Lead Enrichment using Social Data

In this post, we will demonstrate the process of enhancing leads by utilizing social activity found on facebook and artifical intelligence (chat gpt).

But let’s go step by step: First lests define the following concetps:

What is Lead Enrichment?

Lead enrichment is the process of gathering additional information about potential customers or clients to enhance and deepen their profiles. This information includes data such as contact information, job title, company size, and industry, among other things. The primary goal of lead enrichment is to improve the quality of leads by providing a more comprehensive understanding of their needs, preferences, and behavior.

In this post, our main focus will be on how to incorporate behavioral and preference-based purchase information from social networks, with a specific emphasis on data obtained from Facebook. We will explore various techniques and strategies for leveraging this data to enhance lead profiles and improve the overall effectiveness of marketing and sales efforts. By utilizing the wealth of information available on social media platforms like Facebook, businesses can gain deeper insights into the interests, behavior, and preferences of their target audience. This can help them tailor their marketing campaigns and sales tactics to better meet the needs of potential customers, leading to higher conversion rates and improved ROI.

Why using Facebook data for Lead Enrichment?

Facebook provides a wealth of information about its users, including both demographic and behavioral data. One of the key data points that businesses can leverage is user “likes”. When a Facebook user “likes” a particular post, page, or brand, they are indicating an interest or affinity for that topic. By analyzing a user’s likes, businesses can gain insights into their preferences and interests, which can be used to tailor marketing messages and product offerings.

Additionally, analyzing the types of pages a user has liked can provide valuable information about their demographics, such as their age range, gender, and location. Overall, understanding the information available through Facebook likes can be a powerful tool for businesses looking to better understand and engage with their target audience.

Why we need Chat-gpt to make sense of the data?

The data obtained from Facebook, such as user likes of pages, can be vast and overwhelming, making it difficult to extract meaningful insights without advanced analysis tools. This is where ChatGPT can be incredibly useful. As a language model, ChatGPT is capable of analyzing large volumes of unstructured data, such as Facebook likes, and identifying patterns, themes, and keywords. By inputting the raw data into ChatGPT, it can quickly analyze the likes and extract valuable information, such as the user’s interests, preferences, and potential buyer persona.

For example, if a user has liked pages related to healthy eating, fitness, and yoga, ChatGPT could identify the main keywords and themes, and use them to build a persona for that user, such as a health-conscious individual interested in wellness and self-improvement. With this information, businesses can create targeted marketing campaigns and personalized content to better engage with their audience and increase the likelihood of conversions.

In summary, ChatGPT can help make sense of the raw data obtained from Facebook likes by identifying patterns and extracting key information, enabling businesses to better understand their target audience and tailor their marketing efforts accordingly.

Let’s see a Real Example of Lead Enrichment based on Facebook Data

The upcoming example will demonstrate how to extract behavioral insights from a Facebook user to determine their suitability for a fitness campaign. The goal is to launch a marketing campaign offering a 50% discount to individuals who have demonstrated an interest in fitness. We will analyze the user’s likes and interests to determine if they meet the criteria for the campaign. In essence, we are evaluating if the user is a good fit for the fitness campaign.



After observing the Facebook user’s activity, we have noticed that they have shown interest in several Facebook pages. Our aim is to leverage this data to uncover personality traits and preferences. However, before we can proceed, we need to organize the data in a structured format. To accomplish this, we will be using the LikeSpyder tool. LikeSpyder is a handy Chrome extension that can quickly extract all Facebook likes and export the data in an Excel format. To use this tool, we only require the Facebook profile link of the user.

The information provided above consists of a comprehensive collection of the user’s likes obtained through the use of LikeSpyder. As can be seen, the data is quite extensive. Therefore, we can proceed to analyze and interpret this data using ChatGPT. Here is the result obtained:

Based on the information obtained through LikeSpyder, it appears that the Facebook user in question does not have any hobbies or interests related to fitness or gym activities. As a result, it may not be appropriate to target this user for a fitness campaign.

It is crucial to apply the same data extraction and analysis process to all users in your CRM system, such as HubSpot. By doing so, you can segment clients based on their interests and behaviors, allowing you to create personalized and targeted campaigns. This approach can significantly improve the effectiveness of your marketing efforts by tailoring your messaging to the specific needs and preferences of your customers.

Additionally, analyzing customer data can provide valuable insights into trends and patterns, which can inform future product development and business strategies. Overall, taking a data-driven approach to customer segmentation and campaign planning is essential for maximizing the impact of your marketing efforts and driving business growth.


Lead enrichment can be a powerful tool for improving the quality of your leads. By leveraging social data from platforms like Facebook, businesses can gain deeper insights into the interests, behaviors, and preferences of their target audience. With the help of advanced analysis tools like ChatGPT and Matchkraft’s upcoming Facebook data extraction tool, businesses can quickly and easily extract valuable information from large volumes of unstructured data. Although the Facebook data extraction tool is currently in beta, businesses can send a message to info@matchkraft.com if they need access to the tool.

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