Product Leadership
As Product Manager, I owned the roadmap and backlog for a cross-functional 5-person team, including myself, aligned sales, customer enablement, and executives on priorities, and shipped in versions so the business saw value early.
Role
UX Engineer / Product Manager
Team
Myself, 2 designers, 1 developer, 1 content creator
Timeline
Oct 2024 to Sep 2026
Partners
CEO, Director of Operations, Customer Enablement, Sales Rep
customer engagement and retention
of customers in the largest reorder cycle reordered within a month
faster quote processing for customer enablement
audience interaction
Dollar amounts and figures on this page have been altered for non-disclosure purposes. Percentages reflect actual results.
This page is about how I decide, align people, lead a team, and measure outcomes. For what I built myself, see the automation deep dive.
Sales reps had reached capacity and couldn't follow up with every customer and lead. Marketing had no formal process to fill that gap. Open quotes and quote requests were handled manually, so follow-up varied in wording, timing, and frequency from account to account.
The company's goal for the year was to grow revenue. My job was to turn that goal into a product: digitize follow-up in each sales rep's own pitch and tone, so the business could reach more customers and leads without adding headcount.
I audited our customer communications and found gaps at several stages, from qualified leads to open quotes to reorders. I then met with sales reps and the customer enablement team to understand each account's purchase behavior and communication channels: who places the order, who decides, and who requests it.
I set the omni-channel strategy with the CEO, Director of Operations, and Customer Enablement, so messaging stayed consistent across email, customer enablement, and sales.
For version 3, the content creator on my team helped me collect 30+ data points per contact into a spreadsheet. He also handled all of our social media and reported social media campaign data back to me. I turned that data into 3 personas (decision maker, influencer, and end user) that every campaign and communication now uses.
Sales reps
Customer enablement team, logistics manager
CEO, Director of Operations
Decision
Of all the gaps, I prioritized reorder reminders because repeat purchases tied most directly to the year's revenue goal.
Trade-off
Stakeholders wanted campaign stats built into version 1, but that would have put the ship date at risk. I explained that stats could wait for version 2: adding them would cost about a month, and we had already gone too long without talking to customers. Shipping first meant customers heard from us during that month.
Version 1
What shipped: reorder series sent as regular mass and individual emails; stops when the customer places an order
Why: start talking to customers fast
Version 2
What shipped: moved into tracked campaigns with stats
Why: measure what works
Version 3 · Planned
What ships: clean contact data; tailor content by subscription and persona
Why: personalize at scale
Large accounts got their own logic
For 3 major customers, decision makers, influencers, buyers, and end users sit in different parts of the organization. I branched a dedicated version of the series for each, because one generic series could not meet their KPIs.
I owned the product roadmap and backlog for a cross-functional team of 4: 2 designers, 1 developer, and 1 content creator.
Capacity and trade-offs: monitored team capacity, weighed effort against impact, delegated work, and re-prioritized as resources, feedback, and requirements changed.
Scrum from scratch: built and ran stand-ups, sprint, planning, retrospectives, and reviewed code with senior developer so designs shipped as intended.
Growing people: screened and hired designers, ran monthly 1:1 coaching and design reviews for junior designers, and guided content creators in structuring libraries around company goals.
Raising the bar across the company: trained stakeholders on UX best practices.
Design system as a team multiplier: led a centralized design system that cut design inconsistencies by 30% and shortened delivery timelines.
A moment that shows how I lead
Our senior designer estimated a project at 400 hours. The marketing manager wanted it cut to 200. The designer felt that timeline would sacrifice the quality of the work, and the two were at a standstill.
I stepped in to translate each side to the other. The manager needed a faster delivery; the designer needed enough time to do the work well. Both were reasonable, so instead of picking a number, I asked the designer to write out her workload: the phases, the steps, and what each one took.
Seeing her outline helped me understand her process. Combining it with my own background in design, I suggested a few changes that made her process better and faster. We worked through them together, so the plan was still hers.
