IKASI News

Read how telecom companies can leverage causal AI for unprecedented decision-making that unlocks new profits and improved PnL.

The integration of causal AI with gen AI and large language models (LLMs) will reshape decision making, moving from correlation to causation. Mridula sat down with the editors at Customerland. Read her insights on AI trends in 2025 now.

Read insights on how causal AI will impact business grow and revenue across industries. Mridula shares five must read predictions for 2025.

Read insights on how causal AI will enable customer loyalty teams to optimize pricing and offers by identifying specific triggers that impact each customer decision.

Causal AI extends beyond the limitations of traditional AI to understand, predict, and shape customer behavior at the individual level. Learn how Causal AI can be applied to loyalty programs in various ways, including assigning specific rewards to each customer, real-time analysis of marketing campaigns, and optimizing individual customer journeys to make real impact on PnL.

IKASI CRO, Mridula, outlines the benefits and provides five proven steps to ensure a successful causal AI implementation.

Learn how Causal AI can make a significant impact on player engagement and profits. IKASI CRO, Mridula, is featured as a guest columnist in Gambling Insider's week 28 newsletter.

AI is revolutionizing how companies conduct marketing experiments to extract more revenue opportunities and improve investment strategies. Businesses are challenged with determining how much they need to invest for each individual customer.

Traditional approaches — including RFPs — aren’t likely to help you find the best AI solution to solve your problem. We offer three innovative approaches that may deliver better results.

Businesses are navigating serious challenges caused by inflation, supply chain disruptions, retaining top talent, and access to capital. These challenges heighten the role of AI in helping businesses optimize marketing operations and prepare for economic uncertainties. Leveraging AI can result in significant efficiency and productivity gains to mitigate the impact of recessions.

The post outlines the choice companies have between in-house AI development and external solutions, highlighting pros and cons such as customization and time to market. It showcases examples where businesses have effectively used either approach or a combination to address challenges, emphasizing the need to adapt AI strategies to stay ahead continuously.

Read how Enterprises can leverage AI for hyper-personalization by better understand individual preferences and incentives in real time so they can engage with customers in a highly personal way, help motivate them earlier in the funnel, and help strengthen both loyalty and profits.

The rise and challenges of direct-to-consumer (DTC) retail emphasize how the pandemic and rising advertising costs have impacted the model. Integrating artificial intelligence (AI) provides new opportunities for DTC brands to optimize marketing, understand consumer behavior, and deliver personalized experiences, ensuring their continued relevance and competitiveness in the market.

AI revolutionizes decision-making, predicting real-time trends and offering actionable recommendations, especially in hyper-personalization. Success hinges on data quality, infrastructure, and navigating the buy vs. build debate. Ethical AI implementation is crucial, aligning with business goals for innovation and industry impact.

Read insights on the powers of AI-driven experimentation and its capabilities from a data science expert. Imagine conducting hundreds of simultaneous experiments to identify microchanges that can offer meaningful insights. Combined with real-time analysis capabilities, this new method opens up a world of new use cases that can propel significant business growth.

Discover how AI-driven, dynamic pricing can revolutionize holiday shopping, transforming how consumers shop online. Explore the secrets behind dynamic pricing and how businesses adapt their strategies, maximizing profits while offering tailored experiences to keep customers engaged.

Every level of AI—from a helpful assistant to full autonomy—has its place in various scenarios. What truly matters is the thoughtfulness behind its application and aligning the level of risks involved. Dive into IKASI CEO, Anthony Chong’s insights published in Predictive AI and remember: trust and guidance are the secret sauce to unlocking AI’s full potential while minimizing risks along the way.

Reinforcement Learning (RL) in machine learning rewards desirable behaviors within specific environments, fostering iterative, continuous learning and decision-making. RL’s adaptability and iterative approach make it invaluable. Understanding how RL assesses and prioritizes actions offer insights into its diverse applications across sectors, aiding businesses in achieving their specific goals. Read how RL can be leveraged in real-world scenarios such as robotics, self-driving cars, retail, and more.

Personalization matters, and businesses thrive when customers feel special. AI revolutionizes this by understanding individual preferences on a mass scale. With AI, businesses can tailor experiences by understanding individual behaviors beyond demographics. It outperforms traditional market segmentation, pinpointing specific customer preferences and predicting behaviors. It crafts personalized offers and experiences autonomously, continuously learning and evolving without explicit programming. Read how the use of AI in casino marketing is helping to uplevel customer satisfaaction, increase spending, and enhance player lifetime value.

Business Intelligence (BI) tools, once hailed for their insights, are proving insufficient in understanding individual customer complexities. While BI offered generalized insights based on aggregated data, it struggled to capture the diverse behaviors of individual customers, often leading to misleading conclusions. We’ve entered an era where modern solutions revolutionize customer analysis. Read how this shift from group insights to personalized experiences marks a significant leap in customer understanding, guiding businesses towards a more responsive and tailored approach for each unique individual.