We are at 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 such as Siri and Alexa to neural networks such as Google’s DeepMind.
It is integrated into different business processes, including research and development (R&D), finance, sales and marketing.
According to Forbes, the adoption of AI and machine learning (ML) in R&D is the fastest of all enterprise departments in 2019.
Moreover, sales and marketing use AI and machine learning more than any other department in enterprises today.
AI marketing and interaction design are helping shape the world of design and the role of designers.
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 does an increasing number of 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.
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 the 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 geolocation of the user, 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 content of the image to visually impaired users using screen reader software. It also helps Facebook better target people for paid advertising.
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.
A 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 paint a clear picture of 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. AI systems are continuously improving their predictive analytics skills and usefulness based on the data gathered.
Digital assistants, like Siri, are using machine learning to predict better and understand human-language questions and requests. These virtual assistants will be more proficient in human language, boosting its data repository capabilities.
In social media and marketing, AI-enabled platforms use sentiment analysis algorithms to help businesses better manage their marketing operations. By suggesting the marketing activities that yielded the best results, it can promote cost-efficiency and guide businesses in developing their future marketing strategy.
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
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 and ad targeting and predictive analytics among others.
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 out of the question. This is where artificial intelligence and machine learning comes in.
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 as well as their re-use and repurposing for cost-efficient delivery of brand campaigns.
Search engine optimisation (SEO)
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 the real intent behind a query and to deliver more relevant results.
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 time.
Customer support solutions
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 of repetitive tasks and can focus on high-level and complex issues. With machine learning support solutions, customers enjoy quicker responses and resolutions, while businesses experience operational savings.
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 objective 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 some interaction between a user and a product, it also involves user research, buyer personas, and marketing usability testing, among others. 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 in creating 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?
In 2020 and beyond, businesses will be investing more on 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 which will free 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 opening up more opportunities for human and AI cooperation.
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.
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.”
AI Marketing Quotes
“Artificial intelligence and machine learning, as 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
“In our business, we talk about 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 people 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 for it to be successful, enterprises need leadership from the top. This means understanding that when machine learning changes one part of the business — the product mix, for example — then 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-isation of AI is very interesting to me. The efforts by Google, Amazon, Salesforce — they’re bringing AI down to a 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’s going to 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.
Originally published at https://inkbotdesign.com on March 30, 2020.