How Artificial Intelligence AI is Changing Marketing

We are in the age of Artificial Intelligence (AI) technology.

While many people associate AI with robotics, this tech innovation is used in various aspects of life. Its by-product ranges from voice-powered personal assistants like Siri and Alexa to neural networks like Google’s DeepMind. 

It is integrated into different business processes, including research and development (R&D), finance, sales and marketing.

According to Forbes , adopting AI and machine learning (ML) in R&D is the fastest of all enterprise departments. 

Moreover, sales and marketing use AI and machine learning more than any other enterprise department today. 

AI marketing and interaction design are helping shape the design world and designers’ role.

Machine Learning is a branch of AI that  uses algorithms to build models that uncover connections

It is based on the idea that “systems can learn from data, identify patterns and make decisions with minimal human intervention”.

Why do many companies use AI in their marketing and other business processes? What are the examples of AI marketing? AI promotes efficiency by optimising and speeding up complex tasks. 

One of the top brands using marketing artificial intelligence AI is Netflix. To speed up content localisation, robots create layout options for TV show banners in different languages from which designers choose. 

Netflix Artifical Intelligence

In tech manufacturing, Apple manufacturer Foxconn is ramping up its processes by deploying tens of thousands of industrial robots in its production line. 

This speeds up production and eliminates human errors. In marketing, Adobe ’s artificial intelligence AI Sensei can identify patterns to help designers edit and reinvent scenes.

AI improves customer experience and drives conversions. Through marketing AI, websites gather user data to personalise customer experiences. 

It provides valuable information on every visit, including the time of day, the user’s geolocation, the type of device the website is accessed from, and other data points that are useful in delivering a user-relevant experience. 

Personalisation is a powerful driver of conversion rates

Facebook is using AI to understand the images that users upload. This allows the social network platform to describe the image’s content to visually impaired users using screen reader software. It also helps Facebook better target people for paid advertising.

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AI empowers better decision-making. With AI, businesses can avoid the enormous costs of a wrong decision by eliminating human biases and errors. 

One of the products of AI in marketing is a reliable insight into buyer personas . These fictional representations of buyers or customers help businesses make well-informed marketing decisions. 

case study  found that a website moulded on its buyer personas resulted in a 900% increase in visit duration and a 171% increase in marketing-generated revenue. 

AI simulation and modelling techniques clearly depict buyers’ psychology and purchasing behaviour.

“AI does an exceptional job of collecting data about your audience, which allows you to create a precise buyer persona,”

Says Alexei Venneri , CEO and co-founder of Digital Air Strike.

Artificial intelligence AI captures new opportunities. Based on the data gathered, AI systems continuously improve their predictive analytics skills and usefulness. 

Digital assistants like Siri use machine learning to predict and understand human-language questions and requests better. These virtual assistants will be more proficient in human language, boosting their data repository capabilities.

In social media and marketing, AI-enabled platforms use sentiment analysis algorithms to help businesses better manage their marketing operations. It can promote cost-efficiency and guide businesses in developing their future marketing strategy by suggesting the marketing activities that yield the best results.

Artificial intelligence in marketing insights

Big data has become an indispensable marketing asset. 

Large data sets that reveal patterns, trends, and associations help marketers in the marketing industry, designers and the rest of the content marketing team create and execute a solid marketing strategy.

AI in brand management

Brand Management Ai

Starbucks uses predictive analytics to deliver tailored marketing messages to its patrons, such as recommended drinks when they visit a local store. 

Artificial intelligence is relevant in brand management , as it can be used for social listening, content marketing recommendation, chatbots, machine learning, ad targeting, and predictive analytics.

Social media listening

About 45% of the global population of nearly 3.5 billion people actively use social media daily. 

Social networks are a massive goldmine for insights, but manual monitoring of what people are talking about on social media is not the question. This is where artificial intelligence and machine learning come in. 

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AI monitoring tools such as  Crimson Hexagon  and  Digital Air Strike  can tell businesses how people perceive their brands. They offer information on thought influencers, customer sentiment, trending digital marketing topics, public customer information and specific brand mentions.

Digital asset management (DAM)

DAM is the process of organising, storing and retrieving rich media and managing digital rights and permissions. Rich media assets include images, videos, podcasts, and other multimedia content. 

AI-powered DAM automates asset categorisation, indexing and meta-data tagging. This speeds up the search and use of digital marketing assets and their re-use and repurposing for cost-efficient delivery of brand campaigns.

Search engine optimisation (SEO)

Mobile Website Seo Google

SEO is one of the foundations of digital marketing

It involves a set of techniques to boost organic traffic to a website by ranking high on search engine results pages (SERPs). 

