Hila Qu on Hiring and Building a Product Growth Practice

Hila Qu studied biology and liked the idea of scientific experiments, although she jokes that she was not good at lab work. After an MBA she became a data analyst, then joined GrowthHackers as a growth product manager so she could act on the insights as well as analyze them.

She later led growth at Acorns and built a growth team at GitLab. At the time of the interview she advised companies on growth, drawing on experience in both consumer and business products.

At Acorns, Qu says, the roundup feature gave early users a product they loved and generated word of mouth. The company then layered in paid channels, referrals and new product lines; additional revenue could support higher acquisition spending.

Her Acorns team covered the full funnel: acquisition, signup, investment, paid conversion, retention and additional products. Marketing, product, design, engineering and analytics worked together to identify and test opportunities across that journey.

Qu cautions that the Facebook tactics she describes came from an earlier advertising environment and may not transfer after privacy and platform changes. Her broader lesson is the process: a cross-functional team met frequently, shared data and launched creative tests quickly.

The team used targeting and attribution tools but also tested a large volume of ads. She recalls an ordinary-person gas-station ad outperforming celebrity creative and a simple investing math question drawing attention; these are examples from that period, not current platform benchmarks.

For an early company, Qu suggests trying a few channels to learn, then investing in one that works rather than spreading effort too thin. She also recommends developing slower organic channels such as content, search or referrals over time, instead of relying only on paid acquisition.

Many experiments failed. She recalls a NASCAR sponsorship without visible lift and other channels that produced results but were hard to scale. Her advice is to evaluate channels in their actual business context rather than assume a successful playbook transfers unchanged.

A paid referral program gave both the existing user and a friend $5, with additional monthly incentives for multiple referrals. It initially produced good numbers and users, but over time the quality of referred users declined; Qu stresses watching longer-term outcomes as well as short-term conversion.

She defines growth as both a result and a discipline. The result might be users or revenue, ideally sustained; the discipline applies data and experimentation to acquisition, activation, monetization and retention through product and marketing.

At Acorns, the consumer growth organization included acquisition, lifecycle marketing, product experiments and analytics. Qu says a cross-functional team spanning the user journey gave her the ability to connect those levers instead of treating downloads as the only objective.

At GitLab, the core product growth squad also included product, design, engineering and analytics, but the broader B2B buying journey required close work with marketing and sales. Multiple stakeholders and longer purchase cycles make the surrounding organization different from a consumer app.

The usual advice is to find product-market fit before hiring for growth. Qu adds an exception: when collaboration or network effects are fundamental to the product, an experienced growth product manager may help build those mechanisms earlier, including before a Series A.

For a first hire, she often prefers an experienced growth product manager or marketer over either a very senior executive or a complete beginner. She looks for analytical ability, willingness to learn across disciplines and the initiative to work with limited resources.

Founders should explain the culture and opportunity honestly to a prospective hire. Qu says growth work is much harder if the company does not value data and experimentation or the hire must constantly fight for resources and leadership support.

She generally places agencies later in the journey. Founders must understand the core growth model and initial channels themselves, she argues; specialists can help scale a known paid channel or support a bounded need such as pricing or ad creative.

A growth adviser can help map a model, identify possible channels and design product-led mechanisms, but needs a founder or internal team to execute. Qu is herself an adviser and describes a client relationship in which an analytical internal partner helped coordinate the work.

She says advisers may work on a monthly retainer for six months or a year, with a mix of cash and equity depending on stage and the person. She does not provide a fixed equity percentage and says her own arrangements vary; her perspective is informed by her advisory business.

For hiring, the founder first needs a job description grounded in the company's growth model and immediate needs. A business with an established paid channel may need a channel specialist, while one seeking to improve onboarding and conversion may need a product-focused growth leader.

The description can name the north star and initial focus areas, such as onboarding, activation or conversion, without claiming every answer is already known. Qu then recommends using networks and referrals, screening relevant experience and involving the future hire's collaborators in interviews.

Her take-home exercise asks candidates to experience the hiring company's product as a new user, sketch the funnel and identify the metrics that would show whether it works. A funnel that ends at downloading the app, without considering what happens afterward, is a warning sign for her.

She also asks for three experiments with hypotheses and success measures, plus an open-ended analysis of real data. The exercise is intended to show how candidates learn, reason about data and choose what to investigate.

A favorite interview question is the most unexpected experimental result a candidate has seen and what they did next. Qu considers a claim that every test worked as planned a red flag, as well as an ego that prevents someone from learning or cooperating across teams.

In the first week, a new growth hire should learn the tools and earlier initiatives, examine historical data, meet leaders and collaborators, and listen to customer conversations. The aim is to understand the starting point before prescribing changes.

In the first month, Qu suggests picking a metric and a focused area, launching experiments or quick fixes, establishing communication with stakeholders and identifying gaps in tracking. Early wins can build confidence and help a new leader obtain support.

By the end of the first quarter, she wants the team moving from isolated wins to a repeatable program: a growth model, an experiment cadence, a record of results, a weekly meeting and a culture that supports learning. These are her suggested objectives, not guaranteed outcomes for every hire.

A data-minded growth hire can help clean up foundations, but Qu says consumer teams should understand both channel attribution and what users do inside the product. A tracking plan and instrumented events matter more than a dashboard alone.

She observes that business software companies built around sales may have weaker product-usage data. A first step for product-led growth is connecting product events with purchase data; joining those with sales and marketing systems is useful but more difficult.

Qu says a north star should sit at the intersection of the business objective, customer value and current strategic direction. Revenue may be the company-level outcome, but a growth team needs actionable inputs that can improve it.

At GitLab, she says the company tracked annual recurring revenue growth, while her team could work on inputs such as activation and free-to-paid conversion. She favors keeping the north star relatively stable and reviewing specific input metrics more frequently, often quarterly.

Activation and conversion can provide early opportunities because an audit of the website, signup, onboarding and purchase journey may reveal changes worth testing. Qu says quick wins can establish trust, but they still need to be measured and followed up.

She describes content/search, paid and referral loops: an output such as new content, revenue or a new user feeds another cycle of growth. A loop is a strategic way to understand compounding, while a funnel exposes the steps and drop-offs within it.

Drawing a circle does not make a functioning loop. A referral mechanism needs motivation and a smooth experience, and the team has to test whether people actually use it rather than simply assuming it will compound.

The person running an experiment should document its hypothesis, result and next step in a simple shared system. Qu points to GitLab's public handbook as an example, but says a document or slide deck can also work.

Sharing the lesson is as important as storing it. At Acorns, she says a retirement-calculator ad performed well enough that the concept informed emails and a product feature, allowing one channel's learning to help other teams.

For small B2B samples, waiting for statistical significance can take a long time. Qu says teams sometimes make a judgment with incomplete data; she recommends adding qualitative customer feedback and monitoring for adverse effects rather than presenting the outcome as certain.

In quick-fire answers, she says tactics and channels change while data, experimentation and human psychology remain useful principles. Her examples of different operating practices in China and the United States reflect her observations at the time, not rules for every business.

She identifies culture and weak data foundations as common reasons growth teams fail. A prospective growth leader should assess the leadership team and whether the company has the conditions to support the work.

Qu says an early mistake was moving too quickly without stakeholder buy-in: even a successful experiment can face resistance when it is time to implement the result. In 2023 she points to ChatGPT's organic word of mouth and Miro's product-led approach as strategies she admired.

Stebbings thanks Qu for the conversation, and she closes the interview.