For FIRE-minded investors, I’ve been comparing short-term rentals vs passive index fund investing.

2026 STR data showed some interesting numbers:

• Hawaii ranked #1 overall with $269 ADR and 55% occupancy
• Florida led in profit with $26,890 profit per listing and 20.4% growth
• Nebraska surprised as a sleeper market, driven by Omaha’s lower entry cost

The takeaway: STRs can outperform index funds in cash flow—but only if occupancy stays strong and operating costs are controlled.

The tradeoff is obvious:
Index funds = passive, scalable
STR = higher potential returns, but active management + higher risk

For people pursuing FIRE, would you rather optimize for passive compounding or cash-flow-heavy assets?

I ran a city-level underwriting model using:
Cap rate + affordability + investor score + crime per 1,000 residents.

The biggest surprise? Crime changed rankings more than cap rate in many cases.

Examples:

• Cape Coral (#5) — Only 1.1 crimes/1k, moved up despite modest 1.9% cap rate
• Kissimmee (#29) — Decent 4.7% cap rate, but 14.6 crimes/1k crushed its score
• Toledo (#13) — Strong 6.3% cap rate, but 13.9 crimes/1k hurt risk-adjusted returns
• Huntsville (#15) — Lower cap rate, but excellent 2.1 crimes/1k

Crime affects more than safety—it impacts vacancy, tenant quality, insurance, maintenance, and exit value.

Ignoring crime can make a deal look better on paper than it performs in reality.

Do you underwrite crime quantitatively or only at neighborhood level?

A low home price doesn’t automatically mean a good buy.

When comparing markets, I use 5 metrics before calling a city “safe + affordable”:

1. Median home price → Entry cost
2. Crime per 1,000 residents → Risk
3. Population growth/stability → Demand
4. Cap rate / rent potential → Future ROI
5. Overall market score → Risk-adjusted opportunity

Examples from 2026 data:

• Cleveland — $144.9k median, 4.1% cap rate, 7.5 crime/1k
• Huntsville — $142.5k median, low crime at 2.1/1k
• Kissimmee — affordable at $292.5k, but high crime at 14.6/1k

Big lesson: Cheap markets can hide expensive risks.

What metrics matter most to you before buying your first home?

For what it’s worth, Chicago stood out in a 2026 rental market analysis we ran that ranked cities using ROI + crime together, instead of looking at cash flow alone.

Interesting stat: Chicago ranked #4 overall with one of the strongest cap rates in the study at 7.6%, despite a median home price of $422,000.

That’s what made it interesting — strong rental yield kept Chicago highly competitive even with higher entry costs.

Data is useful for screening, but neighborhood-level reality always matters more than city averages.

Locals here probably know this market far better than any dataset — does this match how you’d rank the best and worst neighborhoods in Chicago for investing?

For what it’s worth, Cape Coral stood out in a 2026 rental market analysis we ran that ranked cities using ROI + crime together, instead of looking at cash flow alone.

Interesting stat: Cape Coral ranked #5 overall and was the safest among the top 10 markets with just 1.1 crimes per 1,000 residents.

That’s what made it interesting, some cities with strong cash flow dropped hard once crime risk was factored in, while others moved up because of better stability.

Data is useful for screening, but neighborhood-level reality always matters more than city averages.

Locals here probably know this market far better than any dataset — does this match how you’d rank the best and worst neighborhoods in Cape Coral for investing?

I analyzed 2026 short-term rental performance using 3 metrics:
ADR + Occupancy + Profit per listing

Some interesting findings:

Hawaii ranked #1 overall
• ADR: $269/night
• Occupancy: 55%
Highest pricing power in the dataset.

Florida led in profit
• Profit per listing: $26,890
• Growth: +20.4%
Still one of the strongest STR cash-flow markets.

Nebraska was the sleeper pick
Omaha is quietly driving strong returns with much lower acquisition costs than major vacation markets.

Big takeaway: The best STR markets aren’t always the obvious tourist hotspots. Sometimes profit comes from strong occupancy + lower operating costs, not just high ADR.

Which state are you bullish on for STR in 2026?

Most rental market rankings overvalue cap rate and ignore crime risk.

I ranked 50 U.S. cities using a weighted model:
ROI (70%) + Crime (30%)

Interesting results:

• North Las Vegas ranked #1 — 4.5% cap rate, crime 6.7/1k
• Cleveland ranked #3 — 4.1% cap rate, median price just $144.9k
• Chicago ranked #4 — strong 7.6% cap rate despite higher price
• Worcester ranked #2 even with -0.1% cap rate because crime stayed low (3.3/1k)

Big surprise? Some “hot” markets dropped hard.

