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Location analytics is the map of your marketplace. It tells you where customers want leads (active bids, top prices, interested buyers) and where they’re actually getting them (received, assigned, and charged amounts). When the two sides don’t match (heavy demand in Miami but barely any leads flowing), that’s a supply gap you can close with more sourcing, better ad targeting, or price adjustments. This guide walks through using the analytics views to find those gaps and act on them. For the metric definitions themselves, see the Location analytics feature page.

Prerequisites

  • A role that can view analytics. If the Locations group isn’t in your sidebar, ask an admin on your account.
  • At least a few weeks of lead and bid history. The metrics need volume to be meaningful, so fresh workspaces will see mostly zeros.
  • (Optional) A specific question you’re trying to answer, like “Where are we underpriced?”, “Which states have unmet demand?”, or “Do any counties have bids but no leads?“

1. Open the Locations views

In the sidebar, find the Locations group. It has three pages. Single-country workspaces see that country’s own terms automatically. Multi-country workspaces see combined labels such as States / Territories and Counties / Postcodes. Click Counties (or whichever level fits your question). The table loads with one row per location.
Counties list with demand and lead value columns for each countyCounties list with demand and lead value columns for each county

2. Read the two sides of the table

Bids (the demand side)

Leads (the supply side)

The gap between Active and Received is the headline signal. Many active bids but few received leads means unmet demand, which usually means ad spend or source partnerships belong here. Few bids but many leads means oversupply, which usually means you should recruit more buyers or lower prices.
Sort by Active descending to find your hottest territories. Then scan Received next to each. If it drops off sharply, you’ve found a supply gap.

3. Pick a timeframe and filter by lead type

The lead columns cover the timeframe picked in the top-right of the page (Billing period, Today, 7D, 4W, 3M, 12M, MTD, Last month, YTD, All, or a Custom range). The bid columns always reflect your bids as they are today.
Timeframe picker open with preset ranges and a Custom optionTimeframe picker open with preset ranges and a Custom option
Then click Filters and use Lead types to narrow the view to one or more lead types. Every column recomputes against just that slice. This is where the analysis gets actionable.
  • Unfiltered view gives you the aggregate picture, useful for territory strategy.
  • Filtered to one lead type surfaces product-specific gaps, like “we have 40 bids on this lead type in Texas but only 12 leads landed last month.”
The Counties view adds a State filter, plus Country for multi-country workspaces, so you can narrow to a region before exploring counties. Filters live in the page URL, so you can bookmark a view you check often.

4. Drill into a specific location

Click any row to open the location’s page.
County page with overview tiles, a values row for the last 30 days, a table of county bids with status columns, and the county's ZIP codes in the sidebarCounty page with overview tiles, a values row for the last 30 days, a table of county bids with status columns, and the county's ZIP codes in the sidebar

Overview tiles

  • Active Bids are bids ready to receive leads here.
  • Interested Customers counts distinct customers with any bid on this location, including paused or underfunded ones. The gap between Active Bids and Interested Customers is latent demand, meaning customers who’ve expressed interest but aren’t currently buying. When you re-activate them (fund wallets, lift caps), that demand becomes real.
  • Top Bid is the highest current bid amount.

Values

Four more tiles cover the selected timeframe (the last 30 days unless you’ve picked another), each compared with the previous period of the same length.
  • Leads assigned, with a sparkline.
  • Minimum / Maximum / Average Value.
Rising values mean the market is heating up here, and falling values mean it’s cooling. Combine them with the Active Bids count. Rising values plus plenty of bids means double down, while falling values plus few bids means reconsider your investment.

Bids

A table of the bids set at exactly this level (county bids on a county, state-wide bids on a state, nationwide bids on a country), with the customer, customer status, lead type, amount, and the bid’s Operational, Funding, Cap, and Budget status. Sort by amount to see who’s actually at the top. Use Filters to find, say, every bid here that’s out of funds, then follow up with those customers from their customer page.

Child locations

The sidebar lists what’s inside the location as plain text, so a county shows its postal codes and a state shows its counties. Country pages don’t list children, so go to States and filter instead.
Countries list showing nationwide demand and lead values per countryCountries list showing nationwide demand and lead values per country

5. Export counties to CSV (optional)

The Counties page has an Export button in the top-right. The other views don’t. Counties are the most granular level, so that’s where exports are most useful. Click Export. Your lead type and location filters are respected, but the timeframe isn’t. The file is built in the background, and a County export complete notification lands in the notification bell with a download link when it’s ready. Use the CSV for things like these.
  • Ad-spend allocation models. Pull it into a spreadsheet, overlay cost data, and compute cost per assigned lead by county.
  • Source-partnership pitches. Show a partner the specific counties where you have demand but no supply.
  • Territory reviews in quarterly business reviews.
States and Countries don’t have an export. If you need a state-level roll-up, export counties and pivot by state in your spreadsheet.

6. Act on the patterns you find

The analytics views are only useful if they change what you do. Here are a few common patterns and the actions they imply. Many active bids, few leads received
  • High demand and low supply, so close the gap.
  • Act by recruiting new sources for that region, increasing ad spend on geo-targeted campaigns, or onboarding a partner with supply there (Adding a partner).
Few active bids, many leads received
  • Oversupply, meaning not enough buyers or prices are wrong.
  • Act by recruiting more customers in that region, running a marketing campaign targeting those customers, or revisiting pricing (see Bidding).
High Top Bid, low Avg Value
  • Customers are willing to pay a lot, but auctions are clearing low, which likely means thin competition.
  • Act by telling existing customers about the territory (through notifications or banners, as in Publishing a banner), or by raising the minimum bid on the lead type’s bidding scopes (see Setting up bidding).
High Interested Customers, low Active Bids
  • Lots of paused or underfunded bids. The demand is latent.
  • Act by nudging customers to re-fund wallets (auto-recharge, Managing customer finances), or by diagnosing why they paused (caps hit, too expensive, churned).
Values falling against the previous period
  • The market is cooling here. Budget attention elsewhere.

What happens next

Here’s what a regular rhythm of reading location analytics looks like.
  • In a weekly scan, sort Counties by Active, scan the Received column, and flag any wide gaps for the supply team.
  • With monthly CSV exports, feed a P&L-by-geography dashboard so finance and ops share the same map.
  • In a quarterly territory review, compare this quarter’s top-demand counties to last quarter’s. Customer behavior shifts, and your sourcing should track it.
  • For ad-hoc checks, whenever a customer asks “why am I not getting leads in X?”, open X’s location page to see exactly how many bids compete there and what top-bid you’re up against.
Location analytics is a reference surface, not a dashboard you stare at all day. Build the habit of opening it with a specific question, and it’ll pay for itself every time you spot a gap before the customer does.