How to Perform Customer Segment Analysis? Explaining Segmentation Methods for Actionable Strategies

“You should perform customer segment analysis.”

This is a phrase often heard when working in marketing.

However, when you actually try to do it, you often find yourself stuck.

How should customers be segmented?
Should they be divided by age or industry?
Should they be divided by revenue size?
Should they be divided by those who requested materials versus those who made inquiries?
Once divided, how should these segments be used for strategy?

If you proceed while these points remain vague, customer segment analysis quickly becomes nothing more than “creating a pretty chart and finishing.”

I myself have faced customer segment analysis many times, whether as a planner at an advertising agency, while doing marketing for a BtoC company, or now as a BtoB marketer at a company in Otemachi.

What I feel strongly through that experience is thatthe purpose of customer segment analysis is not to divide customers into fine groups itselfis not the goal.

What is important is that your strategies change after you have segmented them.

Ad messaging changes.
The way the landing page is presented changes.
The theme of white papers changes.
The content of emails changes.
The priority of sales activities changes.
Follow-ups for existing customers change.

Only when it connects to these things does customer segment analysis have meaning.

To start with the conclusion,what is important in the method of customer segment analysis is not to look at “what kind of customers exist,” but to find “which differences affect the results of your strategies.”

Even if you divide by age, it has little meaning if your strategies do not change.
Even if you divide by industry, it is difficult to use if your messaging or sales proposals do not change.
Even if you divide by revenue size, it is a weak analysis if your priorities or follow-up methods do not change.

Conversely, even a simple segmentation method has value if it can be used for strategy.

For example, in BtoB, the following differences directly impact strategy:

・Consideration periods differ by company size
・Pain points that resonate differ by industry
・Materials they want to see differ by department
・Points of concern differ by job title
・Information needed differs between new and existing customers
・Sales approaches differ between companies that are easy to win and those that are easy to lose

Once these differences become visible, marketing becomes much easier to drive.

“Showing the same ad to everyone for no particular reason”
“Sending the same email to everyone”
“Passing all leads to sales with the same priority”

You can break free from this state.

In this article, I will explain in order what customer segment analysis is, common failures, what to decide before starting, usable data, representative segmentation methods, concrete execution methods, and how to apply it to BtoB marketing, sales, and existing customer strategies.

By reading this article, you will be able to think of customer segment analysis not as a “classification task,” but asan analysis that can be used for ads, content, landing pages, emails, sales approaches, and existing customer follow-ups.

You don't need to start customer segment analysis with difficult statistical analysis.

First, decide the purpose of segmenting customers.
Collect usable data.
Segment by criteria that change your strategy.
Compare with the intuition of sales and field staff.
Actually implement the strategy and observe the results.

If you proceed in this flow, the analysis will become something that can be properly used in your work.

"I don't know how to do customer segment analysis"
"I've done the analysis, but I can't apply it to my strategy"
"Even if I explain it to sales, they aren't convinced"
"I can't decide which customers to prioritize"

For people like that, before thinking about how to segment, try organizing why you are segmenting in the first place.

Just by thinking from that point, customer segment analysis will suddenly become much more practical.

What is customer segment analysis?

Customer segment analysis is an analysis that divides customers into several groups to look at their characteristics and differences.

However, what is important here is not simply classifying customers.

Segment by age.
Segment by industry.
Segment by sales scale.
Segment by region.

If it's just this, it will end with just making a table.

What is truly important is whether the segmentation changes your strategic approach.

Not about segmenting customers, but finding differences that can be used for strategy

The most common misunderstanding in customer segment analysis is thinking that the more finely you segment, the better the analysis is.

But in practice, that is not always the case.

For example, suppose you have finely segmented customers by age, region, industry, job title, purchase frequency, and sales scale.
It looks impressive as a table.
But even if you look at that classification, the ad copy doesn't change.
The content of the email doesn't change.
The priority of sales doesn't change.

In this state, it is difficult to use as an analysis.

What you should look at in customer segment analysis are the differences that can be used for strategy.

For example, even among the same prospective customers, those who are not yet aware of their issues and those who are already comparing and considering them need different information.
Even among the same document requesters, the points that department heads and staff members care about are different.
Even among the same existing customers, the way you follow up with high-frequency users and low-frequency users is different.

When you can see these differences, your strategy changes.

Therefore, in customer segment analysis, it is important to think about the following first.

・Does the advertising appeal change after segmenting?
・Does the email content change after segmenting?
・Does the sales priority change after segmenting?
・Does the follow-up method change after segmenting?

A classification method that can answer these questions is a segment that can be used in practice.

Customer segment analysis is not the task of neatly categorizing customers, but the task of finding differences that lead to results.

Differences from target setting and persona design

Customer segment analysis is similar to target setting and persona design.

Therefore, they are sometimes confused.

Target setting is mainly about deciding 'who to target.'
Persona design is about depicting an ideal customer profile as a concrete individual.
On the other hand, customer segment analysis is about dividing actual customers or potential customers into groups to observe differences.

For example, in target setting, you might decide on 'marketing managers at B2B companies with 100 or more employees.'
In persona design, you might depict them as 'a marketing manager who has increasing leads but is struggling with the conversion rate to business meetings.'
In customer segment analysis, you look at actual customer data to see which company size, which industry, and which stage of consideration leads to easier order acquisition.

In other words, customer segment analysis also plays a role in reviewing targets and personas using real data.

In my own practice, I have seen many times that the target profile decided initially and the profile of customers actually placing orders are misaligned.

Internally, there is a desire to 'target this industry.'
But in reality, it is easier to convert business meetings in a different industry.
In persona design, we assume the decision-maker is the executive.
But those making inquiries are often managers of the operational departments.

Such discrepancies are difficult to see without performing customer segment analysis.

Target setting and persona design are for creating hypotheses.
Customer segment analysis is for verifying whether those hypotheses are correct and refining them into a form that can be used for strategies.

Why customer segment analysis is necessary for marketing strategies

One of the reasons why marketing strategies do not go well is doing the same thing for everyone.

Showing the same advertisement to all customers.
Sending the same email to all leads.
Giving the same materials to all potential customers.
Making the same proposal to all sales prospects.

With this, the response will inevitably be weak.

Depending on the customer, their worries are different.
The information they want to know is also different.
The stage of consideration is also different.
The people involved in decision-making are also different.

Therefore, it is necessary to change marketing strategies as well.

Customer segment analysis makes it easier to see which customers should receive what information and at what timing.

For example, content focused on organizing issues might be suitable for customers in the early stages of consideration.
Case studies or pricing information might be suitable for customers currently comparing options.
Usage tips or additional proposals might be suitable for existing customers.

Being able to differentiate your approach in this way improves the precision of your initiatives.

In B2B especially, the consideration period is long and there are many stakeholders involved.
Therefore, sending the same message to everyone may result in it not resonating deeply with anyone.

Customer segment analysis is the foundation for moving marketing from mass distribution toward individual optimization.

How the approach to customer segments differs between B2B and B2C

The approach to customer segments differs slightly between B2B and B2C.

In B2C, factors such as an individual's age, gender, region, lifestyle, values, and purchasing behavior become important.
While it depends on the product, individual interests and life changes are likely to influence purchases.

On the other hand, in B2B, it is necessary to look at the characteristics of the company as well as the individual.

Company size.
Industry.
Department.
Job title.
Budget.
Implementation structure.
Decision-making process.
Presence of existing systems.

These factors are significantly involved in purchases and orders.

For example, even for the same marketing manager, the way consideration proceeds differs between a company with 50 employees and one with 3,000 employees.
In small and medium-sized enterprises, the speed might be faster.
In large corporations, there are many stakeholders, and it might take time for internal approval and security checks.

Also, in B2B, it is common for the user and the decision-maker to be different people.

The staff on the ground cares about ease of use.
The department manager cares about cost-effectiveness.
The management layer cares about business impact.
The IT department cares about security and integration.

Therefore, in B2B customer segment analysis, it is necessary to look at both the company level and the individual representative level.

In B2C, it is 'what kind of person buys'.
In B2B, it is 'what kind of person in what kind of position at what kind of company is considering it, and for what reason'.

Being aware of this difference will significantly change how you create your segments.

Common failures in customer segment analysis

If done incorrectly, customer segment analysis can quickly become an unusable analysis.

You made a table.
You made a graph.
You divided customers into several groups.

However, the strategies never change.
Even when shared with the sales team, they aren't used.
In the end, the next meeting is about something else entirely.

This kind of thing happens quite often in practice.

Stopping after segmenting only by age or industry

A common issue in customer segment analysis is stopping after segmenting only by age or industry.

Of course, age and industry are important information.
In BtoC, lifestyles can change depending on age.
In BtoB, challenges and adoption needs can change depending on the industry.

However, that is not always enough.

For example, even within the same industry, challenges differ depending on company size.
Even at the same age, effective messaging changes if the consideration stage or purpose of use differs.
Even with the same job title, the approach differs between someone proactive about adoption and someone just gathering information.

