Chapter 1 Evolution of a Product

The 4 phases of growing

1. Early phase

  • In the first month, all monthly active users(MAUs) are new usres, no churn(流失) or resurrection(复活).
  • In the second month, there is no resurrection but churn from the first-month users.
  • In the third month, a balance between new users, churn and resurrection begins to emerge.


the total number of active users for a given time period = retention + resurrection + new users
month-over-month net user growth = $\frac{new users+resurrected users}{churned users}$

Healthy products during the Early phase

  • Cohort retention is strong compared to similar products in the space that have similar levels of penetration.
  • There is a group of users that absolutely love the product, which is reflected in very high retention.
  • New users are the largest share of active users.

2. Growth Phase

It’s important to think about who the next hundreds of thousands of users to adopt the product will be — and what changes should be made to accommodate them.


During this phase:

  • the biggest contributor by far to overall active users is retained users
  • new users become a smaller percentage of MAU
  • the product’s market penetration begins to increase

Healthy products during the Growth phase

  • Older cohorts’ retention curves flatten and perhaps slightly improve.
  • New users account for a decreasing percentage of total users.
  • Overall churn remains higher than resurrection but is driven primarily by the newest cohorts.
  • Engagement metrics get stronger.

3. Hyper Growth Phase

During this phase, the one-month (M1) retention levels of newer cohorts begin to increase relative to those of the previous cohorts over the same time frame, thus improving the ratio of resurrection to churn. This typically begins when either 1) a certain level of penetration is reached with respect to the total addressable market or 2) the product becomes very well-known. In addition, older cohorts start to resurrect in greater numbers during this phase and churn begins to decrease. All users, new and old, find value from the product.

In this period, MAU grows dramatically as resurrection exceeds churn and the product continues adding new users. This may be the fastest year-over-year growth your company will ever experience. All engagement metrics, such as L5+/7, number of sessions and MAU/DAU (daily active users) are strong, and the product has achieved both product-market fit and scale.

Healthy products during the Hyper Growth phase

  • Older cohorts’ retention curves improve.
  • Resurrection is greater than churn.
  • Engagement metrics are very strong.

4. Mature Phase

During this period:

  • a high level of penetration
  • the product is no longer growing
  • Every cohort, old and new, has reached a steady balance between resurrection and churn, and, at the cohort level, the sum of retained users is equal to the overall number of active users.

Healthy products during the Mature phase

  • Resurrection and churn have balanced.
  • The number of new users is extremely small compared to the number of retained users.
  • Engagement metrics are retained at very high levels.

After Mature phase

To continue to grow your product after hitting maturity, you must diversify your portfolio and increase your total addressable market. This could mean entering new markets, launching new products, etc.


Growth of additional products or in new environments will again follow an S-curve: growing slowly at first, then accelerating, increasing rapidly and approaching an exponential growth rate, and ultimately reaching saturation. By diversifying, you overlap S-curves and allow for continued growth.


For example, consider Netflix’s journey. The company started its streaming product in the United States in 2007 and went into its Hyper Growth phase in 2010. At this time, executives at Netflix had already started laying the infrastructure for international expansion, and the platform formally launched in other countries in late 2010. By the time U.S. growth hit maturity a few years later, the international business (which is itself a series of overlapping S-curves) was driving most of Netflix’s subscriber growth.
Most businesses should, like Netflix, think proactively about product and vertical adjacencies while in the Growth phase of their primary products. Delaying the launch of a second act — or failing to launch one at all — will stunt growth.

Takeaways

  • The phases of growth resemble an S-curve and include Early, Growth, Hyper Growth and Mature.
  • Early on, new users are the largest contributor to growth, with churn outstripping resurrection.
  • As your product grows and market penetration begins to increase, new users continue to be the biggest driver of net growth while resurrection becomes more significant, with older cohorts achieving a balance between resurrection and churn.
  • In the Hyper Growth stage, retention improves in older cohorts with resurrection outpacing churn.
  • As your product begins to completely penetrate the market, a balance emerges between resurrection and churn with new users contributing negligible growth.
  • Diversification in the form of multiple product lines is critical to achieve sustained long-term growth.



Chapter 2 Measuring Product Health

Consumer companies should measure aspects such as growth, retention, stickiness and engagement.

