Snoopreport took the first critical step in applying machine learning technology to everyday life.
For almost a decade, Snoopreport has been analyzing Instagram data. We understand it thoroughly, as Instagram has been an essential component of previously established marketing campaigns. Using Instagram in a data-centric way, Snoopreport identified audiences, built custom segments, and communicated directly with them. Over time, Snoopreport consistently developed its features holistically.
The foundation of any data-centric approach is the quality and accuracy of the data itself. If we are analyzing social networks, we need to learn how to collect data accurately and efficiently. For example, Instagram’s public API was deactivated in 2018, and collecting data has since become a real challenge—although one solved by today’s programmers.
What is Snoopreport?
The usual way of learning something new about someone is to visit their account and look at their posts. That is the side of the person they want everyone to see—their public persona.
But there are also their likes and follows. Suppose a person likes thousands of posts—how easily can you make sense of that? Or imagine someone follows 100 new accounts in a month—how do you analyze that?
Tracking activity in social networks nowadays is almost impossible without specialized tools, because of the technological difficulties involved. At Snoopreport, our audience can see new activities in the public accounts of their friends, celebrities, or brands.
What is Socialprofiler?
Through our Snoopreport technologies, we have always been able to target audiences on social media. The idea of not just assembling a new segment, but dividing the social network into all possible segments at once, has been a long-term goal for us.
Now, an individual can see all segments of a social network at once. That is important, because how else can one identify which new interests are emerging and which new segments are being born? We are part of a culture that constantly evolves. The ability to predict future trends, as identified in our segmentation analyses, is highly valued and useful.
Socialprofiler achieves this through an approach that allows us to see everything at once. Using machine learning, Socialprofiler identifies communities of people united by common interests and assigns those groups proper classifications.
Now we don’t just track a person’s activity—Socialprofiler analyzes all of their followings by combining them into natural categories. We do this dynamically, identifying when new communities appear on social networks and when new interests arise for the individual being researched.
Differences Between Socialprofiler and Snoopreport
In both applications, we analyze social media data. But Snoopreport focuses on an individual’s likes, providing a list of actions they took and accounts they liked over a period of time. Socialprofiler, on the other hand, examines the depth of their followings and highlights interests detected by our algorithms.
A person can view week-to-week changes in activity with Snoopreport, but it is difficult to analyze all of someone’s followings. That is where Socialprofiler steps in. Socialprofiler reveals the realized interests of a research target, because not everything that a person follows translates into actions.
Analyzing a Person Using Both Socialprofiler and Snoopreport
Let’s analyze an example Instagram account to see what can be learned by combining both services. Since we only analyze public accounts and activities, there are natural limitations across the spectrum of social media platforms.
Exploring one account, we see that the user is female, and since the first week of March 2023, she has made 160 likes and 19 new follows. The account with the most likes was “Instagram Quotes and Humor.” She endorsed a few brands, and her new followings included music accounts, models, and even a tattoo artist. Perhaps she wants to get a tattoo?
(Pic. 1 & 2) New follows made by the user as illustrated by Snoopreport.
Now, Utilizing Socialprofiler, What Else Can You Learn?
(Pic. 3) Follows by user, categorized by her interests via Socialprofiler.
Socialprofiler can analyze all of her followings, collected and categorized over the entire account history, to determine the user’s interests. Additionally, Socialprofiler utilizes a proprietary statistical model to compare these interests to the median user of that social network.
(Pic. 4) “Fashion” share of accounts compared to all other followings, as measured by Socialprofiler.
In this case, the account owner’s interests are more than four times (4.4x) more skewed toward Fashion than the average Instagram user. As indicated by the accounts that comprise this share of interests, she follows a large number of models and cosmetics accounts.
(Pic. 5) Part of the Fashion accounts that the user follows in the Socialprofiler interface.
Looking further, her musical preferences are much lower than average—about 70% below the mean Instagram user’s interest in music.
To recap: Socialprofiler is the more powerful, complex, and significantly advanced next-generation successor to Snoopreport. Its key difference and value lies in highlighting interests through ML algorithms. This approach allows you to review and access data that is not obvious to the average Instagram user.
Final Conclusions About Any Researched Individual
Socialprofiler provides the analytic tools and interface you need to discover something new about the person you want to know more about. From that point, the rest is up to you.