In other words, attributes alone may not reveal differences that can be used for strategies.

What is important is to look at attributes in combination with behavior, challenges, and contribution to sales.

・What industries are most common?
・Which of those industries are easiest to win orders from?
・Which industries have a high conversion rate to business meetings?
・Which industries respond well to advertising?
・Which industries have a high retention rate?

When you look at it this far, the meaning of 'industry' changes.

It is not just about classifying, but looking at the relationship with results.
This is very important in customer segment analysis.

Unable to translate analysis into action

Sometimes, even after performing customer segment analysis, it cannot be translated into action.

This is a huge waste.

The analysis results are certainly interesting.
But I don't know how to change the ads.
I don't know how to segment the emails.
I don't know how the sales team should use it.

When this happens, the analysis ends with the report.

The cause is often that the analysis started without a clear purpose.

Why are we segmenting?
Which strategy will it be used for?
Who will use it?
What kind of decision-making will it be used for?

If these are not decided, even if analysis results are produced, they will not lead to action.

When conducting customer segment analysis, it is better to anticipate your strategies beforehand.

For example, if you are using it for advertising improvements, you need to be able to differentiate your messaging for each segment.
If you are using it for email campaigns, you need to be able to segment by distribution lists or consideration stages.
If you are using it for sales strategies, you need to be able to reflect it in your priorities and proposal content.

Analyses that cannot be translated into strategies often have weak initial objective design.

Before starting your analysis, decide what you will change based on the results.

Classifications that are convenient for your company

In customer segment analysis, you may end up with classifications that are convenient for your own company.

For example, segmenting by internal organizational convenience.
Segmenting by the sales representative's territory.
Segmenting by product category.
Segmenting only by items that are easy to manage.

This in itself is not necessarily bad.
However, if it deviates from the customer's issues and behaviors, it becomes difficult to use for strategy.

Customers do not act based on your company's management convenience.
They act based on their own issues, their own budgets, their own timing, and their own internal circumstances.

Therefore, in customer segment analysis, you need to incorporate the customer's perspective.

Why did this customer consider the purchase?
What were they struggling with?
What were they anxious about?
What information helped them move forward?
Why did we lose the deal?

By incorporating these questions, you can break free from classifications based solely on your company's convenience.

In my own practice, I have seen classifications that were convenient internally but did not really lead to customer understanding.
Even if they look neat in terms of management, they are weak when used for strategy.

In customer segment analysis, it is important to look not only at whether it is easy for your company to manage, but also at whether it correctly represents the differences among customers.

Too many segments to use effectively

Another failure in customer segment analysis is segmenting too finely.

As you analyze, you will see various differences.
You want to segment by industry.
You want to segment by size.
You want to segment by job title.
You want to segment by behavior.
You want to segment by consideration stage.

As a result, you end up with too many segments.

If there are too many segments, the front-line team cannot use them all.

You cannot differentiate all your ads.
You cannot create detailed emails for each.
You cannot prepare dozens of types of sales materials.
Management and updates also become difficult.

If it ends up like this, even if the analysis is detailed, it will not lead to actionable initiatives.

In practice, it is important to limit segments to a usable number.

For example, starting by dividing them into three to five large groups is sufficient.
From there, try using them for initiatives and refine them further if necessary.
This order is more realistic.

More segments are not necessarily better.

Ensuring the number is manageable for the team is also part of analysis design.

Discrepancies between sales team intuition and analysis results

When conducting customer segment analysis, there are times when it deviates from the intuition of the sales team.

According to the data, this segment looks promising.
However, sales says, "That segment is actually quite difficult to close."
Conversely, sales may feel that a customer group that does not stand out in the data is "actually quite easy to target."

Such discrepancies are common.

What is important at this time is not to unilaterally decide that one side is correct.

Data has its own strengths.
It removes biases.
It shows overall trends.

On the other hand, the sales team has qualitative information.
The temperature of the business negotiations.
The difficulty of internal coordination.
What the customer is genuinely worried about.
The reasons for losing in comparison with competitors.

These are difficult to see with data alone.

Therefore, in customer segment analysis, it is necessary to combine data with field intuition.

Share the analysis results with sales.
Ask about areas that feel off.
Ask about the reasons why it is easy or difficult to close deals.
Review how segments are defined if necessary.

Including this process makes it easier for the analysis to be utilized.

Analysis that sales cannot accept will not take root in the field.
Conversely, relying only on sales intuition can lead to misjudging overall trends.

Customer segment analysis becomes stronger through dialogue between data and the field.

Things to decide before starting customer segment analysis

If you start touching data immediately, you will get lost in customer segment analysis.

Which data should you look at?
Which criteria should you use to classify?
How granular should your view be?
What defines a good segment?

If these remain vague, you will lose sight of your objective during the analysis.

Therefore, there are things you must decide first.

Clarify the purpose of segmenting customers

In customer segment analysis, you first determine the objective.

This is the most important part.

If the purpose of segmenting customers is vague, the analysis results will also be vague.
You might segment them using various perspectives, but end up not knowing what to use them for.
This is a common outcome.

It is better to make the objective as concrete as possible.

・Want to increase ad response
・Want to increase the lead-to-opportunity conversion rate
・Want to find customers who are easy to close
・Want to find customers with high churn risk
・Want to find customers who are easy to upsell
・Want to prioritize sales activities

Depending on the objective, the data to look at and the classification methods will change.

For example, if the objective is ad improvement, you need to look at ad response and CVR.
If the objective is improving sales efficiency, you need to look at lead-to-opportunity conversion rates and win rates.
If the objective is existing customer initiatives, you need to look at retention rates and usage status.

If you segment customers without deciding on an objective, the analysis will become too broad.

Start by being able to state in one sentence, 'What do I want to change with this analysis?'

Once the objective of customer segment analysis is determined, what you see will change.

Separate objectives such as revenue improvement, lead acquisition, and improvement of lead-to-opportunity conversion rates

The objectives of customer segment analysis must be narrowed down to one, or at least considered separately.

Do you want to improve revenue?
Do you want to increase lead acquisition?
Do you want to increase the lead-to-opportunity conversion rate?
Do you want to increase the win rate?
Do you want to increase the retention rate of existing customers?

These are similar, but the differences in the customers you need to look at will change.

For example, if the objective is lead acquisition, you need to look at segments that are likely to respond to ads and content.
If the objective is improving the lead-to-opportunity conversion rate, you need to look at customers among your leads who are easy for sales to meet or who have clear issues.
If the objective is revenue improvement, you need to look at segments with high unit prices or high LTV.

Even with the same customer data, your perspective changes if the objective is different.

There are segments with many leads that do not convert into business negotiations.
There are segments with few leads but high order conversion rates.
There are segments that are easy to close but have low unit prices.

Which one to prioritize depends on your objective.

Therefore, in customer segment analysis, you need to be conscious of segmenting and viewing data based on specific objectives.

If you try to solve everything with a single analysis from the start, it becomes difficult to make decisions.

First, decide on the objective for this time.
If necessary, look at a different objective in the next analysis.

This makes it easier to translate into actionable strategies.

Decide whether to look at existing customers or prospective customers

In customer segment analysis, you also need to decide whether to look at existing customers or prospective customers.

The data you should look at differs between existing customers and prospective customers.

For existing customers, you can look at purchase amounts, usage status, duration of retention, churn status, and upsell history.
For prospective customers, you often look at ad responses, site behavior, document requests, seminar participation, conversion to business negotiations, and reasons for lost deals.

Depending on the objective, which one you should look at changes.

If you want to find customers who are easy to close, looking at the characteristics of existing customers is helpful.
If you want to improve ad messaging, you need to look at the reactions of prospective customers.
If you want to reduce churn, you need to look at the usage status of existing customers.

If you mix these up, the analysis becomes difficult to understand.

For example, a segment that looks like a high-value customer among existing customers might have too high a cost for new acquisition.
Conversely, a segment that generates many leads might have a low retention rate as existing customers.

Therefore, decide on the analysis target first.

Are you looking at existing customers this time?
Are they prospective customers?
Or is it the entire flow from lead to order to retention?

Just by deciding on the target, the data you need to look at will be organized.

Decide in advance which department or strategy will use the analysis results

Customer segment analysis becomes easier to translate into practical work if you decide in advance who will use it.

Will marketing use it?
Will sales use it?
Will customer success use it?
Will management use it?

The required perspective differs depending on the department using it.

For marketing, you need segments that can be used for ads, content, landing pages, and emails.
For sales, you need segments that can be used for prioritization and proposal content.
For customer success, you need segments that can be used for ongoing support and churn prevention.
For management, you need segments that can help determine which customer segments to invest in.

If the person who will use the analysis results is not decided, the report may be created but will not be used in the field.

When I share analysis, I am very conscious of 'who will use it and for what'.
If passing it to sales, it is easier to use if you show the customer profile to approach next rather than using difficult analytical terms.
If passing it to an advertising manager, you need language that can be translated into appeals and creatives.

