Cubit's Blog

Welcome back! I’ve got some exciting updates to share with you today that can help boost your business decisions with data-driven insights. Here’s a quick rundown:

TL;DR Summary:

• Point of Interest Maps: Now available as an add-on for your radius reports for just $50.
• ZipTarget Analysis: Learn how I improved my Google Ad campaign by 900% by targeting the right zip codes. You can do it too.
• 2023 Population Data: The U.S. Census Bureau has released new population estimates for cities and counties. Get them now on our state demographic sites.

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Point of Interest Maps: A Data-Driven Decision

I’ve been diving into Invent and Wander: The Collected Writings of Jeff Bezos lately, and one quote really stuck with me:

“Many important decisions we make at Amazon.com can be made with data… math tells us which is which. These are our favorite kinds of decisions.”

I couldn’t agree more! Data-driven decisions make life so much easier for small business owners like me. And guess what? Offering Point of Interest (POI) maps to our reports was one such decision.

After sending out post-purchase emails asking, “What else do you need?” the overwhelming response was a request for POI maps. So, we’ve listened!

Now Available: Point of Interest Maps for $50

For just $50, you can now add Point of Interest Maps to your radius reports. Get a custom map of key locations sent directly to your inbox within one business day. Need more details? Just reply to this post, and I’ll be happy to help!

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ZipTarget Analysis: Boost Your Ad Performance Like I Did

Another powerful quote from Jeff Bezos speaks to the art of decision-making:

“Not all of our important decisions can be made in this enviable, math-based way. Sometimes… judgment is the prime ingredient.”

In the world of targeted marketing, I’ve had to rely on both data and judgment. Earlier this year, my Google PPC campaign took a major hit, losing $289 in just one month. That’s when I realized that relying on Google’s data wasn’t enough. I needed to look at my own sales data.

My Turnaround Story: From Loss to Profit

By analyzing zip codes from my Shopify sales data and matching it with detailed business demographics, I found the sweet spot for my ads. The result? A failing campaign turned into a $2,341 profit within just 30 days, all while cutting my ad spend by $200!

Now, I’m offering to help you achieve similar results with our new ZipTarget Analysis service. For the first 10 clients, I’m offering this service at $99. Learn more here, or feel free to reach out with any questions!

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2023 Population Data for Cities & Counties

The U.S. Census Bureau has just released the 2023 population estimates for most cities and counties. If you want to skip learning how to use the Census’ website, you can get the 2023 estimates for free on our state demographic sites as well as in your Demographics By Cities and Counties Reports and Custom Data Requests. The 2023 data for counties are currently live, and we’re working on adding the same data for cities. 

What’s Available Now?

• 2023 population data for counties is live on our site.
• Data for cities is being added as we speak.

If you’ve ordered a 2022 Demographics By Cities report, don’t worry—we’ll be sending you an updated version with the 2023 data soon.

When Will the Rest of the 2023 Data Be Released?

By December 2024, we’ll have the full 2023 detailed demographics for all geographic areas, including zip codes. Stay tuned!

ChatGPT was down a couple of days ago, and I thought “I should take the day off, because I can’t get ANY work done.” I remember thinking the same thing about the internet in the early 2000’s.

It’s scary how fast ChatGPT has gone from a fun app to a tool that I can’t work without, similar to the internet. But I’m not scared of ChatGPT, because it’s not true artificial intelligence. It’s a word prediction tool…like the predictive text feature on my iPhone…but WAY more powerful. 

As a daily Hacker News reader, I felt well read on AI and large language models (LLMs). But I didn’t grok how LLMs worked until I attended this year’s Texas Data Day. Here’s what I learned.

ELI5 (Explain Like I’m 5) Metaphor for LLMs:

Imagine you have a room filled with different kinds of toys: cars, dolls, balls, and blocks. Each type of toy can be sorted and grouped based on its features, like shape, color, or size. Think of your room as a big space where each area is reserved for a type of toy based on these features.

Turning Data into Vectors:

Because computers are good with numbers, we turn data, like toy characteristics, into numbers. For example, a car might be [1, 4, 7] based on its type, color, and size.

