SHPE User Analysis II

SHPE User Analysis II was the natural evolution of a research program that had already proven its value. Building on the demographic foundation established in the first user analysis, this second iteration tracked changes across the membership, informed spring programming decisions, and secured an additional $2,500 grant from the Associated Students. It also served as a formal "state of the chapter" handoff document for incoming leadership. 

Project Background

SHPE, the Society of Hispanic Professional Engineers, is a national organization dedicated to uplifting Hispanic-identified engineering students through scholarships, professional development, and community building. SHPE Southwestern College is one of many chapters nationwide.

Following the completion of the Fall semester, and with the college announcing expanded in-person activity, our Faculty Advisor and I identified a clear opportunity to conduct a second user outreach campaign. The goals were threefold: re-evaluate member needs and goals, prepare for Spring event scheduling, and measure any changes or improvements from our initial research efforts.

A new semester also brought a new funding opportunity from the Associated Students. Having invested the full Fall semester grant in marketing, events, and professional development, additional funding was both needed and justified.

With e-board elections approaching, we also saw this as an opportunity to leave incoming leadership a comprehensive "state of the chapter" document, complete with updated data points and user personas. The first user analysis had already demonstrated its value by contributing to a 200% increase in chapter membership. We wanted to give the next board the same foundation to build from.

The survey followed the same structure as the first iteration, with one key addition: a question allowing returning members to identify themselves, enabling separate analysis of new versus returning member data to track meaningful changes over time.

Challenges

Compared to the first user analysis, outreach constraints were significantly reduced. By this point, STEM professors across the college were already familiar with our organization and most had actively helped distribute the initial survey. The groundwork had been laid.

The primary challenge this time was methodological rather than logistical. Our Faculty Advisor wanted to differentiate returning participants from new members in order to track meaningful changes over time. This required some back and forth to explain how survey design tools could accommodate that distinction through targeted question logic, without compromising the integrity of the data or requiring a separate survey entirely. It was ultimately a conversation about tech fluency as much as research design, and navigating it gave me early experience translating technical concepts for non-technical stakeholders.

Budget and Timelines

As with the first iteration, the project operated with no budget.

The response window was intentionally shorter than the first survey, running approximately one month in total, for three reasons. COVID-19 protocols had eased enough to allow in-person activity on campus, giving us the opportunity to remind members face-to-face to participate. Professors were already familiar with our organization, eliminating the need for cold outreach. And timing was critical: we needed both the current and incoming board to have access to the findings before the semester ended. A longer response window would have made the data useful only to incoming leadership.

Research Methods 

The research method remained consistent with the first user analysis, a Google Forms survey distributed through faculty and in-person outreach. Consistency was a deliberate choice: maintaining the same format allowed for direct comparison between the two datasets and made it easier to identify meaningful changes over time.

The only structural addition was a single question allowing returning members to identify themselves, enabling separate analysis of new versus returning member responses. This small change significantly expanded the analytical value of the data without disrupting the experience for participants.

Key Findings

Three shifts stood out from the comparative analysis.

First, the chapter's academic profile was diversifying. Mechanical Engineering remained the top major but dropped from 40% to 35.7% of membership. Aerospace Engineering appeared for the first time as a declared major, and Computer Science grew by 6% , a jump significant enough to warrant its own programming track.

Second, the gender gap remained visible and unresolved. Female representation had not meaningfully changed, reinforcing the need for continued intentional programming to close it.

Third, the primary discovery channel had shifted. In the Fall, Social Media drove 38.9% of new member discovery. By Spring, Word of Mouth had taken over at 41.2% — a direct reflection of COVID-19 restrictions lifting and in-person community rebuilding itself.

Each of these shifts informed concrete decisions about programming, guest speakers, and outreach strategy for the incoming board.

Impact

The impact of the second user analysis was felt across three areas.

Financially, the data supported a successful Spring grant application. Spring allocations are historically more competitive — more organizations qualify, meaning the available funding is distributed more broadly. Despite that context, we secured $2,500 for the chapter. The data-backed allocations package justified every line item. We deliberately requested only what we needed, as stronger institutional relationships with UC and CSU partners and San Diego County's professional SHPE chapter were already opening doors to sponsorships and additional funding streams.

Programmatically, the findings directly shaped the Spring calendar. The 6% increase in Computer Science members led to the creation of a dedicated CS-only meetup series focused on networking and resume development. Internship programming and Hackathon prep were added in anticipation of competing in SF Hacks for a second consecutive year. Mechanical Engineering programming remained unchanged despite the slight membership decrease, as it retained the largest share of the chapter's academic profile.

On equity, the persistent gender gap in the data prompted a more intentional approach to representation. The chapter deepened its collaboration with SWE, the Society of Women Engineers, and committed to prioritizing women speakers across all guest speaker programming.

Lessons Learned

The most significant lesson from this second iteration was how quickly user data can shift, and how consequential it is to track those shifts regularly.

In the span of roughly four months, the chapter's academic profile had changed, a new discovery channel had emerged, and an entire segment of the membership had been largely overlooked. The 6% increase in Computer Science members was not just a data point. It was evidence of a group that had been present but underserved, and that only became visible because we looked for it.

This experience gave me a concrete understanding of why organizations conduct user research continuously rather than once. In our case, falling behind on data meant missing member needs. In a corporate context, the same gap translates to missed product opportunities or lost revenue.

The final lesson was about adaptability. Watching the primary discovery channel shift from social media to word of mouth as the world reopened made clear that user behavior does not exist in a vacuum. External events shape how people find, join, and engage with organizations. Research that captures those shifts in real time gives decision makers something reactive strategy alone cannot: context.

At the close of this project, I passed the research framework and findings to the incoming Marketing and Outreach Coordinator as a foundation for their first semester. Two user analyses, one for each semester, had produced a 200% membership increase, two successful grant cycles, and a data-driven programming strategy that the chapter could continue building on.

It was the first time I saw research function not just as a tool for decision making, but as institutional memory, something that outlasts any single person in a role.