Analysis needs to be translated to suit the person viewing it.

Customer segment analysis is more likely to reach the field if you decide on the user before creating it.

Main data that can be used for customer segment analysis

In customer segment analysis, what kind of data you use is important.

However, it is okay if you do not try to gather perfect data from the beginning.

In practice, data is sometimes missing.
Input rules may be inconsistent.
Sales notes may differ from person to person.

Even so, you can start with the information you have available.

Grasping basic information with customer attribute data

Customer attribute data is the basic information of a customer.

For BtoC, this includes age, gender, region, family structure, occupation, etc.
For BtoB, this includes company size, industry, region, department, job title, sales scale, etc.

This becomes the foundation of customer segment analysis.

However, it is also important not to judge too much based on attribute data alone.

Attributes are external information about the customer.
What that person is struggling with.
How much they are considering.
Why they bought.
Why they lost the deal.

These things cannot be seen from attributes alone.

Even so, attribute data is very useful for initial organization.

For example, there might be many specific industries among companies that placed orders.
There might be a company size that is easy to turn into a business negotiation.
There might be job titles that request materials often but are difficult to convert into orders.

This serves as an entry point for discovering such trends.

When looking at attribute data, examine not just the numbers, but also the relationship with results.

Which attributes are most common?
Which attributes are most likely to lead to business negotiations?
Which attributes are most likely to lead to orders?
Which attributes are most likely to lead to retention?

By looking at it this way, basic information transforms into actionable data for your strategy.

Reading interest and consideration levels through behavioral data

Behavioral data is data that shows what a customer has done.

Visited the site.
Downloaded materials.
Clicked on an email.
Attended a seminar.
Viewed the pricing page.
Opened the inquiry form.

Such actions reflect interest and levels of consideration.

For example, someone who has only read a blog post may have a different level of consideration than someone who has repeatedly viewed the pricing page.
The level of enthusiasm also differs between someone who has downloaded a white paper once and someone who is viewing multiple case study documents.

Looking at behavioral data makes it easier to think about the customer's current state.

Behavioral data is particularly important for marketing initiatives.

Provide content for organizing issues to those in the early stages of consideration.
Provide case studies and pricing information to those who are comparing options.
Strengthen sales coordination for those who visit the site frequently.

It can be used for judgments like these.

However, caution is required when using behavioral data alone.

Just because someone is viewing many pages does not necessarily mean they have high purchase intent.
Some people are just gathering information.
Some people are conducting competitor research.

Therefore, behavioral data becomes more useful when combined with attribute data and sales negotiation data.

Viewing differences in sales and retention rates through purchase data

Purchase data is very important in customer segment analysis.

Which product did they buy?
How much did they buy?
How frequently are they buying?
Are they continuing?
Are they making additional purchases?
Have they canceled?

Looking at this information reveals customer segments that contribute highly to sales.

In marketing, it is dangerous to chase only customers who respond frequently.
There are many leads, but the unit price is low.
They are easy to close, but they do not continue.
Ad response is good, but profits are thin.

There are also segments like these.

By looking at purchase data, you can judge not just quantity, but quality.

For example, a certain industry might have few leads, but a high order unit price and a high retention rate.
Another industry might have many inquiries, but many cancellations after the order is placed.

Understanding this difference allows you to review budget allocation and sales priorities.

In customer segment analysis, it is better to look at profit, not just sales.
Even if sales are high, there are customers who require significant support effort, making it difficult to retain profit.
Conversely, even if sales are moderate, there are customers with high retention rates who require little hands-on management.

Purchase data serves as material for considering which customers should be valued.

Finding the characteristics of customers who are easy to close using sales meeting data

In BtoB, sales meeting data is quite important.

No matter how many leads you have, if they do not turn into sales meetings, they will not lead to sales.
Even if they turn into sales meetings, if you do not close the deal, there will be no results.

Therefore, in customer segment analysis, it is necessary to look at the sales meeting conversion rate and the order closing rate.

The following information is useful in sales meeting data.

・Did it turn into a sales meeting?
・Was the order received?
・Was the deal lost?
・What is the reason for the lost deal?
・How long is the consideration period?
・Who is the decision-maker?
・Who are the competitors?
・What is the proposed amount?

Looking at this data reveals the characteristics of customers who are easy to close.

For example, while the number of document requests may be low, leads from specific departments might be easier to convert into sales meetings.
In certain industries, the consideration period might be long, but the order unit price might be high.
For a certain company size, the reason for lost deals after inquiries might be skewed toward budget shortages.

This information can be used for both marketing and sales.

Reviewing ad targets.
Changing white paper themes.
Changing handover conditions to sales.
Changing proposal materials by segment.

Sales meeting data is data for bringing customer segment analysis closer to sales.

Supplementing reasons that cannot be seen with quantitative data alone through surveys and interviews

Sometimes, the reasons cannot be seen with numerical data alone.

A certain segment has a good response.
But I don't know why it's good.
A certain segment has a high churn rate.
But I don't know why they are churning.

Surveys and interviews are useful in these situations.

By asking customers directly, the reasons behind the data become visible.

・Why did they download the materials?
・What were they struggling with?
・Which information was helpful?
・What were they anxious about?
・Why did they choose us instead of a competitor?
・Why are they continuing?
・Why did they cancel?

Such feedback can be used to interpret segments.

In my own practice, my perspective often changes significantly between when I am just looking at numbers and after I have actually heard the voice of the customer.
Even customers who look the same in the data can have completely different depths of concern or reasons for adoption when you talk to them.

Surveys are suitable for seeing broad trends.
Interviews are suitable for understanding the reasons in depth.

In customer segment analysis, combining quantitative data and qualitative information makes it easier to apply to strategies.

Representative ways to classify customer segments

There are several representative ways to classify customer segments.

Rather than one being the 'correct' way, it is important to use them selectively according to your purpose.

Do you classify by attributes?
Do you classify by region?
Do you classify by values or challenges?
Do you classify by behavior?
If it is BtoB, do you classify by company size or job title?

Here, I will organize the basic classification methods.

Demographic segmentation by attributes

Demographic segmentation is a method of classifying by basic customer attributes.

For BtoC, this includes age, gender, occupation, family structure, income, etc.
For BtoB, similar information includes company size, industry, sales volume, number of employees, etc.

This classification method is the most basic and easy to use.

It is easy to obtain as data.
It is easy to aggregate.
It is easily understood within the company.

Therefore, it is suitable for initial analysis.

However, you cannot understand customer feelings based on attributes alone.
Even at the same age, concerns differ.
Even in the same industry, challenges differ.
Even at the same company size, the consideration status differs.

Therefore, after segmenting by attributes, it is important to look at the relationship with behavior and results.

For example, instead of just looking at the number of leads by industry, also look at the opportunity conversion rate and order win rate.
Instead of just looking at the number of inquiries by company size, also look at the average order value and consideration period.
Instead of just looking at the number of document requests by job title, also look at whether they subsequently progressed to a business meeting.

Attributes are just the entry point.
By layering performance metrics onto them, they become usable segments.

Geographic segmentation by region or trade area

Geographic segmentation is a method of dividing customers by region or trade area.

Divide by region, prefecture, municipality, store trade area, sales territory, etc.

In BtoC, it is often used for store-based businesses or community-based services.
In BtoB, it is also important when sales bases or service areas are involved.

Customer needs can change depending on the region.
The competitive landscape is also different.
Business customs are also different.
The ease of making sales visits is also different.

For example, in urban areas, there may be many competitors, making comparative consideration more likely.
In rural areas, building trust and referrals may be more important.
Having a nearby base can also be a factor that provides peace of mind.

However, just dividing by region is not enough.

Unless you look at what is different for each region, it will not translate into actionable measures.

・Is the response to advertising different?
・Are the inquiry contents different?
・Is the sales approach different?
・Are the implementation needs different?
・Is the competitive environment different?

By looking at these factors, geographic segments become easier to use.

When dividing by region, it is important to think of it not just as a classification of addresses, but in conjunction with differences in customer situations and sales activities.

Psychographic segmentation by values and sense of issues

Psychographic segmentation is a method of dividing customers by their values, sense of issues, way of thinking, and interests.

This is a deeper way of dividing than by attributes.

For example, even with the same company size, if the sense of issues is different, the appeal that resonates will change.

Customers who prioritize cost reduction.
Customers who prioritize sales growth.
Customers who prioritize internal operational efficiency.
Customers who prioritize risk avoidance.
Customers who are proactive about new initiatives.

These differences have a major impact on your strategies.

In B2B, segmenting by customer pain points is highly effective.

For example, even with the same marketing support, one company might be struggling with lead volume.
Another company might be struggling with lead-to-opportunity conversion rates.
Yet another company might be struggling with sales alignment.

In this case, rather than using the same ads or materials, it is easier to get a response by tailoring your appeal to each specific pain point.