The Space (aka Your Room):

These numbers place toys in a “vector space,” where similar toys are closer. So, cars and trucks, both with wheels, might be near each other.

Training the LLM: 

Computer scientists teach the LLM by showing it MANY examples of rooms, toys and their features. Then the model recognizes patterns, like toys with wheels, are similar.

Why It’s Useful:

When done, LLMs can do cool things like understanding and grouping new toys it hasn’t seen before. For instance, it recognizes that cars and trucks are similar because of their wheels, aiding in tasks like organizing toys or suggesting new ones similar to those you like.

It’s probably not a surprise, but I used ChatGPT to write the above metaphor and produce the images.

So What About Hallucinations?

Hallucinations are when LLMs return words or images that don’t make sense. Zooming into the images above, you’ll see good examples – things that kind of look like toys but not really.

Hallucinations are no reason to not use LLMs. They just mean that a human needs to apply a common sense check of the output…just like you’d do with any other tool.

So let’s go back to ChatGPT as a tool that I can’t work without. I mean, I could, but I don’t want to. Because working with ChatGPT is fun. It’s fun when it hallucinates, and I can feel superior in my highly evolved human intellect. It’s fun when it gives me tone-deaf advice, and I can tell it to f*** off and no one’s feelings get hurt. It’s fun when it catches my grammatical errors and keeps me from feeling dumb. And it’s really fun when ChatGPT saves me hours of work, and I feel like a superhuman at the end of the day.  

If you haven’t incorporated ChatGPT, Gemini or other LLM into your daily workflow, here’s how to get started:

1. Open https://chat.openai.com/ in a new tab

2. Keep ChatGPT open whenever you work or play online.

• In addition to googling for answers, ask your question of ChatGPT. And let me know if you run into anything scary.

If you have adopted an LLM into your daily workflow, send me your favorite tasks to complete more efficiently. I’m putting together a list to share as this one is long enough as is. 

I used to receive an awesome email newsletter from Trends.vc that would interview an entrepreneur and ask what they were reading. I haven’t received these emails recently, and I’m missing getting reading recommendations from fellow small business owners.

I’m taking a break from writing about the latest in the world of data and instead offering the 10 best non-fiction books that I’ve read over the past 6 months* in case you, too, are looking for a new book to read.

If you only have time to read 1 book, read Die with Zero: Getting All You Can from Your Money and Your Life by Bill Perkins. This book encourages a shift from saving money for retirement to designing a life full of experiences, acknowledging that certain adventures are a better fit for certain ages. It’s a book about how to live a rich life rather than how to be rich.

If Die with Zero doesn’t speak to you, here are 9 more 5-star non-fiction books according to me.

1. Hidden Potential: The Science of Achieving Greater Things by Adam Grant – A roadmap for how to configure scaffolding for people and organizations to reach…you guessed it…their hidden potential.
2. Unraveling: What I Learned About Life While Shearing Sheep, Dyeing Wool, and Making the World’s Ugliest Sweater by Peggy Orenstein – One of my favorite writers journeys into the world of wool as her daughter leaves for college and the world retreats during the pandemic. I don’t care about wool or knitting, but I’ll read anything Peggy Orenstein writes.
3. Going Infinite: The Rise and Fall of a New Tycoon by Michael Lewis – The rise and fall of Sam Bankman-Fried, crypo-king, from the author’s unique perspective embedded within FTX. Lewis is the only author I’d trust to make the shadowy crypto world both understandable and entertaining.
4. Exercised: Why Something We Never Evolved to Do Is Healthy and Rewarding by Daniel E. Lieberman – A fun explaination as to why I STILL don’t want to work out even though I feel much better afterwards.
5. In Search of Sleep: An Insomniac’s Quest to Understand the Science, Psychology, and Culture of Sleeplessness by Bregje Hofstede, Alice Tetley-Paul (Translator) – The science, psychology, and culture surrounding sleeplessness written by an educated lay-person. Having read many doctor-written books on insomnia, this fellow sufferer was able to offer compassion and understanding, if not a workable solution as I won’t be uprooting my family to rural France.
6. Made to Stick: Why Some Ideas Survive and Others Die by Chip Heath, Dan Heath – Offers a formula for how to create messages that are memorable and impactful.
7. Crying in H Mart by Michelle Zauner – A memoir of a Korean-American daughter grieving the loss of her mother through their shared love of food. I cried so much through this one, you guys, so much.
8. The Happiness Hypothesis: Finding Modern Truth in Ancient Wisdom by Jonathan Haidt – Journey through ancient wisdom and modern psychology to add more happiness to your life today. I normally a fan of pop psychology books, but this one was just the right mix of storytelling and reasonable advice.
9. Same as Ever: A Guide to What Never Changes by Morgan House – Who also wrote the blockbuster Psychology of Money. What I like about his new book is that while many of the things that stay the same apply to financial markets, they also are applicable for other important areas of life — like building a business, parenting or staying sane in rapidly changing world. 

