Revolutionize Influencer Search Experience with AI: iKala Accelerates the Development of the Largest Cross-Country Influencer Database
KOL Radar Employs AI Technology to Facilitate "Pre-evaluation," "Post-evaluation," and "Prediction" Analysis for Influencer Marketing in Enterprises
May 25th, 2023 —iKala, a leading AI transformation solutions provider from Taiwan, announced that KOL Radar, their AI influencer data marketing platform, will utilize its extensive database of over 1 million cross-country and cross-platform influencer data, along with advanced AI analytics capabilities. This move comes as generative AI technology and the creator economy drive new momentum in the AI influencer marketing market. The platform will now support brand users in "pre-evaluation," "post-evaluation," and "prediction" scenarios, enabling them to adopt AI-driven, performance-based influencer marketing for enhanced customer acquisition efficiency.
Moreover, iKala has also opened free access to the KOL Radar website's influencer search feature for users in Taiwan, eliminating the need for registration. The company plans to introduce more diverse AI search methods in the future, establishing itself as a leading influencer marketing AI search engine in the industry.
According to Influencer Marketing Hub's estimation, the global influencer marketing market is projected to grow to US$21.1 billion (approximately NT$645.4 billion) by 2023, representing a more than tenfold increase in net growth over seven years. In 2023, nearly 90% of businesses express the interest to incorporate AI technology into influencer marketing projects, indicating a rising demand for AI-driven influencer marketing among enterprises and brand owners. To address the pain points of influencer marketing and empower brand owners, KOL Radar utilizes its unique AI technology to assist clients in the pre-testing, post-testing, and prediction processes of influencer marketing, enabling a scientific approach to influencer marketing and helping brand owners drive their marketing strategies with AI technology.
Pre-evaluation: Observing influencer performance indicators to develop precise strategies.
To assist brand owners in quickly formulating influencer collaboration strategies and accurately finding the most suitable influencers based on influencer marketing budgets and project objectives, KOL Radar utilizes machine learning models to create the "Fan Audience Analysis" feature. It accurately analyzes the fan profiles of influencers based on five metrics: follower growth rate, engagement rate, view rate, number of followers, and posting frequency. By providing a rating system, it helps brand owners make influencer marketing decisions in a more scientific and quantifiable way. Additionally, through machine learning technology, KOL Radar proactively detects and analyzes the recent ratio of sponsored content, content performance, and effectiveness of key opinion leaders (KOLs), enabling companies and brand owners to quickly assess opportunities and outcomes of influencer collaborations. KOL Radar also employs AI machine learning's dynamic labeling feature to automatically categorize the database into 27 different types of influencers, allowing brand owners to gain clear insights into the current influencer categories and explore collaboration possibilities with diverse influencers.
Post-evaluation: Quantify the effectiveness of projects and conduct in-depth evaluation.
During the final phase of influencer marketing campaigns, brands have faced difficulties in quantifying the effectiveness of their efforts and spending significant time consolidating project outcomes. KOL Radar addresses these challenges by providing unique project performance insights through AI data analysis, enabling brands to quickly grasp the collaborative outcomes based on data indicators and make precise adjustments to future project strategies.
KOL Radar's Deep Report utilizes AI-powered analysis of influencer comments to automatically assess platform-specific, influencer-specific, and overall sentiment, assisting brands in swiftly evaluating the social network sentiment associated with a particular project. This significantly reduces the time and effort spent by marketers on post-event reports. Additionally, by analyzing the frequency of hashtag usage, engagement rates, and view counts in comment sections, KOL Radar identifies popular trending topics and generates word cloud analysis of hashtag usage, uncovering potential content opportunities.
Prediction: Estimating the Optimal Combination of KOLs for Enhanced Precision Marketing
To assist brand owners in gaining insights into project collaborations and estimating the future effectiveness of KOL marketing, KOL Radar offers predictive capabilities to reduce the trial and error costs associated with finding suitable KOLs. Additionally, it helps identify potential collaboration opportunities with other KOLs. Through analysis of KOL Radar's Deep Reports, recommendations for similar KOLs and growing KOLs, brand owners can anticipate the optimal combination of KOLs. Moreover, by analyzing and determining content creation trends based on hot topics within social media, KOL Radar assists in predicting and enhancing the output effectiveness of creative content.
Furthermore, KOL Radar introduced two significant features in March this year. The first is the "One-Stop Campaign", which lowers the barriers of collaboration between brand owners and KOLs by facilitating bilateral matchmaking, reducing the cost of negotiation for project collaborations. Combined with the Deep Reports, brand owners can instantly grasp the effectiveness of KOLs' posts and make timely adjustments and optimizations. Additionally, KOL Radar introduced an AI-powered search function called "AI Search," which combines its search engine with generative AI technology. This feature offers a new experience in natural language-based KOL searches, allowing brand users to obtain recommendations for multiple KOLs that meet their requirements with just a single sentence, eliminating the need for specific keyword settings.
iKala Co-founder and CEO, Sega Cheng, pointed out, "The rise of AI opportunities presents both new challenges and opportunities for the overall digital industry. I am optimistic that generative AI technology will drive the development of specialized search engines in various vertical industries and diversify the search methods. iKala is committed to creating the industry's leading influencer marketing search engine with the largest cross-border influencer database. We aim to transform the influencer search experience with AI and empower it with pre-evaluation, post-evaluation, and prediction capabilities to accelerate the effectiveness of influencer marketing and collaborations for businesses and brands."
Finn Yeh, Product Director of iKala KOL Radar, stated, "KOL Radar provides the most real-time and comprehensive cross-border influencer database. We understand the pain points of brand owners. We have successfully assisted a well-known Japanese cosmetics brand in achieving a three-fold higher engagement rate in KOL marketing compared to the industry's platform average during the same period. We firmly believe that with the added value of AI technology, coupled with the 'One-Stop Campaign' feature, we can minimize friction in brand and influencer collaborations and effectively enhance marketing performance and customer engagement."