However, pain points and values are not as easy to obtain as demographic data.

Surveys.
Interviews.
Sales notes.
Inquiry details.
Themes of downloaded materials.
On-site behavior.

You need to interpret these from such information.

Psychographic segmentation takes a bit of effort.
But it is easy to apply to your strategy.

This is because once you understand the pain point, you can use it directly in your messaging and content.

Behavioral segmentation based on actions and usage status

Behavioral segmentation is a method of dividing customers based on their actions.

What they viewed.
What they clicked.
What they bought.
How much they are using it.
How many times they inquired.
Which materials they downloaded.

You segment based on these actions.

Behavioral data is useful for understanding customer interest and their stage of consideration.

For example, someone looking at the pricing page might be in the comparison and consideration stage.
Someone viewing multiple case study pages might be looking for an implementation image.
Someone who downloaded service materials might be preparing for an internal presentation.

For existing customers, you can see their level of utilization and churn risk from usage frequency and login status.

Customers who use it frequently.
Customers who have just started using it.
Customers who haven't used it recently.
Customers who only use specific features.

This type of segmentation can also be used for customer success initiatives.

The good thing about behavioral segmentation is that it is easy to connect to specific actions.

Changing emails based on behavior.
Changing follow-ups based on usage status.
Displaying different ads based on viewed pages.

In this way, it is easy to translate into concrete measures.

However, it is also important not to rely too much on behavior alone.
This is because data alone cannot explain why those actions were taken.

Behavioral data becomes more powerful when viewed in conjunction with pain points and sales meeting information.

Classification methods based on company size, industry, department, and job title, which are important in B2B

In B2B customer segment analysis, company size, industry, department, and job title are particularly important.

This is because in B2B, purchasing decisions are not determined solely by individual preferences.

Company size.
Industry-specific challenges.
Role of the department.
Job title of the person in charge.
Internal decision-making process.

These factors significantly influence consideration and order acquisition.

The larger the company, the more stakeholders there are, and the longer the consideration period may be.
Challenges and implementation goals change depending on the industry.
The information they want to see differs by department.
The points of concern also change depending on the job title.

For example, on-site staff are concerned about ease of use.
Department managers are concerned about team-wide results and budgets.
Management is concerned about business impact.
The IT department is concerned about security and operational burden.

If you ignore these differences and provide the same materials or advertisements to everyone, the response will be weak.

In B2B, it is necessary to consider segments at both the company level and the individual level.

What kind of company is it?
Who within that company?
What is that person concerned about?

By looking at these aspects, B2B customer segment analysis becomes easier to use for strategies.

How to create customer segments that can be used for strategies

Customer segments are not just about dividing them up.

They need to be in a form that can be used for strategies.

Segments that can be used in practice have common characteristics.

Related to results.
Different challenges and needs.
Different approaches.
Understandable by the field team.
Easy to operate.

Meeting these conditions makes it easier for analysis to lead to strategies.

Segmenting by perspectives that have a large impact on sales and profit

To create customer segments that can be used for strategies, it is important to look at their impact on sales and profits.

A customer group that is simply large in number is not necessarily important.

There are many leads, but the order conversion rate is low.
There are many orders, but the unit price is low.
Sales are high, but support man-hours are high.
There are few, but the retention rate is high and they are likely to remain profitable.

These are the kinds of differences that exist.

In customer segment analysis, it is necessary to look at quality as well as quantity.

For example, even if a segment has a low response to advertising, it is important if the order unit price is high and the LTV is also high.
Conversely, continuing to spend budget on a segment that has many responses but is difficult to convert into business negotiations needs to be reviewed.

When looking at the impact on sales and profits, the following indicators can be used.

・Sales amount
・Gross profit
・Order unit price
・Retention rate
・LTV
・Sales man-hours
・Support man-hours

Customer segments should be judged not only by how easy they are to understand visually, but also by their impact on the business.

Even if you divide them by criteria that are unrelated to results, it is difficult to determine the priority of measures.

Segmenting by criteria where customer issues and needs change

It is important to divide segments that can be used for strategies by criteria where customer issues and needs change.

This is because when issues and needs change, the appeal also changes.

For example, even with the same business efficiency service, customer concerns differ.

I want to reduce work time.
I want to prevent reliance on specific individuals.
I want to reduce mistakes.
I want to compensate for labor shortages.
I want to make reporting to my boss easier.

If you understand these differences, you can change the wording of your advertisements and content.

On the other hand, even if you divide by criteria where issues do not change, the measures will not change much.

For example, even if you divide by region, if the issues and reactions are the same, there may be little need to change the advertising appeal.
Even if you divide by age, if the reasons for purchase are the same, there may be little point in dividing them finely.

In customer segment analysis, please look at whether the information the customer wants changes when you divide by that criterion.

If it changes, there is a possibility that it can be used for strategies.
If it does not change, it is better to look for another criterion.

When you can see customer issues and needs, it becomes much easier to drive marketing.

Segment by units that change your strategic approach

It is important to divide customer segments by units that change your strategic approach.

This is quite important in practical work.

For example, suppose you divide customers into Segment A and Segment B.
But the ads are the same.
The emails are the same.
The sales materials are the same.
The follow-up methods are the same.

In that case, there is not much point in dividing them.

Conversely, if your approach changes for each segment, that way of dividing them has value.

・Changing ad messaging
・Changing the first view of the LP
・Changing the theme of white papers
・Changing the order of emails
・Changing sales proposal content
・Changing customer success follow-ups

In this way, segment analysis is useful if it changes your strategies.

When I divide customers, I always think about 'what will I change with this segmentation?'
If I cannot think of any strategies to change, that segment is often not yet in a state that can be used in practice.

Divide by segments that are easy to act on, not just easy to analyze.

This is what is important.

Make the segmentation something that sales and customer success can agree with

Customer segment analysis does not end with marketing alone.

Especially in BtoB, whether sales and customer success can use it is crucial.

Even if marketing says 'this segment is good,' it won't move forward if sales is not convinced.
If customer success feels that 'this way of dividing cannot be used for follow-ups,' it will not translate into existing customer strategies.

Therefore, it is necessary to make the segmentation something that the front line can agree with.

Segments that are accepted have a sense of reality for the front line.

'Ah, it is true that this industry finds it easier to move forward with business negotiations.'
'Companies of this size take time to implement.'
'People in this position are concerned about that point.'
'Customers with this usage status certainly have a churn risk.'

When these kinds of reactions emerge, the analysis becomes easier to use.

To do that, it is important to listen to the voices of the front-line staff during the analysis.

Do not draw conclusions based solely on data; check with sales and customer success teams.
Ask for the reasons behind any points that feel off.
Adjust the criteria if necessary.

Including this process makes it easier for the analysis results to be adopted by the front-line teams.

Prioritize ease of execution over ease of analysis

In customer segment analysis, it is tempting to choose criteria that are easy to analyze.

The data is clean.
It is easy to aggregate.
It is easy to put into a table.
It is easy to graph.

This is important.

However, segments that are difficult to execute are meaningless.

For example, even if they are clearly divided in the analysis, you might not be able to target them separately in ad delivery.
You might not be able to separate them in an email list.
Sales staff might not be able to make decisions based on them.
That information might not be in the CRM.

If this is the case, it becomes difficult to translate into actionable strategies.

In practice, not only analytical accuracy but also operational feasibility is important.

・Can that information be obtained continuously?
・Can it be managed in a CRM or MA?
・Can it be used for ad delivery?
・Can sales staff understand it when they see it?
・Can strategies be differentiated based on it?

You need to create segments while considering these factors.

An analysis that can be used in the field leads to better results than a perfect analysis.

For customer segment analysis, being able to take action is more important than looking smart.

Specific methods for customer segment analysis

From here, I will organize the specific methods for customer segment analysis.

You don't need to overthink it.

You can create a form that is useful in practice without doing advanced analysis from the start.

The important thing is the order.

Determine the objective.
Collect data.
Select variables.
Divide into groups.
Articulate the characteristics.
Determine priorities.
Implement into strategies.

Following this flow makes the analysis easier to use.

Determine the objective and narrow down the analysis target

First, determine the purpose of the analysis.

If this is vague, you won't be able to decide which data to look at.

For example, just saying "I want to increase sales" is too broad.
It is better to be a bit more specific.

・I want to increase the order conversion rate
・I want to increase the sales meeting conversion rate
・I want to lower the lead acquisition cost
・I want to increase the retention rate
・I want to find customers who are likely to upsell

Once the objective becomes specific, you can narrow down the analysis target.

If you want to look at the sales meeting conversion rate, you need data from leads to sales meetings.
If you want to look at the order conversion rate, you need data from sales meetings to orders.
If you want to look at the retention rate, you need usage data or contract data of existing customers.

If you broaden the analysis target too much, you will get lost along the way.

First, let's decide what you want to judge with this analysis.

Determining the objective is the entrance to analysis and a map to avoid getting lost.

