The quiet hum of keyboards and muffled voices of developers fill the Tangiblee office. Here, amidst lines of code and user flow diagrams, Diana Lebedeva orchestrates the symphony of product development. Her desk is a command center, where sticky notes with ideas neighbor analytics printouts, and her monitor displays Jira, Figma, and Google Analytics simultaneously.
"In product development, there's no room for 'maybe' or 'someday,'" Diana says. "Every decision is a choice between 'now' and 'never.'"
Diana Lebedeva is a technical PM with experience in international companies and startups. Her journey from developing fintech solutions to creating AR technologies for e-commerce giants is marked by her ability to balance ambitious business goals with technical constraints. At Tangiblee, Diana became the first product manager, building processes from scratch that allowed the company to scale and attract clients like Pandora, Bulgari, and Kate Spade.
This interview is your chance to peek behind the curtain of product development and learn how decisions that shape the future of technological products are made. Whether you're an aspiring product manager, an experienced developer, or an entrepreneur looking to improve processes in your company, Diana's insights will help you gain a fresh perspective on task prioritization and product management in the dynamic world of technology.
Diana, can you tell us how you came into the role of a technical product manager and what unique challenges this position presents in terms of prioritization?
My path to becoming a technical product manager was quite organic. Starting my career in fintech projects, I quickly realized how critical a deep understanding of the technical side of the product is for its successful development. At Tangiblee, this need became even more evident—we work at the intersection of e-commerce and cutting-edge AR technologies, where every decision has both business and technical implications.
The key challenge in my role is the need to constantly balance three aspects: technical capabilities, business goals, and user needs. For example, working on the Tangiblee 'Embed' project, we aimed to create a seamless user experience by integrating our widget directly into clients' pages. This required not only technical solutions for asynchronous loading and performance optimization but also a deep understanding of our clients' business metrics, such as conversion rates and time on site.
In the context of prioritization, this means that every decision must be viewed through the lens of these three aspects. We constantly ask ourselves: How technically feasible is this? How will it affect key business indicators? Will it improve the user experience?
Another unique aspect of my role is the need to 'translate' between technical and business languages. I often have to explain the business value of certain features to developers, and technical limitations and possibilities to management. This is crucial for proper prioritization and ensuring that the entire team is moving in the same direction.
Finally, working with advanced technologies like AR and machine learning adds an extra layer of complexity to prioritization. We often encounter tasks for which there are no ready-made solutions, and we have to balance between innovative experiments and product stability.
At Tangiblee, you were the first product manager. How did you approach creating prioritization processes from scratch? What key factors did you consider?
We started by implementing a data-driven culture, systematically collecting and analyzing usage metrics, client feedback, and performance indicators.
A key element was developing a task evaluation matrix that considered impact on business metrics, technical complexity, strategic alignment, and urgency. Each parameter was rated on a scale of 1–5, giving us a quantitative basis for decision-making.
Given the specifics of AR in e-commerce, we created a separate category for innovative projects critical for long-term success but not yielding immediate results.
We involved the entire team in the prioritization process through regular planning sessions, which improved the quality of decisions and increased engagement. Implementing quarterly priority reviews ensured flexibility in response to market and technology changes.
This iterative process significantly accelerated product development, increased customer satisfaction, and improved resource utilization efficiency. Experience has shown that effective prioritization is not just a technique but a culture that requires constant development and support.
You mentioned creating task evaluation rules. Can you share what criteria you used for evaluation and how this helped in setting priorities?
This development became a key element of our prioritization process at Tangiblee. We created a system that balances objectivity with the specifics of our AR product for e-commerce. The main criteria include business value (30%), technical complexity (25%), strategic alignment (20%), urgency (15%), and innovation potential (10%). Each criterion is evaluated on a five-point scale, giving us a quantitative basis for decision-making.
For assessing technical complexity, we use T-shirt sizing, translating it into numerical values. It's important to note that high complexity doesn't always mean low priority—complex tasks can bring the greatest value.
This system brought us several advantages: objectivity, transparency, flexibility, improved communication, and focus on value. However, we face challenges, the main one being the need to maintain the system's relevance constantly. We regularly review the criteria and their weights to reflect current business and market realities.
It's important not to get carried away with the 'mathematics' and remember the real users and business needs behind the numbers. Therefore, we always complement quantitative assessment with qualitative analysis and team discussions. This system has become a powerful tool, structuring the decision-making process and significantly increasing the efficiency of our product work.
It's interesting to hear about your experience working on the Tangiblee "Embed" project. How did you balance technical constraints and business goals when prioritizing tasks in this project?
The Embed project at Tangiblee presented a complex challenge of integrating our virtual try-on widget directly into clients' pages. This required careful balancing between business goals and technical constraints.
From a business perspective, our goals were clear: increase user engagement, improve conversion rates, and optimize the user experience by making it more intuitive. Technical challenges included the need for asynchronous loading, ensuring compatibility with various CMS and frameworks, minimizing impact on client site performance, and guaranteeing data security.
Our approach to solving this task was multifaceted:
- Phased implementation: We divided the project into stages, starting with basic widget integration. This allowed us to quickly receive feedback and iteratively improve the product.
- Intensive A/B testing: We systematically tested each significant change, allowing us to make decisions based on real data rather than assumptions.
