Interview with Rumz E, Partner, Dreamy Leads

Connectively

Connectively connects subject-matter experts with top publishers to increase their exposure and create Q & A content.

• 8 min read

Interview with Rumz E, Partner, Dreamy Leads

© Image Provided by Connectively

This interview is with Rumz E, Partner, Dreamy Leads.

For Connectively readers, how do you introduce yourself and your work as a Partner at Dreamy Leads in mortgage, insurance, and solar lead generation?

I’m Rumz — I help run the Dreamy Leads Research Desk. The simplest way to describe what we do: we publish free, independent research that helps ordinary people make sense of three of the most stressful financial decisions they’ll ever face — getting a mortgage, insuring their home, and going solar.

People in these moments are usually overwhelmed and a little scared, and almost everything they find online is a sales pitch wearing a cardigan. Our whole reason for existing is to be the opposite of that: clear, current numbers, in plain language, at no cost and with nothing to buy. We pull from primary sources:

  • HUD
  • Freddie Mac
  • state insurance filings
  • utility rate schedules
  • CFPB

We turn those sources into things a homeowner can actually use, like a metro-by-metro look at the income you need to afford a home, or a tracker of which insurers are still writing policies in Florida.

So my days come down to two questions: what’s actually true and current in these markets right now, and how do we explain it so a stressed-out person feels informed instead of sold to? If a reader leaves understanding their own situation better—even when the honest answer is “wait”—we did our job.

What’s the story of how you arrived at your current Partner role in this space?

It started with watching people I care about get lost in these decisions. Someone shopping for a mortgage or staring at a non-renewal letter doesn’t need another glossy ad — they need a straight answer to “what does this actually cost me, and what are my real options?” And that answer is weirdly hard to find for free, because most of the internet in these categories is built to sell, not to inform.

So Dreamy Leads grew out of a simple idea: take the public data that already exists — government housing figures, insurance rate filings, energy and utility numbers — and translate it honestly for the people it actually affects. No paywall, no gatekeeping, no pressure.

What’s kept me in it is how rarely anyone does this with real empathy. It’s easy to dump a spreadsheet on someone; it’s harder to sit with the fact that they’re anxious about money and meet them there. The thing I’m proudest of isn’t traffic or rankings — it’s that a person can come to us, get the real picture for their city or county, and walk away calmer and more in control. That’s the entire point, and it’s what I want every piece we publish to do.

In your day-to-day, what is the single most important way you tailor acquisition strategy between mortgage, home insurance, and solar?

I reframe it slightly, the thing we tailor isn’t acquisition; it’s empathy. Each of these decisions hits people in a completely different emotional state, and the research has to meet them where they are.

Mortgage is usually time-pressured and math-heavy. Someone is mid-purchase or watching rates, and they need precise, current numbers fast — real monthly payments, what income a home actually requires in their metro area, and an honest refinance break-even point.

Home insurance, especially in Florida, is increasingly about fear. A non-renewal letter or a premium that doubled overnight is genuinely frightening. There, the job is to calm and orient — who is still writing policies in your county, what is driving the price, and what your realistic options are.

Solar is about rebuilding trust. The category burned many people with hype, so we lead with sober payback math and what is actually changed with net metering — no inflated savings.

So the “strategy,” if you want to call it that, is just refusing to use one tone for three very different human moments. The data procurement is rigorous across all of them; the delivery is tailored to whether someone is rushed, scared, or skeptical.

At the top of the funnel, which first-party signals best predict a funded mortgage or bound policy in your programs?

This is where my answer probably differs from a typical one — we don’t measure ourselves on funded loans or bound policies, because we’re not the ones funding or binding anything. Our outcome is whether a person genuinely understood their situation and made a confident, informed decision. So the signals I care about are signals of understanding, not transactions.

The ones that tell us it landed:

  • People spending real time with the substantive material — a methodology section, a payment breakdown, a county-by-county premium table — instead of bouncing.
  • Repeat visits, and people returning to a tracker when their situation changes.
  • The questions readers send us, because a sharper question means the earlier material did its job.

The signal I distrust is shallow speed — a fast skim of nothing. That’s not someone we helped.

If I had to name the single best sign we actually served somebody, it’s this: they engaged with the hard, specific data about their own city, county, or rate — and then asked a more precise question than they started with. That’s the texture of a person who’s been informed rather than marketed to.

What is one AI workflow you’ve implemented—whether for lead scoring, creative, or pre-qualification—that produced a measurable lift, and by how much?

For us, the highest-impact use of AI isn’t scoring people or generating ads — it’s keeping a small research team’s data genuinely current. In these categories, that’s everything. Rates, insurance filings, and incentive rules go stale fast, and stale information isn’t just unhelpful — it’s harmful when someone is making a money decision.

So we built what we think of as a research brain: it continuously watches our primary sources — HUD, Freddie Mac, state filings, utility schedules — flags what’s changed, and helps us draft updates that a human then verifies against the original source before anything publishes. That lets us keep two-dozen-plus living data trackers current instead of letting them rot.

The measurable result shows up in how often we get cited as a source. Over a recent three-month stretch, Microsoft’s Copilot referenced our pages a little over 1,000 times across 52 different URLs — mostly the research and comparison work. For a small, free resource, being pulled into AI answers that often is a strong signal the information is accurate, current, and genuinely useful.

