IBM in Artificial Intelligence (AI)

IBM AI marketing

IBM AI Marketing

It could seem challenging to deliver tailored ad interactions without identifying information. New AI technologies, however, are revolutionising the marketing sector, shifting away from audience tagging and tracking strategies and toward audience behaviour prediction without the use of cookies or private data.

These results are achieved by utilising technology accessible to an open ecosystem and science-based realities about human behaviour. Brands and marketers may use the best timing and creative components to communicate their stories at scale and engage their audiences. These tools allow brands and marketers to break out of walled gardens and lay down the law.

With IBM Watson Advertising, companies like CVS, Mastercard, Audi, and L.L. Bean is already working to future-proof business plans and make more educated and effective decisions.


What is artificial intelligence?

In essence, artificial intelligence (AI) is the simulation of human intelligence in devices that have been programmed to think and behave like people. Although “artificial intelligence” is a term that is frequently used, “augmented intelligence” might be a better description of AI. In contrast to artificial intelligence, augmented intelligence uses technology to enhance, complement, and support human cognitive functions (rather than replace humans).


What role has AI played in marketing so far?

Marketing and its surroundings are changing as a result of AI. To create better campaigns with a more significant impact, marketers want to make the most of the vast amounts of data.

AI is playing a more significant part in marketing. It was impossible to evaluate the success of marketing and decide where to place money before the advent of AI.

The advertising business as a whole, however, is not the only one affected. Planning, analytics, and creativity are all impacted by AI. Thus, cognitive advertising enabled by AI has the potential to alter a company’s marketing and advertising strategy completely. Combining AI, machine learning, and big data may help advertisers make wiser financial decisions.


How is IBM using AI for marketing?

AI systems like Watson and Albert have been explicitly used for this. Artificial intelligence (AI) in marketing and advertising can help marketers manage enormous amounts of data, maintain continual and quick contact with customers, and personalise the customer experience. Big data’s development has allowed marketers to understand their customers better and tweak their campaigns for a greater return on investment.

AI may help with the analysis of customer data, the development of consistent branding across all channels, and the production of personalised marketing experiences. Similarly, AI in marketing can significantly affect how clients get information and engage with your offerings. By utilising tools like chatbots and AI to instantly respond to common consumer questions, gather data with minimal effort, and predict consumer behaviour, these technologies can be the next step toward better and more efficient marketing.

Data-driven marketing is rising in acceptance. Big data not only produces insightful information that helps to improve customer experience, but it also aids in the development of AI by amassing knowledge that can be used for various tasks. At the moment, data centres use AI and machine learning to automate and monitor security and infrastructure. There are undoubtedly concerns about how the adoption of GDPR might impact data-driven programmes and AI. In the long run, GDPR might be a blessing for marketers. Because AI is developing so quickly and is supported by big data, marketing will experience a radical change in how they approach customer objectives.


How to leverage AI into marketing?

Artificial intelligence-based campaigns can more effectively target audiences while delivering pertinent messaging. Marketers can use these initiatives to boost ROI and show more individualised adverts. The following examples illustrate how machine learning can be used in marketing:

1. Make use of the proper marketing channels.

Marketing on websites and apps used by your target market can assist make a meaningful connection between your product or service and your clients.

2. Develop more powerful adverts

Prioritise conversational marketing in your marketing strategy. Personalization is crucial in conversational marketing: A customised solution considers user data when generating answers to potential customers’ inquiries about your business. These interactions can strengthen the consumer’s affinity with your brand by forging a personal connection.

3. Pick the right people.

AI can help you get the right audience at the right time, giving you a higher chance to connect with the right clients when they are most prepared to take action. Examples of these targeting strategies include ads that are activated by the weather and ads that are location-based. IBM Watson Advertising Weather Targeting transforms the relationship between temperature, location, and complicated data sets like health needs, product sales, and consumer activity into workable, tested solutions that don’t rely on third-party cookie data. It uses artificial intelligence and the power of weather to predict consumer behaviour.

4. Deliver adverts that are more effective by using context.

Using context signals in contextual advertising helps determine which ads should be shown to your target market. By examining the page’s content and other factors, it can choose where to display messaging and advertisements. Contextual advertising will become increasingly important in a world without cookies. It enables marketers to keep sending relevant communications without using personally identifiable data (PII).


Which brands are using AI for marketing?

Here are two instances of AI used in marketing:

1. Behr uses conversational marketing to engage customers.

Behr engaged IBM Watson Advertising to enhance their consumers’ experience by choosing paint with tailored recommendations. Real-time recommendations were given to customers by Behr using conversational marketing and AI advertising, which increased purchase consideration by 17% and foot traffic by 8.5%.

2. A well-known shoe retailer uses location information to target potential consumers.

A well-known shoe manufacturer seeks to boost foot traffic at their retail locations. They aimed to increase brand exposure by utilising the precise meteorological data provided by IBM and consumer behaviour. Using a variety of media platforms, this campaign mainly relied on location-based marketing to help IBM target the right consumers. The campaign produced 21,000 more shop visits, a 57 per cent drop in ad waste, and a 41.4 percent increase in foot traffic (360 per cent above the benchmark).


Final words

Due to the abundance of data available now, AI is most frequently used to identify trends, make predictions, and offer previously unavailable insights. This is possible because AI can learn from examples instead of being explicitly programmed to follow instructions, unlike traditional computer technology.

These resources are intended to enhance our wisdom and confidence. AI is helping experts in various fields to perform better and develop their skills faster. It will support information gathering, build our knowledge, and enhance the human condition.


Leave a Reply