How to create product "growth power"?

Being able to demonstrate early growth is a key enabler for the proliferation of SaaS businesses. According to forward-looking forecasts, the scale of my country's public cloud SaaS market will reach 37 billion yuan in 2021, and the scale of enterprise-level SaaS market will reach 74 billion yuan. It is estimated that by 2026, the scale of my country's public cloud SaaS market will exceed 100 billion yuan, and the scale of enterprise-level SaaS market will exceed 270 billion yuan.

There are a lot of key metrics that describe the growth potential of SaaS: MAU, ARPU, DAU, K-factor, customer churn, MRR, LTV, NPS, etc.

"Key indicators" refer to demonstrating the growth potential of a product with the least cost and time.

For example: A few college students in a dorm room can demonstrate growth and develop products that millions or even billions of people want to use.

If the number of users is relatively small, then a SaaS startup can generate objective data that provides a good demonstration of its product/market fit (PMF).

However, it is much more difficult to collect objective data on hardware startups that have not yet shipped a product.

Hardware startups can also show growth potential just like SaaS businesses. But this requires some creativity, and every product and market is different, so generic metrics may not be precise enough.

There are some tips to make the process easier to implement, but a big mistake hardware startups often make is thinking they need a large number of users to evaluate product/market fit.

But when it comes to hardware products, getting data from tens of thousands of users often requires full production, which defeats the whole purpose of collecting key metrics.

Feedback from approximately 30 qualified potential customers was highly accurate in predicting long-term market adoption.

But the premise is:

• You know how to measure your product experience;
• The people you ask for feedback from must be your ideal target customers in order to gain valid insights.

Both of these are difficult to do, and you can implement them through the following three steps:

1. Understand your target users

1) Good “consumer” hardware startups need to understand and acquire data to characterize their customers in detail

• They understand the psychological and demographic characteristics that the earliest adopters (often called innovators or thought leaders) will have;
• They discover which marketing regions these users are most likely to live in and do work to prove that people in these marketing regions are likely to provide positive feedback after using the product;
• They know how many people in this country/world fit this profile and how best to reach them;
• They made the right assumptions about how to expand their customer base from innovators to early adopters.

2) Great B2B startups understand their market structure from the inside, often by talking to key stakeholders in the industry.

• They have a good understanding of the sales cycle timeline;
• They can make purchasing decisions within different types of organizations and determine how much money the decision makers need to spend;
• They have actively networked with client executives and prospective client field personnel, and some companies have even obtained signed letters of intent describing a given client’s willingness to purchase your product;

Understanding how to quantify customers is the basis for demonstrating growth potential. In the process of target user identification/quantification, startups that seek to find a small number of qualified users have a greater advantage.

2. Measure user engagement

Once you have identified your target customer base, the next step is to evaluate whether they respond well to your product.

This usually requires building a solid, functional prototype that users can interact with directly.

Focus on a strong minimal feature set MVP.

The best measure of growth is the number of people who have used your product. Mock “buy now” buttons and crowdfunding campaigns provide feedback on the number of people who want to solve a problem, not whether your product actually solves it.

At this stage, you can use some of the following tools to demonstrate growth:

2.1 Subjective Feedback

A long-standing mainstay of the product design process is conducting customer/user interviews, during which potential customers interact with product prototypes and answer a series of questions.

It would take several years to get interviews done well without significant bias, but it is a good data collection point regardless of objectivity.

Although written feedback is the most common, recorded videos may prove more effective.

2.2 "NPS" (Net Promoter Score)

Net Promoter Score is used to assess customer interest in your product.

When it comes to objectively measuring feedback, NPS is a great tool to have in your arsenal.

By asking customers “How likely are you to recommend our product to a friend?” on a scale of 0 to 10, startups can semi-objectively determine product/market fit (PMF).

NPS can find statistical correlations with small samples (about 30 people), making it an ideal tool for prototyping and customer development.

It’s proven that the more likely someone is to recommend a product, the more likely they are to purchase it.

NPS can only be accurately tracked if someone has used your product, and its simplicity removes much of the bias implicit in subjective feedback.

Among them, 0-6 points are not recommended, 7-8 points are not included in the NPS calculation range, and 9-10 points are recommended.

NPS = [(number of recommended users - number of non-recommended users) / number of users who return scores] * 100. It is generally believed that 30 points is good, 50 points is very good, and 70 points is excellent.

New Energy Vehicle NPS Ranking:

2.3 Sentiment Analysis

Most product designers are proficient at asking clear questions and reporting back on the clear answers given by users.

But this often overlooks the most important feedback we get: emotional feedback. Many people don’t realize that emotions trump rationality when it comes to making purchasing decisions.

When doing customer interviews for your product, recording basic emotional characteristics on a 1-5 scale is very helpful in showing how early users feel about the product.

2.3.1 Two driving factors for purchasing hardware products

Every purchasing decision made by a user is made up of both rational and emotional aspects.

Explicit content caters to your rational brain, for example, taglines, product descriptions, and reviews;

Implicit content is designed to appeal to your emotional needs, for example, images, colors, and advertisements.

Take the following product examples for example:

The product made two successful promises to users:

The first and most obvious promise is that it can save consumers energy and money.

It entices consumers to view their high-priced purchase as an investment rather than just a gadget.

But that’s not really why people buy.

Would the company be just as successful if their marketing profile looked like this:

Probably not; even if the two WiFi-connected thermostats did exactly the same thing, it would be hard for a company to sell them at a high price.

The second promise the product makes is more subtle, but more powerful.

It says: "No other thermostat in the world looks this good."

This promise is aimed at consumers who value aesthetics, a simple user interface and unique product qualities that make the product stand out from the competition.

It's an emotional and aspirational promise, and like almost all successful consumer products, the emotional factor is a big reason why people pay irrational prices for highly rational devices.

In the above example, the simple design and brand value drove the target consumer to pay, but as soon as someone (e.g., a family member or colleague) questioned the unreasonable purchase price,

The rebuttal is simple: “It saves us energy, it’s a long-term investment, and we’ll save this much money.”

2.3.2 Brand Premium

The valuation of consumer hardware products is the difference between the cost of selling the device and the irrational price that consumers are willing to pay. The difference between these two numbers is the brand premium.

A brand is more than a logo, and even more than marketing copy: a brand is a promise.

Brand is an unspoken language for consumer identity, which means that when buying products, emotion always outweighs reason.

Consumers don’t buy features, they buy into the promises made by brands:

Alibaba promises to make it easy to do business anywhere;

Tesla promises to show you as a visionary world changer;

Xiaomi is committed to enabling everyone to enjoy a better life brought by technology.

These promises cause us to open our wallets without really knowing why, even if we’re quick to make up a reason once we’re questioned.

The most valuable thing a consumer hardware startup can do is transform a rational product category into an emotional one.

When startups set out to develop consumer products, they should remember that they are not just building a gadget with a set of functions, but rather building a brand driven by emotion.

2.4 Word of mouth

While this doesn’t apply to all products/markets, the community that develops around a product and how it interacts with other users is a good predictor of overall market success.

You can demonstrate how the community has grown around your product, roughly equivalent to the “K factor” in SaaS products.

The K factor, also known as the viral coefficient, is used to measure the effectiveness of a recommendation, that is, how many new users a user who initiates a recommendation can bring.

K factor = number of users who initiated invitations * conversion rate.

example:

K = 3 * 0.3 = 0.9, which means that a user who initiates an invitation can eventually bring in 0.9 users.

Summarize

Demonstrate the core growth power of hardware products and be an inspiring product designer.

Author: Jianyi Business

Source: Jianyi Business