Podcast Summary
Understanding Engagement and Retention: Identifying shifts in user engagement and retention through cohort analysis is crucial for product growth. Engagement is a valuable metric for investors and demonstrates user stickiness, making it harder to manipulate compared to user acquisition. Network effects and the focus on power users are key aspects of successful products.
Engagement and retention are crucial aspects of product growth, especially after the initial user acquisition phase. As the user base evolves, users may engage with the product differently, and cohort analysis can help identify these shifts. Network effects and the progression of successful products may lead to a focus on engagement and retention, as acquiring new users becomes more challenging. Engagement is a valuable metric for investors as it demonstrates user stickiness, and it's harder to manipulate compared to user acquisition. The experts, Andrew Chen and Jeff Jordan, discussed various aspects of engagement and retention, including network effects, the importance of measuring and finding power users, and the power user curve.
Understanding user engagement through cohort analysis: Cohort analysis groups users based on join date and examines their activity levels over time to reveal engagement patterns and trends, helping businesses adapt strategies for retention and re-engagement.
Analyzing user engagement through cohort analysis is crucial for understanding and improving retention and long-term growth in a business, especially in marketplaces. Cohort analysis involves grouping users based on when they joined and examining their activity levels over time. The resulting curves often reveal similar patterns of engagement, with some users remaining active and others gradually becoming less so. Identifying trends in these curves can help businesses understand how usage patterns change and adapt their strategies accordingly. As a startup grows, the focus shifts from acquisition to retention and then to re-engagement. The net monthly active users (MAUs) of a business can be calculated using the growth accounting equation, which takes into account new users, churned users, and re-engaged users. Understanding the degradation of user engagement and where it goes is essential for building successful business models in marketplaces.
Understanding user cohorts in network effect businesses: Cohort analysis is vital for assessing network effect businesses' value over time. Segment cohorts demographically or geographically for hyperlocal insights, or compare engagement levels in B2B companies with varying team sizes.
Analyzing user cohorts is crucial for understanding network effect businesses, as these businesses become more valuable as more users join. Cohort analysis can reveal if the business is indeed more valuable over time, as newer cohorts should exhibit better behavior. Segmenting cohorts based on demographics or market geography can provide valuable insights for hyperlocal businesses, while comparing engagement levels in B2B companies with varying team sizes can help assess product usage. After acquiring new users, ensuring they become engaged users is essential, often involving an onboarding process that helps users understand the product's value. This moment of understanding can be a turning point, but user engagement can also be a cumulative effect as more users join the platform.
Identifying and optimizing the 'magic moment' for users: Companies must understand and engineer the moment users first experience value and engagement to maximize retention and growth. Facebook leverages existing user base and content, while Pinterest prioritizes localized content and compelling information for new users. Post-acquisition, focus on activation, retention, and upselling to existing users.
Understanding and engineering the "magic moment" for users is crucial for the success of a product or service. This moment is when users first experience the value proposition and become engaged and retained. For some companies like Facebook, the magic moment lies in the existing user base and content, making the experience more powerful. For others, like Pinterest, it may require localized content and compelling information to attract new users. Once users are acquired, efforts shift towards activation, retention, and engagement to maximize the value derived from each user. Companies like Pinterest also prioritize upselling to existing users over acquiring new ones due to the higher cost of acquisition in the SaaS context. Ultimately, identifying and optimizing the magic moment is essential for businesses to deliver a valuable experience to users and drive long-term growth.
Mapping user engagement and moving users up the ladder: Identify user behaviors and profiles of successful users, refine product and education, offer incentives, and analyze user behavior to optimize engagement strategies.
Understanding user engagement and moving users up the ladder of engagement is crucial for long-term success of a product or service. Companies should segment their users into an engagement map and identify the behaviors and profiles of successful users versus those who are not. Each product has a ladder of engagement, and moving users from one step to the next requires content and education, incentives, and product refinement. The frequency with which a product is consumed also plays a role in marketing and user implications. For instance, commerce apps like eBay can have high engagement due to users' passion, while services like OpenTable and Airbnb have more episodic usage. Facebook, with its large user base, analyzes user behavior to identify long-term, sticky users and optimizes engagement accordingly. Companies should invest in data science to understand user behavior and optimize engagement strategies.
Measuring User Behavior: Frequency and Retention: Understanding user behavior through frequency and retention metrics like DAU/MAU and l28 helps tailor engagement strategies to specific products, improving overall engagement and retention.
