What are Customer Data and its Collection?
Customer data refers to the personal, behavioral, and demographic information that a customer provides. It is acquirable through interactions with companies and businesses via mobile applications, marketing campaigns, websites, surveys, and other offline and online methods.
Customer data collection represents the amassing and gathering of numerous qualitative and quantitative information about the clients and users through diverse grouping methods. In today’s world, this practice is the parameter that determines a business’ development and possible achievements. It helps a company flourish by understanding its customers and communicating and engaging with them.
What are the Different Kinds of Customer Data?
Customer data comprises numerous facts and statistics. Overall, they can get categorized into four different kinds based on the type of information they entail.
Personal data is any information that relates to the private life of a customer. It can be of two sorts. They include PII (Personally Identifiable Information) and Non-PII (Non-Personally Identifiable Information).
- PII is any information that represents and proves the identity of an individual. It can further get classified into:
- Linked Information: It can identify a person without requiring any additional data. It consists of their full name, physical and email address, passport and driver’s license number, date of birth, phone number, and so on.
- Linkable Information: It cannot identify a person unless it gets clubbed with other substantial data. It consists of their first or surname, country, gender, pin code, age group, job, ethnicity or race, and so on.
- Non-PII comprises the anonymous information that cannot get used as an identity proof of an individual. They include the device ID, IP address, and cookies that a person utilizes on a website. Although they do not help to identify individuals, they get categorized as personal data by various laws.
Engagement data provides information on the methods and outcomes of the interaction that ensues between a customer and a company, business, or brand. They take place through the various marketing strategies, avenues, and plans targeted towards an audience group. This type of data comprises records of the customer’s behavior on a website, their engagement via social media or customer service, and other communication processes.
Engagement data collection can take place through:
- Mobile App and Website Interactions: They consist of the data acquired from user flows, most visited sites and pages, traffic sources, etc.
- Email Engagement: They comprise open rate, email forwards, bounce rate, click-through rate, etc.
- Social Media Engagement:They include data from post shares, likes, views, replies, etc.
- Paid Advertisement Engagement: They consist of cost per click, conversions, and click-through rate. These are acquirable through remunerated ads.
- Customer Service Information: They comprise data from query details and the number of feedbacks, tickets, and complaints, etc.
Behavioral data gets acquired from a customer’s purchase history. It helps to analyze the underlying patterns behind their product selection and buying style. They can come from:
- Transactional Data: They include details from subscriptions, purchases and customer loyalty and order programs, the average value of customer lifetime, etc.
- Product Usage Data: They comprise information from online task completion feature duration and usage, etc.
- Qualitative Data: They consist of information from the clicks and scrolls made by the user. The areas where they place their attention also get included.
Attitudinal data depends on the emotions and feelings of a client or customer and the way they perceive a product or a brand. It is a qualitative analysis method that needs to get combined with quantitative information to proffer concrete outputs.
This type of customer data collection ensues through various methods. They include reviews, feedbacks, surveys, customer complaints, interviews, and so on.
Attitudinal data comprises a customer’s:
- Purchase criteria
- Product desirability
- Challenges and motivation
How Does Data Collection Help?
In recent times, all companies are becoming data-driven. The reasons behind it include:
Improves Customer Database
The various types of data collected at regular intervals help strengthen the customer database that a business records and uses. The greater the scale of the data, the more the company can gain an insight into the market trends.
The analysis of the customer database allows for an understanding of the changing customer dynamics. It helps predict future trends. Data collection enriches a customer database both qualitatively and quantitatively.
Conceptualizes Better Services and Products
Customer data collection helps acquire cumulative information on how the target audience perceives the performance of a product and other services. If the statistics do not represent a favorable response, it implies that the scope of improvement exists. The collected data also aids in pointing out the areas of weakness of a product or service and creating strategies to remove the gaps.
Enhances Pricing Strategy
The price of a product depends on its demand and supply in the consumer market. Before the launch and promotion of a new item, the pricing gets decided. It gets done by analyzing the information acquired from customer data collection.
The data delivers and drives pricing analytics that is necessary to overcome the price optimization challenges. Additionally, it helps identify the appropriate marketing channels that would proffer the maximum profit and conceptualize the promotion strategy.
Strengthens Campaign Strategies
Customer data helps understand the preferences of the target audience. It assists the checking the effectiveness of a particular marketing campaign. It is possible by analyzing the impression it has on the clients. Depending on the acquired results, it helps shift to a more beneficial campaign strategy. Thus, a customer base strengthens a plan to be fool-proof.
This work gets enhanced through forecasts of predictive analysis that a customer data collection proffers. It also streamlines and filters the generated leads to help choose the most profitable ones.
Improves Customer Satisfaction
Customer purchase history provides an idea of a client’s reviews, buying behaviors, post-purchase comments, and suggestions. It helps create better customer service frameworks that offer a more satisfying experience.
Regular customer data collection helps update the history and modernize the provided services accordingly and constantly.