I then walked the manager through the revised process. He agreed with it but still pushed back on the hours, and we met in the middle at close to 300.
Project estimate, in hours
What it shows
I don't settle a disagreement by splitting the difference blindly. I get into the work itself, find where it can actually improve, and bring both sides a plan they can stand behind.
Featured
Problem. Booth visitors and qualified leads from trade shows were not followed up consistently once the show ended, and sales reps did not have capacity to reach them all.
What I did. I identified the gap, mapped the customer journey from first invite to purchase, and turned it into a repeatable template: an invite before the show, a reminder the day before, and follow-ups after the show that move booth leads toward prospect and purchase.
Iterating. For the second trade show, I narrowed the list to hot, qualified leads that needed follow-up right away, to raise conversion.
Scale. The same journey can be replicated across trade shows, industries, and each sales rep's sales strategy.
Reused at scale: the templates were used for 7 trade shows across 3 industries: healthcare, education, and federal and state agencies.
Adapted by the sales reps: after each journey, the sales reps analyzed what worked and what didn't, then adapted the best parts to their own industry, and sometimes to the specific account they were talking to.
Results across 2 shows
Dollar amounts and figures on this page have been altered for non-disclosure purposes. Percentages reflect actual results. Customer and district names are replaced with placeholders.
Also led
Problem. The customer enablement team received 1 to 10 quote requests a day by email and processed each one by hand. Requests came in every shape: plain text, product codes typed in the body, PNG screenshots, PDFs. Someone had to read each one, work out who was asking for which products in what quantities, then check logistics and pricing before a quote could go out.
Buy or build
The company first planned to buy an AI-powered tool for this. I evaluated the vendor demo and found it was built on prepared scenarios that didn't match the requests we actually received, so the results looked too good to be true for our case. Instead, I went to the source.
I interviewed the logistics manager to learn how quote requests really worked:
With the research done, I worked with our developer, who built it, to define the requirements and shape the logic.
Keeping everyone aligned
I met frequently with the logistics manager through research, requirements, and testing, and monthly with stakeholders on progress and alignment.
Testing and scope
The first controlled test in production went through, but it surfaced MVP requirements that had not been included at the start. Adding them extended the project by a month. I explained to stakeholders, in detail, why each requirement was essential to a usable first version. There was pushback, but the explanation won their consent. When I left, the project was in its second round of controlled testing in production.
Result
35% faster
The logistics manager estimated that it sped up the customer enablement team's process by 35%. To confirm the exact number, I would pull reports on all requests for equal periods before and after go-live, comparing date and time received, ticket created, and fulfillment time.
Also led
I proposed a self-initiated journey for a large school district account to improve communication on a big opportunity. No one asked for it: I learned how the account makes budget decisions through its sales rep and designed a journey around that cycle. See the customer journeys page for the full journey.
I measured the product against the numbers sales reps already track, not just engagement metrics:
| Outcome | Result |
|---|---|
| Customer engagement and retention | +26% |
| Largest reorder cycle: customers who reordered within a month | 96% |
| Quote processing speed for customer enablement | 35% faster |
| Audience interaction (open, click, response rates) | +25 to 34% |
| Trade-show leads after targeting hot, qualified leads | 56 to 180 per show; first-email opens 33% to 64% |
| Design inconsistencies after the design system | 30% fewer |
Three lessons stayed with me.
Shipping early beat waiting for perfect requirements. Version 1 had us talking to customers a month sooner, and every version after it was shaped by real data instead of guesses.
A product earns adoption when it is measured on the team's own goals. Sales reps cared about closed-won deals and reorders, not open rates, so those are the numbers I reported.
The best answers came from going to the source: interviewing sales reps before mapping a journey, sitting down with the logistics manager instead of trusting a polished vendor demo, and asking a designer to walk me through her process before anyone cut her hours.
If I were continuing this work, I would ship version 3 to tailor content by subscription and persona, and pull before-and-after reports on quote intake to replace the 35% estimate with a measured number.