Harnessing Customer Profiling to Improve Your Sales Pipeline

Arooj Fatima
Arooj Fatima

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Customer segmentation and profiling are easy-to-approach data analytics techniques that can help you understand your customers. Let's take a closer look at what they are, and how they can be implemented. 


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What is the difference between customer profiling and customer segmentation anyway? While the two are used to group customers based on similar traits to better understand them, they do have subtle differences.

Connecting with your customers becomes easier when specific customers are targeted with relevant messages. Customer profiling is best used to determine how to talk to your audience/customers: what key messages to convey, the right things to say; and even what images, colors and styles to use, to best encourage them to take action. However, a thorough understanding of Customer Segments must come first to do this effectively. These work together to form the ideal marketing campaign, which would ultimately translate to better sales pipeline management.  

3 Different Types of Customer Segmentation 


1. Segmenting by Buying Stage

Buyer stage scoring is a tool that helps you locate an individual’s exact position in the buying cycle. These scores give you an idea of what purchasing stage your buyers are in, what you can provide to educate them best and how you can guide them further down the buying cycle.

2. Segmenting By Product Interest

Product interest profiling relates to your buyer’s perspective. Particularly, you perform analysis on how a customer navigates websites, emails and content. The analyses helps you arrange your website content in the best way that addresses your customer’s needs, and allows you to recommend other products to your customer.

3. Segmenting by Buyer Persona

Buyer persona profiling consists of a combination of demographic information as well as website activity. If someone consistently reads through your developer blog and technical information, your next likely step would be sending them relevant tactical material to guide their research. If someone is only consuming your case studies, high-level blogs, and ROI analyses, you can profile that individual as a business decision maker and ensure that your marketing is brief and targeted to what that buyer persona wants to learn.

Customer Segmentation is the division of customers based on specific shared characteristics such as demography, geography and buying behavior.

Customer Profiling follows segmentation as it is used to describe customer personas, grouping them for marketing and advertising purposes. It takes the information collated through customer segmentation to create more meaningful and usable information. 

They are essentially two sides of the same coin.

Customer Personas can be refined with a deeper understanding of customers. This can be achieved with some or all of the profiling techniques below. 

4 Different Types of Customer Profiling 


1. Affinity Profiling

Affinity profiling is a method to study the buying habits of people to determine what kinds of products a particular customer likes.

2. Demographic profiling 

Demographic profiling uses geographical location, marital status and educational qualifications of a person to help sellers identify customers and sell them relevant products.

3. Psychological profiling 

Psychological profiling groups customers by their psychological nature, such as consumer personality traits, values, attitudes, interests and lifestyles. As with most types of data-enabled analysis, data points are assigned to certain criteria that is important to the business. In psychological profiling, statistics help to identify and classify customers according to predefined parameters. This information can then be used for marketing purposes.

4. Cluster Coding 

Cluster coding is a method that classifies groups of customers based on data similarities. It identifies similar data points that are shared by customers, and clusters them together in a single group. Hence, useful features that distinguish certain groups can be identified, and outliers can be eliminated.

Applications of customer profiling


Sales and Marketing

Customer profiling is essentially a sales tool - you simply cannot sell products or services if you don't know who your customers are. It is also frequently applied to marketing. Creating customer profiles of the people you are aiming to sell to is critical to a successful marketing strategy.

Product managers are masters of curating user profiles for the creation of new products. Product marketing can take this one step further, looking at data points to segment customers that will influence promotional strategies and ultimately purchasing decisions. By target advertising to a specific market segment, companies and marketers can find more success in selling products or services and increase profits.

Email Campaigns 

A subset of marketing are email campaigns. Customer profiling can be used to design different emails for each profile to maximize the results of each newsletter campaign. Accurate customer profiles can help the brand stand out in an otherwise crowded inbox. That means delivering messages that meet the interests, habits, needs and characteristics of the individual user. The idea is to lead  to higher email-opening rates, leads and conversion rates, and revenues.


Use Case: Customer profiling by a travel company

In this case study, a travel company wanted to categorize the travel preferences and needs of three different customer segments. Its team then designed custom messages that would appeal to the different profiles.

The company worked with third-party data providers to better understand and further segment their customer profiles according to preferences and demography. Once they were segmented, the client applied analytics to research the most popular destinations searched by each group.

Group A - Preferred luxury city breaks

City Prosperity: People with ample wealth who live in the most pursued after neighborhood.

Group B - Preferred family holidays to European and long-distance trips

Prestige Positions: Qualified professionals in successful careers who are enjoying financial ease in suburban or semi-rural homes.

Group O – Preferred global city trips

Rental Hubs: Young, well-educated city inhabitants who enjoy the enthusiasm and diversity of urban life.

The data further whittled down the preferred activities for each segment:

  • Group A – Luxury holidays, restaurants
  • Group B – Family, all-inclusive holidays
  • Group O – Restaurants, nightlife, deals

acting on These insights

By understanding each group’s likely preferences, the company took a data-driven approach to develop content & messages to better engage each customer.

Group A

  • Likes to spend holidays abroad
  • Prefers non-money offers
  • Clicked on inspiring images

Group B

  • Prefers to spend the holiday in Europe
  • Prefers financial discounts
  • Clicked on family images
  • Chose website for contact, not phone

 Group O

  • Prefers to spend the holiday in the UK
  • Wants large discounts to convert
  • Clicks on high energy images


From the data presented above, you can already begin to see how a marketing strategy can be planned around specific user groups (profiles). Each company will obviously group their customers differently based on the nature of their business and the objectives of their analysis. The best place to start the process of understanding your customers is to look at your best customers. Once macro-level customer segments are in place, profiling can be used to determine how to communicate with these customers.

Customer profiling helps to describe ideal customer types. It is a tool that businesses can use to target, attract, and qualify the most likely prospects. Profiles should ideally include demographic, behavioral and psychographic information.

Conclusion 

Segmentation and profiling are two sides of one coin. They can be jointly used to form the ideal customized marketing campaign and enhance sales pipelines. How ready is your company to harness the insights and knowledge contained within your data? DataVLT is offering a free analysis of your capabilities through the Pilot Partner Program. Find out more here.

 


 

ABOUT DataVLT

DataVLT is an affordable, on-demand analytics platform secured by blockchain technology. It is designed to simplify the complexity of data science. Backed by artificial intelligence and machine learning capabilities, DataVLT empowers enterprises to make meaningful sense of their big data and scale cost efficiently. Essentially, it is an end-to-end data/information management platform.

Learn more at www.datavlt.com

 

 

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