Got a book recommendation for me? Send me a message and let me know. I’ve still got room on my giant pile of books to read. 

* P.S. “Wait? Whaaaaaat? You’ve read more than 10 non-fiction books in 6 months.” Don’t you have…like…two kids…and a business to run…and 4 soccer teams to play on?

Yes, yes, and yes. Goodreads says I read around 100 books a year, but that includes kids books and books I quit because they didn’t speak to me. 

If you caught my nod to insomnia in the description of In Search of Sleep above, I’m sensitive to TV and movies before bed. So after I read with my kids, I read my back-lit Kindle Oasis for until I get sleepy. When I wake up in the middle of the night, I read myself back to sleep. And when I wake up at 4 am, I usually read before starting work.

Non-fiction books work well for this reading as I can get sucked into page turning fiction stories and stay up too late reading…the opposite of what I’m going for. Also like older fiction books like George Elliot’s Middlemarch (which I’m also reading now) work well for this type of reading too.

A couple other reading hints…

• I check out books to read on my Kindle for free from my AMAZING Austin public library.
• Goodreads syncs with my Kindle to produce rough tracking like the graph above and a list of what I’m read.
• And Readwise syncs my Kindle highlights (you can highlight passages that speak to you in a Kindle) and emails me 10 highlights a day, helping me remember what I’ve read. 

Are you aware of how housing costs impact your customers’ spending habits? Understanding the financial burdens of your customers can help you tailor your marketing and sales strategies. For instance, in states like Florida, Nevada, and California, a higher percentage of renters are housing-burdened, which impacts their discretionary spending.

The Definition

The Department of Housing and Urban Development considers those who pay more than 30% of their income on housing to be “housing-burdened.”

Renters vs. Homeowners: Who’s More Burdened by Housing Costs?

It turns out, over half of the renters in the US are shouldering a significant housing cost burden. In 2022, a staggering 52% of renters and 23% of homeowners spent more than 30% of their income on housing (source: US Census). While these figures have fluctuated over the past decade, they remain high.

Prices of Homes Rising.

Nationally, the cost of homes has soared by 74% from 2010 to 2022, outpacing wage growth which saw a 54% increase (sources: Bureau of Labor Statistics, Federal Housing Finance Agency). This widening gap can significantly impact consumer spending power.  

Because of this trend in rising home prices, we recently added more high value categories to our radius reports. The example below is a location in New York City.

Let’s go Low, Low, Low, Low, Low, Low, Low, Low

While I love USAFacts’ analysis of housing burden by state and tenure, state geographies are usually too large for most business owners to use in their decision-making. So let’s look at similar data for metro areas.

List of Metro areas sorted by housing burdened owners

You can download this Google Sheet to sort and filter for your markets by going here: https://docs.google.com/spreadsheets/d/1dbOFaxboBGYtMqbqoERqvtbWy_4Cs8ZJYgKye1IdaQY/edit#gid=0 Then click on File/Download.

Most housing burdened markets for owners with mortgages

The 2022 American Community Survey data presented lists the percentage of housing units with a mortgage that cost the owner 30% or more of their income in various U.S. metropolitan areas. Two areas tie for the highest percentage, Kahului-Wailuku-Lahaina in Hawaii and Aguadilla-Isabela in Puerto Rico, both at 43.7%. The Yauco metro area in Puerto Rico follows at 41.6%, and the Los Angeles-Long Beach-Anaheim area in California is close behind at 41.5%.

