English Q&A Rehearsal

Hi, I'm Johanna. It's great to meet you both. I recently graduated from Gonzaga University with a triple major in Economics, Mathematics, and Data Science.

That combination shaped how I work: Economics helps me see goals and trade-offs, Mathematics keeps the logic precise, and Data Science turns signals into a process I can test and improve.

Across my experience, the pattern is simple: I take scattered information and turn it into a clear next step. At Double Service, I organized client issues into handoffs engineering could use. In a group-buying community, I used member signals to make product recommendations more relevant, helping it grow from about thirty to six hundred members.

That's the work I want to do at Trend: understand what the client needs, make sense of what the campaign data is telling us, and help the team decide what to do next.

One process I'm proud of improving was at Double Service, where I supported a B2B SaaS platform used by twelve municipal clients. Issues came through LINE, email, and conversations. Some could disappear, and engineers sometimes received reports as thin as, “The button is broken.”

I didn't want to just move faster inside the mess. I stepped back and built a Notion issue board so every case had an owner, status, client impact, evidence, and next action.

Then I noticed the handoff was still slowing engineering down. I asked the engineers what customer support should check before escalating, taught myself SQL Server Profiler, and turned that into a simple checklist for reproducing the issue and attaching useful evidence.

Traceability reached about ninety percent, and average resolution time fell from roughly fifty minutes to thirty. What stayed with me is simple: make the work visible, then help the next person start from a better place.

Working with AI is a lot like working with a teammate: I make the goal clear, give it enough relevant context, and explain what good looks like. But the responsibility is different. AI handles repeatable work; I own the judgment and the relationship.

My own job search is a good example. First, I define whether a role fits, whether I have the evidence, and whether it deserves my time. AI uses those rules to narrow more than one thousand fresh openings to a shortlist. The goal isn't volume. It's finding the few worth pursuing. I make the final call.

Second, before a networking draft, I give it the context that matters: who the person is, where the conversation stands, and what the message needs to do. AI drafts; I decide what to send.

Third, I check every claim against the source. For higher-stakes work, a second model reads the result independently. If the two disagree, I go back to the evidence.

When reply, silence, and rejection patterns showed that one role pool wasn't producing momentum, I removed it from my default targeting. I fixed the rule, not just the next output.

AI makes iteration faster; I make each iteration trustworthy.

A friend and I ran a group-buying community that started with about thirty members. Our first approach was scheduled flash discounts. They brought people in for a moment, but when the discounts stopped, the buying stopped too.

At that point, I could have just added more deals. Instead, I stepped back and asked what the result was telling us. The problem wasn't reach. We weren't offering products that matched what people actually wanted.

I reviewed more than one thousand member messages and organized them into buying signals: what people were asking about, which products drew real interest, and who needed a follow-up. Then we shifted from pushing the same promotion to everyone toward recommending more relevant products to the right people.

Repeat purchases and word of mouth improved, and the community grew from about thirty to six hundred members. That experience changed how I think about tenacity: when something is not working, I do not just push harder. I read the signal and change the method.

The more I've learned about Trend, the more I want this job. Trend's job is getting the right lead to the right client, across many clients and industries where accuracy matters. That is a lot to learn, and honestly, that is what excites me.

I like that every client brings a new industry, audience, and definition of success. Finding structure in unfamiliar information is one of my strengths, and I want to get really good at understanding client goals, reading performance signals, and helping the team decide what to do next.

The in-person environment matters to me too. I want to learn beside experienced people, ask questions early, and turn feedback into more reliable work. Through this process, I've felt that Trend is willing to develop someone who is ready to grow. I really value that trust.

I want to build here, take on broader account responsibility, and become someone the team and clients can count on.

You should hire me because I know how to become useful quickly in a new environment. I find what matters, turn scattered client information into a clear next step, and check the details before a handoff.

I don't know Trend's platform, client mix, or internal playbook yet. I'll learn them by asking early instead of guessing and applying feedback quickly.

When someone teaches me something, I don't want them to have to teach me the same thing twice. I build that lesson into how I work, so the next round is more reliable. My goal is to earn your trust over time—first with the work, and then with the client relationship.

I do, thank you. I have two questions. First, Trend has grown quickly. As the account side scales, what is the first part of the client workflow you most want this role to make more reliable?

Second, Michael, what separates the people who grow fastest on the account team from everyone else?

Before we wrap up, I want to say it plainly: I want this job. Talking with both of you today has made me even more certain. If there's anything you'd like me to clarify, I'm happy to. And could you share what the next steps and timing look like?