Social media platforms are so important for the advertising industry. Companies have a huge amount of budget for advertisement and try to select an influencer as the face of their brand for these advertisements. Each brand is related to a specific segment of customers. When the true influencer is followed by this segment, advertising companies contact him/her. The objective of this work is to facilitate the job of the advertising company by matching the brand and the influencer to use the budget of the advertising company appropriately. Accordingly, our work makes an analysis of real/fake account detection, gender, and age range prediction of the influencer’s followers. In this work, it is focused on the real accounts by eliminating the fake ones and the gender, age- range prediction of these real accounts is considered. The detection of fake accounts is transformed into a binary classification problem by observing the features of real and fake accounts. Another binary classification solution is presented for gender detection by checking the pictures of the account owners and their names together. A pre-trained deep learning model for follower age range prediction is provided based on the pictures of these followers. The accuracy of the predictions is evaluated for each of the three situations and the success of our approach is observed for influencer/follower matching.