Understanding user behavior through measurement is crucial for engagement and retention strategies. Frequency is a key engagement metric, with daily active users (DAU) divided by monthly active users (MAU) providing insights into user activity levels. However, DAU/MAU may not be suitable for all products, as some naturally have lower frequencies of use. Facebook popularized the DAU/MAU metric due to its advertising business model, but it's essential to consider the product's nature when selecting metrics. For instance, a travel product may have a low DAU/MAU ratio due to its infrequent use, yet still be valuable. Another metric, l28 (last 28 days), is a histogram that shows the number of users using a product each day in a month, providing insights into user segments and retention. It's essential to consider various engagement metrics and adapt strategies based on the product's unique characteristics. In summary, measuring user behavior through engagement metrics like frequency and retention helps tailor strategies to specific products, ensuring a better understanding of user behavior and improving overall engagement and retention.
The Power of Engagement in Venture Businesses: Engagement is a valuable and rare indicator of a product's potential, leading to increased acquisition and user behavior. Metrics like DAUs and MAUs provide insight into user involvement, and high levels of engagement signal a strong connection between users and the product, attracting investor interest.
Engagement is a crucial factor in the success of a venture business beyond just raw growth. The speaker emphasized that a significant engaged audience is rare and valuable, as it leads to increased acquisition and is difficult to game. Growth can be artificially inflated through various means, but engagement is more challenging to manipulate and is the true indicator of a product's potential. Social media platforms like Facebook, WhatsApp, and Instagram, as well as commerce sites like OfferUp, have shown the power of engagement in driving user behavior and value. Engagement metrics, such as daily active users (DAUs) and monthly active users (MAUs), provide insight into the stickiness of a product and the depth of user involvement. The speaker also noted that sending out more notifications or emails can actually decrease engagement rather than increase it, as hardcore users are already engaging and casual users may become disengaged. Ultimately, investors are interested in businesses that not only show growth but also high levels of engagement, as it indicates a strong connection between users and the product.
Understanding Network Effects and Engagement for Business Growth: Network effects and engagement are crucial for business growth. Network effects make a platform more valuable as more users join, while engagement keeps them coming back. Engagement and retention are related but not the same, and focusing on both leads to a more valuable and sustainable business.
Engagement and network effects are crucial elements for the growth and success of a business. While network effects make a platform more valuable as more users join, engagement keeps those users coming back. Network effects can be analyzed as a curve rather than a binary yes or no, and improving engagement often leads to better investment returns. Engagement and retention are related but not the same – for example, weather apps have high retention but low engagement frequency. By focusing on both engagement and network effects, businesses can attract and retain users, leading to a more valuable and sustainable business.
Engagement vs Retention: Two Different Metrics: Companies must excel in engagement or retention to succeed, with frequent use not always equating to long-term retention. Netflix's binge-watching format makes it harder for new products to capture users' minutes, and content providers must compete against various distractions.
Engagement and retention are two distinct metrics in the world of consumer products. While engagement refers to how frequently or how much time a user interacts with a product, retention is about whether they continue using it after a certain period. The weather app example illustrates this, as people may check it frequently but not retain it for long, while high-engagement products like games or ebooks may have less frequent use but higher retention. Companies must excel in at least one of these areas to succeed, and it's becoming increasingly challenging to capture users' attention as competition grows. The taxonomy of metrics includes acquisition, engagement (frequency and time), and retention, with retention and frequency having different models. Netflix's binge-watching format is a game-changer, making it harder for new consumer products to capture users' minutes, which are increasingly dominated by incumbents like Facebook, Amazon, and Google. Additionally, content providers must recognize they're competing for attention against various distractions, not just other media outlets.
Tailoring retention metrics to unique business models: Companies should customize their retention metrics based on the specific needs and behaviors of their user base to accurately measure engagement and retention.
Assessing the retention of a consumer business can be a complex task due to the varying frequency and nature of consumer engagement. While some businesses, like Netflix or YouTube, focus on long-term engagement, others, such as Google or costume stores, thrive on intermittent usage. To effectively measure retention, companies need to tailor their metrics to the unique characteristics of their business model. For instance, Google prioritizes getting users to their advertisers as quickly as possible, while Zillow focuses on staying top of mind even if users aren't buying houses frequently. Another approach is to measure upstream signals, such as website visits or app checks, to gauge consumer interest and engagement. Ultimately, the key is to understand the specific needs and behaviors of your user base and design your retention metrics accordingly.
Understanding business dynamics and improving through data-informed decisions: Focus on data-driven decisions to understand business dynamics, choose the right metrics, and build a sustainable product that engages customers and drives growth.
Building a successful product involves both intentional planning and continuous iteration, informed by deep data analysis. The product's behavior may evolve over time, and it's essential to test hypotheses and adapt strategies accordingly. While marketing can be both art and science, in the consumer internet, a data-driven approach tends to be more effective. Focus on understanding your business dynamics and improving it through data-informed decisions. Choose the right metrics that demonstrate value to your customers and build your team and product roadmap around that. Look for loops and networks within your product that can sustain engagement even in the face of competition. Ultimately, growth and engagement are key indicators of success.
