Email open rate nearly tripled. 4.2% reply rate on a database that previously generated near-zero responses.
Engagement map
From operating problem to measured outcome
3 weeks delivery · 4 tools in the implementation stack
Challenge
A 12-agent team was sending a monthly market update email to 1,800 contacts.
What we built
We built a segmentation and personalization system on top of their CRM.
Result
Open rate jumped from 14% to 38% after the first two personalized campaigns.
Recorded outcomes
Delivery timeline: 3 weeks. Metrics are shown in the same context as the published engagement.
A 12-agent team was sending a monthly market update email to 1,800 contacts. It covered general market conditions, median prices, days on market, inventory levels. It looked professional, went out consistently, and got a 14% open rate. The problem: someone looking for a 3-bedroom in the suburbs got the same email as someone who'd inquired about a downtown condo two years ago.
We built a segmentation and personalization system on top of their CRM. Contacts are tagged by property type, price range, neighborhood preference, and engagement stage (active buyer, past client, cold lead). The monthly update pulls market stats relevant to each segment from MLS data, median prices for their specific criteria, new listings matching their profile, price changes in their target neighborhoods. Each email is generated fresh for that segment.
Open rate jumped from 14% to 38% after the first two personalized campaigns. Reply rate went from near-zero to 4.2%. The team attributed two listings and one buyer referral directly to contacts who responded to their personalized update within 60 days of the campaign.
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