Artificial intelligence (AI) is one of the most popular topics in technology and has become an integral part of many industries including marketing and advertising. Artificial intelligence is basically intelligence exhibited by machines and the term “artificial intelligence” is applied when a machine mimics “cognitive” functions that humans associate with other human minds such as “learning” and “problem solving” (known as Machine Learning) (see the Wikipedia definition).
The artificial intelligence industry is estimated to reach USD 5.05 billion by 2020, with average annual growth rate of 53.65% between 2015 and 2020. In the context advertising and marketing; artificial intelligence means more personalized and interactive consumer experience. And the reason for the hyper growth is the increased usage of machine learning technology where computers learn from data by themselves.
Here are some examples of the AI in advertising and marketing industry:
- Ad targeting: Machine learning already has a big impact in advertising industry, one example being programmatic advertising. Self-learning algorithms used in running online ad campaigns help marketers to identify the most valuable customers, show personalized ads to each customer and encourage them to take the desired action. When it comes to targeting of programmatic ads, machine learning helps to increase the likelihood a user will click or take the desired action. This might be optimizing product mix, ad model or demographics to get the highest ROI possible from an ad campaign.
- Product recommendations: The automated recommendations are based on purchase habits of different customers and show product recommendations to the customers with the highest possibility to buy that specific product.
- Search engine: Artificial intelligence or machine learning is used to have better search results in terms of quality and relevance.
- Product pricing: With thousands of products and many factors that impact sales, an estimate of the price to sales ratio or price elasticity is difficult. Dynamic price optimization using machine learning can correlate pricing trends with sales trends by using an algorithm. It is also used in category management and inventory level optimization.
- Predictive customer service: Knowing how a customer might get in touch and for what reason is obviously a valuable information. With the help of AI, the companies can guess how many users will contact for what products through which channel; which results in improved customer satisfaction.
- Customer segmentation: Combining first- and third-party data into an algorithm, then using the results in a CRM is an effective way to connect with the customers and increase the sales .
- Bots and messengers: Chatbots are automated services powered by machine learning, that allow customers to interact with brands via messaging. A person can have one-to-one conversation with one person but AI can talk to 500 people at the same time. This means better and faster customer service for brands.