Vishal Bhatnagar, a seasoned entrepreneur with 22+ years of experience across different facets of Product Development and Technology. Have experience in developing, managing Mobile App (VOD, Live Media Streaming, and Dual Channel Live Chat) and SaaS based solutions in EduTech, B2B, B2C Industry verticals.
In conversation with Prisila, Correspondent, Asia Business Outlook Magazine. Vishal discusses prioritizing product backlog and the crucial role of data analysis in informing product decisions.
Balancing short-term and long-term goals in product management is a common challenge that requires careful planning, prioritization, and communication
Prioritize features or improvements in a product backlog and its factors.
Prioritizing features or improvements in a product backlog is a common and most important challenge for product managers and developers. There are many techniques and frameworks that can help decide what to work on first, depending on your goals, resources, and user feedback.
I personally prefer to use the RICE prioritization framework as it helps in making objective and data-driven decisions about what to work on next, based on the potential value and cost of each option. It also assists in communicating priorities to your team and stakeholders, and explains the rationale behind them.
Here is a brief explanation of each factor in the RICE framework:
Reach: This is the number of people or users who will be affected by your feature or idea in a given time period, for eg monthly active users, sign-ups, conversions, etc. As a PM one should estimate how many people will benefit from or encounter your feature or idea within a specific time frame, such as a month or a quarter.
Impact: This is the degree of positive or negative change that the feature or idea will have on your users or customers. You can use any measure that reflects your product goals, such as revenue, retention, satisfaction, etc. One should rate the impact on a scale from 0.25 (minimal) to 3 (massive), depending on how much value or improvement the feature or idea will provide.
Confidence: This is the level of certainty or uncertainty that you have in your estimates of reach and impact. You should rate the confidence on a percentage scale from 0% (low) to 100% (high). The higher the confidence, the more reliable will be the RICE score
Effort: This is the amount of effort or resources that the feature or idea will require to implement such as person-days, person-hours, story points, etc. You should estimate how much time or effort it will take to complete your feature or idea from start to finish.
To calculate the RICE score for each item in your backlog, you need to use this formula:
RICE score = (Reach x Impact x Confidence) / Effort
“Higher the RICE score, > higher will be the task Priority”
Some other popular methods which can also be used:-
Cost of Delay
PMs can also prioritize their product backlog by combining / customizing them according to their needs and preferences.
“The important thing isto have a clear and consistent process for making decisions and communicating them to your team and stakeholders”
Data analysis and quantitative measurement essential in product management.
Data analysis and quantitative measurement are essential in product management because they help in
Tracking and evaluating the performance of the product against the key performance indicators (KPIs), such as revenue, retention, satisfaction, LTV etc. Quantitative metrics, such as quality metrics, impact metrics, etc generally assist in measuring how well the product is achieving business goals and strategy.
1. Understanding and improving the user experience and behavior of your product.
We can use qualitative and quantitative data, such as feedback, surveys, interviews, A/B testing, etc. to gain insights into what users think, feel, need, and want from the product.
Data analysis techniques, such as trends analysis, path analysis, attribution analysis, cohort analysis, retention analysis, funnel analysis, etc. help to identify patterns, problems, opportunities and solutions for your product
2. Prioritizing and communicating the roadmap and features of your product. Data analysis and quantitative measurement help in validating assumptions and hypotheses about the product ideas and initiatives. As mentioned above, frameworks and methods, such as RICE, Kano model, MoSCoW and Cost of Delay help to rank and evaluate different features or improvements planned in the product
Data analysis and quantitative measurement is essential in product management because “they help in making clear objectives and arriving at data-driven decisionsthat can help deliver value to users and to business”
Concept of the conversion funnel and it's relevant to product management.
The conversion funnel is a visual representation of the customer journey that leads them to make purchases, subscribe, or sign up to use a product or service.
It is relevant to product management because
it helps teams to track and measure the performance of their product against their key goals and metrics, such as revenue, retention, satisfaction, etc
It helps teams to understand and improve the user experience and behavior of their product, by identifying the stages, steps, and actions that users take or skip in their journey, and the reasons why they do so
There are many methods to optimize the conversion funnel, depending on the product type, goals, and user needs. Some of the common methods are:
Segmenting the users into different groups or cohorts based on their characteristics, preferences, behaviors, or outcomes. This helps the teams to tailor their product features, messages, and offers to different user segments, and increase their relevance and engagement
Experience Testing different variations of the product features, design, content, or layout using methods such as A/B testing, multivariate testing, or split testing. This help teams to compare the results of different options and choose the ones that perform better in terms of conversions
Analyzing the user feedback, surveys, interviews, reviews, ratings, or comments to understand the user pain points, needs, expectations, and satisfaction with the product. This can help teams to identify the gaps and opportunities for improvement in the product value proposition, usability, functionality, or quality
Monitoring the user behavior and actions using tools such as analytics, heatmaps, session recordings, or funnel analysis. This helps teams to visualize and quantify how users interact with the product, where they drop off or convert, and what factors influence their decisions
"The conversion funnel is a visual representation of the customer journey that leads them to make purchases, subscribe, or sign up to use a product or service"
Tools and methodologies use for tracking and measuring product metrics.
Tracking and measuring product metrics is an essential part of product management, as it helps understand how the product is performing, how users are engaging with it, and how you can improve it to achieve your goals. There are many tools and methodologies that you can use for this purpose, depending on your needs and preferences.
Here are some examples:
Product analytics tools: These tools allow you to collect, analyze, and visualize data from your product and users. They can help you measure metrics such as user behavior, retention, conversion, satisfaction, etc. Popular product analytics tools are Amplitude, Mixpanel, Google Analytics, Twilio Segment etc …
KPI tracking tools: These tools allow us to define, monitor, and report outcomes against defined KPIs. These are the metrics that reflect the product's strategic objectives. They can help you track metrics such as revenue, growth, churn, etc.
A/B testing tools: These tools allow you to run experiments on your product features, design, content, or layout by comparing different versions of them with a subset of your users. They can help you optimize metrics such as conversion rate, engagement rate, click-through rate, etc. Some of the popular A/B testing tools are Optimizely, VWO, Unbounce, A/B tasty etc ..
Survey tools: These tools allow you to collect feedback from your users or customers through online surveys or forms. They can help you measure metrics such as customer satisfaction, net promoter score (NPS), customer effort score (CES), etc. Some of the popular survey tools are Okendo, Yotpo, SurveyMonkey, Typeform, Qualtrics, etc
Balance short-term and long-term goals in product management, especially when it comes to driving conversions and maintaining a sustainable product roadmap
Balancing short-term and long-term goals in product management is a common challenge that requires careful planning, prioritization, and communication.
Here are some tips on how to achieve this balance:
Step 1 : Focus on your vision and strategy: Have a clear and shared vision of what you want to achieve with your product in the long term, and how you plan to get there. This will help align your short-term needs with your long-term goals, and evaluate the impact and value of each option. You can ask yourself questions such as:
How does this short-term work move us closer to our vision?
What elements of this work can be reused or leveraged in the future?
Is there any risk or opportunity that this work creates or eliminates for our long-term success?
Step 2 : Assess your reality: It is important to understand the current situation of your product, your market, your users, and your resources. This will help you identify the gaps, problems, opportunities, and solutions that you need to address in the short term, and how they affect your long-term goals. You can use methods like
market research, and
other methods to gather and validate information about your reality
Step 3 : Be practical: Be realistic and pragmatic about what you can achieve in the short term, and what trade-offs you need to make. Use Frameworks and methods such as