Getting audience attention has become increasingly difficult for brands in today’s online world due to the insurmountable amount of noise on the internet. This puts brands in a position to come up with innovative digital marketing strategies.
On the other hand, consumer expectations are also gradually changing. In the process of finding different approaches to gain audience attention, brands recognized the power of influencers.
As audiences’ craze for social media keeps flying high, it has evolved to be an integral part of today’s businesses. Many brands spend a substantial sum of time and resources in this hyper-connected world to carry out successful influencer marketing campaigns.
Especially despite the elusive nature of ROI measurement in this space, brands are pouring significant budgets into collaborating with powerful influencers out of fear of missing out on new opportunities.
Brands are just enthralled by the enticement of vanity metrics (likes, comments, and shares), which provide only a hazy picture of the true influence of their influencer campaigns.
Although it has the power to reach vast audiences, the inability to precisely gauge the ROI of influencer campaigns, on the other hand, is indeed a significant challenge for them.
Establishing specific campaign goals as well as determining measurable key performance indicators (KPIs) that are aligned with broader business objectives is crucial for successful campaigns. Thus, to properly address the issue of ROI measurement in influencer marketing, brands and influencers must collaborate to create a structure that goes beyond vanity metrics.
AI-powered performance marketing could be an innovative solution to the problem of measuring ROI in influencer marketing campaigns. Here are a few ways it can help marketers:
Data-Driven Influencer Selection: This data-driven approach guarantees that brands collaborate with influencers who are more likely to produce a positive ROI.
Attribution Modelling: AI algorithms only allocate credit to influencers on the basis of their influence throughout the customer journey by analysing multiple touchpoints and customer interactions.
Monitoring Performance: By utilising AI algorithms, brands obtain instantaneous insight into the efficacy of their influencer partnerships and can make data-driven changes on an ongoing basis.
Fraud Detection and Brand Safety: Machine learning algorithms analyse patterns and data points to detect suspicious activities and can assist brands in filtering out deceptive influencers and protecting their investments.
Comprehensive Analytics and Reporting: AI algorithms help brands gain a holistic view of their ROI by combining data from multiple sources. Furthermore, it can help brands evaluate performance, optimise strategies, and justify marketing investments by providing clear and measurable ROI metrics.
As influencer marketing grows, accurate ROI measurement becomes increasingly important. Leveraging the endless possibilities of AI-powered performance marketing in influencer campaigns can be a key to effectively managing it.