Almost every organization recognizes the importance of having useful customer profiles to support targeted marketing and sales efforts. A customer profile is a precise description of the characteristics of buyers for a specific product or service and typically includes information such as role, education, title, interests, and so on. Often, profiles are a precursor to creating personas, are use by marketers to develop relevant messaging and offers.

Two Common Types of Customer Profiles

There are two common types of customer profiles:

1. Demographic, which provides a set of characteristics. For example, John, a college graduate with a finance degree, is married, has 2 children, commutes to his office, lives in an upscale suburban neighborhood, has a subscription to 3 News magazines, is a demographic profile. Demographic profiles are helpful in defining communication channels and communication vehicles. 
2. Behavioral, which tells you about actions. For example, John visits financial website every day, posts at least one business related news story daily to his LinkedIn and Facebook pages, participated weekly in his LinkedIn Finance group discussion, follows and retweets influential members of the financial press two times per day, is more of a behavioral profile. A behavioral profile is a valuable tool for predicting future action. 

Modeling and Profiles

Modeling is a bit like profiling but models enable you to look at action over time. Models look at a set of customers engaging in a certain behavior and try to find commonality among them. As a result behavioral profiles support modeling.

Why? Research suggests that customer behavior is a much stronger predictor of your future relationship with a customer than demographic information. Behavioral data offers a view into satisfaction (I’ve stopped visiting your website and downloading your content), into propensity to purchase (Every time you have a new offer I’m willing to trial).  Behavioral profile information is very important in the consideration and retention phases. If you know the likelihood of a customer’s behavior, you can then make intelligent decisions on how to interact with this customer or types of customers. 

Building models takes talent and experience and the type of model depends on the business and available data. Why should you care about modeling? By understanding how customers are likely to behave you can potentially increase customers. You can use models to answer basic marketing questions: Which customer should I invest in? Which offers will be most likely to secure a response? What kind of future business can I expect from existing customers?

Even if you are not ready to create customer behavioral models, you can use customer behavior profiles to drive response among the best customers, do targeted messaging, execute retention programs and predict the future value of customers. 

How to Create Behavior-based Profiles

Creating behavioral profiles takes data.  Almost any part of the marketing and sales process can incorporated into your behavior profiling. Behavior-based profiles are created by looking at customer activity such as purchases, page views, downloads, phone calls, and event participation. 

Short on data and the time or money to do a thorough job or seek expert help? Here is an potential option to create your ideal customer profile and develop a scoring methodology:

1. Make a list of who you think your best customers and your worst customers are. On a spreadsheet create five columns: Best Customers, Worst Customers, Best Customer Characteristics, Worst Customer Characteristics, and Ideal Profile.
2. In the first column, make a list of all your Best Customers or as many as you can think of. Don’t think about why you put these customers on the list, just get your ideas and thoughts down.
3. In the second column, make a list of your Worst Customers or as many as you can think of. Don’t worry about why you chose them just yet.
4. For each Best Customer, make a list of why you think they are a “best” customer, such as buys frequently, serves as a referral, etc.
5. For each Worst Customer, make a list of why you think they are a “worst” customer, such as pays late, regularly delays projects, etc).
6. Identify characteristics each of your Best and Worst Customers have in common, transfer the list from the Best Customers and then craft an opposite for each of the Worst Customer Characteristics ñ for example pays late to pays upon receipt.
7. Transfer this list into the final column to create your Ideal Customer profile and create a weight for each criteria and a score.

Now you can compare new prospects against the list and score them on how well they meet each criterion. Invest your limited marketing and sales resources with those prospects that have the highest score against the most important criteria. To start creating personas for your organization, purchase our 54-page workbook “Using the Customer Buying Process to Align Sales and Marketing & Create 3 Key Enablement Tools.”

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Common Information for the Typical B2B Customer Profile

At a minimum, B2B companies should create customer profiles that contain the following  types of information (this is the data is generally available):

• Type of Customer
• Customer Demographics (buyer title, location, size, industry, etc).
• Buying Decision Criteria (price, quality, service, convenience, etc)
• Buying Process (internal buying process, whether they direct or indirect, touch points, channels, etc).
• Buying Frequency
• Problem Your Offer Solves

The better and more actionable your profiles the more you can maximize sales to your best customers, lower acquisition costs by seeking out customers whose behavior mirrors those of your best customers, and retain your best customers. 

7 Data Sets to Create Actionable Customer Profiles

As a result the profiles while descriptive are not necessarily actionable. Today’s customer-driven environment calls for creating more actionable customer profiles. At the very least, an actionable customer profile needs to include the following information:

• Description: This section should include the data that defines the customer. These are the traditional data elements related to demographics.

• Needs: This section should clarify the customer’s requirements, needs, and desires; why they need the product/service/solution you are offering, and how they attempt to solve the problem today.

• Value: This section should provide insight into the worth of the customer now and in the future.

• Psychological: This section requires data that reflect the values and opinions of the customers and how they make decisions (pragmatic, financial, social responsibility, etc).

• Relationship Strength: This section should reflect the status of the customerís relationship with their current provider and your organization. If they are satisfied why and they are not satisfied, why not.

• Interaction History: Most profiles forget to include any information about the past or current status of the relationship with the organization. Operational history and prior interactions should be included in this section ñ such as website visits, marketing offers sent and acted upon, marketing offers sent but ignored, service requests, prior sales visits, etc.

• Sphere of Influence: With social networks now mainstream, an effective customer profile should include data about which social networks and other communities the customer uses and some understanding of the influence of each network and community on the customer.

Customer profiles that include data related to these seven categories will enable both sales and marketing to more effectively engage the customers represented by the profile. Learn more about how to tap our customer intelligence and insights services.

FAQ:

• Demographic Profiles: Describe static characteristics such as age, education, family status, and lifestyle, useful for selecting communication channels.
• Behavioral Profiles: Capture actions and engagement patterns like website visits, social media activity, and purchase behavior, providing predictive insight into future customer actions.

• Customer type and demographics (e.g., buyer title, industry)
• Buying decision criteria (price, quality, service)
• Buying process details (internal steps, channels)
• Buying frequency
• Problems your offer solves

1. Description: Demographic and firmographic data
2. Needs: Customer requirements and problem-solving approaches
3. Value: Current and future worth of the customer
4. Psychological: Values and decision-making styles
5. Relationship Strength: Satisfaction and loyalty indicators
6. Interaction History: Past engagements and marketing interactions
7. Sphere of Influence: Social networks and community impact

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