Table of Contents

    What is consumer lifestyle data?

    Consumer lifestyle data provides intelligence on the lifestyle characteristics of consumers, including habits, interests, hobbies, political affiliations, and attitudes. This data helps with customer lifestyle segmentation based on age group, gender, location, and income range.

    This data delivers consumer insights into how they spend their time, their consumption patterns, social trends, motivations, needs, and wants.

    Where does the data come from?

    The primary way to directly gather the data is through surveys at national or local levels, including interviews with members of target markets. It is sometimes augmented with other marketing data, demographic data, or transaction and purchase history of individuals.

    Another prominent methodology of gathering this type of customer data is through tracking the online and eCommerce shopping behavior of consumers. Cookie tracking, web scraping, and social media tracking can quickly provide lifestyle data of a large base of consumers. This data comes from several sources of mobile and online data collection methods, with details of location, movement patterns, number of devices, downloaded apps, time spent on apps, and in-app purchases.

    At times, private surveys can provide custom information on lifestyle and lifestyle choices.

    Financial institutions, health care insurers, and banks gather data on their customers, which they can use in their own marketing.

    What types of attributes should I expect?

    This data is often organized into demographic market segments such as age group, gender, location, education, profession, employment status, income bracket, and marital status. Depending on your requirements, many vendors offer custom segmentation to match your target market segmentation.

    The standard attributes include:

    • Interests including entertainment choices and sports
    • Hobbies in which consumers actively participate, including online gaming
    • Social events they attend, including unique national or regional public events
    • Tourist destinations they visit
    • Travel mode preferences
    • Political affiliations
    • Social media platforms consumers engage with
    • Statistics on popular trends
    • Causes they care for

    How should I test the quality of the data?

    The quality of the data depends on its sources; the number of devices tracked for each consumer may not deliver accurate identity validation. Some of the devices may be used by family members or other individuals not related to the owners. Comprehensive, accurate tracking of each consumer across all channels and devices is the primary focus while testing for high-quality consumer lifestyle data.

    Source credibility, data consistency, and privacy compliance are other factors you need to validate before using the data for the intended purpose.

    To test the quality of the consumer lifestyle data:

    • Ensure that the complete identity validation of the tracked data is available.
    • Ensure the source credibility.
    • Test the data for accuracy, regular updates, and consistency.
    • Confirm that the dataset can easily integrate with your systems and models.

    Who uses consumer lifestyle data?

    All types of industries use this data for sales, marketing, messaging, and customer care use cases. It is also helpful to build personalized customer experiences. Market research based on consumer lifestyle data provides deeper insights and can drive targeted marketing campaigns. Knowing where and how consumers spend time helps plan focused advertising campaigns that are more likely to engage with the targeted consumer segment. You can also use this data for reaching out to past customers who no longer use your products or services.

    Consumer lifestyle data is leveraged to make brands more identifiable and attractive to the target consumer segment. This data also drives decisions about endorsements from celebrities and social influencers.

    Trends indicated by consumer lifestyle data help travel, hospitality, and entertainment companies to forecast demand and identify pricing.  Other industries sometimes use this data to learn how their business can benefit from new lifestyle trends.

    What are the common challenges when buying consumer lifestyle data?

    A common challenge when looking for consumer lifestyle data is ensuring its accuracy and timeliness. This data drives several strategic decisions about product development, marketing, sales, pricing, and customer care. Poor quality consumer lifestyle data cannot deliver the right insights to support appropriate decisions.

