract the integer `location_ids` and `product_ids`. You MUST use these integers as arguments for all subsequent data and filter tools.