By Michael Olson | Posted on September 07, 2012
This is the third in a series of blog posts outlining best practices for integrating social technologies on your site.
Traditionally, brands have relied on three sources of data to inform customer intelligence – explicit data collected at registration, clickstream data, and transaction history. Unfortunately, clickstream data can be unreliable due to the fragility of browser cookies, and the friction associated with traditional registration methods means that brands often struggle to convince consumers to share personal information at sign-up. As evidence of this friction,88% of consumers report having provided false personal information when asked to complete a traditional registration form.
So, where does this paradigm leave marketers who are seeking to develop deeper relationships with customers? Brands can gain a more sophisticated understanding of their users by leveraging the profile data that people already maintain on their social networks. Social profile data includes not only basic demographics such as name, age, gender, geography and email address, but also deeper psychographic information such as interests, marital status, political views, hobbies and friends.
Because the profile information that users maintain on their social networks is transparent to friends, family and coworkers, it is more likely to be current and accurate than personal data that users may supply during a traditional registration process. And unlike the clickstream, social networks maintain declared data on users (in other words, information that consumers have provided about themselves), which possesses a much higher degree of integrity and stability.
Social login makes it possible to gain permission-based access to profile information from a user’s social network. When a user chooses to register or login on a site with a social identity, a permission screen asks her to approve sharing her profile data. Depending on the identity provider, brands can choose which data fields and permissions they wish to request, and the person can choose which specific profile fields she is comfortable sharing.
Once brands have access to social profile data, the next step is to store and utilize it in a flexible database that can pair legacy data, site activity data and offline or third-party data with a social profile to build a true 360-degree view of a user and inform data-driven marketing programs.
The vast amounts of demographic and interests data contained in a social profile provide the foundation for customer intelligence and effective targeting and segmentation. A platform to collect social profile data via social login and store and leverage it in a flexible database makes it all possible.
It’s hard to fight a battle with one hand tied behind your back. Similarly, marketers struggle to make smart decisions when they lack a unified view of a customer because online user data is stored in multiple silos such as email, CMS or CRM. Social profile data is most useful when it is combined with existing information you already collect about your users, such as site activity data, transaction data, or offline data. An effective database solution should marry user data across each of these disparate sources to provide a single, global view of a user.
User data needs structure in order to be actionable. For example, it can be a colossal challenge to query age ranges for users in a database when dates of birth are stored in inconsistent formats. Your database solution needs to normalize profile data that gets placed into the system, and enforce some structure to ensure that the data can be easily queried and applied for practical use in marketing campaigns. A flexible schema ensures that profile information stored in your user database works with you, not against you.
Simply storing social profile data isn’t enough. The data needs to be easily accessible for applied use, which is why your user profile management system needs to be pre-built to support integrations with component technologies commonly used by brands to connect with consumers. For example, your database solution should integrate seamlessly with email marketing solutions, eCommerce and merchandising platforms, personalization and recommendation engines, CMS, and targeting systems.
Your user profile database should make it easy to create target segments of users and feed user data into your email marketing system to send tailored offers. Suppose, for example, that you wish to promote an upcoming concert in London by sending a tailored email offer to 18-24 year old females who are located in the United Kingdom and fans of Taylor Swift. Or, perhaps you would like to target male users with a declared interest in camping, in order to personalize product recommendations on your eCommerce site. Social profile data improves the relevance of marketing initiatives.
If one of your users changes her email address or location, how likely is she to let you know about it? Data quality is a problem for marketers, many who are working with databases that have been infested with John Doe and cartoon characters. Since our social network profiles are transparent to friends, we are all more likely to keep the information stored accurate and up-to-date. Each time a user signs in to your site using a social identity, you can collect a fresh copy of profile data from their social network to help maintain a clean and current database.
Hopefully you wouldn’t put someone through the wringer on your first date by asking 50 questions … Right? Dating advice is surprisingly relevant when it comes to learning more about your online users. Don’t ask your users to share their life story on your first date. Build progressive profiling workflows that invite users to share more information about themselves at the right moments. The points at which people post comments, share content, purchase products or write reviews all present an opportunity to inquire and build a deeper, more comprehensive customer profile.
Sears uses social login to collect a rich set of profile data from shoppers, including interests and social graphs (friends). Using this data in parallel with its personalization engine, Sears offers relevant product recommendations for shoppers based on the interests in their social profile, as well as gift ideas for a shopper’s friends based on the birthdates and interests of those friends in her social graph.
To learn more about collecting and storing social profile data as well as other social technologies, check out our Definitive Guide to User Management.
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