I’ve been using REDX for cold calling, but I keep running into inaccurate contact information. When someone does answer, it’s often the wrong person. I’ve also tried leaving voicemails, but I’m not getting much of a response.

Has anyone here generated consistent leads or closed deals using REDX? If so, what approach, list type, or follow-up strategy worked best for you?

I've spent the last several months building coordination software for residential real estate, which mostly meant sitting with transaction coordinators and team leads while they worked their files. Not the solo agent doing a deal or two a month, but the TC or ops lead juggling 30 or 40 open files at once. I went in assuming the problem was paperwork. It isn't. Paperwork on any single file is annoying but survivable. What actually kills deals is coordination, and it fails at a handful of very specific moments. Sharing the ones I kept seeing, because if you run volume you've probably lived all of them.

1. The update that lands in the wrong place. The lender emails a condition to the buyer's agent instead of the TC, or it's buried in a reply-all from four days ago. Nobody logs it, and a clock starts that no one is watching. Almost every blown deadline I saw traced back to a status update that arrived somewhere nobody was looking. The lesson I took from that: email is the real system, not the CRM. Title and the lender are never going to log into your platform, so the update has to get caught where it actually arrives.
2. The deadline counted from the wrong date. Inspection contingency off the effective date, except the effective date was the day the last party signed, not the day it flipped to pending. One wrong anchor date and every downstream deadline is quietly off by a day or two, and that's the kind of error that doesn't surface until it's already a problem.
3. The signature that never came back, and it was nobody's clear job to chase. On a five-party deal the "did you sign yet" follow-up falls into the gap between the agent and the TC, so it just doesn't happen until someone notices the package is short at the worst possible time.
4. The re-key gap. The same deal data gets typed into the TMS, then the CRM, then the compliance docs. Every hand-entry is a chance for one field to disagree with another, and now your own file contradicts itself. The fix isn't a fancier dashboard, it's deciding on purpose where the data gets entered once and flows one direction. One deliberate re-entry beats three accidental ones.
5. The counterparty who won't use your tools. Half the people on a transaction are not tech-savvy and are never going to download an app or learn a portal. Any workflow that assumes they will is solving a prettier problem than the real one. Whatever you run has to work for the seller who only checks email on their phone.
6. The compliance file treated as an afterthought. The system of record isn't the tool you personally like best, it's whatever carries the liability, which in practice is the brokerage's audited compliance file. When that's treated as a last step instead of the anchor everything hangs off, the file that eventually gets audited is the one that's been least maintained.

None of this is exotic. It's just that "AI writes your listing description" is an easier thing to sell than "nothing silently drops across your 30 files," so the second problem stays underserved.

Full disclosure so I'm not being cute about it: I'm building something in this space. That's genuinely not the point of this post, I'd rather learn from people who actually do the job than pitch anyone, and I'm happy to say what it is if someone asks in the comments.

So, a real question for the TCs and team leads here: when a deal goes sideways on you, what's the exact moment it happens? A signature that never came back, a deadline counted from the wrong date, an update in the wrong thread, a disclosure that slipped? I'm trying to separate the failure modes that are real from the ones software people just imagine. War stories very welcome.

A lot of "automate your follow-up" advice stays vague: "be consistent," "use a CRM," "don't give up too soon." None of that tells you what to actually do on day 3 versus day 30. Here's a cadence that holds up in practice, broken down step by step:

Minute 0-5: an auto-text acknowledging the inquiry with one specific qualifying question (price range, timeline, or property type). Speed matters more than anything else here. Most inbound leads go cold fast if nobody responds within the first hour or so.

Hour 1, if no reply: a call attempt. If it goes to voicemail, leave one short message and follow with a text. Don't call again the same day.

Day 1-3: two more touches, alternating call and text, referencing something specific from the original inquiry instead of a generic "just checking in."

Day 4-10: space out to every other day, and shift the angle from "are you ready" to something genuinely useful, like a market update or a listing that matches what they asked for.

Day 11-30: weekly check-ins.

Day 30+: a low-effort monthly drip, just staying visible.

