Hello Lucy. Please solve my marketing problems
IBM’s Watson’s Lucy can be used to determine market segments, develop products, conduct competitive or market analyses, handle media planning, provide the numeric marketing data needs in writing a marketing plan, and assist with salient information in developing a marketing strategy. DR MYLES WAKEHAM, CARL WAKEHAM and MARIA HAMMAN give some idea of the power of AI in marketing.
Artificial intelligence (AI) refers to the creation of human-like intelligence that can process, learn, reason, plan, and discern natural language.
AI comes in three forms, namely, narrow AI, with which we are involved with on a daily basis and which is designed to perform specific tasks within an area (technology with intelligence in a particular domain) and general AI which is not area-specific and can learn and perform tasks anywhere and finally strong AI, which is an artificial super intelligence. Thus far, we have only managed to master narrow AI.
AI uses, among other technologies, natural language processing, speech recognition, robotics, machine learning (ML) and computer vision. An example of AI that you may already be engaging with is SIRI, presently available on Apple iPhones, who reacts to your voice on command. SIRI has the ability to ‘learn’ from you as you request information in the future.
According to Carolyn Frantz (Microsoft’s Corporate Secretary), AI will have a major influence on business and will equally have a dramatic impact on jobs. Frantz asserts that in the future, AI will make as much as 75 million jobs disappear in the USA but will be replaced by 133 million more challenging and less repetitive roles.
Besides its impact on HR, AI will also influence operations and production, inbound and outbound logistics, supply chain management (SCM), finance and as importantly, marketing.
One of the ways that AI is influencing marketing is with AI marketing assistants such as IBM Watson’s Lucy, a cognitive problem solver (in contrast with emotional), which acquires knowledge through a determined learning process.
Lucy can be used to determine market segments, develop products, conduct competitive or market analyses, media planning, providing the numeric marketing data needs in writing a marketing plan, assist with salient information in developing a marketing strategy, creating structured marketing content through a process called Natural Language Generation and so on.
According to IBM, Lucy is a powerful tool marketers “…can use for conducting online research, segmentation and planning and it is so powerful that it can do more in a minute than an entire team of marketers can achieve in months”.
Needless to say, the advantage of a marketing assistant like Lucy is that it can digest and analyse literally all the data a company possesses and once it has absorbed all of this data, marketing personnel, according to Watson, can ask the following questions, when attempting to solve marketing problems:
- What are the personality characteristics and attributes of the organisation’s target audience based on a set of predetermined variables?
- Which segments, towns or regions should be targeted first in order to maximise sales?
- What content mix should be created for the target audience to maximise the attainment of the marketing and promotional mix objectives?
- What is the current competitor activity and how can the organisation use such data to make better marketing decisions specifically within environments like retail channels?
The above are questions that companies need to answer in order to formulate marketing strategies that achieve the marketing goals as set by the enterprise. Lucy and similar AI marketing assistants can, therefore:
- Create viable segments of a company’s target audience so that it can develop highly personalised content that is designed to appeal to such an audience (target market)
- Assist in the planning of marketing strategies by interrogating the needs and wants of the target market and how best to maximise sales and profits because of such market intelligence through programmatic targeting as an example
- Implement and control the different strategies so that the firm’s objectives may be realised based on data feedback loops put into place
- Create promotion content that is customer-specific so that the organisation’s strategy and promotional mix can be directed specifically at satiating customer and organisational needs and wants.
According to MIT’s Brian Bergstein’s article, which was published in the MIT Technology Review in February 2020, AI as it currently stands:
- Cannot question decisions so it is basically led by data which could be incorrect
- Cannot explain the decisions it has made to qualify or quantify the decision
- Cannot understand causation (why things happen following on from an occurrence)
- Cannot measure psychographic typologies
- Cannot reason qualitatively, e.g. how people feel about a brand; and as importantly
- Cannot understand the concept of, for example, customer loyalty outside of quantitatively ‘crunching’ numbers
So, from the above points, AI must not be seen as a cure-all for an organisation’s marketing woes but rather a tool to assist the firm in achieving better results in the marketplace.
Application of AI in marketing
AI, and systems like Lucy (there are numerous others), will undoubtedly have a huge impact on content marketing as they become more affordable and more popular. They will help companies better understand their audience, and the data garnered by means of AI will allow marketers to position brands more effectively in the minds of current and future customers and put together more effective strategies so that organisational objectives may be attained.
AI will also help them understand what outcomes they can expect by pinpointing accurate customer expectation so that customer-specific targeting can be better planned based upon more reliable forecasting and market intelligence. According to the publication Smart Insights: The Financial Brand (March, 2018), the applications of AI in marketing can be found in Figure 1 below:
Figure 1: Application of AI in marketing
At present Cookies and other engagement tools follow customers as they interact with websites, products, and applications by providing various data sets that will form a personal ‘ecosystem’ that is programmatically targeted by tools and systems. Here relevance is the key to successful engagement by the consumer with variable pricing bases upon the propensity of interest and purchase.
AI can have an explosive impact on marketing throughout the organisation’s relationship with its customers… from demand generation through to the instilling of customer loyalty. It can therefore be used to cement strong and mutually rewarding relationships with customers and help to maximise the lifetime value of the customer.
The IMM Graduate School’s Dr Myles Wakeham is a motivated and well-connected academic and businessman who was instrumental in introducing and adopting CIPS at CPUT as a series of qualifications. He has consulted to a variety of institutions and organisations, such as the South African National Treasury, National, provincial and local government. He is also involved in international research, and with an academic consortium has researched the impact of IT on university education.
Carl Wakeham is a semi-retired ex marketing executive specialising business and brand strategy based on the Wild Coast. He is an ex director and shareholder of a marketing company based in Johannesburg. His special interests are brand development and positioning and has had the opportunity to work throughout Africa with businesses within the Naspers Group and many others He has had the opportunity to gain experience in the Far East and selected countries in Europe where he has lived. He has a BA/MBA and studied other business related fields whilst living in the Philippines and Ireland. He provides a consultancy service to various clients based on project work specifically in the communications /digital fields. He is actively involved in a digital media company where he is a shareholder.
BIO: The IMM Graduate School’s Maria Hamman has over 17 years of combined market research and CX consulting experience. She has worked on both market research projects and customer experience improvement projects with a broad knowledge of research due to working with multiple research methodologies both qualitative and quantitative.
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