Collect and organize customer data

Once the objective is determined, collect customer data.

CRM.
MA.
Ad management screen.
Access analysis.
Sales management tool.
Billing data.
Surveys.
Sales notes.

The data that can be used differs depending on the company.

There is no need to demand perfect data from the beginning.
However, the meaning of the data must be consistent.

For example, the notation of industry names may be inconsistent.
There are customers with the number of employees entered and customers without it.
The input rules for sales status may also differ depending on the person.

If you analyze in this state, the results may be off.

Therefore, once you collect the data, first organize it.

・Eliminate duplicates
・Correct inconsistent notations
・Check for missing items
・Verify outdated information
・Standardize items used for analysis

It may seem mundane, but this is very important.

The quality of customer segment analysis changes significantly depending on data preparation.

Selecting variables for analysis

Next, select the variables to be used for analysis.

Variables are the items used to categorize customers.

Examples include company size, industry, job title, number of document downloads, whether a business meeting was held, order value, and usage frequency.

The important thing here is that you should not just include everything.

Select variables that are relevant to your objective.

If you want to see the business meeting conversion rate, choose items that seem related to business meetings.
If you want to see the order conversion rate, choose items that seem related to orders.
If you want to see the retention rate, look at usage status and contract information.

If there are too many variables, the analysis becomes complex.
Conversely, if there are too few, you cannot see the differences.

Initially, it is recommended to select them based on a hypothesis.

"Does the consideration period differ by company size?"
"Do the challenges differ by industry?"
"Does the business meeting conversion rate after requesting materials differ by job title?"

Formulating hypotheses in this way determines which variables you should look at.

Analysis is more useful for practical work when approached with a hypothesis rather than just looking at the data.

Dividing customers into groups

Once you have selected the variables, actually divide the customers into groups.

The method of division depends on the objective.

Divide by company size.
Divide by industry.
Divide by consideration stage.
Divide by level of activity.
Divide by purchase amount.
Divide by usage status.

At first, simple classification methods are fine.

For example, by company size: small, medium, and large.
By consideration stage: awareness, information gathering, comparison, and in negotiation.
By usage status: high-frequency, low-frequency, and dormant.

If you make it too granular, it becomes difficult to use.
It is more realistic to start with broad categories and see if there are any differences.

Once you have divided them into groups, look at the performance metrics for each.

・Number of leads
・Opportunity conversion rate
・Order conversion rate
・Average order value
・Retention rate
・LTV
・Customer acquisition cost

Looking at it this way, you can see which groups are important.

It is important not just to divide them, but to look at the relationship with results.

Articulating the characteristics of each segment

Once you have grouped your customers, articulate the characteristics of each segment.

This part is very important.

Because numbers alone are difficult to use for strategy.

For example, suppose you have data showing that "the opportunity conversion rate is high for manufacturing companies with 300 or more employees."
This alone has meaning.
However, to translate it into a strategy, you need to put it into words a bit more.

Why is it easy to convert into an opportunity?
What kind of challenges do they have?
Who is doing the consideration?
What kind of materials are they reacting to?
What should sales be proposing?

Once you articulate this much, you can use it for your strategy.

For example, you can express it as follows:

・Struggling with the personalization of on-site operations
・Department heads are gathering information as an improvement theme
・Likely to react to case studies
・More interested in reducing on-site burden than in cost-effectiveness

With these words, you can incorporate them into advertisements and sales pitches.

It is also good to make segment names easy to understand within the company.

If you use names that allow you to visualize "what kind of customer they are" rather than just classification names, they will be easier to use in the field.

Determining the priority for each segment

Once you have created the segments, determine their priority.

It is difficult to put the same amount of effort into every segment.

Advertising budgets are limited.
Sales resources are limited.
Content creation time is also limited.

Therefore, you need to decide which segments to prioritize.

There are several perspectives to consider when looking at priorities.

・Are sales and profits high?
・Is the order conversion rate high?
・Is the lead-to-opportunity conversion rate high?
・Is the LTV high?
・Is the acquisition cost low?
・Is the sales workload manageable?
・Can we leverage our company's strengths?

For example, there are segments where the sales volume is large, but it takes too long to close a deal.
Conversely, there are segments with medium sales volume, but high order conversion rates and high retention.

Which one to prioritize depends on your business strategy.

The important thing is not to decide based on intuition alone.

Combine data with field insights to determine priorities.
This leads to the accuracy of your initiatives.

Translating into initiatives and verifying results

Finally, apply the analysis results to your initiatives.

Only by doing this does customer segment analysis become meaningful.

For example, change advertising appeals for each segment.
Change the first view of your landing page.
Change the theme of your white papers.
Change the content of your email nurturing.
Change the priority of your sales efforts.
Change how you follow up with existing customers.

Then, once you execute the initiatives, look at the results.

Did the response rate increase?
Did the CVR increase?
Did the lead-to-opportunity conversion rate increase?
Did the order conversion rate change?
How is the feedback from the sales team?
How is the customer's reaction?

You only know if your analysis results were correct after executing and verifying them.

The segments you create initially do not need to be perfect.
Rather, they are things to be reviewed while running your initiatives.

Customer segment analysis is not something you do once and finish; it is something you cultivate through the results of your initiatives.

Customer segment analysis for B2B marketing

In B2B marketing, customer segment analysis is particularly important.

This is because B2B involves long consideration periods, many stakeholders, and complex decision-making.

Even for the same service, the appeal that resonates significantly changes depending on company size, industry, department, and job title.

Examining differences in consideration periods and decision-makers by company size

In B2B, the progress of consideration changes depending on the size of the company.

In small businesses, decision-making can be fast.
There are cases where the president or department head makes the decision directly.
Therefore, if it matches their needs, business negotiations can proceed in a short period.

On the other hand, in large companies, there are many stakeholders involved.

On-site staff.
Department heads.
Information systems department.
Purchasing department.
Legal department.
Management.

The more people involved, the longer the consideration period becomes.

If you apply the same strategy without considering these differences, a misalignment will occur.

Small businesses may need materials that allow for quick decisions and easy-to-understand pricing.
Large companies may need implementation case studies, security information, and materials that can be used for internal approval.

When looking at company size, look not only at the number of leads but also at the consideration period and order conversion rate.

・Number of days from inquiry to business negotiation
・Number of days from business negotiation to order
・Number of stakeholders
・Reasons for lost deals
・Required materials

Looking at this information makes it easier to create strategies for each company size.

Examining differences in challenges and implementation needs by industry

Industry-based analysis is an easy-to-use approach in B2B marketing.

When industries differ, challenges can also change.

Manufacturing.
Logistics.
Retail.
IT companies.
Finance.
Medical industry.
Education industry.

Each has different operational workflows, terminology, and decision-making criteria.

Even for the same service, the reason for implementation that resonates changes depending on the industry.

For example, in manufacturing, on-site efficiency and quality control may be important.
In IT companies, speed and flexibility may be prioritized.
In the financial industry, security and regulatory compliance may become important.

When analyzing by industry, do not just look at the number of orders received; also look at the challenges and reasons for lost deals.

・Which industries generate the most inquiries?
・Which industries are most likely to convert into business negotiations?
・Which industries are easiest to close deals with?
・Which industries have a high LTV?
・What are the reasons for lost deals by industry?

By looking at these factors, it becomes easier to create appeals tailored to each industry.

This can also be used to decide on creating case studies or white papers for specific industries.

Changing appeals and content to resonate with different departments

In B2B, the appeals that resonate change depending on the department.

Even within the same company, the marketing department, sales department, information systems department, human resources department, and corporate planning department all focus on different challenges.

The marketing department might care about lead generation and negotiation conversion rates.
The sales department might care about sales efficiency and order win rates.
The information systems department might care about security and operational load.
The corporate planning department might care about company-wide return on investment.

If the department is different, the necessary content also changes.

For the marketing department, case studies on strategy improvement.
For the sales department, proposal materials that lead to sales results.
For the information systems department, explanations of security and integration.
For management, return on investment and business impact.

Being able to differentiate content in this way makes B2B marketing stronger.

When analyzing by department, look at the department of the person requesting materials and the department participating in the business negotiation.

Which department serves as the entry point?
Which department is likely to oppose it?
Which department's approval is necessary?

When you can see this, your content design will change.

Categorizing information needs and concerns by job title

Job title is also an important segment in B2B.

Staff members, managers, department heads, and executives all have different information needs.

Staff members care about whether it is actually easy to use.
Managers care about whether it will improve team operations.
Department heads care about the impact on budgets and results.
Executives care about the impact on the entire business and return on investment.

Even with the same service material, the points of focus differ depending on the job title.

For staff members, the operation screen and specific usage methods might be important.
For department heads, implementation effects and case studies from other companies might be important.
For executives, the connection to management issues might be important.

When you look at segments by job title, the messaging in your ads and landing pages also changes.

Reducing on-site work,
Increasing team productivity,
Visualizing department-wide results,
Organizing data for management decisions.

