Название: Impact of Artificial Intelligence on Organizational Transformation
Автор: Группа авторов
Издательство: John Wiley & Sons Limited
Жанр: Программы
isbn: 9781119710271
isbn:
1.4.1 Creation of Customer Profiles/Market Segmentation
The customers’ needs and wants are of immense importance for marketers. Traditional marketing generally used the feedback from consumers’ and also the marketers had to rely on the data provided by the market research firms. With the advent of AI and more people inclined to use the digital platform to search for their requirements, the marketers can now precisely segregate the customers for their product/service requirements. The technological advancement has let the marketers collect the customer’s data such as customer’s name, mobile, email, gender, search pattern, and so on. With this data, marketers can create customer profiles. Therefore, the customers can be segmented and targeted for personalized promotions. It can also help in retaining the customers. Studies indicate that VPSAs (Virtual Personal Shopping Assistants) can predict and optimize the tastes and needs of customers [11]. Lucy: it is created by Equals3 and is named after the granddaughter of IBM’s founder Thomas Watson. It can analyze structured and unstructured data. It helps in segmentation, planning, and interaction with humans in an easy way. SOFMs (self-organizing feature maps) are used for market segmentation, i.e., portioning of a large market into small homogeneous groups of consumers.
Hidden Layer
Figure 1.2 ANN for market segmentation.
The market segmentation for an organization provides translate the opportunity for not only optimally utilizing the resources but also, at the same time, ensuring high profitability. But it remains a big challenge to translate the market’s needs in a precise manner. The ANN provides the solution with several methods developed over a period of time. The SOM (self-organized feature maps), GKA (genetic K-means algorithm), and ART (adaptive resonance theory) are some of the methods used for clustering/segmentation.
An ANN can be constructed for segmenting the market, suppose the parameters for the customer are socio-economic factors, demographic factors, and so on (input layer). The organization aims to segment the market to two segments (output layer). The hidden layer contains the algorithms that result in an outcome. The same can be demonstrated as in Figure 1.2 [39].
1.4.2 Cognizance of Consumers Purchase Behavior/Intention
AI is helpful in comprehending the behavioral aspects of the customers. AI not only helps in understanding customer loyalty but also customer engagement. AI precisely predicts the CLV, i.e., customer lifetime value. This enables the organizations to maintain a better and attractive customer relationship with high valued customers. AI and ML can provide accurate recommendations to organizations on product features and display by pattern analysis of the behaviors of customers purchasing. This helps to improve the customer’s experience. AI is now able to analyze and understand human emotions such as delight, sadness, and anger. Ampsy uses hyper-local geo wall/fence to store publically shared content. This content is analyzed to understand consumer’s intention toward purchase. For example, Alibaba, the world’s largest e-commerce provider company uses AI to predict the pattern of customer purchase. Also, Alibaba is a solution provider to traffic maintenance with the help of AI [24].
1.4.3 Pricing
AI can help increase the sales of an organization by precisely the dynamic pricing. AI recommends the prices for the product and service by analyzing the demand/supply data. An app or website bot which keeps track of the history of sites and cookies can be used for the predictive analysis, thereby enabling the customer to enjoy real-time pricing. For example, during the lean season, the hotel room’s occupancy reduces, and AI can recommend dynamic pricing/real-time competitive pricing. AI helps to provide dynamic pricing by analyzing the historical transactions, competitor’s pricing, customer’s preview/reaction on social platforms, etc. There are several AI platforms, for example, Wise Athena recommends pricing and advertising decisions. Navetti Price Point uses ML to recommend pricing. Perfect Price empowered by AI provides dynamic pricing for auto rentals [5].
1.4.4 Content/Product/Service Recommendations/Search Optimization
According to lexico.com, content marketing is “a type of marketing that involves the creation and sharing of online material (such as videos, blogs, and social media posts) that does not explicitly promote a brand but is intended to stimulate interest in its products or services.” In recent times, the marketers are using AI tools to write content/recommendations to the target audience based on their likes and dislikes. Some of the AI tools are Wordsmith, WordAi, Rocco, etc.; these tools help the marketers by creating the content which is known as Content Curation and Content Automation. The rationale of these tools is to provide organized and customized content to the target audience for better customer engagement. The recommender systems developed with AI can enrich the shopping experience of customers. For example, personalized recommendations suggested by Netflix and Spotify.
1.4.5 Sales Prediction Based on Consumer’s Demographics
Based on the analysis of data, AI can predict and prioritize sales leads. AI can estimate the probability of a purchase by a customer. AI and ML analyze the data from the emails and phone calls that are with the company. This analysis can predict the present and future sales trends. Pointillist’s Behavioral Marketing Platform discovers and analyzes the path and patterns of behavior of the consumer to predict sales. Dominos uses AI tool called Dom Pizza Tracker. According to its website, in-store cameras “use advanced machine learning, artificial intelligence, and sensor technology to identify pizza type, even topping distribution and correct toppings”.
1.4.6 Virtual Assistants/Real-Time Conversations
AIs, known as chatbots like Alexa, Google Assistant, and Siri, are voice recognition technology that can understand and recognize speech or spoken words and execute the command from the internet through an AI drive assistant. For example, Indian Railways use chatbots as ask Deesha, etc. These chatbots simulate the natural language simulation and usually are prepared to answer the FAQs. This can reduce human intervention and reduce response time. Google is incorporating and innovating the use of AI and ML. Google’s division Waymo is working on AI for self-driving technology for automobiles. While Google Duplex has introduced the voice interface with the help of AI to automate phone calls. Amazon has introduced the AI-based voice assistant, Alexa. Also, Amazon is using AI to beforehand predict the products required by the customers. Microsoft is using AI in developing intelligent capabilities in its products and services, such as Cortana, Skype, and Bing [24].
1.4.7 Visual Searching
ML and AI provide the platform to the customers to search for the product with the help of a picture. It is far advanced from text-based searches. Pinterest CEO, Ben Silbermann predicts, “The future of search will be about pictures rather than keywords” [38]. For example, ZALORA online fashion retailer has a catalog of 3,000+ brands on their website. By implementing Search by Image (Visual Searching) and Visually Similar Product Recommendations, Zalora enabled a better search experience for its customers. Facebook uses Deep Text, an AI-based application to interpret the content of the posts, СКАЧАТЬ