• Boston #22 — -0.3% cap rate, $837k median price
• Cambridge #26 — -1.4% cap rate, $1.78M median price

My point: High appreciation markets often look weak when you prioritize actual rental cash flow + risk.

Would you weight crime at 30%, or is that too high?

I analyzed Cleveland’s 2026 rental market using 4 core metrics: cap rate, affordability, investor score, and local crime risk.

Here’s what stood out:

• Median home price: $144,900
• Cap rate: 4.1%
• Investor score: 61/100
• Crime rate: 7.5 per 1,000 residents
• Population: 383,331

My takeaway: Cleveland is still one of the more affordable Midwest rental markets, which makes entry easier for investors. The cash flow potential is decent, but not extraordinary unless you buy in the right neighbuorhoods.

The biggest variable here isn’t price, it’s location selection. Some areas cash flow really well, while others carry higher vacancy and crime risk.

If you were buying a rental in Cleveland today, which neighbourhoods would you actually consider?

My wife teaches students with special needs, and we’ve been talking a lot about AAC apps lately. She’s curious what experiences people have had with them.

For parents, SLPs, teachers, caregivers, or AAC users:
- What app do you use?
- What do you love about it?
- What frustrates you?

Is there anything you wish these apps did better?
Just trying to learn from people with real experience. Thanks!

I’m not looking for any type of diagnosis or medical advice, I just want to see if anyone has a similar story to ours?

My daughter is 3 years 9 months old. She has a language delay. She has well beyond the amount of words she should know by now and she labels everything (even hard words like xylophone). She also makes simple requests like “I want _____ please”, “open door”, “go to car” “I want to go potty” and she answers yes or no questions. However, she is nowhere near answering open ended questions like “what are you doing” or “what do you want to do?”. I’m confused bc she is perfectly capable of communicating. In fact, she literally never stops talking. She repeats her favorite scripts she’s learned and makes up her own scripts, and she sings songs all day long. Like never stops talking ever!!

Did anyone else have an almost 4 year old like this? When were they able to start answering open ended questions?

Disclaimer: we hardly ever use screen time, but we are desperate.

Does anyone know of any websites or apps that can help my language delayed 3 year old learn back and forth conversation skills? She is in speech therapy, we read a lot of books, and I reinforce what therapy has taught us/my own research. I’m just looking for something else to add that might be engaging and helpful to give an extra boost. She needs help with vocabulary and answering open ended questions…

I’m building automated lead generation tool, that helps founders identify relevant people and make conversations , research prospects, and draft personalized outreach.

I’m now planning its organic marketing strategy and would appreciate advice on:

• pSEO: What useful pages could I create without producing thin or repetitive content?
• Directory listings: Are SaaS directories still worthwhile? Which ones generate real traffic or backlinks?
• XML sitemaps: Should feature, use-case, comparison, integration, and template pages have separate sitemaps?
• Keyword strategy: Should I prioritize high-intent terms, competitor alternatives, or problem-based searches?
• Distribution: Beyond SEO, which channel would you test first for this audience?

The product is still in beta, so I want to build the right foundation instead of publishing hundreds of low-value pages.

Website I'll add in comment for context

There are more SEO tools than ever in 2026, ranging from traditional platforms focused on rankings and backlinks to newer tools covering content, technical SEO, AI visibility, competitor analysis, and reporting.

The challenge is that many tools seem to overlap. Some are excellent at keyword research, some at backlink analysis, some at content optimization, and others at tracking visibility in AI-driven search experiences. For businesses and marketers with limited budgets, it's not always clear which platform provides the best overall value.

So curious, which is the best all-in-one SEO tool that is worth paying for in 2026?

We have build a automation tool that emails when there is a failed-payment recovery sequence.

When a customer's card is declined, the automation tool automatically sends a series of reminder emails over the next few days, prompting them to update their payment details before their subscription is cancelled.

It's simple, takes very little setup, and quietly recovers revenue that would otherwise be lost to failed payments and accidental churn. For many subscription businesses, this single automation outperforms more popular flows like cart-abandonment emails because it targets customers who already intended to stay.

I’ve been looking at cold email performance recently, and one thing keeps standing out:

Sometimes two emails targeting similar people with similar offers perform completely differently.

One gets ignored.
The other gets replies.

And often the difference isn’t massive.

I compared two cold emails sent to similar prospects.

The ignored one looked something like this:

• Generic subject line
• Long intro about who we are
• Too much talking about ourselves
• Broad value proposition
• Weak CTA

It wasn’t terrible, just very easy to ignore.

The one that got replies looked very different:

• Simple subject line
• Straight to the point in first line
• Clear relevance to the prospect
• Focused on one pain point
• Low-friction CTA

What stood out most was this: the better-performing email didn’t feel “better written.” It just felt easier to read and easier to respond to.

