See where your emails really land — and what it's costing you
An email campaign is only worth what actually reaches the inbox — but senders usually can't see whether their emails land in the inbox, the spam folder, or get blocked entirely, and it varies from one mailbox provider to the next. Worse, they have no way to connect those deliverability problems to real money: a campaign quietly landing in spam at Gmail can cost serious revenue without anyone noticing. Mailody needed a platform that shows customers exactly where their emails land across providers, why, and what it's costing them — in plain, actionable terms.
We built Mailody's Inbox Testing platform, which shows customers where their emails actually land across the major mailbox providers (Gmail, Outlook, Yahoo, GMX, Web.de and more) and flags whether they hit the inbox, spam or are blocked. It pulls placement results from a seed-list testing provider, checks sender authentication (SPF, DKIM, DMARC) per provider, and presents it all in a clear dashboard. Crucially, it connects deliverability to revenue: by integrating with the customer's e-commerce data (Klaviyo), it estimates the "potential missing revenue" tied up in emails that never reached the inbox. The platform also generates AI-powered, customer-facing deliverability analysis — using Claude (Anthropic) — that explains the results and recommends concrete fixes, which the team can review and send on. It ships as a customer-facing app plus an internal admin panel, all on a shared backend.
Customers can finally see, provider by provider, where their emails land and where authentication is failing — instead of guessing. By tying placement to real revenue, the platform turns an abstract "deliverability score" into a number that gets attention: the money being lost to spam and blocked mail. The AI analysis gives each customer a clear, written explanation and an action list, while the admin panel lets the team review and tailor it before it goes out.
We started with the core deliverability picture: ingesting seed-list placement results and presenting clear, per-provider inbox/spam/blocked outcomes alongside authentication checks. We then added the revenue layer — integrating e-commerce data so customers could see deliverability problems as lost revenue, which is what makes the product land commercially. Background workers keep results synced automatically. Most recently we added an AI analysis pipeline that turns each test's data into a written, customer-ready report with recommendations, designed so AI output supports the team rather than replacing their judgement — analyses are reviewed in the admin panel before they reach customers. The product was built as a customer app and an internal admin tool over one shared backend.
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