- Developing a flexible architecture: We invested significant time in creating an adaptive architecture. This decision, while requiring large initial investments, substantially simplified further adaptation of the widget to various client requirements.
- Strict performance control: We established rigid performance criteria, for example, limiting the increase in page load time to no more than 200 ms.
- Comprehensive monitoring: We implemented a real-time monitoring system tracking both technical metrics (load time, error frequency) and business indicators (conversion, duration of interaction with the widget).
The results exceeded expectations: some clients saw conversion rates increase by up to 23% while maintaining high performance and solution flexibility.
The key takeaway from this project: technical constraints and business goals should not be viewed as contradictory factors. On the contrary, the right balance between them often leads to innovative solutions that move the product forward. The project's success was based on constant communication between technical and business teams, an iterative approach, and data-driven decision-making. In product development, while intuition is important, it's more reliable to rely on objective data and thorough analysis.
In working on "Embed," you interacted with the machine learning team. How did this affect the prioritization process? What new aspects did you have to consider?
Working on the 'Embed' project with the machine learning team revolutionized our approach to task prioritization. We faced a new level of uncertainty—try accurately estimating how long it will take to train a model for body part recognition! This forced us to seriously reconsider our processes.
We introduced a category of 'research tasks,' divided the evaluation of ML tasks into research and implementation stages, and began to consider specific ML metrics in prioritization. Regular cross-functional discussions became our lifeline—they helped keep everyone on the same page.
Interestingly, working with ML made us think about ethics. When your model recognizes body parts, privacy issues come to the forefront. We even included an ethical aspect in our prioritization matrix.
The most challenging part was explaining to the business why we needed to invest in ML research that doesn't yield immediate results. We created a special dashboard that visually demonstrated how improvements in the ML model affect the time users spend in the application and conversion rates.
In the end, we not only integrated ML into the product but also created a more flexible development culture. The main lesson? ML in product development is not just about technologies but also about the ability to manage uncertainty and effectively explain complex things in simple terms.
In your experience, there's a project on automating monitoring and alerts. How did you determine priorities when developing internal tools, considering their indirect impact on the final product?
At Tangiblee, we launched a monitoring automation project that truly tested our approach to prioritization. The main challenge? Convincing management to invest in something that customers don't directly see. We approached this with numbers in hand: we showed that developers were spending a whopping 20% of their time on manual monitoring, and we calculated the cost of delays in problem detection.
To prioritize tasks within the project, we developed our own matrix, taking into account the criticality of problems, their frequency of occurrence, the complexity of automation, and potential effect. This helped us focus on what really matters.
Interestingly, throughout the project, we constantly discovered new problem areas. So we had to act flexibly, regularly reviewing priorities. We actively involved developers in this process—their insights were invaluable.
The results exceeded expectations: response time to critical issues was reduced by 70%, data loss incidents decreased by 85%, and developers regained 15% of their time.
The main lesson? Working on internal tools can radically improve team efficiency and product quality. But to achieve this, you need to be able to link this work to business goals, involve users in development, and be ready to constantly adapt.
You mentioned working with various methodologies, including Agile. How did you adapt these approaches to optimize processes in your projects?
At Tangiblee, we didn't just take Scrum and start using it. We approached the development process creatively, taking into account the specifics of our AR product. For example, we played with sprint durations—sometimes a week, sometimes two, depending on the task. For routine support tasks, we incorporated Kanban to avoid slowing down the main development.
We significantly enhanced user feedback by inviting users to demos after each sprint. This really helped us improve the product faster. Within the team, we created mini-teams for different parts of the product, which accelerated decision-making.
A special feature was 'technical sprints' for refactoring. This allowed us to keep the code clean and avoid accumulating technical debt. We also dedicated time to innovation—10% of the team's time went to research and experiments.
When we started working with machine learning for virtual try-on, we had to adapt again—model training processes required a different approach.
The main thing I realized: there's no ideal methodology for everyone. You need to take the best from different approaches and not be afraid to experiment. Thanks to this, we were able to speed up the release of new features by 40% and significantly increase user satisfaction. In modern development, the key to success is flexibility and readiness to constantly change.
Looking back on your experience, what advice would you give to aspiring technical product managers in terms of process optimization and working with priorities?
To aspiring technical product managers, I would advise, first and foremost, to deeply understand the business goals of the company and the product—this is the foundation for proper prioritization. It's critically important to develop data skills and technical expertise—this will help you communicate effectively with both developers and business stakeholders. Create a clear system for prioritizing tasks, but be flexible in applying development methodologies. Invest time in building efficient processes and constantly focus on the user, regularly collecting feedback.
Don't forget about technical debt and the importance of innovation; allocate time for research tasks and refactoring. Learn to manage expectations, be ready for compromises, and develop empathy—this will help you find more effective solutions and manage conflicts. Implement a culture of continuous measurement and analysis of results; this is the basis for continuous process improvement. And remember, the role of a technical product manager is about constant learning and adaptation. Be open to new experiences, don't be afraid of mistakes, and always strive for improvement. Your ability to learn and adapt will become a key factor for success in this dynamic and exciting role.
Overall, my main advice is this: be curious, don't be afraid to experiment, and always strive to understand how your product can make users' lives better. This is the true mission of a product manager—to create products that truly change the world for the better.
* This is a contributed article and this content does not necessarily represent the views of sciencetimes.com