Taiwan-based AI transformation solutions provider iKala is expanding across Southeast Asia with its influencer marketing platform KOL Radar, aiming to capitalize on the region’s booming creator economy. From iKala’s observation,fragmented influencer ecosystems and limited  analytical capabilities within the influencer marketing industry pose hurdles for brand owners.

Founded in 2011, iKala offers AI-powered solutions helping brands connect with influencers and manage campaigns. A core product is SaaS platform KOL Radar housing over 2 million verified profiles. Co-founder and CEO Sega Cheng explains their expansion is driven by rising social commerce, saying “brands and even e-commerce platforms are using influencer marketing to sell to their clients.”

As Cheng explains, “in 2018, there was a paradigm shift in digital marketing. Everyone started to ask the question – how can we save more cost in doing digital marketing and how can we use AI to facilitate precision marketing to really target the audience.” KOL Radar applies AI search and analytics to facilitate influencer discovery and partnerships.

“Southeast Asia is one of the most active regions for the creator economy,” Sega Cheng explains. “Brands and even e-commerce platforms are using influencer marketing to sell to their clients and engage their audience.”

To capitalize on this opportunity, iKala chose to focus expansion of their influencer platform, KOL Radar, across Southeast Asian markets. However, limited competitor databases and analytics posed challenges.

“While there are not so many counterparts that compete with our offering iKala’s KOL Radar in Southeast Asia, the database and number of influencers in the industry is simply not enough across different platforms,” Cheng explained. “We have over 2 million influencers from Southeast Asia, North Asia and East Asia. That’s one of the advantages we have compared to competitors.”

This robust database of verified influencers enables precision matching between brands and content creators best positioned to meet campaign goals. Backed by AI-powered analytics on audience demographics and engagement, KOL Radar provides the targeting capability lacking in the region.

Additionally, fragmented creator ecosystems pose obstacles to launching cohesive regional campaigns. As Cheng noted, “everyone is selling on social media” in Southeast Asia. Brands struggle to identify and coordinate qualified influencers across different platforms and country markets.

By consolidating influencer profiles, performance data and search tools under one SaaS solution, iKala Radar simplifies the influencer activation process for brands. Campaign management functionalities further optimize collaboration, analytics, and reporting.

As more consumers shift to social commerce and digital engagement, iKala sees massive growth potential for influencer marketing in Southeast Asia. But first, brands need access to robust influencer databases and campaign analytics. By tackling these creator economy gaps, iKala’s expansion aims to empower brands to maximize this opportunity.

“We are positive and optimistic about Southeast Asia,” Cheng stated, as emerging AI capabilities transform regional digital marketing strategies.

IKala Bets On AI To Capitalize On Southeast Asia’s Creator Economy Boom

Challenges Unique to Southeast Asia

While the booming creator economy presents opportunities, iKala CEO Sega Cheng outlines significant challenges in developing an influencer analytics platform across the diverse Southeast Asian region. He notes Southeast Asia consists of over 10 countries, each with distinct cultures and business landscapes that shape unique influencer ecosystems.

“Every country has its own different culture, business culture and creator landscape,” Cheng stated. “As an analytics and discovery platform, we must adapt our products, localizing and globalizing them for different countries.” This poses difficulties in balancing localization with regional scalability.

Additionally, the scale of iKala’s over 2 million profile database amplifies infrastructure and analytical complexities according to Cheng. “It’s not just about putting information in a database,” he said. “You have to scale infrastructure for analyzing huge influencer data in real time.” By tackling these hurdles, iKala delivers updated performance analytics brands can leverage for targeting. But continually scaling this extensive data presents persisting challenges as the database expands.

Southeast Asia’s linguistic diversity further complicates market expansion. “There are many languages – Mandarin, Japanese, Thai, Vietnamese, Malay – you must ensure brands access information in languages they need,” Cheng explained. Catering to these varied languages while pursuing additional country launches remains an ongoing obstacle.

iKala’s Creator Search Functionality

At its core, iKala positions its influencer platform KOL Radar as “a vertical search engine for discovering influencers.” Like Google provides a portal to access general information, KOL Radar enables targeted searching within a vast database of over 2 million influencer profiles and performance analytics.

As CEO Sega Cheng explained, “You just put in keywords and we give you search results – influencer analytics and listings.” This simplifies the influencer identification and selection process for brands seeking partners. Cheng noted KOL Radar’s mission is “to organize the world’s influencer information and data.”

Behind this searchable front-end, AI powers crucial analytics capabilities. “AI plays a critical role behind the scenes,” said Cheng. “For every analytics feature we have, there is a language model behind it.” For example, KOL Radar leverages natural language processing to generate influencer audience profiles – key insights for campaign targeting.

Additionally, AI helps detect inactive followers to provide an accurate picture of audience engagement. “Brands aren’t just satisfied with follower numbers,” Cheng stated. “They want to know who is active and who is not.” Rather than inflating perceived reach, KOL Radar’s AI-enabled analytics surface the real, high-value audiences that matter most to campaign success.

To simplify influencer selection, iKala developed an algorithm that rates creators based on engagement and relevance – the K-score. Instead of showing inflated follower counts, this metric helps brands discover high-value partners tailored to campaign goals.

As CEO Sega Cheng explained, the K-score calculates “effectiveness and activeness of audience” for each influencer profile. Quantifying engagement metrics alongside reach paints a more accurate picture than vanity metrics alone.

“We don’t just look at the number of followers, but engagement rate for each of their posts and photos on social media,” said Cheng. With these inputs, iKala’s algorithm weighs influencer-audience resonance to benchmark performance.

As Cheng described, “We use keyword matching and language understanding of an influencer’s posts to calculate a [K-score.]” Natural language processing helps surface profiles discussing related topics.

Combining this contextual search functionality with performance-based rankings enables brands to instantly identify “recommended influencers with particular keywords” per Cheng. Rather than sifting through individual profiles, KOL Radar’s AI-powered discovery platform surfaces customized shortlists for campaign needs.

What’s next for iKala

The rapid emergence of generative AI in 2022 stands to substantially impact influencer marketing according to Cheng. By enabling more conversational search experiences and explainable recommendations, iKala looks to integrate these capabilities within its KOL Radar platform.

Cheng stated, “We are working on many exciting new features. For example, we have  launched natural language search last year, so brands can find influencers by typing sentences like ‘I want some influencers capable of promoting beauty products in Thailand.'” Instead of keywords, brands can express campaign needs conversationally.

KOL Radar also looks to leverage AI to provide reasoning behind influencer recommendations and rankings. As Cheng explained, “We can use AI to summarize why we give certain search results and showcase particular influencers.” These AI-generated explanations aim to further build trust and transparency between the platform and advertisers.

Additionally, Cheng highlighted the rise of cookieless marketing solutions in a post-identifier landscape as another trend impacting influencer analytics, saying “We are also working on cookieless solutions for our advertisers.” As consumer data privacy standards evolve, iKala is developing innovations to help brands precisely target audiences in an privacy-centric ecosystem.