I’m also noticing that personalization alone doesn’t guarantee replies anymore. A personalized opener means nothing if the rest of the email feels generic or too salesy.

Right now, I think the biggest reply killers are:

• Overexplaining
• Sounding too polished
• Weak relevance
• Asking for too much in the CTA

Curious what others are seeing.

When you look at cold emails that perform well vs badly, what usually makes the biggest difference?

Is it the opener, offer, targeting, or CTA?

I’m curious what everyone’s up to herecold emailing feels a lot tougher than it did just a year ago.

Deliverability is now a persistent problem. It seems the traditional model of one inbox per rep isn’t very effective anymore, unless your volume is exceptionally low.

Recently, we’ve been reconsidering our outbound infrastructure, and inbox rotation consistently emerges as a key factor in sustaining sender health.

Here’s what I’ve observed Sending limits appear to be enforced more strictly lately New inboxes require significantly more warm-up time than they used to Minor errors can quickly damage domain reputation Tracking email deliverability now feels nearly as crucial as crafting great copy More teams are adopting multiple inboxes per rep, but there’s no clear consensus on the ideal numberit varies based on volume, market, and targeting.

Some people believe that three to five inboxes per representative is sufficient. Others are outpacing them significantly.

What are each of you up to at the moment?

How many inboxes are you rotating per representative, and what daily sending limit has proven most effective without compromising deliverability?

Perhaps the most aggravating part of email marketing is watching engagement decline when you KNOW your subscribers actually wanted to hear from you.

Sometimes the offer isn't the issue. The copy isn't the issue. The timing isn't the issue. The problem is that your email, in growing number, is not reaching the inbox.

I've learned that most of the delivery issues I see lately stem from a few predictable factors. I use this checklist when investigating why my emails are landing in the spam folder:

1. Check SPF, DKIM and DMARC.

Authentication is no longer optional.

Ensure that:

• Your SPF records are set up correctly and updated.
• DKIM is configured and working.
• Your DMARC record is correctly configured and aligns with the email domain.

A small error here can drastically impact deliverability.

2. Review your domain and subdomain strategy.

Most marketers separate transactional and marketing emails.

3. Monitor subscriber engagement.

Mailbox providers use engagement to determine send reputation.

Here are key metrics to monitor:

• Opens
• Click-through rate
• Replies (if relevant)
• Spam complaint rate
• Deletions without reading

If many of your subscribers never engage with your campaigns, deliverability issues will arise.

4. Practice list hygiene.

Inactive subscribers pose a significant risk.

Consider:

• Segmenting and identifying inactive segments.
• Sending win-back campaigns.
• Suppression of unresponsive subscribers.

A small, highly engaged list will outperform a large, non-responsive one.

5. Avoid volume spikes.

A sudden increase in sending volume can lead to deliverability issues.

When increasing volume:

• Gradually increase the number of emails.
• Maintain a consistent sending schedule.
• Keep a close eye on your sender reputation indicators.

Consistent sending is far more predictable than inconsistent sending.

6. Review your content and formatting.

Deliverability problems aren't always technical.

Look for:

• broken links
• too many images compared to text
• poor mobile rendering
• misleading subject lines
• overly aggressive promotional copy

You want to deliver a positive experience, not trigger spam filters.

7. Monitor bounced and complaint rates.

Here are two numbers I track diligently:

• Hard bounce rate
• Spam complaint rate

If you see these numbers climb, it's an early indicator of future inbox placement problems.

8. Track inbox placement-not delivery.

A delivered email is not necessarily an inboxed email.

If possible, try to track:

• Inbox placement rate
• Promotional tab placement rate
• Spam folder placement rate

Relying only on delivery rates is not enough.

9. Keep up with Gmail and Yahoo requirements.

Recent changes to these providers have made sending to their users more difficult.

Here's a summary of what to look for during your audits:

• Updated authentication methods
• Functional unsubscribe options
• Current sender best practices

1. Keep track of the right numbers.

Beyond open rates and clicks, here are some key metrics to monitor:

• Complaint rate
• Hard bounce rate
• Unsubscribe rate
• Inbox placement rate
• Engagement metrics by subscriber segment
• List growth rate versus list churn

The best indicators of deliverability are often found here.

What has been the most challenging deliverability issue for your email program, and how did you uncover it?

I've seen a trend develop over the last few months within SaaS discussions of operations & customer support. 

So many companies come to the following two questions, "Should I build an AI voice agent or AI chatbots?"  
 
And this is the wrong question to ask, instead, the question should be what kind of interaction are you looking to optimize? 

