Predictive analytic solutions using AI
Abstract : This conceptual paper exclusively focused on how artificial intelligence (AI) serves as a means to identify a target audience. Focusing on the marketing context, a structured discussion of how AI can identify the target customers precisely despite their different behaviors was presented in this paper. The applications of AI in customer targeting and the projected effectiveness throughout the different phases of customer lifecycle were also discussed. Through the historical analysis, behavioral insights of individual customers can be retrieved in a more reliable and efficient way. The review of the literature confirmed the use of technology-driven AI in revolutionizing marketing, where data can be processed at scale via supervised or unsupervised (machine) learning.
? In particular, the existing approaches to topic extraction, modelling and classification rely on statistical bag-of-words techniques such as Latent Dirichlet Allocation(LDA).
? Predictive models examine existing data on the target population, a limitation for actuary risk assessment tools as well, given that actuary risk assessment tools are rarely validated with the population of interest.
? These data islands include data exists as mainly in an unstructured format (such as social media streams, web blogs, news agencies, reviews etc.).
? In particular, AI mostly uses algorithms to learn a process and involves logical reasoning, learning, and problem solving whereas automation and robotics use sensors and manual programming.
? The main purpose of AI is to develop software to imitate a human mind just like how humans handle general problem solving, learning, and decision making in specific ways through an expert system and computer vision.
? AI has made segmentation easier and cheaper, as it is designed like the human brain to recognize and solve problems.
• The equal opportunity by design, proposed based on the inadvertent biased outcomes based on the structure of big data techniques, is considered a guiding principle to avoid discrimination against protected attributes.
• In the developed proposed system framework, each entity is linked with a specific class in the ontology.
• All the top entities annotated using the developed proposed system framework indicate politics entities, although some of the most frequently occurring terms extracted using LDA and SLA are political entities.
? Segmenting customers is very vital to develop effective and efficient marketing programs.
? In particular, AI retrieves, analyses, and presents data in a reliable and efficient way for marketers to acquire a specific marketing plan.
? Machine learning improves the efficiency of marketing functions in every step taken by the customers.
? Through segmentation, companies can gain competitive advantage as they can optimize their resources on the target customers.
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