by LeadFollow (LX AI)
I started LeadFollow after noticing that most agents send the same thank‑you note after every showing, regardless of what happened during the visit. The message feels generic, and the chance to move the conversation forward slips away. Below is the way I shape the follow‑up to match the exact moment a buyer leaves the property.
When a showing ends, the agent opens the LeadFollow extension inside their email client. The tool pulls the property address, the date and time of the showing, and any notes the agent typed during the walk‑through. From that data it suggests a short message that reflects the stage the buyer is in.
The agent picks one of four stages: Initial thank you, Needs clarification, Ready for next steps, or Check‑in after a pause. Each stage maps to a different tone and call‑to‑action.
Based on the chosen stage, LeadFollow inserts placeholders for the property’s key features, any questions the buyer raised, and a suggested next step. The agent can edit the placeholders, add a personal anecdote, or change the wording before hitting send.
After the note is finalized, the agent sends it directly from their usual email address. LeadFollow logs the sent timestamp and later shows open and reply rates inside the dashboard, all without leaving the agent’s inbox.
Choosing the right stage is the core of a message that does not feel like a template. I describe each stage with concrete examples so you can see where it fits.
Below is the exact sequence I follow when I want to turn a showing into a meaningful conversation. Feel free to copy it into your own routine.
This workflow takes under two minutes per showing and keeps the communication relevant without sounding scripted.
I want to be transparent about where LeadFollow does not promise miracles. This section states plainly what the tool does not guarantee.
If any of those points feel like a deal‑breaker, LeadFollow may not fit your current process.
Even with a good framework, agents slip into habits that dilute the impact of a follow‑up. I list the most common slip‑ups and the concrete checks I built into LeadFollow to keep them from happening.
Without a stage selector, it is easy to default to a generic “Thanks for looking” note. LeadFollow forces a stage choice before showing any text, so the same template cannot be used twice in a row.
Some agents try to attach every brochure, price sheet, and inspection report in the first email. The tool limits the generated note to three sentences plus one optional link, encouraging brevity and clarity.
A note that reads like a form letter gets ignored. The placeholder system highlights where you must insert a specific observation — such as a comment about the buyer’s reaction to a room — before you can send.
If you wait too long, the moment fades. LeadFollow adds a automatic reminder that appears 20 minutes after you close the showing log, prompting you to send the note while the experience is still fresh.
Without data, you cannot improve. The dashboard shows open and reply rates per stage, letting you see which messages need tweaking and which are working.
I built LeadFollow to sit beside the tools you already use, not to replace them. Below are the ways I keep data in sync without manual copy‑pasting.
When you mark a showing as complete in your CRM, a webhook pushes the property ID and timestamp to LeadFollow. The extension then pre‑fills the showing details when you open the sidebar. Conversely, after you send a note, LeadFollow writes a activity log entry back to the CRM under the contact’s timeline.
If you schedule a second showing or a follow‑up call during the email thread, LeadFollow scans the message for date‑time patterns and offers to create a calendar event with one click. The event includes the property address and a link to the original email for context.
The suggestion engine relies on a language model that I monitor for safety. I consult the OWASP Top 10 for LLM Applications https://owasp.org/www-project-top-10-for-large-language-model-applications to check for prompt injection risks, and I follow the NIST AI Risk Management Framework https://www.nist.gov/itl/ai-risk-management-framework to document model behavior and mitigation steps. These references help me keep the generated notes accurate and free from unwanted bias.
Post-showing and nurture emails that keep you top of mind.
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Generated 2026-09-17 · primary sources only · no fabricated traffic metrics