Being visible on the first page of a Google SERP, though, is not just about incorporating popular keywords in content marketing

Google has released a deep understanding of the intent of searchers’ queries to match and provide relevant results. This is also referred to as search intent. Search intent is the “why” behind a search query .

A piece of content marketing with the right search intent ranks on SERPs, ultimately increasing traffic to a website or web page.

Google uses RankBrain, its first machine learning algorithm update, to carefully sort search results based on search intent. RankBrain uses machine learning to discern a query’s real intent and deliver more relevant results.

Competitive benchmarking

Not all businesses have the resources to monitor their competitors for competitive marketing benchmarks. AI simplifies the otherwise overwhelming task of tracking competitors via competitive analysis tools. 

AI-enabled program  Crayon  tracks competitors’ digital footprint through various channels such as websites, social networks and mobile apps. It allows businesses to scale their competitive intelligence ai program by getting ten times the data in 10 times less.

Customer support solutions

Chatbots Plugins 2019

Businesses are saving on human resources and financial resources by incorporating AI into their customer support systems. 

Digital Genius  and ChattyPeople automate answers to customer queries and direct concerns to appropriate marketing departments. 

The customer support agents are spared repetitive tasks and can focus on high-level and complex issues. Customers enjoy quicker responses and resolutions with machine learning support solutions, while businesses experience operational savings.

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Artificial Intelligence in interaction design

Interaction design is the design of the interaction between users and products. Its main goal is to develop products that enable users to achieve their objectives in the best possible way. 

Interaction design involves elements such as aesthetics, motion, sound and space. Is interaction design similar to UX design? The quick answer is “No”. 

While a big part of UX design includes interaction between a user and a product, it also involves user research, buyer personas, and marketing usability testing. However, whether it is interaction design or UX design, AI insights can make tasks easier and results better. 

Businesses now use artificial intelligence in some of the following ways:

  • recommending different content to different users, such in the case of Netflix’s personalised TV show and film suggestions;
  • understanding different languages and speech styles;
  • recognising an entire class of entities; and
  • displaying dynamic content more efficiently

More designers are exploring and applying marketing AI to create intuitive user experiences . They are working with data scientists to develop data sets and models focused on the user. 

These models required to solve user problems are trained, opening opportunities for human-centric solutions.

What are we looking forward to in artificial intelligence?

Benefits Of Ai Artificial Intelligence For Marketing

In 2020 and beyond, businesses will be investing more in research development and deployment in marketing, while the debate on the vast social implications of artificial intelligence will rage on. 

Bernard Marr,  writing for Forbes , predicts more significant reliance on automation, freeing the workforce from time-consuming yet essential administrative work. 

He adds that businesses will be rolling out machine learning solutions that offer personalised customer experiences and open up more human and AI cooperation opportunities. 

Custom processors designed to carry out real-time analytics on the fly will be widely used, despite slow or non-existent internet connections. The new year also promises more AI-generated music, poetry, films and games. 

In January 2020, Netflix released a Martin Scorsese film, “The Irishman”, which used AI to de-age its actors. 

Artificial intelligence will also play an increasingly important role in cybersecurity. AI is currently used to identify patterns of digital activity likely linked to nefarious activities, particularly on social media.

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Finally, there will be more significant interaction between humans and artificial intelligence in digital marketing. 

“Given the ongoing investment and maturation of the technology powering machine learning bots and portals, 2020 could be the first time many of us interact with a robot without even realising it.”

