Sweta Portfolio

User Behaviour Metrics/Frameworks:

1. User Funnel Analysis: This framework involves tracking user behavior at different stages of the conversion funnel to identify areas of improvement and optimize user flow. Key metrics include:
2. Acquisition: Metrics related to user acquisition, such as the number of visitors, traffic sources, and cost per acquisition (CPA).
3. Activation: Metrics that measure user engagement and initial onboarding, such as account sign-ups, app installations, or initial usage.
4. Retention: Metrics that assess user retention and engagement over time, such as active users, user churn rate, or user sessions.
5. Revenue: Metrics related to revenue generation, such as conversion rates, average revenue per user (ARPU), or customer lifetime value (CLTV).

• User Engagement Metrics: These metrics focus on measuring user interaction and engagement within a product or service. Examples include:
• Time spent on the platform or app
• Number of sessions or visits
• Actions per session (e.g., clicks, likes, comments)
• Feature adoption rate (percentage of users utilizing specific features)
• Task completion rate (percentage of users successfully completing desired actions)
• Social sharing or referral metrics (e.g., shares, invites, referrals)

• User Experience (UX) Metrics: These metrics assess the quality of the user experience and usability of a product or service. Examples include:
• User satisfaction surveys (e.g., Net Promoter Score – NPS)
• System usability scale (SUS) scores
• User error rates (e.g., frequency and severity of user errors)
• Task success rate (percentage of users successfully completing specific tasks)
• Time on task (time taken by users to complete specific tasks)

• Cohort Analysis: Cohort analysis groups users based on a specific characteristic or time period to understand how user behavior evolves over time. Examples include:
• Time-based cohorts (e.g., users who signed up in a specific month)
• Behavioral cohorts (e.g., users who completed a specific action)
• Demographic-based cohorts (e.g., users of a particular age group or location)
• Retention cohorts (e.g., users who continued using the product over a specific period)

• A/B Testing and Conversion Rate Optimization (CRO): A/B testing involves comparing different versions of a product or feature to determine which performs better in terms of user behavior and conversions. Key metrics include:

• Click-through rate (CTR)
• Conversion rate (percentage of users who complete a desired action)
• Bounce rate (percentage of users who leave without further engagement)
• Average order value (AOV)
• Revenue per visitor (RPV)

Market Behaviour Metrics/Frameworks:

1. Market Size and Growth:
2. Total Addressable Market (TAM): The total market demand for a product or service.
3. Serviceable Available Market (SAM): The portion of the TAM that a company can realistically target and serve.
4. Share of Market (SOM): The percentage of the market controlled by a company or product.
5. Market growth rate: The rate at which the market is expanding.

• Competitive Analysis:
• Market Share: The percentage of the market controlled by a specific company or product.
• Competitive Positioning: Assessing how a product or company differentiates itself from competitors in terms of pricing, features, value proposition, or market positioning.
• SWOT Analysis: Analyzing the strengths, weaknesses, opportunities, and threats in the market, both for your own product/company and competitors.
• Porter’s Five Forces: Analyzing the competitive forces in an industry, including the bargaining power of suppliers, buyers, and competitors, as well as the threat of new entrants and substitutes.

• Market Segmentation:
• Demographic Segmentation: Dividing the market based on demographic factors such as age, gender, income, education, etc.
• Psychographic Segmentation: Dividing the market based on psychological factors like values, attitudes, lifestyle, and behaviors.
• Geographic Segmentation: Dividing the market based on geographic factors such as location, climate, culture, etc.
• Behavioral Segmentation: Dividing the market based on user behaviors and usage patterns.

• Customer Insights:
• Surveys and Interviews: Collecting qualitative data directly from customers to understand their preferences, needs, pain points, and buying behavior.
• Market Research: Conducting studies to gather quantitative data about market trends, customer behavior, and consumer sentiment.
• Social Listening and Sentiment Analysis: Monitoring and analyzing social media platforms, online communities, and review sites to understand customer sentiment and gather insights.

• Adoption and Diffusion:
• Technology Adoption Lifecycle: Identifying the different stages of customer adoption of a technology product or innovation, such as early adopters, early majority, late majority, and laggards.
• Diffusion of Innovation: Analyzing how new products or innovations spread within a market, including the innovators, early adopters, early majority, late majority, and laggards.

Both user behavior metrics/frameworks and market behavior metrics/frameworks are important for product managers. User behavior metrics focus on understanding and improving the user experience, while market behavior metrics provide insights into the broader market dynamics, competition, and customer segments. By combining these metrics and frameworks, product managers can make informed decisions to optimize product features, target the right market segments, and drive growth and profitability.