Which message resonates depends on the person's position.

In analysis by job title, it is important to look not only at the person making the inquiry but also at meeting participants and decision-makers.

Even if the entry point is a staff member, the final decision may be made by a department head or executive.
In that case, you need information for both the staff member and the senior-level decision-maker.

Differentiating strategies for new and existing customers

New customers and existing customers require different strategies.

New customers do not yet know enough about your company.
They may not be aware of their challenges.
They may be in the process of comparing options.
They may also have concerns.

Therefore, for new customers, you need strategies that lead to awareness, understanding, comparison, and inquiries.

On the other hand, existing customers already have a relationship with you.
They are using your service.
They have already implemented it.
There is a certain level of trust.

Therefore, for existing customers, it is important to focus on usage promotion, retention support, upselling, cross-selling, and churn prevention.

Even for the same customer, the metrics you should look at differ between new and existing status.

For new customers, look at CVR, meeting conversion rate, order rate, and acquisition cost.
For existing customers, look at usage rate, retention rate, LTV, upsell rate, and churn rate.

If you only focus on new customer acquisition, you may overlook the growth potential of existing customers.
Conversely, if you only look at existing customers, you cannot expand your new customer base.

In customer segment analysis, it is important to think about new and existing customers separately.

How to use customer segment analysis for lead generation

Customer segment analysis can also be used for lead generation.

Who should you target with your ads?
What theme should you use for your white paper?
What kind of seminar should you hold?
What should you emphasize on your landing page?
Which segment should you allocate your budget to?

You can use it for these purposes.

Changing ad appeals to resonate with each segment

In lead generation, it is important to differentiate your advertising appeals.

If you show the same advertisement to all customers, the message will inevitably become blurred.

For example, even within the same marketing support, the words that resonate differ between someone struggling with lead volume and someone struggling with lead-to-opportunity conversion rates.

For those struggling with lead volume, an appeal about "increasing prospective customers" might be a good fit.
For those struggling with conversion rates, an appeal about "increasing leads that lead to sales meetings" might be a good fit.
For those struggling with advertising costs, an appeal about "reducing wasted ad spend" might be a good fit.

Customer segment analysis allows you to see these differences.

Which segment is reacting to what?
Which appeal is leading to sales meetings?
Which leads from which advertisements are easier to close?

Looking at these points makes it easier to improve your advertisements.

Advertising appeals are not created based on intuition alone.
They are created based on the challenges and reactions of each customer segment.

Ads that resonate are created after observing the differences between customers.

Differentiating themes for white papers and seminars

White papers and seminars are also strategies where customer segment analysis can be effectively utilized.

Rather than presenting the same theme to everyone, it is easier to get a response if you differentiate themes by segment.

For example, for customers in the early stages of consideration, materials on problem organization or checklists might be a good fit.
For customers in the comparison stage, case studies or guides on how to choose might be a good fit.
For management, themes related to return on investment or market changes might be a good fit.
For frontline staff, practical implementation methods or templates might be a good fit.

Even for the same service, the entry-point content changes.

In BtoB marketing, I also pay close attention to who the target audience is when thinking about white paper themes.
Sometimes, a theme that resonates with a segment that leads to sales meetings is more valuable than a theme that is simply downloaded widely.

When differentiating themes, it is easier to organize your thoughts by considering the following:

・Which segment is this for?
・What is that person struggling with?
・What stage of consideration are they in?
・What do you want them to do after reading the material?

Once you decide these, it becomes easier to use the content for your strategy.

Optimizing LPs and CTAs for each segment

Customer segment analysis can also be used to improve LPs and CTAs.

Even with the same landing page, the points that resonate differ depending on who is looking at it.

Business owners might want to see results or return on investment.
Front-line staff might want to see specific usage methods or an image of what it's like after implementation.
People in the comparison phase might want to know the differences from other companies and the pricing.

If you ignore these differences, your landing page becomes aimed at everyone, and your appeal weakens.

It is ideal if you can separate landing pages by segment.
Even if that is difficult, sometimes just reviewing the first view or the wording of your CTA can make a difference.

For example, for someone in the early stages of consideration, 'Check with this checklist first' might be a good fit.
For someone in the comparison phase, 'Read case studies' might be a good fit.
For those with clear intent, 'Request a free consultation' might be a good fit.

It is important to match your CTA to the customer's stage of consideration.

If you ask for an inquiry too abruptly, you may cause them to leave.
Conversely, if you present a CTA that is too light to someone who is already far along in their consideration, it becomes difficult for them to move to the next step.

By using customer segment analysis, you can think about your landing pages and CTAs in terms of 'who you are targeting and what you are encouraging them to do.'

Changing email nurturing content based on the consideration stage

Customer segment analysis is quite useful for email nurturing.

If you send the same email to all leads, your response rate may weaken.

Sending an email encouraging an implementation consultation to someone who has only just realized they have a problem.
Sending only basic explanations to someone who is already comparing options.

In these cases, the customer's state and the email content are misaligned.

If you separate emails by consideration stage, the response will change.

At the awareness stage, focus on problem organization or failure stories.
At the information gathering stage, focus on know-how or checklists.
At the comparison stage, focus on case studies or how to choose.
At the pre-negotiation stage, focus on pricing or information that can be used for internal approval.

It is important to change the content according to the recipient's state in this way.

In customer segment analysis, you consider which actions indicate which stage a person is close to.

Did they just download a document?
Are they looking at multiple pages?
Did they attend a seminar?
Are they looking at the pricing page?

If you change your emails based on their actions, your nurturing will be stronger than mass distribution.

Allocating budget to segments that are likely to convert into business negotiations

In lead acquisition, it is important to look not only at the number of leads but also at the ease of converting them into business meetings.

Even if you acquire many leads through advertising, it will not lead to sales results if they do not turn into business meetings.

By performing customer segment analysis, you can identify segments that are more likely to convert into business meetings.

For example, a specific industry might have a high conversion rate for business meetings even if the number of leads is low.
Requests for materials from specific job titles might be easier for sales to meet with.
Leads acquired through white papers on specific themes might be more likely to lead to orders.

Once these segments are identified, you can change the priorities for advertising budgets and content creation.

Of course, increasing the number of leads is also important.
However, in BtoB, chasing only quantity can increase the burden on sales.

The important thing is to increase the number of leads that lead to business meetings.

Customer segment analysis provides material for considering where to allocate your budget.

How to utilize customer segment analysis for sales strategies

Customer segment analysis can be used not only for marketing but also for sales.

In fact, in BtoB, the effect is halved if it is not used in conjunction with sales.

Which customers to prioritize.
What kind of proposals to make.
Which reasons for lost deals are most common.
How to align the perceptions of sales and marketing.

It can be utilized here.

Sharing the profile of customers who are easy to win with sales

What you want to share with sales first through customer segment analysis is the profile of customers who are easy to win.

Which industries are easy to win orders from?
Which company sizes are easier to progress with?
Which departments' inquiries are easier to convert into business meetings?
What kind of challenges do customers who are easy to close have?

When this becomes visible, the priorities of sales will change.

Instead of chasing all leads in the same way, it becomes easier to spend time on customers with high potential.

However, it is difficult for sales to act if you only hand over the data.

It is necessary to share not only that 'this segment has a high order rate' but also why it is easy to win.

・Clear issues
・Easier to secure budget
・Easier to explain the effects after implementation
・Easier to win in competitive comparisons
・Easier to reach decision-makers

Articulating these reasons makes it easier for sales teams to use.

When marketing and sales can share a profile of customers who are likely to convert, the entire strategy becomes aligned.

Tailoring proposals for each segment

Sales proposals also need to be tailored for each segment.

If customers have different issues, the same proposal will not resonate.

For example, for customers who prioritize cost reduction, you need to focus on cost-effectiveness.
For customers who prioritize sales growth, you need to convey growth opportunities and sales impact.
For customers who want to reduce the burden on their staff, ease of operation and support systems become important.

Even for the same service, the order of presentation changes.

Using customer segment analysis allows you to create proposal templates for each segment.

・Issues to discuss first
・Case studies to highlight
・Features to emphasize
・Explanations to resolve concerns
・Materials to prepare for the next proposal

Organizing this will improve the quality of sales proposals.

Instead of relying solely on individual sales experience, you will be able to share winning patterns for each segment.

Identifying customers to prioritize

Sales resources are limited.

You cannot spend the same amount of time on every lead.
Therefore, you need to identify which customers to prioritize.

Customer segment analysis can be used for this judgment.

For example, the following types of customers might have high priority.

・Industries with high conversion rates
・Company sizes with high rates of turning into business meetings
・Inquiries with clear issues
・Leads who have viewed the pricing page multiple times
・Leads who have downloaded case studies
・Companies with characteristics similar to existing customers

Defining these conditions makes it easier for sales to determine the order in which to follow up.

Conversely, for leads with low engagement, it may be better not to have sales follow up immediately, but rather to nurture them via email.

