How to build a product operation data indicator system!

In the era of big data, the importance of data indicators to enterprises is self-evident. Data indicators are like the dashboard of the company's plane, allowing the captain to understand the aircraft's operating conditions in real time, when to accelerate and when to adjust direction, etc.

01. The rise of data indicator system

Everything starts with the story of the advertisement~

Today we have entered an era of universal informatization. There are actually many essential differences between the Information Age and the Industrial Age.

The biggest difference is the advertising and marketing method, which has progressed from the traditional indiscriminate publicity in print and electronic media to the current one-size-fits-all approach represented by Taobao.

In the past, some well-known consumer products were actually marketed through television advertisements.

Because at that time, consumer product manufacturers knew that as long as they sold advertisements on TV, their products would always become very popular in a short period of time.

However, at that time, no one had thought about what data changes were actually behind the best-selling products.

At that time, advertisers were more willing to spend more time polishing copy and creativity, and did not spend time studying such illusory data as advertising.

At that time, only one outstanding advertiser began to think in this regard, and he was the advertising godfather "David Ogilvy".

With the changes of the times, we have gradually entered the Internet age.

In just twenty years, the act of watching TV has been gradually eliminated by the younger generation of users (no longer watching programs on TV).

This means that the path for manufacturers to market through television advertising is gradually being blocked, and all advertisers are starting to think, since television is gone, can we move advertising to the Internet?

Subsequently, advertisers gradually shifted the marketing battlefield from traditional print and electronic media to new channels such as portals, elevator advertisements, and even Weibo information streams.

However, advertisers are facing a new round of challenges. They have no idea which channel users actually see the ads and then make purchases.

However, we cannot cut channel funding just because the current advertising conversion effect is not very obvious.

What if the funding for the channel with the best conversion rate is cut, leaving only the channel with poor conversion rate?

It was at this time that advertisers began to realize that this is no longer the same era as before, and it would most likely no longer be possible to use the old marketing methods.

So we started advocating two things:

• On the one hand, we study how today’s consumer decision paths have changed compared to the past.
• On the other hand, we should start learning about data analysis and gradually improve our data awareness, be as targeted as possible, and spend more money on high-conversion channels while saving the company's funds.

(Today’s Consumer Decision Chain)

At this point, we should all understand that if today's companies have achieved pm/f, they actually need to build their own data indicator system as soon as possible, otherwise it will be like flying a plane in the sky without a fuel gauge.

02. Product/Market Fit

Before we build an in-depth indicator system, we need to understand this concept first.

What is P/MF?

We have to mention here that we all know that "demand is the cornerstone of all growth". If there is no demand for the product, no matter how much time you spend, it will be a waste of time.

According to a survey by consulting firm CBinsights, the reasons for failed startups are usually the following:

In essence, the existence of the P/MF concept is to avoid the above-mentioned problems, so Product/Market Fit was born.

In order to meet the needs of the market, there are basically three different P/MFs in startups:

• Use better product experience to satisfy an existing market, for example: NetEase Cloud Music vs Kugou, QQ Music
• Use a product to meet an existing but partially unmet market demand, e.g. wireless headphones vs wired headphones, Didi vs taxi
• Use a product to create a new market, e.g. iPhone, Ford Motor

Therefore, during the company's business exploration, it is recommended to conduct analysis based on your own specific situation.

Of course, the concept of P/MF is emphasized here more to illustrate that only when P/MF is achieved can growth hackers have room to display their abilities.

If a company rushes to grow without even achieving P/MF, it will only accelerate the death of the product.

In other words, your product meeting market demand is the basis of growth hacking, and growth hacking is just a way of using data to help your product be discovered by users faster.

So, how do we verify whether our products have achieved P/MF ?

The answer is retention rate. Retention rate is a great way to measure product-market fit .

You must know that retention is the cornerstone of growth and the best lever for product growth rate by far.

A deeper understanding of retention rate will help us have a clearer understanding of users and guide the direction of product development.

If the retention rate is very poor and users leave immediately after coming in, then our product is not a funnel but a straight tube. Even products that are growing will eventually lose the favor of users over time.

So, how do you define retention?

Generally speaking, the definition of retention has three elements: target user group + time period + defined event

For example: The percentage of users who logged in today and logged in again within 7 days

In the example, login is an event, the users who log in today are the target user group, and the inspection period is within 7 days. It should be noted here that the previous and subsequent events must be consistent.

To help us view the changing trend of retention rate, we can reflect the retention rate by plotting the percentage of target users who repurchase the product or have a certain core feature (event) after a period of time (observation period).

There are three typical retention rate curves:

The method for drawing the retention curve is shown in the appendix at the end of the article.

After calculating for about 30 weeks in a row, you can get the retention curve. See what your retention curve corresponds to:

Downward trend: seen in most products, indicating that PMF has not been reached

Flattening: This means the product has reached PMF and has a good foundation for growth.

Smiling type: The product not only reaches PMF, but also has a large number of returning users, so that there will be a "negative flow"

However, if the retention rate remains stable at a very low level, we cannot say that the product has achieved PM/F.

To determine the “right” standard for long-term retention for your product, we can look to similar products and create benchmarks based on similar products.

For example, e-commerce companies can compare their products with other competing products of the same type.

Note: For reference only, sourced from the US YCombinator 2017 Growth Guide.

Of course, in addition to the above method for verifying PMF, the following two testing/observation methods can also be applied!

Sean Ellis Test :

Tell current users: You will no longer be able to use this product. If 40% of people say they are “very disappointed” with your product, then your product has achieved P/MF.