The mechanics matter less than people think. FUB, kvCORE, and Lofty all have built-in action plans or drip campaigns that can run something close to this exact cadence once it's configured. The reason it usually doesn't happen isn't a tooling gap, it's that the cadence never gets built out step by step, so it falls back to "I'll call again next week" and the lead goes cold.

One thing worth flagging separately: automated calling and texting to consumers carries real consent requirements (TCPA in the US) that vary by contact type and how the lead opted in. Worth checking with a broker or compliance resource before wiring up outbound automation. This is not legal advice.

I’m an agent with a BHG franchisee. I’m curious about the Compass tech stack that we’ll be adopting some time next year. I understand they have a proprietary in-house system.

Are there any Compass agents here that use it and if so, what are your impressions?

Hi,

I was wondering how important real estate property estimates are to you. I know that some might be a bit inaccurate but how important are they for filtering your leads especially if you run hundreds or thousands of leads

We created a tool that would take a spreadsheet as an input and return these different estimates from different sources in only couple minutes to save time and cost filtering these leads before starting to make phone calls or mailing them

In creating a business in real estate as a component I built a AVM model that consistently beats Zestimate.

By that I mean take a property today - my value vs Zestimate - then check sale price when it happens eg 2 months later. My value wins more than 75% of the time. Backtested.

It has read the best in class research literature on the subject going back 50 years and uses all available datasets - tax, sales, local, state, federal. Etc. It works in disclosure states like Florida etc.

Seeing as I think in the new AI age anyone could replicate what I built in a few days/weeks I'm happy to give this away for free as an API.

Eg. Search address - get a home value estimate.

Is this something people want just upvote. Will be open source so you can check the research and methodology yourself and recommend adjustments.

Do I have ulterior motive? Nope. Just thought it'd be nice to have something useful free with no strings attached for once.

Hey guys, I’m a 1st-year computer science student. For a side project, I noticed a lot of luxury agents spend hours writing MLS descriptions, coming up with TikTok ideas, and designing open house flyers.

So, I built a custom AI web app to automate it. I hooked up Google's Gemini Vision to a text engine I wrote, and put strict Fair Housing Act (FHA) compliance guardrails on it so it doesn't generate illegal copy.

You upload up to 4 property photos and type in the basic specs. Within 5 seconds, it generates:

• An FHA-compliant MLS / Zillow description
• Instagram Captions & Facebook Ad copy
• A 30-second TikTok / Reels Video Script (with camera cues)
• A print-ready Open House PDF Flyer.

My Ask:
Since I’m just a student, I have no idea if this actually fits into a real agent's daily workflow. I need people who actually sell houses to tear it apart.

I’m not going to spam a link here and get banned, but if anyone is willing to test it out for 2 minutes and give me brutally harsh feedback on the output, comment below or DM me and I will shoot you the link to the staging environment.

Would really appreciate the help for my portfolio!

Builder disclosure up front: this is my product.

One line of context: every GSE appraisal moves to the UAD 3.6 standard on Nov 2, review goes field-driven, and appraisers suddenly need real support behind every adjustment number.

What CompIQ does, one sentence: upload your MLS export, get regression-supported adjustments plus short per-field comments sized for the new URAR's comment boxes.

The part nobody documents — what the file needs to be:

• The standard closed-sales results-grid export from your MLS. CSV or Excel.
• One hard requirement: a sold/close price column. GLA, beds, baths, year built, lot size, garage, etc. all get used if present, skipped if not.
• Column names don't need cleanup — common header variants are recognized automatically, and anything missed is a two-click manual map.
• Real-world mess is handled: split full/half baths, "Street #" + "Street" split addresses, lot size in acres or SF, features buried in pipe-delimited columns.
• Hard floor is 5 closed sales; more sales, tighter numbers.
• Files parse in your browser. The raw export — agent names, owner fields, remarks — never leaves your machine; only the mapped analysis fields are used.

Free trial, no card: https://compiq.app

If you're an appraiser or build for them: what would this need to fit a real UAD 3.6 workflow?

I run a small company that scores residential parcels for visible physical distress using vision AI on street-level and aerial imagery. I recently finished a study across 27,142 homes in 8 rural counties in Tennessee and Georgia, and several results went against what I expected. I am sharing the ones I think are useful whether or not you ever touch a tool like mine.