Instead of passing everything to sales, differentiate your approach based on the segment.

When you can do this, sales efficiency improves.

Customer segment analysis is not meant to increase the burden on sales, but to help sales focus on customers that lead to results.

Analyze reasons for lost deals by segment

In customer segment analysis, it is important to look not only at customers who placed orders but also at those who did not.

Looking at the reasons for lost deals reveals points that need improvement.

Did you lose on price?
Were features lacking?
Did you lose to a competitor?
Was the timing for implementation off?
Did it get stuck in internal approval?
Was the sense of urgency weak?

Looking at this by segment is even more useful.

In certain industries, price tends to be a bottleneck.
In certain company sizes, deals tend to get stuck in approval.
Inquiries from certain job titles are easy to turn into meetings, but hard to connect to decision-makers.
Customers with certain issues are prone to being lost in competitor comparisons.

When these trends become visible, you can change your strategies.

If price is a bottleneck, prepare materials on cost-effectiveness.
If it gets stuck in approval, create materials for internal explanation.
If you lose to competitors, organize comparison points.
If you cannot connect to decision-makers, prepare content for higher-level management.

Reasons for lost deals are a treasure trove for improvement.

Looking only at customers who placed orders leads to biased analysis.
By also looking at customers who did not, you get a segment analysis closer to reality.

Reducing the gap in perception between marketing and sales

Customer segment analysis can also be used to reduce the gap in perception between marketing and sales.

Marketing thinks, "Leads are increasing."
Sales feels, "There are few leads that turn into meetings."
Marketing thinks, "We should target this industry."
Sales feels, "In reality, other industries are easier to move forward with."

Such gaps occur frequently.

By using customer segment analysis, you can talk based on data rather than just intuition.

Which segment are leads coming from?
Which segment is turning into meetings?
Which segment is placing orders?
Which leads are easy for sales to pursue?

By looking at this together, conversations become constructive.

The important thing is that marketing should not use analysis to persuade sales.
It is also not for ignoring the intuition of the sales team.

It is used to combine data with field experience to make better decisions.

Customer segment analysis becomes a common language for marketing and sales.

How to utilize customer segment analysis for existing customer strategies

Customer segment analysis can be used not only for new customer acquisition but also for existing customer strategies.

In fact, analyzing existing customers is quite important.

Which customers are likely to continue?
Which customers are likely to upsell?
Which customers are at risk of churning?
What kind of follow-up will increase satisfaction?

When you can see these things, it leads to stable revenue.

Identifying the characteristics of customers with high retention rates

In existing customer strategies, it is important to first look at the characteristics of customers with high retention rates.

There is a reason why customers continue to stay.

Their challenges and the service are a good match.
Their purpose for implementation was clear.
Their usage frequency is high.
It has become established within their company.
They are able to feel the results.
They have a good relationship with support.

When these characteristics are identified, they can also be applied to new customer acquisition.

This is because acquiring customers similar to those with high retention rates is likely to lead to higher LTV.

Conversely, there are segments that are easy to win but have low retention rates.
In this case, there may be a mismatch in expectations at the time of new acquisition.
There may also be a lack of utilization support after implementation.

When looking at retention rates, let's look at usage status in addition to whether the contract is simply continuing.

There are also customers whose contracts continue but who do not use the service much.
In this case, there is a future risk of churn.

Identifying the characteristics of customers with high retention rates leads to improvements not only in existing customer support but also in marketing as a whole.

Identifying customers who are likely to upsell or cross-sell

Customer segment analysis can also be used for upselling and cross-selling.

Making the same additional proposal to all existing customers will not yield a good response.

Customers who are already using the service sufficiently.
Customers who are still only using basic features.
Customers whose scope of use is expanding.
Customers whose departments are increasing.
Customers whose challenges have moved to the next stage.

The content that should be proposed differs for each.

Customers who are easy to upsell have specific characteristics.

・High usage frequency
・Used by multiple people
・Realizing results
・Additional challenges are visible
・Room for internal expansion
・Good relationship with the person in charge

Finding these segments makes it easier for sales and customer success teams to make proposals.

Conversely, if you suddenly make an additional proposal to customers with shallow usage, it may feel like a hard sell.
First, you need to provide support for utilization.

Using customer segment analysis allows you to separate customers who should receive additional proposals from those who should receive support first.

This is important for increasing sales without lowering the satisfaction of existing customers.

Identifying customer segments with high churn risk

Particularly important in existing customer strategies is identifying churn risk.

It is sometimes too late to respond to churn after it has already happened.
You need to find the signs before that.

In customer segment analysis, we look at the characteristics of customers who are prone to churn.

・Usage frequency is decreasing
・Logins are decreasing
・Inquiries are decreasing
・Only using specific features
・Introduction purpose was vague
・Person in charge has changed
・Not realizing results

Customers with these characteristics may have a high risk of churn.

Also, there may be cases where churn is high in specific industries or company sizes.
In that case, there may be issues with compatibility with the service or implementation support.

When looking at churn risk, not only numerical values but also notes from customer interactions are important.

“Response has been slow lately”
“The person in charge has changed and the situation is unclear”
“Utilization is not progressing”
“Questions about cost-effectiveness have increased”

Such field information is useful for risk assessment.

If you know which segments have high churn risk, you can follow up early.

Customer segment analysis can also be used as a preventive measure to stop churn.

Tailoring follow-ups based on customer satisfaction and usage status

Follow-ups for existing customers do not need to be the same for everyone.

Customers with high satisfaction.
Customers who are not yet utilizing the service effectively.
Customers who are dissatisfied.
Customers with potential for additional proposals.
Customers at risk of churn.

Each requires a different type of follow-up.

For highly satisfied customers, case studies, referrals, or additional proposals might be appropriate.
For customers who are not utilizing the service well, support on how to use it is necessary.
For dissatisfied customers, early identification of issues is required.
For customers at risk of churn, changing the representative or checking their usage status is necessary.

Looking at usage data reveals the priority for follow-ups.

For customers who use it frequently, propose the next step in utilization.
For customers who are not using it, provide basic onboarding.
For customers using only some features, propose expanding their scope of use.

You can change your approach in this way.

In existing customer strategies, it is important to provide follow-ups tailored to the customer's state.

Customer segment analysis can also be used to determine what should be done for existing customers.

Metrics to look at in customer segment analysis

In customer segment analysis, it is important to decide which metrics to look at.

If you choose the wrong metrics, your judgments will also be off.

Should you look only at the number of leads?
Should you look at the conversion rate to sales meetings?
Should you look at the order win rate?
Should you look at LTV?
Should you even look at sales labor hours?

Choose your metrics according to your objectives.

Contribution to sales and profit

The first thing to look at is the contribution to sales and profit.

Look at how much revenue is generated by each customer segment.

However, it is better not to judge based on sales alone.

There are customers who generate high sales but leave little profit.
There are customers who require heavy support resources.
There are customers who demand frequent discounts.
There are customers who require excessive sales effort before closing.

Therefore, it is important to look at profit and resource costs as well.

For example, there may be a segment with moderate sales but high profit margins and high retention rates.
Such customers are highly valuable to the business.

By looking at the contribution to sales and profit, it becomes easier to judge which segments to focus on.

Look at the segments that contribute to the business, not just the segments with the most leads.

This perspective is important.

Win rate and lead-to-opportunity conversion rate

In B2B, win rates and lead-to-opportunity conversion rates are important.

No matter how many leads you have, they will not lead to sales results if they do not turn into opportunities.
Even if there are many opportunities, they will not become revenue if they are not won.

Looking at conversion rates and win rates by segment reveals differences in quality.

For example, one segment might have many leads but a low conversion rate.
Another segment might have few leads but a high win rate.

Seeing these differences allows you to rethink the priorities of marketing and sales.

If the conversion rate is low, your messaging might be too broad.
If the win rate is low, your proposal content or target might be misaligned.
If you have many opportunities but many lost deals, there may be issues with expectations, pricing, or how features are presented.

Win rates and conversion rates are important indicators for assessing the quality of customer segments.

LTV and retention rate

LTV and retention rates are also important in customer segment analysis.

LTV is a concept for looking at how much revenue and profit a customer generates over the long term.

If you only look at new acquisitions, you tend to prioritize customers who close quickly.
However, in the long term, customers with high retention rates and a tendency for repeat purchases can be more important.

Segments with high retention rates may have a good fit with the service.
Segments with high churn rates may have misaligned expectations or a lack of usage support.

By looking at LTV, you can understand value that is not visible through short-term sales alone.

For example, even if the acquisition cost is slightly high, it is worth investing if the LTV is high.
Conversely, if the acquisition cost is low but they churn immediately, it needs to be reviewed.

In customer segment analysis, it is important to look not only at the entry point but also at subsequent retention.

Acquisition cost and sales man-hours

In customer segment analysis, you should also look at acquisition costs and sales man-hours.