The non-negotiable: AI drafts and monitors, but it never gets the final word on a fact. Every number a stressed homeowner reads has been checked by a person against the primary source. The “lift” is doing the tedious verification at scale — not letting a model improvise on people’s money.

Your Florida home-insurance non-renewal work highlights bindability and price shocks; what do you do differently in pre-qualification to reduce dead-end quotes before handing a lead to an agent?

Florida home insurance is perhaps the clearest example where honest information spares people real pain. A non-renewal letter is scary, and the worst thing you can do at that moment is give someone false hope.

So what we do differently is set expectations honestly and early. Instead of implying coverage is easy to find, our non-renewal tracker tells people the things that actually determine whether they can get a policy at all — which carriers are still writing in their specific county, how roof age and claims history factor in, what the realistic premium band looks like now, and that “now” may be very different from the price they paid three years ago.

The point isn’t to discourage anyone. A homeowner who already understands they might be looking at Citizens or a surplus-lines option — and roughly what it will cost — is far less likely to be blindsided. They can plan instead of panic.

We’d genuinely rather someone leave our page thinking, “Okay, this is hard, but I understand it,” than chase a number that doesn’t exist anymore. Being upfront about price shock is uncomfortable, but it’s the respectful thing to do when someone is worried about keeping their home insured.

Your 36-metro affordability research shows payment stress; what specific messaging or calculator experience using total-cost and refinance break-even framing has most improved mortgage application-to-close rates for you?

The framing that helps people most is total monthly cost, not the rate. Everyone shops for an interest rate, then gets blindsided by the all-in number — taxes, insurance (which in Florida can rival the loan payment itself), PMI, HOA. Our 25-metro affordability analysis, built on HUD and Freddie Mac data, is basically one long argument that the honest question is ‘what income do I really need for the true monthly payment in my city’ — and people trust it precisely because it matches the anxiety they already feel.

On refinancing, the most useful thing we offer is a straight break-even: given this rate change and these closing costs, here’s the month you actually start saving — and if you might move before then, don’t do it. Telling someone not to refinance is exactly what makes them believe us when we say it’s worth it.

I won’t dress this up with conversion stats — we measure success by whether someone made a clear-eyed decision, not by a transaction. But the pattern is consistent: when the numbers reflect a person’s real situation instead of a best-case teaser, they make calmer, more confident choices. Honest math doesn’t push people; it steadies them. That’s the experience we’re after.

In solar, what offer structure or sequencing with mortgage/insurance homeowners has most improved LTV-to-CAC in your experience?

I’ll step outside the framing here — we don’t think about solar in terms of unit economics, because we’re not selling panels or financing. We think about it in terms of not letting someone make a 20-year mistake.

The most important thing we do in solar is timing and honesty. Solar only makes sense for certain homeowners — the roof, how long they’ll stay, the utility, and the local net-metering rules all matter — and the industry’s bad reputation comes from ignoring all of that to close a sale. So our research leads with sober payback math specific to a person’s state and utility, and it’s blunt about what’s changed: California’s NEM 3.0, for instance, genuinely shifted the economics, and pretending otherwise would do readers a disservice.

We’re just as willing to tell someone solar isn’t right for them as to explain how it could pay off. A shaded roof, or a homeowner planning to move in three years, should hear that plainly.

If there’s a “strategy,” it’s that trust compounds. Someone who feels we gave them the straight story on solar — even a “not yet” — believes the rest of our research too. Serving the person is the whole model; everything good follows from that.

For publishers and partners using Connectively, what 30-day playbook would you run to launch a compliant, high-intent test across these verticals, including channels and the primary KPI you’d track?

Here’s the 30-day version, biased toward earning trust over chasing volume:

  1. Week 1 — pick one vertical and one real, specific human problem. Not “mortgages” but “what income do I need to buy in my city,” or “what do I do after a Florida non-renewal.” Build one genuinely useful, free asset for it — a clear calculator, a county table, an honest comparison — sourced from primary data. Get your disclosures and consent language right before anything goes live; in money topics, that isn’t optional.
  2. Week 2 — put it in front of people actively asking that exact question (search intent), plus your own audience. Do not blast broad channels; the specificity is the whole point.
  3. Week 3 — listen. Watch whether people actually engage with the substance, what they ask next, where they get confused — and fix it.
  4. Week 4 — keep it current, and expand only into the adjacent questions people are really asking.

Primary KPI: Not cost-per-anything — usefulness. Concretely: are people spending real time with the substantive content, coming back when their situation changes, and citing or sharing it as trustworthy? If the information genuinely helps, the things publishers care about tend to follow. Optimize for the transaction first and you erode the trust that made it work.

Thanks for sharing your knowledge and expertise. Is there anything else you’d like to add?

Just one thing I’d leave readers with: In money decisions, the kindest thing you can do for someone is tell them the truth, including when the truth is “don’t do this yet.” That’s the whole ethic behind Dreamy Leads. We keep the research free, current, and independent because people facing these choices deserve a place that’s genuinely on their side.

If your readers ever want a straight, no-cost starting point, everything we publish is open:

Up Next

Sign up