Top 10 Books on Artificial Intelligence & Marketing

Sale Bestseller No. 1
Marketing Artificial Intelligence: AI, Marketing, and the Future of Business
  • Hardcover Book
  • Roetzer, Paul (Author)
  • English (Publication Language)
  • 256 Pages – 06/28/2022 (Publication Date) – Matt Holt (Publisher)
Bestseller No. 2
The AI Marketing Canvas: A Five-Stage Road Map to Implementing Artificial Intelligence in Marketing
  • Hardcover Book
  • Venkatesan, Raj (Author)
  • English (Publication Language)
  • 384 Pages – 05/18/2021 (Publication Date) – Stanford Business Books (Publisher)
Sale Bestseller No. 3
Introduction to Algorithmic Marketing: Artificial Intelligence for Marketing Operations
  • Katsov, Ilya (Author)
  • English (Publication Language)
  • 508 Pages – 12/01/2017 (Publication Date) – Ilya Katsov (Publisher)
Sale Bestseller No. 4
Artificial Intelligence for Marketing: Practical Applications (Wiley and SAS Business Series)
  • Hardcover Book
  • Sterne, Jim (Author)
  • English (Publication Language)
  • 368 Pages – 08/14/2017 (Publication Date) – Wiley (Publisher)
Bestseller No. 5
Artificial Intelligence Marketing and Predicting Consumer Choice: An Overview of Tools and Techniques
  • Kogan Page
  • Struhl, Dr Steven (Author)
  • English (Publication Language)
  • 272 Pages – 04/25/2017 (Publication Date) – Kogan Page (Publisher)
Bestseller No. 6
Using Artificial Intelligence in Marketing: How to Harness AI and Maintain the Competitive Edge
  • Amazon Kindle Edition
  • King, Katie (Author)
  • English (Publication Language)
  • 224 Pages – 02/03/2019 (Publication Date) – Kogan Page (Publisher)
Bestseller No. 7
Bestseller No. 8
Data-Driven Marketing with Artificial Intelligence: Harness the Power of Predictive Marketing and Machine Learning
  • Unemyr, Magnus (Author)
  • English (Publication Language)
  • 240 Pages – 06/06/2018 (Publication Date) – Independently published (Publisher)
Bestseller No. 9
The Rise of the Cobot: Grow Your Business Exponentially with Collaborative Artificial Intelligence
  • Amazon Kindle Edition
  • Rauscher, John (Author)
  • English (Publication Language)
  • 175 Pages – 05/24/2020 (Publication Date) – IT-Startup (Publisher)
Bestseller No. 10
Artificial Intelligence for Business (SpringerBriefs in Business)
  • Akerkar, Rajendra (Author)
  • English (Publication Language)
  • 92 Pages – 08/20/2018 (Publication Date) – Springer (Publisher)

AI Marketing Quotes

Artificial Intelligence Quote

“Artificial intelligence and machine learning, a dominant discipline within AI, is an amazing tool. In and of itself, it’s not good or bad. It’s not a magic solution. It isn’t the core of the problems in the world.” — Vivienne Ming, Executive Chair & Co-Founder, Socos Labs

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“Our business discusses emerging technologies and how they impact society. We’ve never seen a technology move as fast as AI has to impact society and technology. This is by far the fastest-moving technology that we’ve ever tracked in terms of its impact, and we’re just getting started.” — Paul Daugherty, Chief Technology and Innovation Officer, Accenture

“AI is a complex field, and I am the first to say that computer scientists have not progressed as far as many believe. For instance, we currently have no credible research path to any kind of intelligent AI algorithm, and there are no robots that are truly autonomous or able to make their own decisions — so don’t worry about walking terminators.” — Richard Socher, Chief Scientist, Salesforce

“There’s no one thing that defines AI. It’s more like a tapestry of modern intelligent technologies knit together in a strategic fashion that can then uplift and create an automated knowledge base — where you can extrapolate findings from there.” — John Frémont, Founder and Chief Strategy Officer, Hypergiant

“The playing field is poised to become a lot more competitive, and businesses that don’t deploy AI and data to help them innovate in everything they do will be at a disadvantage.” — Paul Daugherty, Chief Technology and Innovation Officer, Accenture

“Harnessing machine learning can be transformational, but enterprises need leadership from the top for it to be successful. This means understanding that when machine learning changes one part of the business — the product mix, for example — other parts must also change. This can include everything from marketing and production to supply chain, and even hiring and incentive systems.” — Erik Brynjolfsson, Director of the MIT Initiative on the Digital Economy

“The gradual platform station of AI is exciting to me. The efforts by Google, Amazon, and Salesforce are bringing AI down to the level of not needing to be an expert to use it. … I think the day that any good software engineer can program AI will be the day it proliferates.” — Kai-Fu Lee, Chairman and Chief Executive Officer, Sinovation Ventures

“I think what makes AI different from other technologies is that it will bring humans and machines closer together. AI is sometimes incorrectly framed as machines replacing humans. It’s not about machines replacing humans, but machines augmenting humans. Humans and machines have different relative strengths and weaknesses, and it’s about the combination of these two that will allow human intents and business process to scale 10x, 100x, and beyond that in the coming years.” — Robin Bordoli, Chief Executive Officer, Figure Eight.

Last update on 2022-09-20 / Affiliate links / Images from Amazon Product Advertising API

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  • Interesting article! For marketers, the coming changes are important because your business will benefit from being aware of AI-based tools and techniques before your competitors are. If you work on the agency side, you want to help your clients lead with AI. Although marketers don’t need to understand AI in great detail, they do need to know enough about AI to spot opportunities.

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