Method: Conduct a questionnaire survey on users

Data volume requirement: At least 40-50 responses are required to judge

Target user selection:

• Experienced with the core functions of the product
• Used at least twice
• Used in the past two weeks

Note: Don’t go to your relatives, friends or colleagues, as they may lie to save your face…

Indicator observation method :

That is: by observing some key indicators to prove whether the product has achieved P/MF.

The key indicators selected should basically meet the following three principles:

• Significant new user growth
• User retention
• Meaningful product usage behaviors

Common key indicators are quantified as follows:

• 30% next day retention
• New DAU exceeds 100
• Reach 100,000 users
• Users use the product more than 3 days a week
• 5% paid conversion rate
• LTV/CAC>3
• Monthly churn rate is less than 2%
• Payback time for user acquisition costs is < 12 months

03. How to set growth strategy priorities

Once the product reaches P/MF, we need to start analyzing the current business growth focus.

Why is it so important to develop a reasonable growth strategy as soon as possible after reaching PM/F?

Because although the AARRR model is essentially applicable to various industries, the actual focus of growth will also be different due to differences in market cycles, product stages and product categories.

If you don't understand the growth focus of your company, it's easy to focus on areas where you shouldn't be focusing at the moment. This can lead to a waste of manpower, material resources and time at best, and even the company's survival can become a problem at worst.

For example, Chatbao began to promote itself aggressively and used radical means such as cash withdrawals before it even started to retain users. In the end, it was destroyed by its own efforts.

Screenshot from: Baidu Encyclopedia

Only by combining the specific situation of the product can we clearly understand what the focus of the current growth strategy should be.

Evaluate the Growth Priorities Table.

Question 1: If our market is in the incremental stage, then we should focus more on acquiring customers and grabbing land, such as the price war between Didi and Uber, and the battle between thousands of groups. If you are in the stock market, you should focus more on how to strengthen retention and monetization, such as e-commerce, Taobao, Jingpin

Question 2: The key points that need to be considered in different stages of a product’s life cycle are also different.

Exploration phase: verify PMF, focus on retention

Seed users are willing to stay and use the product repeatedly. While verifying PMF, we can obtain real feedback, which enables us to continuously iterate and upgrade based on MVP. We can also lay the foundation for acquiring and retaining a larger user group in the future through the operation of seed users.

Growth stage: focus on attracting new users and taking into account monetization

When entering the growth stage, the product's core functional business processes have been fixed, and the business model's corporate barriers have been discovered and studied by other potential competitors.

A large number of competing products enter the market. At this time, the focus is to quickly stake out territory, acquire more users, and seize as much market share as possible before competing products.

But it should be noted that attracting new customers does not mean doing it at all costs. It is necessary to take into account monetization based on the actual situation to ensure that the company can survive. Of course, wealthy companies are welcome to do as they please.

For example, Pinduoduo and Taojiji are in sharp contrast. Pinduoduo's "10 billion subsidies" allowed it to compete vigorously with e-commerce giants, while Taojiji once had 70 million MAUs, but it had to leave the market due to a broken capital chain caused by its rapid expansion.

Mature stage: retention + monetization + new customer acquisition

Entering the mature stage, the product has reached its own "stock market", there are very few potential users, and the focus is on retention and monetization. Focus on user activity and expanding monetization business. Try to realize user value as much as possible without affecting user experience.

Decline stage: retention + monetization + traffic diversion

As we enter a recession, while striving to slow down the recession trend and maintain retention and monetization, we will look for new incremental markets, explore new usage and consumption scenarios, and drive traffic for new products.

Question 3: To which category does the product belong? We need to analyze it based on the following figure:

• E-commerce and SaaS: Optimize the payment conversion path, increase repurchase rate, and support long-term product growth, such as Taobao and JD.com
• Tools and content: Cultivate users to combine different scenarios, form habits, and seize users' time, for example: Youdao Dictionary
• Platform: Both retention and monetization are important. For the platform, it also requires a balance between supply and demand to facilitate transactions, for example: Douyin
• Social and gaming: Guide users to form high-frequency interactions, establish network effects, and acquire customers through self-propagation by old users bringing in new users, laying the foundation for long-term monetization, such as WeChat and King of Glory.
• Hybrid (such as social e-commerce): refer to the growth focus of platform + social and games, such as: Pinduoduo, community group buying

Question 4: What other important factors in the business model need to be considered? The following are some common important factors in our industry, for reference only:

• E-commerce: supply chain, goods
• Finance: Compliance, Policy, Law
• Platform: supplier selection, commerce, sales
• Video: content and algorithm-accurate recommendations, etc.

It is important to note that what is considered here is more about which industry-specific factors can greatly restrict growth or drive growth.

For example: After the gaming industry was subject to new policy supervision, policy became a new important factor. The important factors for free e-commerce brands are suppliers, logistics, etc.

After filling in the corresponding questions in the form, we can basically summarize where the company's current growth focus should be.

For example: Pinduoduo’s growth focus breakdown

(Pinduoduo’s growth focus analysis)

Once we have determined the focus of our growth strategy, we can start building a product data indicator system. To know what happens next, please listen to the next episode.

Final summary:

1. The rise of the data age has forced us to improve our data awareness and build other data indicator systems

2. Before we can grow, our product must first meet the PM/F prerequisites

3. Retention curve, Sean Ellis test and indicator observation method are three common methods to determine whether a product has reached PM/F status

4. Four questions to help you determine your growth priorities:

• What stage is your market in?
• What stage of the life cycle is your product in?
• What category does your product belong to?
• What are the important factors that are unique to your business model?

In the next article, we will introduce what the North Star indicator is, how to find the North Star indicator that suits us, and how to use the North Star indicator and context model to build our indicator system~

Author: Product Talk

Source: Product Talk