Draw your "ideal customer" in 3 steps: a guide for efficient customer acquisition for B2B companies

In the growth process of B2B enterprises, accurately positioning the "ideal customer" is the key to achieving efficient customer acquisition and customer success. This article provides a practical guide for To B operators, detailing how to build an "ideal customer portrait" in three steps for your reference.

Recently, we have been visiting a lot of customers. In addition to communicating with customers face to face and understanding their real needs to polish our products, we are also sorting out our standard customer portraits.

In the early stages of To B enterprise development, if there is no clear customer portrait, several problems will arise:

1. Inaccurate market launch;

2. Sales is following up with invalid customers;

3. Signed customers are easily lost;

These problems are real in our actual business process, especially when discussing product iterations in the early stages. When we see the needs of certain customers, we may even think that these customers should not be signed. Because not all customers are worth serving, only by finding the "right people" can we achieve customer success.

So today we are going to talk about how to sort out our "ideal customers" to make customer acquisition more accurate and efficient.

1. What is the Ideal Customer Profile (ICP)?

Ideal Customer Profile (ICP) is a model used by companies to define the target customer group that is "most likely to benefit from products or services and bring long-term value". It helps companies accurately locate high-potential customers, optimize resource allocation, and improve sales and marketing efficiency through a series of clear standards.

For example, accurate portraits can be used to score sales leads, perform precise content marketing, and efficiently allocate customer service resources.

2. Draw your “ideal customer” in 3 steps

Step 1: Discover the DNA of “golden customers”

To sort out the ideal customer portrait, we must first understand the characteristics of the customer. Companies at different stages of development will have some differences in sorting out customer characteristics:

Start-up To B business:

For start-up To B companies, product design often comes from the founder’s know-how about the industry. The basic data of customer portraits may be initially completed by a few initial seed users.

In the future, we can further improve our customer profile by interviewing customers to more accurately understand their business processes, demands, purchase motivations, and usage feedback based on the growth of our seed users.

To B business in the development stage:

To B companies in the development stage already have a certain customer base, and we can improve our customer profiles based on basic customer information + customer behavior data + customer renewal and additional purchases. Generally, we use the company's CRM and operation workbench to sort out customer profile information.

Of course, AI functions are gradually maturing, and we can use AI functions to summarize key information items and summarize ideal customer portraits. For example, although we don’t have an operations workbench now, we are trying to record, organize, and summarize in the form of multi-dimensional tables. Recently, the multi-dimensional documents of DingTalk and Feishu have been connected to Deepseek, which I think is quite useful.

Mature To B business:

For mature businesses, especially SaaS companies, financial data is also an important reference dimension for sorting out the "ideal customer portrait". Whether customers renew or increase their purchases, as well as the renewal rate, can also provide feedback on whether the product has captured the customer's pain points or whether it has found the right track.

To sort out the ideal customer portrait, we mainly analyze it through three key dimensions:

1) Industry and scenarios;

2) Enterprise size and development stage;

3) Decision chain portrait;

You can summarize and sort it out in the form of a table. The figure below is an illustration. If you want to do it well, you still have to sort out the table headers according to the specific business of the enterprise, so that you can make accurate judgments and applications.

Then we can organize our ICP customer portrait according to the table:

Step 2: Outline your “ideal customer”

Above we said that B2B companies at different stages can sort out customer portraits based on the data they have. Now that we have the data, we need to convert the data into implementable ICP standards.

1) Hard indicators

• Industry restricted areas: Which industries are excluded? (For example, the education industry has high policy risks)
• Size threshold: number of employees, revenue, and IT budget.
• Technical adaptation: Are the conditions for use met? (For example, an ERP system must have been deployed)

2) Soft indicators

• Business pain point priority: What is the most urgent problem for customers?
• Cultural fit: Do you recognize the value of long-term cooperation?
• Decision-making style: technology-driven or price-sensitive?

3) Template tools

Tables are always the most convenient tools. You can use them to create standardized templates and then just fill them in.

Step 3: Use ICP to drive efficiency growth

Okay, now we can apply the portrait to specific business scenarios to improve our conversion efficiency.

The main application scenarios of ICP portraits are:

1. Sales lead management;
2. Market acquisition;
3. Customer success;

1) Sales lead management

There has always been a contradiction between marketing and sales. Sales do not approve of some leads obtained by marketing, and the poor quality of marketing leads is blamed for poor sales conversion. Many companies have started to develop a lead scoring mechanism to output leads approved by sales (also known as SQL).

Label leads according to ICP standards (such as A/B/C levels) to improve the efficiency of lead flow between marketing and sales.

2) Market acquisition

The core of the ICP standard in the market is accurate delivery. Only by understanding the accurate customer portrait can you know what kind of customers you want to target for accurate delivery and what kind of delivery materials can attract customers to leave their clues.

On the content marketing side, we can also generate white papers or related article content around ICP pain points, such as: How the manufacturing industry can reduce costs by 30% through XX tools.

3) Customer Success

On the customer success side, there are two main applications:

1) Service resource allocation: Allocate more service resources to high-potential customers to ensure customer activity and renewal.

2) Demand feedback closed loop: Synchronize ICP customer needs with the product team to optimize product iterations.

3. Several Misconceptions about “Ideal Customer Portrait”

We also encountered some problems when sorting out our own "ideal customer portrait", which resulted in our early ICP output not being so accurate (mainly because it was not detailed enough), and led to some detours in the direction of customer acquisition and product iteration.

Misunderstanding 1: Blindly pursuing big customers

Problem: Large enterprises have long processes and high customization requirements, and small teams have difficulty providing services.

Solution: Define “right size” based on your ability to deliver.

The stratification of enterprise size is actually not easy to control. For example, some companies serve companies with a team size of 500 to 2,000 people. However, the needs of customers with a scale of 500/1,000/1,500/2,000 may be quite different.

Therefore, we need to pay attention to the segmentation of customer size, which customers we can serve currently, and which customers will increase our costs if we take them on.

Mistake 2: Ignoring the complexity of the decision chain

Problem: Only the CEO is contacted, but the actual decision-making power lies with the technical department.

Countermeasure: Restore the real decision-making process through customer interviews.

In small companies, decisions are generally made directly by the boss, but in large companies, the decision chain is more complicated. The main decision maker may be the head of the information department or the head of the business department. The specific details still need to be explored through actual communication with customers.

Myth 3: Images are too static

Problem: Failure to adjust in time to market changes, missing out on opportunities in emerging industries.

Countermeasure: Review customer data every quarter and dynamically optimize ICP.

The growth of SaaS business is inseparable from the mining of market information, not only the mining of customer needs, but also the mining of derivative industry opportunities. Therefore, the ICP portrait is not static and needs to be frequently iterated.