What made you want to do the work you do? Please share the full story.
I studied at Florida International University with a research-heavy focus, and I initially thought that path would lead me toward academia or straight data analysis somewhere far removed from anything a regular person would read. During a project involving consumer financial decisions, I kept noticing how much confusion people had around insurance specifically, not because the information didn’t exist, but because it was buried in dense policy language or scattered across sources that contradicted each other.
A family member’s car accident made it personal. Watching them try to understand why their premium jumped after a single at-fault claim, and getting three different answers from three different people, showed me there was a real gap between the data insurers use and what a driver actually understands about their own risk. That gap is what I decided to spend my career closing, translating the same rate factor data insurers rely on into something a person without a research background can actually use to make a decision.
Tell us 3 surprisingly easy and 3 surprisingly difficult things about your business.
Surprisingly easy: getting raw rate data from our carrier partners once the reporting relationships are established, since the underwriting side is more standardized across companies than people assume. Explaining basic terms like liability versus full coverage also comes easily once you’ve done it a hundred times, the concepts themselves aren’t complicated. Building the initial outline for a comparison piece is quick too, because the rate factor categories, age, claims history, driving record, repeat across almost every article I write.
Surprisingly difficult: getting an exact, defensible dollar figure for how a specific violation affects premiums, since that number shifts constantly by state, carrier, and individual driver profile, and readers want a single answer where there often isn’t one. Keeping content accurate as carrier pricing models change is a constant battle, since a percentage that was true six months ago can be outdated by the time someone reads the piece. And translating statistical nuance into something confident-sounding without oversimplifying it into something misleading is harder than it looks, because hedging too much loses the reader and not hedging enough risks giving bad guidance.
What are the 3 things you like best about your work and why?
I like the moment when a complicated data set turns into one clear sentence a reader can actually use, because that’s the entire point of the research background I bring to this job. I like that the work stays grounded in real numbers rather than opinion, since insurance pricing is something you can actually verify and explain rather than just assert.
And I like hearing from readers who say a specific article helped them understand a bill they were confused about, because that feedback loop confirms the translation actually worked and didn’t just sound good on paper.
What are your greatest 3 skills and how have they helped you succeed?
My research background lets me go straight to primary data, actual rate filings and carrier pricing patterns, instead of relying on secondhand summaries that might already be diluted or wrong, and that’s kept my work more accurate than pieces built on assumption. My ability to write plainly without stripping out the actual substance has helped readers trust the content enough to act on it, since insurance writing fails the moment it either oversimplifies into uselessness or stays too technical to follow.
And my comfort sitting with ambiguous or incomplete data, rather than forcing a false sense of certainty into a number that isn’t fully settled, has kept my published work defensible even when carrier pricing models shift underneath it.
Tell us about a time you were dead wrong about something.
Early on, I assumed that a DUI would raise premiums by roughly the same percentage across every state, since the violation itself is treated similarly in most legal codes. I published an early comparison piece built partly on that assumption, only to have a reader from a state with unusually strict insurance regulations point out that the actual increase they experienced was more than double what my article suggested.
Going back through the state-specific rate filings, I found the gap came down to how differently individual states allow insurers to weight that particular violation in their pricing models, something I hadn’t dug into deeply enough before generalizing. I corrected the piece to break the figure out by state instead of giving one blended number, and it changed how I approach every rate factor article since, I no longer trust a single national average without checking whether the underlying state data actually supports treating it as one number.
Have you considered buying a business? Tell us about that experience.
I looked seriously at buying a small content agency about two years ago, one that specialized in financial writing for smaller regional companies. I got as far as reviewing their client contracts and traffic data before walking away, mainly because the agency’s growth was built almost entirely on a couple of large retainer clients rather than a diversified base, which felt too fragile for what I was willing to take on.
The experience taught me more about evaluating a business than any class could, especially how to separate a healthy revenue number from a genuinely stable one. I still think about acquiring something similar down the line, but next time I’ll be looking much harder at client concentration before I get emotionally invested in a deal.
What is a habit you try to stick to and how has it helped you?
I pull the actual state insurance filing data before I write a single sentence of any article, even when I think I already know the number from a previous piece. It’s tempting to work from memory once you’ve covered rate factors for a while, but pricing models shift more often than people assume, and I’ve caught outdated assumptions in my own thinking more than once by forcing myself back to the primary source every time.
That habit has kept my published work accurate in a field where being slightly wrong with a number can mislead someone making a real financial decision, and it’s become the one non-negotiable step in my process regardless of deadline pressure.
What achievement are you the proudest of and why?
I’m proudest of a state-by-state DUI rate impact guide I rebuilt after realizing my earlier version had blended a national average that didn’t hold up under scrutiny. Reworking it meant pulling individual state filings one at a time instead of relying on one convenient combined figure, which took considerably longer than the original piece did.
That guide is now one of the most referenced pieces I’ve written, and readers regularly tell us it’s the first place they found a straight answer specific to their own state instead of a vague national range. It’s proof that the slower, more rigorous version of the work is the one that actually helps someone.
What is your favorite book and why?
I keep coming back to “How to Lie with Statistics” by Darrell Huff, even though it was written decades before anyone imagined the kind of data I work with now. It lays out, plainly and without jargon, all the small ways numbers get twisted into misleading conclusions, whether through cherry-picked averages or graphs that exaggerate a trend.
Reading it early in my research training changed how I look at every data set I touch, including my own work, since it’s just as easy to accidentally mislead someone as it is to do it on purpose. I reread sections of it whenever I start a new project involving rate comparisons, as a kind of check against my own shortcuts.
If you do charity or volunteer work, what is it and why do you do it?
I volunteer with a local financial literacy program that runs evening sessions for young adults who are about to buy their first car or apartment, walking them through things like reading an insurance quote or understanding what a deductible actually means before they sign anything. I do it because so much of what confuses adults about insurance is stuff nobody ever sat down and explained to them the first time it mattered.
Watching someone go from nervous about a stack of paperwork to confidently asking the right questions is the same reward I get from writing, just in a room instead of on a page, and it keeps me connected to the actual person behind every rate factor I write about.
Who has been your biggest mentor in life (personal or professional) and how have they helped you?
A professor at Florida International University pushed me hard on distinguishing correlation from causation in every single project I brought her, to the point where I started hearing her voice in my head before publishing anything with a number attached to it. She never let me get away with a claim that sounded right but wasn’t actually supported by the underlying data.
That discipline is the entire foundation of how I approach insurance writing now, since this industry is full of numbers that sound intuitive but fall apart the moment you check the source, and she’s the reason I check the source every time instead of trusting the intuitive version.
Just for fun, what is your favorite food?
Arroz con pollo, made the way my grandmother used to make it, with the rice slightly crisped at the bottom of the pot. It’s the kind of dish that takes real patience to get right, which honestly reminds me a little of good research, you can rush it, but you’ll notice the difference if you do.