How to Use Artificial Intelligence in Marketing

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Parag Utekar
Student (MBA), India

How to Use Artificial Intelligence in Marketing

Artificial Intelligence (AI) is a disruptive technology that will impact a diverse range of industries. Even though the majority of the marketing managers are conscious of the ground-breaking potential of AI, many of them are unaware of its benefits or of how they can adopt AI to upgrade their marketing. To put things in perspective, only few marketers actually use the advanced capabilities which AI offers like personalizing campaigns, collaborative filtering and predictive models.

However in today's times, because of the availability of data and modern computing power, AI can garner insights that go beyond those of traditional statistical methods. Multiple customer-focused applications across a variety of fields are now possible.

ARTIFICIAL INTELLIGENCE AND MACHINE LEARNING
Classically, AI is a technology that enables a machine to learn and perform human-like functions. Machine Learning (ML) software can detect patterns and make predictions and recommend solutions by processing the data rather than by inserting explicit programming instructions.

Applications of AI in Marketing
Here is an organizing framework to help modern marketers understand the practical uses of AI for strategic marketing:
  • CURRENT SITUATION ANALYSIS: This step involves a fundamental understanding of the macroeconomic factors that directly affect the organisation, the stakeholders and the marketing. AI methodology, including social listening, can draw conclusions on markets and consumers, including customer satisfaction, purchasing patterns and demand analysis. Current applications include; understanding unstructured data, anomaly identification, sentiment analysis etc.
  • UNDERSTANDING CUSTOMERS AND MARKETS: Here, the marketers aim to understand the specific market they wish to operate in and the customers they want to target. AI can mine customer preferences from the web data, social media and mobile activity, which could then be analysed to provide feedback and take immediate actions. Current applications include; Market research using facial expression, eye movements, and audio comments, etc., mapping customer journey, including touchpoints (ads, influencers) etc. Medallia is one such consumer-experience software.
  • STP ANALYSIS: This involves developing and understanding customer Segments and then Targeting them with effective Positioning. AI assists marketers to predict customer intent and further segment them into more refined groups. For example, Harley-Davidson used Albert (developed by Adgorithms) to help automate and simplify marketing planning, which was done by providing past customer data. The data enabled the software to create similar audiences and match potential customers who resemble the current buyer. This software was responsible for 40% of Harley-Davidson's motorbike sales and also led to a nine-fold increase in inbound calls.
  • PLANNING DIRECTION, MARKETING SUPPORT AND OBJECTIVES: This stage involves making long-term goals and develop short-term objectives to support more prominent strategies. AI and chatbots can be integrated into apps or social media for encouraging customer purchase. For example, the Starbucks Barista, which is available on the Facebook messenger, enables you to order coffee via voice command or messages. The use of AI in customer service is projected to grow by 143% from 2019 to 2023.
  • PRODUCT STRATEGY DEVELOPMENT: At this stage, marketers have to make decisions involving the product design, quality, features and customisation. The opportunities for AI include identifying gaps for the development of a new product, production of customised products and also assisting product delivery and logistics.
    For example, Lily AI encourages the customer to 'complete the look' at the checkout, i.e. it suggests a real-time head-to-toe look suggestion enabling the retailers to increase the basket size at checkout. Levi's uses AI to optimise product availability at their stores and improve size availability. Nike uses clustering algorithms to advice which products should be displayed together at the store. And Samsung uses Crimson Hexagon's AI-powered insights platform to understand how customers interact with the products and thus making marketing campaigns that the customers can relate to.
There is a range of opportunities that AI offers in marketing, but there is still a lingering fear that AI will replace human work roles across different professions. But to look at the broader perspective, AI will offer automation that will enable marketers to invest more in creativity rather than the process. Thus, regardless of the speed of AI adoption, future AI-enable marketing techniques will have and require both AI and human intervention.

⇒ What are your ideas and experiences with AI in the field of Marketing?

Source: Campbell et al., (2019) "From data to action: How marketers can leverage AI", Elsevier Inc., 2019, March-April 2020, Vol 63, pp. 227-243

  Chloe Xu
Director, Australia
 

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