The growing popularity of social networks and the emergence of online influencers have changed the way consumers discover and purchase products or services. Online influencers have become opinion leaders who have begun to influence consumers decisions through their posts.This phenomenon has also been recognized by companies and so a new advertising trend called influencer marketing began. However, with the desire and need for larger marketing campaigns, companies encountered problems that affected their efficiency and results. In addition to the problem of campaign manageability, companies worked with influencers whose followers were untrue or unsuitable for product or service advertising because of their nationality. There is also the problem of measuring results, as companies that do not have the right performance indicators fail to measure the impact of campaigns. On the other side of collaboration, we have influencers who want to be fairly paid for their work and who are willing to participate in various campaigns by companies they can identify with. In the master thesis we present a system that we have developed based on model of leading platforms in various markets for online advertising and platforms for online work. We described the architecture of the system and the technology used, which enabled us to develop our system efficiently. The entire system was evaluated and compared with existing approaches. The company spent 4 times less time compared to the manual management of influencer campaigns, and in addition the collaborations were completed faster. We provided both performance measurement and insight into influencer analysis making it easier for the company to select the most appropriate influencers. Campaigns that involved influencers with better analytics score showed better advertising profitability and as well as ROAS value.
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