A basic model I've seen to work well:  

  

1. Channel Preference

  

 If your customers automatically turn to the phone to solve a problem, voice might make the most sense. If customers prefer to reach out through your website, app, or messaging channels, chatbot is likely the most appropriate option. 

2. When do I need to use voice?

 

In situations where time is of the essence-booking an appointment, service downtime, urgent tech support issue-voice can help minimize friction and speed up resolution. 

For regular requests-status inquiries, FAQ, onboarding queries, chat will likely suffice. 

 

3. Size and Expense

 

Both can cut down on labor-related tasks, but there are budget considerations. 

For most early-stage SaaS companies, AI chatbots will often be easier and cheaper to deploy and maintain. 

When conversational volumes increase, that equation may shift. 

4. Complexity of Conversation

 

When interactions are very structured, chatbots are great. 

But conversations which may require some clarification, back-and-forth, and more natural speech may fare better with an AI voice agent. 

 

What I have seen most  

The fascinating part about this is that usually, the answer is "both".  

Many businesses adopt both:  

• AI chatbots: for website and in app support  
• AI voice agents: for telephone support, or emergency situations.

  

 It's often less a choice of technology, and more a question of customer's behavior, and business support workflows.  

 

 For teams who have implemented either AI voice agents, or AI chatbots (or both)  

 What finally pushed the button - customer needs, price, volume of requests, conversion, or another factor? 

While it's common for support teams to track a multitude of KPIs, not all of them indicate whether a customer is likely to stick around.

While retention is influenced by factors like product quality, pricing and market dynamics, support data can sometimes give you early indications of customer loyalty. The five most common CX and support metrics for those signals are here:

1. Customer Effort Score (CES)

Every customer wants to resolve their issue with the least effort possible.

Repeating information to support agents, having to switch channels, or navigate complex processes can increase customer frustration. If you're measuring CES you can see friction that might otherwise be missed.

The key question to ask: How easy is it for your customer to get support when they have a problem?

2. First Contact Resolution (FCR)

Closing out an issue on the first contact improves your customer's perception of the support experience. While not every issue can be resolved on the first contact, low FCR can highlight:

* Gaps in the agents' knowledge base

* Issues with your processes

* Whether agents have enough autonomy to solve problems

* An indication of product complexity

There are times when FCR alone isn't everything, but it's generally a very helpful indicator of efficient operations.

3. True Resolution Time

While it's good that your customers receive swift support, what they care about most is when their issue is solved. If the support ticket is answered quickly but then languishes for days, it may not build a great customer experience. Tracking resolution time is a better reflection of the end-to-end support process.

4. Re-open Rate

Closing a ticket isn't always the same as resolving the issue. A reopened ticket could signify that the core problem hasn't been addressed and if it's happening too often, this can point to recurring issues in your support system.

5. Sentiment Trend

While one point in time satisfaction scores are good for an overview, it can be helpful to look at trends. An increasing positive sentiment score may build customer trust and confidence in your product and support system. Declining negative sentiment scores could be an indicator of customers who are on their way out even before any major churn happens.

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Although none of these are individual indicators of customer retention, these 5 common metrics are the ones that most CX and support agents will track to get a better understanding of the overall customer experience and whether their customers will stay with the company.

For CX and support professionals, what is the one metric you can rely on most to identify and keep your most loyal customers?

I used to believe as a founder that more support channels equalled more CX. 

  

Add email? Done. 

  

Live chat? Added. 

  

WhatsApp? Added. 

  

Social DMs? Added. 

  

On paper this looked great, our customer could contact us anywhere. 

  

We later realised we were running multichannel and not omnichannel support. 

  

This was crystal clear when our customer switched between the support channels they use: they would start the discussion on chat, continue on email and later send another message on Whatsapp. Since every conversation was separate they would have to repeatedly ask the same questions as the support agent couldn't easily see previous conversations. 

  

Customers felt like they were talking to different companies. 

  

What often passes for omnichannel is just multiple independent channels that co-exist side-by-side. The solution isn't to add more channels, the problem is identity resolution. Is the email you received yesterday the same customer that used the chat service? Are conversations all visible to support agents? Are customers able to resume conversations? These are the questions that define omnichannel support. Fortunately not all fixes necessitate a big replatform. Some that helped us were: establishing a primary identifier for the customer (email, phone number, account ID), creating unified profiles based on interaction history, and unifying conversations on a single screen so agents can see past interactions regardless of how they occurred. Adding channels is simple. Knowing who is calling, where they previously contacted support and being able to resume this discussion in the form of the customers experience. That is where the great gains in CX lie. How do you approach this at your organization and what methods have worked in making this transformation without completely redoing your entire support stack?