The data suggests that homeowners in these regions are likely to spend a significant portion of their income on housing costs, which can be indicative of high housing prices, low incomes, or a combination of both. Notably, three of the top five areas with the highest owner costs are in Puerto Rico, highlighting a potential regional pattern of housing affordability challenges.

Most housing burdened markets for renters

1. High Rental Cost Burden: All the listed MSAs have more than half of their renters spending over 30% of their income on rent, indicating a high rental cost burden in these areas. This suggests that affordability is a significant issue for renters in these regions.
2. Florida's Rental Market: Florida appears prominently on this list, with four MSAs featured: Gainesville, Punta Gorda, The Villages, and Naples-Marco Island, with Miami-Fort Lauderdale-Pompano Beach having the highest percentage at 62.6%. This points towards a statewide trend of high rental costs relative to income in Florida.
3. Diversity of Locations: The MSAs are geographically diverse, covering various parts of the country including the East Coast, West Coast, and the Mountain States. However, there is a noticeable cluster in the state of Florida, suggesting regional market dynamics that affect rental affordability.
4. College Towns: Several of the MSAs listed, like Gainesville, FL (University of Florida), Boulder, CO (University of Colorado), and Ithaca, NY (Cornell University), are known as college towns. This could imply that the presence of a large student population may drive up rental prices due to demand, possibly impacting the affordability for non-student renters as well.
5. Variation in Cost Burden: While the percentage of renters experiencing a high cost burden is significant in all these MSAs, there is a noticeable variation, with Gainesville at the lower end (58.7%) and Miami-Fort Lauderdale at the higher end (62.6%). This variation might reflect differences in local economies, housing supply constraints, and demographic pressures.

Need housing burden data for smaller geographies than MSAs?

We can help. You can request this data as your 1 free table add on when you purchase a spreadsheet report. Or for $100, you can get a custom manual calculation added to your radius report.

Got more questions about housing burden data? Send me a message, and we’ll be talking about data in no time.

Sources: 

Bureau of Labor Statistics

• Quarterly Census of Employment and Wages (updated March 8, 2023)

Federal Housing Finance Agency

• Annual House Price Indexes - Counties (Developmental Index; Not Seasonally Adjusted), Annual House Price Indexes - States (Developmental Index; Not Seasonally Adjusted) Updated March 28, 2023

US Census Bureau

• 2022 American Community Survey 1 Year (updated September 2023)

The US Census Bureau released the updated 2022 American Community Survey demographics for all geographies earlier this month. And we’ve been scurrying around like Santa’s elves to bring you the latest data and geographies as well as new features.

New 2022 Demographics & Geographies

The most remarkable change was a complete reconfiguration of Connecticut counties. As you can see in the maps below, the 2022 Connecticut counties don’t play nice (aka aren’t contiguous with) the 2021 counties — which is going to make historical comparisons tricky.

Map of 2022 Connecticut Counties

Source: data.census.gov

2021 Connecticut Counties

Source: data.census.gov

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Radius Report Updates

You now get 4 new types of data included in your Radius Reports for no additional fee.

• 1. Median Home Value Estimates and 2. High Home Value Categories

Back in 2010 – which was around when we first started offering radius reports – about 10% of US homes had value estimates of over $500,000 cite. According to the latest 2022 data, over 26% of US homes now have value estimates of over $500,000 cite.

Now your radius reports include more detailed categories describing these high-value homes. The new fields are highlighted below in an example report for New York City.

• 3. Population Density in people per square miles

• 4. The count and percentage of Families in Poverty

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Income By Zip Code Lists and Demographics By Lists Updates

Income By Zip Code lists and Demographics By Zips/Cities/Counties have been polished up with the following improvements.

• Improved human-readable headers to help you scan the data and understand it

• Improved database-friendly headers so you can upload the file to ChatGPT, and it natively understands what’s in each column

• Improved Citations & Notes

• Moved GEOIDs to the end to get them out of your way

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Income By Zip Code Maps

New Feature! You can now export data for selected zips from the Income By Zip Code map interface. Here’s how.

Got questions about 2022 Census data or the new features above? Have ideas for additional features that save you time? Send me a message, and we’ll be geeking out about data in no time.