No matter how good a customer is, if the acquisition cost is too high, efficiency will be poor.
Even if the order value is high, if the sales man-hours are too heavy, it becomes difficult to retain profit.

Looking at it by segment reveals differences in efficiency.

Some segments require high advertising costs.
Some segments require a high number of sales meetings.
Some segments take a long time for internal approval.
Some segments have a high support burden.

This information is important for determining priorities.

Especially in B2B, sales man-hours become a major cost.

It is important to look not only at the order rate but also at how much time and effort it takes to close a deal.

If you find an efficient segment, you can make decisions to allocate marketing budgets and sales resources there.

Response rates and CVR after implementing measures

Once you implement measures for each segment, you need to observe the response.

Ad click-through rate.
LP CVR.
Email open rate and click-through rate.
White paper download rate.
Seminar participation rate.
Sales meeting conversion rate.

By looking at these metrics, you can confirm whether the measures for each segment were appropriate.

For example, if the response to an ad created for a certain segment is good, the appeal might be correct.
If the response is poor, the message or delivery channel might be off.

The important thing is not to stop after implementing the measures.

Customer segment analysis can be improved by incorporating it into measures and observing the results.

Whether the analyzed segment is correct is something to be confirmed by the response to the measures.

How to continuously improve customer segment analysis

Customer segment analysis is not something you do once and finish.

The market changes.
Customer challenges change.
Competitors change.
Your own products and services change.

Therefore, segments also need to be reviewed periodically.

Do not fix your segments too rigidly

Customer segments are not something that can be used forever once created.

Of course, the basic way of dividing them can be used for a while.
However, if you fix them too much, they will drift away from reality.

For example, an industry that used to respond well might now be harder to win orders from due to increased competition.
You might have focused on small businesses before, but now inquiries from mid-sized companies might be increasing.
You might have dealt with staff members as the entry point before, but now you might be receiving more consultations from management.

If you overlook these changes, your strategies will become outdated.

In customer segment analysis, it is important to have a habit of reviewing them periodically.

It does not have to be every month.
It is good to decide on a timing to review them, such as every quarter, every half-year, or after important initiatives.

Segments are not the absolute truth, but hypotheses that represent your current understanding of customers.

Because they are hypotheses, they need to be updated.

Reviewing segmentation based on the results of your initiatives

Segments should be improved while looking at the results of your initiatives.

The way you divided them at the beginning is not necessarily always correct.

When you ran an ad, the segment you thought would respond didn't.
When you sent an email, a different segment responded better.
When you handed them over to sales, the customer profile that was easy to convert into a business meeting was different.

These things happen normally.

In such cases, you should review how you divide your segments.

It might be better to divide by challenge rather than by industry.
It might be better to divide by consideration stage rather than by company size.
It might be better to divide by behavioral data rather than by job title.

The results of your initiatives are the answer key for your segments.

Reasons for a positive response.
Reasons for a negative response.
Reasons for converting to a sales opportunity.
Reasons for losing the deal.

Updating your segmentation while reviewing these points will make your analysis more practical.

Gather qualitative information from sales and customer support teams

Qualitative information is essential for improving customer segment analysis.

There are things that numbers alone cannot reveal.

Pain points heard by sales during meetings.
Barriers to usage felt by Customer Success.
Inquiries received by support.
The actual language customers use.
Honest feedback given when a deal is lost.

This information can be used to refine your segments.

For example, customers who look the same in the data may have completely different challenges on the ground.
Once you understand those differences, you can re-segment them.

When gathering qualitative information, it is also important to create a system for it.

Conduct regular interviews with sales staff.
Add fields to sales meeting notes.
Categorize reasons for lost deals.
Conduct customer interviews periodically.
Share Customer Success insights with the marketing team.

Having such a system in place keeps your customer understanding up to date.

Customer segment analysis is refined not just by data, but by the voice of the customer.

Update according to changes in the market environment and customer needs

When the market environment changes, customer segments change as well.

Economy.
Competitors.
Regulations.
Technology.
Work styles.
Customer budgets.
Internal priorities.

Customer needs change due to these shifts.

Efficiency might have been the key before, but now cost reduction might be prioritized.
Customers who were previously open to new investments might now be prioritizing risk avoidance.
Implementations that were previously driven by the front line might now require strong management decisions.

If you do not update your customer segment analysis, it becomes difficult to notice these changes.

When marketing campaigns suddenly stop getting a response, you need to look at whether the segments themselves have changed, not just the creative or ad operations.

If customer pain points change, your messaging should change too.
If the customer's decision-making process changes, your content should change too.
If the customer's budget perception changes, your sales proposals should change too.

By continuously updating segment analysis, marketing becomes better equipped to keep up with market changes.

Summary: In customer segment analysis, using segments for strategies is more important than the act of segmenting itself.

You might feel that customer segment analysis sounds a bit difficult.

Data analysis.
Classification.
Graphs.
Metrics.
CRM.
MA.
LTV.

When these terms are listed, I think some people might feel intimidated.

However, the essence of customer segment analysis is not that difficult.

Finding differences among customers and changing strategies to match those differences.

This is the most important thing.

Instead of showing the same advertisement to everyone, change the appeal to resonate with them.
Instead of sending the same email to everyone, change the content according to their consideration stage.
Instead of treating all leads the same, prioritize customers who are likely to convert into business opportunities.
Instead of providing the same follow-up to all existing customers, respond according to their usage status and churn risk.

Only when you achieve this does customer segment analysis become useful for your strategies.

Clarify the purpose of segmenting customers

The first thing you should do in customer segment analysis is to clarify your purpose.

Why are you segmenting customers?
Is it for improving advertisements?
Is it for lead generation?
Is it for improving the conversion rate of business opportunities?
Is it for improving sales efficiency?
Is it for improving the retention rate of existing customers?

If you start the analysis without deciding this, both your classification methods and metrics will waver.

Conversely, once the purpose is decided, the data you need to look at is determined.
The metrics to use are determined.
How to incorporate it into strategies is also determined.

If you are lost on how to perform customer segment analysis, please return to this question first.

"What do I want to change after seeing the results of this analysis?"

Just by being able to answer this question, your analysis will become much more practical.

Create segments by combining data and field insights

In customer segment analysis, data alone or field insights alone are insufficient.

Data shows overall trends.
It removes biases.
It provides material for making decisions based on numbers.

On the other hand, there is information in sales and customer success settings that cannot be seen through numbers alone.

The customer's true feelings.
The temperature of a business negotiation.
Reasons for lost deals.
Stumbling blocks after implementation.
The words used.
Points where internal approval gets stuck.

By combining this information, customer segments become easier to use in practice.

Confirm trends found in data with the sales team.
Verify the sales team's intuition with data.
Listen to the voice of the customer and review your segmentation methods.

This repetition is important.

Effective segments are created together with the front lines, not through desk-based analysis.

Change appeals, customer journeys, and sales approaches for each segment

Customer segment analysis is only meaningful if you change your strategies accordingly.

Just dividing them won't produce results.

Decide what to change for each segment.

・Change ad messaging
・Change white paper themes
・Change the first view of the LP
・Change CTAs
・Change email content
・Change sales proposal materials
・Change follow-up methods for existing customers

It is important to break things down into actionable steps like this.

If customer issues differ, change the message.
If the consideration stage differs, change the customer journey.
If job titles differ, change the materials shown.
If usage status differs, change the follow-up.

Once you can do this, customer segment analysis becomes a weapon for marketing and sales.

Continuously verify and improve analysis results through strategies

Finally, what is important is to verify analysis results through your strategies.

The segments created initially are merely hypotheses.

Will that appeal really resonate?
Is that segment really easy to convert into a business negotiation?
Is that customer group really easy to retain?
Will strategies really work with that segmentation method?

You won't know until you actually try it.

Therefore, always check the results after executing your initiatives.

Response rate.
CVR.
Sales opportunity conversion rate.
Order conversion rate.
LTV.
Retention rate.
Sales evaluation.
Customer feedback.

By looking at these results, you can improve your segments.

Customer segment analysis is not something where you get the right answer on the first try.

Segment.
Use for initiatives.
Check results.
Review segmentation methods.
Use for initiatives again.

It is a cycle of repetition.

If you are currently struggling with how to perform customer segment analysis, you don't need to aim for a perfect analysis right away.

The first thing you should do is simple.

Who are the important customers for your company?
What are those customers struggling with?
How are they different from other customers?
Which initiatives will you change to match those differences?

Please start from here.

Customer segment analysis is not a task for the sake of dividing customers.
It is a mindset for creating more effective initiatives for each customer.

Don't just divide and stop there.
Use it for initiatives.
Check results and improve.

If you can create this flow, customer segment analysis will be effective for advertising, content, sales, and existing customer follow-ups.

When you can see the differences between customers, your marketing measures will become more concrete.
And the more concrete your measures are, the higher the probability of achieving results.

First, while looking at your current customer data, try thinking about "which differences change your initiatives."
From there, customer segment analysis will transform into something you can use in practice.

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