Brand Analytics

our updated brand analytics is in beta see docid\ m0x7o9e1hvysazjidrdp1 brand analytics gives brands visibility into how their categories, products, and skus are performing across the retail partners where they’re sold powered by real pos data brand analytics tabs docid\ hycv9afwen0aq6gj52hq0 transactional insights (order, revenue) docid\ ozjg qorh nlyg9kecpxi understand how you're acquiring and retaining customers over time docid\ cwmqhipbzizwtggs2n48g breakdown by retail partner carrying your products docid\ lhon36vhwwmemgjearbh5 analyze your customer base by age, gender, and region across all retail partners market spotlight market spotlight is currently being maintained with an intended deprecation in 2026 a date will be announced shortly see docid 4vvgj6pvxmctodb4fwmbl for help how to share a brand analytics report navigate to brand analytics set your desired date range using the "report" filter click the "share" button in the top right corner in the side drawer, select which tabs to include (all tabs are selected by default) click "generate link" and copy the link to share with others how to download analytics csvs navigate to brand analytics and select a tab (e g orders, demographics, etc ) scroll to the table you want to download (e g report period breakdown) click on the ( ) menu in the top right click "download csv" the downloaded csv reflects your current filter selections (date range, comparisons, products, etc ) how to compare periods compare any time period against a past period to identify trends and track changes click the "report period" filter and select your current time period click the "compare" filter and select a past period to compare against review the updated charts and tables past period data appears shaded in charts and marked "(past)" in tables a "% change" column shows the difference between periods filters saved filters access and apply previously saved filter configurations see below for instructions on saving a filter report period select the time range for your data analysis compare compare performance across different time periods to identify trends and changes select a comparison period to view metrics side by side with your primary reporting period (e g this month vs last month) companies & locations filter data by specific retail partners or store locations categories filter by product categories to analyze performance within specific product segments products filter by individual products or product groups useful for analyzing specific sku performance or comparing related products across retailers and locations when setting up filters, save time by inputting selections across filters and clicking 'apply' at the end how to save a filter save frequently used filter combinations to quickly access them later saved filters carry across all tabs where applicable navigate to brand analytics and select a specific tab apply the filters you want to save (time period, comparison, products, etc ) click the "save filters" link to the right of the filter row in the modal, enter a name for your filter click "save" to access the filters again in the future, click on the filter labeled "saved filters" and select your saved filter how to see analytics by alias / sub brand navigate to brand analytics in the top right, there will be a dropdown button to the left of the "share" button if your brand has multiple brand aliases, you'll see a dropdown that allows you to switch between them how to use aliases to clean up data product, category, and brand aliases allow you to take dirty data and make it clean you can map different naming conventions to a single "alias", resulting in more accurate and cleaner data docid\ cj sbmcmcq990ax23mi4r docid\ fbiuzhwhtoxvoqhw3fqc2 docid 7scv0hskazy2x00k2btbs faqs where did the category insights tab go? it has been deprecated as of february 2026 in the retail partners tab, i see a category listed that i don’t sell why is this showing up? brand analytics data is populated from pos data across mutual aiq retail partners if one or more of those retailers has that category configured in their pos, it may appear in your analytics, even if you don’t personally sell products in that category you can clean this up by using docid\ fbiuzhwhtoxvoqhw3fqc2 aliases to map categories so your reporting reflects how you want to view your data