What PrimeStreet actually does (from store listing)
The PrimeStreet System
CONNECTING TO THE RIGHT CLIENTS
Sales is a numbers game- the challenge is sifting through all the dead-end leads quickly to find those who are ready to go. PrimeStreet qualifies buyer and seller inquiries with only transaction-ready referrals connected to agents.
NURTURING
Buyers often need time to get their credit in order, save for a down payment, or wait for their current lease to expire. Historically, these consumers fall through the cracks while agents f…
Sales is a numbers game- the challenge is sifting through all the dead-end leads quickly to find those who are ready to go. PrimeStreet qualifies buyer and seller inquiries with only transaction-ready referrals connected to agents.
NURTURING
Buyers often need time to get their credit in order, save for a down payment, or wait for their current lease to expire. Historically, these consumers fall through the cracks while agents focus on people who are closer to transacting. The PrimeStreet system nurtures prospects until they’re ready and then passes the referral to the agent to be closed.
LIVE TRANSFER
Once a buyer or seller is ready to transact, PrimeStreet’s proprietary matching algorithm ranks agents nearby based on their probability to close. After an agent accepts the referral, an introduction is made from our call center and we coordinate a warm handoff to create trust with the buyer or seller.
Each forecast combines App Store rating, ratings count, monetisation model, pricing tier, IAP signals and ad-supported flag.
The base estimate is then multiplied by a per-category scaling factor learned from apps with founder-verified MRR.
Every number on this page comes from public APIs and bumetric's own snapshot history.
Full methodology covers input variables, accuracy bands per category and how we treat apps without comparable anchors.
See also the live data on PrimeStreet's tracker page for current rating, reviews and snapshot timeline.
Building something similar? Get a free AI audit with $-revenue forecasts for every recommendation.