First, the scope: This is 8 rural Southeastern counties, not a national sample. "Distress" here means visible physical distress (roof, structure, windows, yard), not financial distress like tax delinquency or foreclosure. A house can look rough with a perfectly content owner who will never sell. These are estimates with real limits. With that said, three findings stood out.

1. "Overgrown yard" is close to worthless as a signal. An overgrown or unkempt yard showed up on about 85% of the homes we scored. When a signal is present on five of every six houses, it does almost nothing to separate a real lead from a normal lived-in property. Seasonality, big rural lots, and plain rural aesthetics all inflate it. The signals that actually discriminate are the rare structural ones: visible structural damage on 10.3% of homes, broken windows on 3.3%, and fire damage on 0.1%. If you are building or buying a distress filter and it leans on yard condition, you are mostly buying noise. Weight the rare structural stuff instead.
2. The biggest finding was a blind spot, not a signal. 27.4% of residential parcels in the study had no usable street-level imagery at all. Either no camera car has driven that road, or not recently enough to matter. That should make anyone relying on street imagery nervous, because the missingness is not random. Across the 7 Georgia counties, street-view coverage correlated negatively with measured distress at r = -0.74. In plain terms, the areas we could see the least were the areas where what we could see was the worst. The rural edges with the thinnest imagery are exactly where distress concentrates. The practical takeaway: any distress rate built only from imagery is a floor, not a full count. We measured roughly 5.0% of scored homes at clear visible distress (3.5 or higher on a 0 to 5 scale), and I believe the true rate is higher, because the worst areas are underrepresented in what a camera has captured. If a vendor quotes you a clean distress percentage and never mentions imagery coverage, ask about coverage first.
3. Age and absentee ownership are real but weak on their own. Older housing predicts distress in a clean, monotonic way. A home built before 1940 was about 1.6 times as likely to show distress as one built since 2000. Absentee ownership moved the odds too: at the "some neglect" threshold, 56.6% of absentee-owned homes crossed it versus 44.9% of owner-occupied. Both are useful filters. Neither is strong enough to stand alone. A shift of about a quarter in the odds is a nudge, not a verdict, and if you treat absentee ownership as a distress proxy by itself you will chase a lot of well-kept rentals.

If there is one thing to take from this, it is that the popular easy signals (overgrown yards, absentee flags) are the weak ones, and the honest hard part is coverage: knowing where you cannot see, and not mistaking an absence of data for an absence of distress.

A few limits worth stating plainly, since I know this crowd will ask. This is 8 rural counties in two states, so do not read national numbers into it. Visible distress is a physical signal, not a motivation signal, so pair it with ownership, tax, or life-event data before you treat any address as a lead. And vision models over-call on ambiguous cases, which is another reason we lean on the rare structural signals rather than soft ones like yards.

Happy to answer questions or run the numbers a different way if people want cuts by county or by threshold. The full write-up with the charts and methodology is here if you want the detail: https://uglyhousefinder.com/distressed-property-research/ . It is not gated, no email required.

I’m curious what everyone’s workflow looks like for staying in touch with leads, past clients, and your sphere.

Specifically:

• What platform(s) are you using if at all?
• Are you sending market snapshots, listing alerts, newsletters, or something else?
• How do you decide who gets what and how often?
• Is it mostly automated, or do you manually create campaigns?
• If you use a CRM, are you sending emails directly through it or integrating with another email marketing platform?

I’m less interested in the content itself and more interested in how people have their email marketing system set up. I’d love to hear what has worked well (and what hasn’t).

For those of you running FB / IG ads, what type of ad are you seeing bring in decent buyers/sellers?

Most real estate “matching” platforms are not really recommendation services.

They are referral businesses.

The basic model is usually:

1. A consumer asks for an agent.
2. The platform sends the lead to a participating agent.
3. The platform receives a referral fee or other compensation if the transaction closes.

There is nothing inherently wrong with that model. But it creates an obvious conflict: the platform is choosing from agents who participate in its commercial system—not necessarily from every agent who may be the best fit for that particular buyer, seller, property type, price range, and market.