    • Data accuracy: Some of the consumer lifestyle data sources may not use ethical and reliable methods to collect the data, risking its accuracy. As this data powers consumer segmentation, its attributes about their habits, needs, and wants must be accurate to provide any value to marketers.
    • Data timeliness: Consumer lifestyle data can quickly get obsolete as the habits and wants of consumers change periodically. Timeliness of this data is essential to ensure accurate analysis and actionable insights. Obtaining real-time data points, and ensuring that the data is not outdated is becoming difficult.
    • Data consistency and completeness: Consumer lifestyle data can be collected through different channels using various methods. Data must be consistent across all the sources to be of any value.  Some sources may deliver only selected attributes such as the causes consumers support or social events they attend. It may get challenging to ensure data completeness when data gets aggregated across a limited number of sources.
    • Privacy compliance: Consumer lifestyle data can include personally identifiable information (PII) when collected. In such situations, it must comply with the data privacy regulations applicable to all the regions of operation.

    What are similar data types to consumer lifestyle data?

    Consumer lifestyle data is similar to consumer behavior data, consumer intent data, consumer propensity data, and other related demographic data categories used for marketing and targeted advertising.

    You can find a variety of examples of consumer and demographic data in the Explorium Data Catalog.

    Sign up for Explorium’s free trial to access the data available on the platform.

    What are the most common use cases of consumer lifestyle data?

    The most common use cases for consumer lifestyle data are data-driven advertising, audience targeting, and customer segmentation. This data can also be leveraged for product personalization, dynamic pricing, and increasing customer lifetime value (CLTV).  You can also use this data to enrich other types of consumer demographic data for use in your industry.

    • Data-driven advertising: It is a modern, scalable, automated communication method that can be personalized. Consumer lifestyle data can be used with other categories of audience data for targeted, personalized advertising campaigns. The use of large data volumes helps build better audience segmentation and delivers higher ROI on advertising investments.
    • Audience Targeting: Data-driven audience targeting leverages technology to identify accurate target audiences based on their online and offline behavior. A strong model based on behavior characteristics helps target the people likely to use specific products or services.  Consumer lifestyle data delivers valuable insights into target audience characteristics, driving better engagement and deeper personalization.
    • Customer Segmentation: Technology provides a way to divide target customers into smaller segments for more accurate targeting. Consumer lifestyle data offers a wide range of information about the interests, habits, needs, and wants of consumers to help refine the segmentation.
    • Customer Lifetime Value (CLTV): CLTC is the value that individual customers bring to a company over the course of their lifetime. This metric places a higher emphasis on long-term customer relationships compared to turnover or profits. Considering that companies require a reasonable customer acquisition cost (CAC) in modern markets, they must focus on CLTV to improve profitability. Consumer lifestyle data provides inputs for more accurate CLTV models, along with other demographic data categories.

    Which industries commonly use this type of data?

    CPG, retail, travel, hospitality, leisure, and entertainment industries leverage consumer lifestyle data for marketing. Financial institutes, insurance providers, and banks also use this data, augmented with their own tracking of consumer spending, to offer specific products for their target segments.

    How can you judge the quality of your vendors for consumer lifestyle data?

    The vendors for consumer lifestyle data supply large data volumes with a variety of attributes.  You can use several methods to assess the data quality, consistency, and suitability for your requirements. Vendor websites provide the details of attributes with segmentation and regions. You may find customer reviews on the websites, which are good indicators of vendor quality and reliability.  A demo helps evaluate if the datasets match your requirements and if they can easily integrate with your current technological tools.  Interacting with vendor reps is a good idea to get your queries resolved quickly.

    • Case studies and customer testimonials: Reviews and testimonials from customers indicate how reliable the vendor is. They can also provide a summary of vendor engagement. Case studies illustrate the capability of the vendors in meeting customer requirements and providing custom solutions.
    • Demo: A comprehensive demo indicates the data quality and range of available attributes. Many vendors provide test datasets to help assess the suitability of data for your planned use. A demo and sample dataset are good options to see if the vendor data matches your requirements.
    • Interacting with vendor reps: One of the best methods for determining vendor quality is talking to the reps. They can respond to your queries and offer an effective solution to your challenges.  Questions about the attributes, scaling capability, data recency, methods of data collection, and integration capabilities can be resolved in these interactions. It is also an opportunity to evaluate vendor interest and commitment.