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Cindy Zhu (Yuan)

Staff Data Engineer @ Shopify

Professional Background

Connie Carey, known for her relentless pursuit of excellence in product management, is currently making significant strides as a Product Manager at Heap, a leading company that empowers businesses to harness customer data for enhanced decision-making. At Heap, Connie is instrumental in shaping the product roadmap, ensuring that data-driven product decisions remain at the core of the company's mission. Her extensive experience in various high-profile roles has equipped her with a unique perspective on product growth and user engagement.

In her current position, Connie focuses on delivering a best-in-class digital experience, enabling organizations to understand their customers on a deeper level through comprehensive data insights. Heap’s innovative platform changes the way analytics are approached—from reactive reporting to proactive insights, allowing businesses to drive acquisition and delight customers while minimizing the burden on engineering teams.

Before joining Heap, Connie honed her skills in data engineering and business intelligence across several prominent tech companies, including Shopify, Square, and Instagram. Through her diverse roles, she has accumulated extensive experience in transforming raw data into actionable insights and has consistently contributed to the development of data strategies that empower businesses to thrive in a highly competitive landscape.

Education and Achievements

Connie's academic journey is rooted in engineering, having earned both her Bachelor of Science in Engineering (Bioengineering) and her Master of Science in Engineering (Systems Engineering) from the prestigious University of Pennsylvania. This strong educational background has not only provided her with technical expertise but has also equipped her with analytical and problem-solving skills essential for success in the tech industry.

Her academic endeavors included serving as a Teaching Assistant for BE301 (Signals and Systems) and EAS105 (Introduction to MATLAB), where she demonstrated her understanding of complex engineering principles and helped guide students through intricate concepts, further solidifying her leadership capabilities.

Career Trajectory and Notable Contributions

Connie’s career trajectory is impressive, to say the least. She began her professional journey at Old Navy as a Business Analyst focusing on Inventory Planning, where she developed a keen understanding of data's role in optimizing business operations. Her transition into the tech world took a significant leap as she joined Gap Inc. as a Business Intelligence Intern, where she cultivated her data analysis skills.

Following her internship, Connie further developed her expertise at Glossier, Inc., where she worked as a BI Engineer, contributing to marketing strategy, planning, and analytics. At Square, she held multiple roles, including BI Engineering Lead and BI Engineer - Marketing Strategy, demonstrating her adaptability and leadership in various contexts.

One of her notable roles was as a Product Growth Analyst at Instagram, where she influenced product decisions that led to significant user engagement improvements. Her time at Shopify as a Staff Data Engineer honed her technical skills and exposed her to a fast-paced SaaS environment that thrived on data-driven innovation.

Connie's vast experience across these roles underscores her capability to bridge the gap between technical proficiency and product management, making her an invaluable asset in any organization she engages with. At each step of her career, she has consistently contributed to elevating data analytics practices, thereby fostering a culture of insights-driven decision-making.

Achievements

Throughout her career, Connie has achieved numerous milestones that showcase her capabilities as a thought leader in product management and data engineering. At Heap, she leverages her wealth of experience to develop innovative products that facilitate actionable insights, ensuring businesses can respond to their customers' needs swiftly and effectively.

Moreover, Connie actively shares her insights and perspectives through initiatives such as the

where she explores pressing questions and challenges facing the industry today. This not only highlights her commitment to professional development but also her dedication to fostering a community where knowledge-sharing is paramount. Her work continues to inspire other professionals in the field to pursue excellence and prioritize user-centric product development.

title

Product Manager, Data-Driven Decision-Making, Heap

Engineering, Bioengineering, University of Pennsylvania, Data Analyst, Product Growth Analyst, Engineering Lead, Business Intelligence, Marketing Strategy, E-Commerce, Teaching Assistant, Analytics Intern, Digital Experience, User Engagement, Product Roadmap, Customer Data Insights, Insights-Driven Decision-Making, Data Analytics, Data Engineering

Highlights

Oct 19 · linkedin

When our data scientists analyzed millions of user events and found that 𝟖𝟒% 𝐨𝐟 𝐟𝐮𝐧𝐧𝐞𝐥𝐬 𝐝𝐞𝐥𝐢𝐯𝐞𝐫 𝐦𝐢𝐬𝐥𝐞𝐚𝐝𝐢𝐧𝐠 𝐝𝐚𝐭𝐚, we knew we had to build something better. That’s why today we’re proud to release 𝐉𝐨𝐮𝐫𝐧𝐞𝐲 𝐌𝐚𝐩𝐬.

Journey Maps helps you understand the real journeys customers take on your site, surfacing the choices users encounter — and take — as they move through the experience you’ve created. And paired with Heap's foundational, complete data you can know:

➡️ If users who do step X are more likely to convert ➡️ Which steps users skip (and which users skip them) ➡️ Which key steps are you unknowingly not tracking ➡️ Which funnels are you unknowingly not tracking ➡️ What alternative paths users take

These aren’t things funnels can currently show you. Journey Maps is the only tool on the market that tracks these user choices so you can quickly and accurately understand how every single user behavior affects conversion.

Check it out! #GetRealInsights (Check the Comments for the blog post!)

Jul 26 · linkedin

"𝐅𝐨𝐫 𝐞𝐯𝐞𝐫𝐲 𝐝𝐨𝐮𝐛𝐥𝐢𝐧𝐠 𝐨𝐟 𝐞𝐟𝐟𝐨𝐫𝐭, 𝐰𝐞’𝐯𝐞 𝐨𝐛𝐬𝐞𝐫𝐯𝐞𝐝 𝐜𝐨𝐧𝐯𝐞𝐫𝐬𝐢𝐨𝐧 𝐫𝐚𝐭𝐞 𝐝𝐫𝐨𝐩𝐬 𝐛𝐲 𝐚𝐛𝐨𝐮𝐭 𝟏𝟔 𝐩𝐞𝐫𝐜𝐞𝐧𝐭𝐚𝐠𝐞 𝐩𝐨𝐢𝐧𝐭𝐬." When you notice that a user flow has a lower than expected conversion rate, do you know what's causing it? How do you dig into that question?

Here at Heap, we often hear teams worry over reducing the number of steps in a funnel (more steps means it takes longer to complete the user flow, right?).

But that's only part of the picture. It also matters that users aren't expending too much "effort" on any one single step. Each step of your user flow is made up of many interactions (think filling out forms, click or tapping around), and "effort" can be quantified as the number of interactions the average user takes to complete a step in your flow.

When lots of interactions are needed to complete a step, it's a strong signal that the step is difficult to complete. Our team found that every doubling of effort decreases the conversion rate by 16%. If your user flow consists of many steps—and that adds up!

Historically, quantifying effort has been really hard. PMs have relied on qualitative data (in aggregate), low sample size user testing, or watching session replays. Unfortunately, these techniques don't scale.

That's why we're excited to offer Effort Analysis. Teams can now quantify the effort needed to complete each step of the funnel. With Effort Analysis, PMs can easily isolate steps to improve, justify the investment, and watch your conversion rates go up.

Check it out! #Illuminatedinsights #Effortanalysis

Related Questions

How did Connie Carey develop her expertise in product management at Heap?
What strategies does Connie Carey implement to drive user engagement through data insights?
In what ways has Connie's education at the University of Pennsylvania influenced her career trajectory in engineering?
How has Connie's experience at major tech companies shaped her approach to product growth and analytics?
What are some challenges that Connie Carey has faced in her career and how has she overcome them?
Cindy Zhu (Yuan)
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New York, New York, United States