--- title: "Create new visualizations in Omnichannel Insights" slug: "searching-omnichannel-insights-in-explore" tags: ["insights", "platform", "sales", "dashboard", "omnichannel manager ", "data model"] updated: 2025-01-22T08:36:20Z published: 2025-01-22T08:36:20Z canonical: "docs.newstore.com/searching-omnichannel-insights-in-explore" --- > ## Documentation Index > Fetch the complete documentation index at: https://docs.newstore.com/llms.txt > Use this file to discover all available pages before exploring further. # Create new visualizations in Omnichannel Insights Search data to create Insights reports for your key performance indicator (KPI) use cases. These insights can then be used as custom widgets for your custom liveboards. See [Managing Omnichannel Insights](/v1/docs/managing-omnichannel-insights#omnichannel-insights) for more information on sales reports and dashboards and a way to get started with the templates that are provided. In this guide, we demonstrate a small sample of available metrics. These examples are designed to illustrate a method of querying data that can be used across all the available data: - Net Sales for a specific store - Item-level activity tracking - Returned items by selling associate name ## Use cases To understand the terminologies used in the omnichannel insights, see [Managing Omnichannel Insights](/v1/docs/managing-omnichannel-insights#omnichannel-insights). ### Items sold by the store In this scenario, you can see that the New York 5th Ave store sold a series of items via multiple attributed associates. This is accomplished by filtering the data on `Sale Location = "new york 5th ave"`. ![](https://cdn.document360.io/c2d22fcd-a44b-4e1e-bf3a-84f0ffba0dbe/Images/Documentation/e83fed3d-1439-4b30-a2a4-455e48524f8b.png) ### Tracking the lifecycle​ of an item In this scenario, you can see an e-commerce order was placed, routed to a DC which did not have the expected available inventory and was rejected. The item was then re-routed to the New York 5th Ave store and fulfilled from there. ![](https://cdn.document360.io/c2d22fcd-a44b-4e1e-bf3a-84f0ffba0dbe/Images/Documentation/9e120396-dc3b-449a-9fc2-b0e6dd102a11.png) In order to replicate this data set in `Insights > Explore`, navigate to `Search Data`, add the columns shown in the table above by typing them into search, or double clicking the fields on the left to add them to the search bar, then filter on a single Order or Item Order ID (UUID) that required fulfillment. ## Activity schema data model An activity schema models an entity taking a sequence of activities over time. For example, a sales associate (entity) has completed an item refund (activity). Each row in the table represents a single activity taken by the entity at a point in time. In other words, it has an activity identifier, an entity identifier, a timestamp, and some basic metadata called features. The following image shows a representation of the data model, illustrating the exclusive groups of attributes; Common or Activities, Sales, Return, Fulfillment, etc. Columns and Rows orient attributes into groups and their members. ![](https://cdn.document360.io/c2d22fcd-a44b-4e1e-bf3a-84f0ffba0dbe/Images/Documentation/bd74f264-180a-4519-be58-3ffb4a0234cd.png) For sales, Sale Price Net is important because it reflects the actual price paid that is reduced by discounts. **Sale Price Net does not include tax.** Sale Price Tax is broken out as a separate field that can be added to Sale Price Net via a formula, if needed. ## Searching and pinning data to a liveboard After you study the data model, you can start querying your data sources to fetch relevant insights from your business. The formulas or data sources can be used as an important tool to analyze a specific metric about your business transactions. Refer to the Net Sales formula example in the above-mentioned section. - Navigate to `Insights` > `Search Data` and select the `wrench` icon to see the new data source or to add a new formula to drill-down to granular level details. - Navigate to `Insights > Search Data` and add a new formula by selecting the `+` sign next to `Formulas..`. For more information, see [Understand formulas in searches](https://docs.thoughtspot.com/software/latest/formulas). > [!TIP] > Note > > Ensure you are using the latest data set, which introduces Net Sales and fulfillment data. > > The templates (such as `Template - Daily Sales` or `Template - Omnichannel`) are using the latest data set and can be copied. > > Additionally, while selecting `Search data`: > > 1. Select the wrench icon next to `Sources` in the top right corner. > 2. Selecting the `Activities`, `Clienteling Conversations`, or `Clienteling Sales Attribution` data sources. Below are some examples of how to achieve some common metrics. **How many orders happened today?** The data set is at the item level, so it is important to `unique count Order` to count orders for a time period. Similarly to count Items for a time period, use `unique count Item`. To show how many orders happened today, use the following search query: `Activity Date = today unique count Order Activity Type = item` **What are the sales for last week?** For sales, `Sale Price Net` is important because it reflects the actual price paid that is reduced by discounts, and without tax. `Sale Price Tax` is broken out as a separate field that can be added to `Sale Price Net` via a formula, if needed. To show the sales for last week, use the following search query: `Activity Date = last week Sale Price Net Activity Type = item` Adding something such as `Sale Location` , or `Sale Attributed Associate Name` can let you know which store sold the item, and which associate was credited with the sale. **What is the average order value?** `Sale Price Net` is the value of the item without taxes (Price Tax). Take the sum of all of `Sale Price Net` and divide by the unique count of Order IDs. This will require a formula to be able to do this calculation. To see how this works, make a copy of the AOV widget on the default `Daily Sales Overview`. To add a new formula to a search: 1. Select the `+` sign next to `Formulas` on the left side of the `Search Data` screen. 2. Next, use the `Formula Editor` to take the sum of all orders, and divide by the unique count of order IDs. The `Formula Editor` will be shown as follows: ```plaintext safe_divide (sum ( Sale Price Net ), unique count ( Order ID )) ``` 3. Saving the formula will automatically add the new field into the search bar and the data will populate. You can build on what has been presented in the templates by going to an existing liveboard, and by clicking `...` in the top right corner of a liveboard/widget and by choosing `Make a copy`. 4. After the search is complete, pin the answer to a liveboard by selecting `Pin` in the top right corner. ## Finding and understanding data fields To view all available fields, select `Search Data` in `Explore` so the left side of the screen will show all available columns in the data. Hovering over an item in the list will display more detailed descriptions. **Related topics** - [Managing Omnichannel Insights](/v1/docs/managing-omnichannel-insights#omnichannel-insights)