Databox vs LeadJourney: KPIs from every tool on one dashboard against revenue per channel from your own tracking

Databox is a KPI dashboard: it connects to 130+ tools, shows their numbers on shared dashboards and scorecards, tracks goals against them and sends alerts. Every number on it was produced by a connected source. LeadJourney is an all-in-one attribution platform: it tracks on your own domain server-side, syncs spend from the ad platforms, follows the lead through the CRM stages to the closed deal, tracks the shop order through the Shopify integration or a manually connected shop, records calls with static and dynamic numbers as an add-on, attributes that revenue with every model including AI search as a source, sends stage changes back to Meta, Google, LinkedIn and Microsoft, and reports on all of it with Atlas. Databox shows the KPI; LeadJourney is where the marketing KPI comes from.

No, and it does not try to. Databox's breadth is the point of Databox: finance, product, support and marketing numbers on one scorecard, with unlimited users from Pro. LeadJourney covers the marketing part properly instead of broadly. It records the click and the conversion itself, needs only the ad platforms for spend, the organic and AI sources for the visit, the CRM for the stages and the revenue, the Shopify integration or a manually connected shop for the orders, and a webhook for the rest, and joins them per lead. That join, cost per qualified lead and revenue per channel, is the KPI a Databox source cannot report, because none of them knows which click made the deal.

Both publish their prices. Databox has a free plan, then Analyst at $64, Pro at $159 and Growth at $399 a month billed annually ($79, $199 and $499 monthly), with extra data sources at $5.60 each on Pro and Growth and a Custom tier on quote, all in US dollars. LeadJourney prices by marketing spend: €129 a month up to €5,000 of spend, €249 up to €15,000, €499 up to €50,000, €799 up to €100,000 and from €999 above that, monthly or yearly, with tracking and attribution included, after a 14-day trial without a card.

Yes, and that is the usual arrangement. Databox keeps the company-wide scorecard; LeadJourney supplies the marketing numbers it should show. There is no native Databox connector for LeadJourney, but Databox's own REST API accepts metrics from any source, and LeadJourney's API and Zapier app can push cost per qualified lead and revenue per channel onto the scorecard on a schedule. A data team reaches the same data today through the API, webhooks and the MCP connection; the data warehouse export to BigQuery or Snowflake is on the roadmap. Most teams then retire the ad platform tiles that disagreed with each other.

Genie answers questions and writes performance summaries on the metrics Databox has collected, drawing on 50 to 4,000 AI credits a month depending on the plan. Atlas answers questions about your campaigns, leads and CRM revenue across everything LeadJourney tracks itself, so it can say which campaign produced the deals that closed last month, not only how a metric moved. Atlas agents watch the data on their own and send daily or weekly reports to email, Slack or WhatsApp. The same data is open to Claude, ChatGPT or Cursor over MCP, as Databox's MCP server opens its metrics.

Not from what its pricing page lists. Databox connects HubSpot, Salesforce and Pipedrive as data sources, so deal counts and pipeline value sit on the dashboard next to the ad spend, but each source reports its own numbers and nothing on the feature list joins a deal to the click that started it. LeadJourney records that click on your domain, follows the lead through the CRM stages to the closed deal, attributes the revenue with every model, and sends the deal back to the ad platforms as an offline conversion so they optimise on it. That is the row the two tools differ on most.