With several laws regarding data privacy and consensually getting user information, the importance of first-party data becomes more glaring by the day. From improving your marketing campaigns from a better understanding of your target audience to deriving insights that can reduce customer churn, data intelligence enables you to get your business’s services in front of those who need it.
Google announced its intent to remove support for third-party cookies by 2023, and Apple’s iOS 14.5 requires marketers to receive the user’s permission for app tracking. These two major announcements set to shift the marketing moves to concentrate on acquiring first-party data.
What is First-Party Data?
First-party data refers to the data a business gathers directly from its customers. The keyword here being “directly” means data from customers’ interaction with your platforms, including your website and app. Examples of first-party data include survey data, membership data, client feedback and user registration. First-party data differs from second-party and third-party data in several ways.
Second-party data is obtained from consumers’ interaction with a product but is sold off to a non-competing company. It’s not all the time that second-party data has to be paid for, though. Sometimes all that is needed is a simple partnership between the companies. In contrast, third-party data is data that originates from several different sources.
Second and third-party data are based on the concept of utilizing users’ data as a means of exchange; as such, they are valuable. First-party data are equally valuable but with lesser risks of privacy rights infringement. Other advantages of first-party data collection are:
- First-party data attract zero penalties and are considered safe
- Better targeted advertorials and tailored user interaction
Top Tips for Collecting First-Party Data to Improve Your Business’s Marketing
Data collection and usage have become increasingly delicate when you consider several requirements that have to be met and the associated penalty when you do not meet them. However, user data is expensive to obtain but essential for a business’s marketing funnel. To avoid operating an inefficient marketing strategy and spending unjustifiable amounts for data, here are three tips on collating first-party data.
User Registration
User registration is one of the most popular ways companies often obtain data from users. They do not require any complex strategy to pull off. All you need is an incentive tempting enough for consumers to give their data in exchange. It could be an ebook, discount service or a referral contest. These details can serve as the foundation of a better efficient campaign in the future as users are already familiar with the brand.
Progressive Profiling
Progressive profiling uses subtle techniques in collecting data from your leads in small doses without making it look like you are data-hungry. This method offers a much deeper insight into your users because the data gathered over time is demographic-specific and is classified accordingly. For example, you could begin with an initial sign-up request and proceed with subsequent data requests like birthdays and company size. Progressive profiling data is even more accurate and efficient in marketing campaigns than data obtained from user registration data only.
User Reviews
Reviews and feedback are a great way to collect data from your active users and consumers. Besides helping you rediscover and optimize your services, reviews help your company determine consumer profiles that interact with your products and services the most. With the ideal customer profiles and statistics collated, products can now be developed with the most active and engaging user base in mind. First-party data are also invaluable when used in predictive analysis due to the clean nature of the data.
What is Predictive Analysis and How Does It Work?
The production and service industry is fast-moving and repeat data collation can be time-wasting. This is why corporations have found ways to utilize data collected for multiple purposes and future consumer projections. One such way is predictive analytics.
Predictive analytics involves using machine learning and AI to predict and project consumer behavioral metrics from datasets collected at different points of a consumer’s journey. Behavioral projection is essential to stay ahead of the competition as more alternatives swarm the market.
You can incorporate and use predictive analysis in several ways. Predictive analytics helps you understand your users better based on previous interactions with your platform. You are able to determine which consumers may adopt the competition and plan accordingly. This could be either targeting these consumer classes less frequently or integrating their needs into future products.
As a result, product development and marketing budget are better optimized, and targeted campaigns like hyperlocal SEO and Facebook ads are more effective. For predictive analytics to be high-level hinges, your company must collect precise lead data. This is why the manner of data usage is just as significant as the collation process. Invest in both worlds to achieve optimum and long-lasting results for your business.
Consult With Deliver Media Today to Make the Most of Your Data Analytics.
Traditional marketing methods are becoming increasingly dated, and data is poorly utilized because of suboptimal sales funnel strategies. At Deliver Media, we deliver the most custom marketing experience for your business by using our trademark technology with your data. We focus on general KPIs and individual customer behavior metrics for the best marketing decisions and results. Contact us at (800) 377-4683 or send an email to testdrive@delivermedia.com to get the best out of your marketing campaigns.