User adoption and growth

  • The total number of active users is the truest measure of your product’s impact.
  • It is important to understand product and user growth in the context of the overall market.
    • the number of users
    • the total addressable market (TAM) of your product (总潜在市场)
    • the different between the number of users and TAM
    • the serviceable addressable market(SAM)
    • your competitor’s share of market(SOM)
  • S curve (4 phases)

How do you know if you are growing at the “right” rate?
It’s valuable to benchmark your product with other products at the same stage. Knowing how fast similar products grew at the same level of market penetration can give you a sense of whether your product is special.

Market metrics

To monitor growth, it is useful to track both your monthly active users (MAU) as a percentage of overall installs and the total number of installs as a percentage of your market.

As installs approach maximum TAM penetration, new user acquisition is no longer a tactic for incremental net growth, retention of your older cohorts needs to improve over time in order to produce net growth.

Keep in mind, different genres of apps have very different behaviors. For example, all games have a shelf life, regardless of how popular they may be at their peak.

Growth metrics

  1. The top growth metric you should track is the number of active users:
    • the total number of people who actively use the product on any given day is daily active users (DAU)
    • the number of unique active users in a given week is weekly active users (WAU)
    • the number of unique active users in a given month (MAU)
  2. Understanding how the number of active users changes:
    • day-over-day (D/D), week-over-week (W/W), month-over-month (M/M) and year-over-year (Y/Y)
    • tracking its rolling seven-day average may be more meaningful
    • it is best to use rolling metrics as opposed to calendar-based metrics
      For example, comparing MAU between February and January is misleading, as the months are different lengths; a 28-day rolling MAU would be preferable. Comparing 28-day rolling windows has the additional advantage of avoiding a day-of-the-week effect that could skew results.

  3. The growth accounting framework helps us understand which factors contribute most to growth by splitting growth into new users, resurrected users, retained users and churned users.

    Δ growth = new users + resurrected users — churned users

    Between any two timestamps (t1 and t2), the change in growth = new users acquired within this time frame + users who were not active at time t1 but came back by time t2 — users who were present in time t2 but not there in time t1.

  4. Some rates:
    • New users/MAU
      • For unhealthy companies, new users sometimes remain the largest driver of growth even after the product reaches a high degree of market penetration.
    • Sign-ups/Installs

Growth considerations

Possible segmentations It’s useful to monitor growth by multiple dimensions depending on what is most meaningful to your business: country, device, age, gender, phone year class, connectivity class, platform, age in product, etc. Keeping track of the referrer source (paid, organic, SEO, App Store) is particularly important.

Retention

Retention is the best indicator of whether your product is valuable and whether you have product-market fit — because it tells you whether people who tried your product liked it enough to return and use it again.

Generally, the first day or week is critical for a product with a new group of users. Do they have enough content to consume? Do they have a few close friends to chat with? Do they have a mental model of what the product is?

To enable healthy retention and build a successful product, you must have a core set of users. When you are starting out, always build your product for this set of users, focusing on the use case that matters most to them. This involves both creating a “magical moment” in which users first “get” the product and identifying the tipping point that establishes user retention.

For Facebook, the magical moment is when a new user sees the face of a friend for the first time. For WhatsApp, it’s the first message a person receives. For Amazon, it could be when a buyer receives their first purchase or has their first interaction with the customer service team.

Retention is also the most important lever for your product’s growth. Early retention can be a strong predictor of long-term retention. While the absolute value of retention depends on the type of product (social, gaming, messaging, etc.) and the time frame you choose to measure (daily, weekly, monthly, etc.), it’s always true that the higher the retention, the better.

Retention curves

  1. worst-case scenario : long-term cohort retention drops to zero and the product eventually dies
  2. nomal-case scenario : the retention curve flattens out at a number greater than zero. This ensures the product has active users — the higher it flattens out, the more users you have.
  3. best-case scenario : there may be a Hyper Growth phase in which the older cohorts start to increase their retention

Retention metrics

Retention is assessed in terms of cohorts — that is, by tracking a set of users who install a product on a given day, week or month and seeing what percentage of them return Ultimately, the goal is for the product to retain at high levels over a long period of time.

  • Dn/Mn/Wn (The D1 retention rate is D1/D0, the fraction of your cohort retained for one day. (D0 is the number of installers in a cohort, and D1 is the number in that cohort who still use the product after one day.)

  • Cohort curves

    Some additional tips for healthy retention:

    • Compare new cohort retention rates to old cohort retention rates and make sure they remain healthy over time.
    • Benchmark retention rates against similar products.
    • Ensure that cohort retention flattens — preferably at a high rate.

      STICKINESS