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Engagement Part VII: Summary and Product Implications

Data Science Team

Previous posts in this series covered content production, connections and inventory, ranking, consumption and feedback. In this post, we offer additional considerations that affect engagement overall.


Great products provide value by delivering highly engaging experiences, often multiple times per day. When you offer users “magical moments” and they truly love your product, they will come back to it more often—increasing their number of sessions per week and eventually becoming daily active users (DAUs). Because these DAUs continue to be weekly active users and monthly active users, as well, they ultimately increase the intensity of engagement for each group. Thus, engagement drives stickiness, which in turn drives retention and growth.

In an activity feed environment, these high levels of engagement are achieved by making content production easier for users, helping them connect with the content that is most relevant to them, showing them the right content in the right order, making sure they can consume content easily on any device and network, and enabling interaction (feedback) with your product (see Figure).

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Social pressure

As your users acquire larger audiences, they often feel pressure not to share what they see as low-quality content. Your Product team must establish a strategy to alleviate this pressure by offering a simple way for users to choose the audience for each type of content they share. You should also brainstorm ways users can share without feeling competitive.


Activity feed environments are generally best for surfacing relevant, recent activity. While users may want some content, such as photos and posts major life events, to be prominent permanently and shared with everyone, they may feel differently about the “everyday moments.” Building ephemerality into your product will encourage users to post this content. While Snapchat is the most obvious example of impermanence, this feature is also used by Facebook and Instagram, where users are prompted to share impermanent “stories.”

Consumption vs. Production

Users who get into “consumption mode” and spend their time watching videos, reading articles, etc., are less likely to produce their own content. Understanding the exchange rate between production and consumption and the types and amount of content users consume is therefore critical to making effective trade-offs. Specifically, it is useful for your Product team to quantify the degree to which content production decreases when a user is deep in content consumption mode.

Mission vs. organic product adoption

A founder’s vision for a product doesn’t always align with how people actually use it—and sometimes, organic adoption of your product conflicts with your company’s mission. For example, your product team might intend to build a social live video app through which users can share everyday personal moments, but users could adopt it to share socially offensive or sexually explicit material. Finding the right balance between what you envision the product to be and how users are adopting it is critical for long term success.

Explore versus exploit

In very low- and very high-inventory environments, it can be difficult to determine user preferences and make suggestions. In very low-inventory environments, there is simply not enough information; in high-inventory environments, a user may consume so little of their overall inventory that it is difficult to know whether they would have liked something they missed. You should determine whether it’s best to to optimize for (“exploit”) what you already know these users value or “explore” users’ responses to types of content they haven’t previously tried.

Mimicry and feedback

Because these are two of the most important drivers for producing content, you should consider how to address them as you build your product. While it is important to first achieve product-market fit, viral growth requires the effective use of both mimicry and feedback.


In the next series of posts, we will focus on providing guidance on engagement in the professional content context.


  • Engagement drives stickiness, retention and growth.
  • Driving a sustainable highly engaging product requires careful considerations.

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This work is a product of Sequoia Capital’s Data Science team. Chandra Narayanan and Hem Wadhar wrote this post. See the full data science series here. Please email with questions, comments and other feedback.

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