Demographic Data

Demographic data provides statistical information about a specific population, including age, gender, race, and location. Companies leverage it to learn about demographic trends and build demographic profiles to help with create more accurate customer segmentation, driving better decision making around lead generation and sales campaigns.

This data comes from a large variety of data sources. Surveys are considered as a primary source. Governmental organizations, private organizations, or industry analysts regularly conduct surveys across industries and populations to collect relevant information on demographic characteristics. Surveys need to adhere to privacy compliance, which may lead to lower responses or incomplete information. Survey information may quickly get outdated if conducted on large sample sets. Surveys can be expensive, considering the efforts required for information gathering and the subsequent analysis. Modern technologies provide a better alternative, gathering information from location, preferred language, self-reported profile information, and other online activities. Technological tools deliver data quickly and can also provide deeper insights. You can further enrich demographic data with event tracking or the use of cookies. You can manage privacy compliance and scalability more effectively when you collect data with such tools. It is also available from public records, such as census information from the U.S. Census Bureau (www.census.gov) and publicly accessible administrative records. This method can be challenging, as the information may be incomplete or not recently updated. For example, the decennial census only occurs every ten years.

Demographic data provides characteristics of a specific population sample (subsets of populations) as statistics and offers the following attributes:

• Age group
• Gender
• Contact details: Address, Email, landline number, mobile number
• Educational attainment
• Ethnicity: ethnic group, languages, ancestry
• Financial data: Employment status, occupation, primary income source, income, net worth, home ownership, economic data
• Lifestyle data: Hobbies, product ownership, leisure activities
• Geographic data: Residential address, office address, birthplace, locations visited, population growth, population changes, population estimates
• Life-stage data: age group, marital status, number and age of children, veteran status
• Labor force data

Testing the quality of demographic data involves validating the credibility of the data sources. Databases supplying the data are either reliable or currently updated, but rarely both. Surveys are usually manual, and the information collected may not be complete or current. Addresses, income, or life-stage information can quickly change, and surveys may still provide obsolete information. Online tools deliver updated information, but they derive data from self-reported information or online activity that may not be reliable. Consider the following aspects to decide the relevance, accuracy, and recency of data to your use case. To test the quality of the data:

• Verify that the sources provide trusted data
• Confirm that the data collection process is suitable for your proposed use
• Validate that the data is complete, accurate, and recently updated
• Request a historical data sample and verify it
• Ensure that the data is compliant with the regional privacy regulations

You can compare the geographical spread and attributes different vendors deliver and evaluate if they meet your requirements.

All types and sizes of organizations use the data for customer segmentation, which can help with market research, marketing strategies, lead generation, and marketing campaigns. You can also use demographic data to identify your key audience segments and track audience sentiments. Insights generated by demographic data can determine the idea for new products and uncover new markets. For more accurate customer segmentation, you can augment demographic data with other types of marketing data.

The biggest challenge in buying demographic data is ascertaining the sources. While a primary and reliable source, surveys provide information that may not be recent or complete. Other sources can deliver more current information, but it may not be accurate. Demographic data powers customer segmentation, and it needs to be accurate, timely, and as complete as possible.

• Source credibility: Demographic data scraped from the web can provide several attributes, but their credibility and frequency of updates need to be thoroughly verified.
• Data completeness and accuracy: Demographic data collected from census data or administrative records can be accurate but incomplete. On the other hand, data gathered with online tools can be complete but inaccurate. Using inaccurate or incomplete data for customer segmentation can deliver skewed results. Ensuring data completeness and accuracy is a significant challenge for demographic data.
• Data timeliness: While using demographic data for customer segmentation, its recency plays a critical role. As details of income or locations can change quickly, vendors must update demographic data frequently to ensure that your analytical results are accurate.
• Privacy compliance: Demographic data contains personally identifiable information (PII), which must comply with the relevant privacy regulations. As regulations such as GDPR and CCPA are region-specific, managing compliance for all the applicable regions is challenging.

Demographic data is used primarily for customer segmentation to offer personalized messaging and targeted sales campaigns. It can also contribute to other marketing use cases in retail and financial services. You can use demographic data to enrich other types of company data or B2B data for strategizing marketing and advertising campaigns.

• Customer Segmentation: Dividing the customers and prospects into distinct segments, where each segment has customers with similar profiles, helps companies customize offerings. Customer segmentation provides opportunities for companies to offer personalized experiences and maximize the value each customer generates. Companies use customer segmentation to focus on the segments aligning with their products. They also use the segmentation insights to develop new products targeted for specific segments. Demographic data contributes to customer segmentation by providing a wide range of attributes.
• Product Personalization: To meet the increasing customer expectations, several companies offer personalized products or services. With sophisticated technologies making inroads in marketing, customer expectations are evolving, and companies are rushing to catch up. Product personalization begins with leveraging demographic information to predict customers' needs and actions. Learning iteratively from customer buying behavior, the prediction is optimized to offer personalized products and services to specific segments.
• Lead Scoring: Companies focus on qualified leads with the highest conversion probability to maximize the returns on marketing investments. Lead scoring ranks the leads according to the perceived value they represent for the company. A good lead scoring model leverages demographic data to arrive at an accurate ranking. Price Segmentation: Offering the same products or services at different prices for different customer profiles is a common marketing strategy (dynamic pricing and promotion scheduling). Companies offer discounts to Gold members or students, based on the prediction of their buying behavior. Demographic data helps identify the best-suited prices for different segments to maximize sales and increase customer loyalty.
• Insurance Pricing: The pricing of insurance products is based on several risk factors and historical insights. A good insurance pricing model leverages demographic data to offer the best pricing and low switching costs for gaining a competitive edge. Price optimization drives customer loyalty while maximizing profits for the insurance company.

Demographic data gets used across all types of industries, notably retail, eCommerce, and consumer goods or CPG companies. Other industries that use this data include manufacturing, hi-tech, banks, insurance, and financial services.

The quality of vendors supplying demographic data depends on the quality of their sources and the methods used in data collection. You can use the following indicators for assessing vendor quality.

• Customer reviews and testimonials: Customer reviews are always a good measure of customer engagement and satisfaction with the vendor. Most vendors provide customer testimonials on their websites, along with case studies or success stories. This feedback helps to assess the credibility and data quality of the vendor.
• Demo: Besides customer reviews, another method of judging the quality depends on the demo of the datasets offered. An opportunity to see the offerings in action, a demo is a reliable way to estimate if the data quality and attributes match your requirements.
• Interacting with vendor reps: If you are satisfied with the information, demo, and customer stories provided by the vendor, the next step is interacting with the reps. You can discuss vendor sources, data collection methods, vendor engagement, and other details. This is also an excellent opportunity to get your queries answered.