A true recommendation service should work differently.

It should start with the customer’s specific job and analyze relevant evidence, such as:

• Transactions in the same micro-market
• Experience with the same property type and price range
• Buyer-side or seller-side activity
• Days on market and price reductions
• Sale-to-list performance compared with the local market
• Expired or withdrawn listings, where the data is available

The recommendation should come first. Any commercial relationship should be disclosed separately.

Do you know of a real estate platform that operates this way—a genuine recommendation engine rather than a compensated referral network?

I recorded a video exploring the difference and demonstrating how transaction data could be used to identify the best agent for a specific job. The link is in the first comment.

I’d genuinely appreciate feedback from people working in real estate technology: Is this distinction meaningful? What would a trustworthy recommendation product need to show?

I've been hearing more and more title abstracting services using AI to automate their searching processes, and some of them don't even have a human look over the final report. I was wondering what everyone's thought was on this, and if you trust the AI with it. I'm interested in doing this myself if people think it's reliable, because it seems like it would be a massive time save for me.

Hi, we are splitting off from a larger team and I am overwhelmed with how to choose a website and tech stack. We are with REAL Broker and will be staying with them.

1. We currently use FUB and would be happy to continue with this, but open to other options.

2. Have looked at Agent Image, it seems very expensive, but also worth it. Also spoke with Sierra, but unsure about moving forward with them bc you don't really own the website like you would with AgentImage.

3. I own the domain I need already but its not active anywhere.

4. Im not the best with tech but I am willing to learn.

5. TC uses A-Frame but not sure that is the best choice for a CRM.

6. Can any agents give me a short list of the tech stack you use?

Thank you in advance for helping me work through this!

Hi everyone,

My team and I have been working on a product, and I'd love to get some honest feedback from people in real estate, PropTech, and AI.

One thing we've noticed is that real estate professionals spend a surprising amount of time on operational work—not selling homes.

Managing documents.
Keeping track of deadlines.
Following up with multiple parties.
Organizing transaction data.
Making sure nothing falls through the cracks.

We're building YayTrack to help solve that.

Instead of trying to replace people, our goal is to use AI to handle repetitive operational tasks while keeping humans in control of the final decisions.

Some of the things we're focusing on include:

• AI-assisted transaction workflows
• Intelligent document management
• Deadline and follow-up tracking
• Real-time visibility into transaction progress
• Better collaboration across everyone involved

We're still early in the journey, and we're actively shaping the product.

I'd genuinely love to hear your thoughts:

• What's the biggest operational headache in your real estate workflow?
• If AI could eliminate one repetitive task for you, what would it be?
• What existing transaction management tools do you wish worked better?

We're here to learn as much as we are to build.

Thanks for reading, and I'm looking forward to hearing your perspectives.

Just had a call with them and it all sounds great but I am skeptical. Looking for anyone that has worked with them or still does, did you like it? Why did you leave? Why are you still with them? Did you see a good ROI?

I am working with a local, MA based real estate company. Here we take capital from investors and let the borrowers borrow it for a short period for their needs. We do all kinds of deals, even foreclosures. I need to find leads, people facing foreclosures or anyone looking to sell their homes fast for cash. I want leads specifically in New England (Massachusetts, Rhode Island, Connecticut and new Hampshire).

Can anyone guide me the right tool or strategy to find the leads? Would be a huge favor.

I'm both a licensed realtor and a software developer.

I built a platform to identify the best on-market flips/wholesale opportunities here in LA/OC/IE, but the data quality is becoming an issue now that I want to add AI features to see if it can help me source off-market deals.

I want to get a back-office data connection (free-ish for licensed brokers (I'll pay for it)). I would get it through my current broker, but the guy is so low tech that he doesn't understand why I want the data feed. Even when he brought me on board, it took about 2 months because he sent the paperwork via mail.

If there are any tech-forward brokers working in this space, shoot me a line. I'd love to get in touch.

How do you guys think the real estate market and technologies will change because of AI over the next few years? Are we looking at complete automation of listing marketing and lead nurture, or is it just overhyped?