Emerging marketing trends with ML – By Aditya Abeysinghe
Marketing has improved its reach to target customers over the last decade with the use of newer technologies. While marketing using online websites and mobile applications are the widely used methods, new methods of online marketing are rising that use machine learning models. These emerging marketing methods have enhanced marketing to reach a large volume and variety of market types.
Analyzing target market segments
Machine learning (ML) is used to analyze target markets. The common method of finding target markets is to group people of similar characteristics such as by location, gender and purchasing methods. However, this is often difficult for large businesses that market services or products due to the large variety of customers. ML is used to identify people with similar behavior based on methods such as classification and clustering. ML could also be used with other systems to automatically feed data from models to analyze and make decisions.
Clustering is used in many marketing models today. This method is used not only to identify clusters of people but also to identify clusters of behavior, buying trends, usage of a business platform etc. Classification is used in classifying customers to different groups based on a set of conditions. For example, based on the age, products frequently purchased, and location, a model could classify whether a product should be marketed to a customer. Prediction is used to identify trends of customers and to make predictions on which markets products or services should be marketed.
Enhancing marketing campaigns
Marketing is of different types. Online marketing is commonly used type currently due to low cost, large audience and the ease of managing marketing outputs. Businesses which use online advertising companies for marketing submits their ads and select the audience, the amount of reach and other inputs and the total cost is then paid to reach customers. These advertising websites use ML models to analyze customer view trends. These are then used by sellers who market to view user data analytics, change marketing related content, and market to other customer clusters. This provides sellers to reach customers of different groups with less time and focus on what customers usually consider when viewing ads.
Personalized ads
Many online marketing campaigns use personalized content from users to target marketing related advertisements. Video hosting services are popular at displaying video clips of advertisements before and during a video. Users could skip the advertisement or watch the whole advertisement which offers advantages for both the viewer and the promoter. The content of most advertisements shown are similar to the content to the video the viewer opts to view. Models are used by these services to identify the content the viewer views and then recommend ads based on the content of the video. The same method is used in other social media and data sharing services to filter ads.
Chatbots
Chatbots are widely used to engage with a business’s customer segments. With large customer markets, human marketing agents often cannot serve on time to customers. Chatbots are often used to serve customers reducing the waiting time. Chatbots are beneficial for both customers and providers of services/products as they are often fast, cost effective and accurate in most tasks.
Many ML methods are used in chatbots to engage with customers. Speech analysis, text analysis and complex models that depend on deep learning or artificial neural networks are some common methods which use ML. While most chatbots use such ML methods newer methods of interacting with customers are also adopted by some sellers. Some new methods of virtually interacting with customers depend on 3D models, augmented reality and bots which replace humans. These have changed the usual way customers reach sellers while ensuring high customer outcomes.
Image courtesy: https://altitudemarketing.com/
