Artificial intelligence application in digital marketing
One of the disruptive technologies in the 21st century is Artificial intelligence (AI). Artificial intelligence has taken the world by storm, while the marketing and advertising world is no exception.
AI has been defined in the leading AI textbook as a device that automatically takes notes of its environment and eventually takes action to achieve its goals. AI teaches machines to react and behave like humans will do imitating human brain architecture.
Therefore, AI is now becoming more accessible than ever, making different brands both small and big to enjoy the advantages offered by AI, which includes insights and optimization.
According to Forbes (https://www.forbes.com/sites/louiscolumbus/2019/09/08/state-of-ai-and-machine-learning-in-2019/#421607011a8d), in their write up on the state of AI and machine learning in 2019, they made it known that 40% of the marketing and sales team says data science which revolves around AI and machine learning has been crucial to their success as a department.
Machine learning is a subset of AI, that applied algorithms to build models, used to make decisions with minimum human interference
(https://www.sas.com/en_ph/insights/analytics/machine-learning.html).
Machine learning in marketing
AI have been applied in digital marketing through machine learning. Machine learning involves data analysis from diverse businesses, including the interaction of business with customers, as well as the customer responses to the business. This data provides insights on which future decisions can be based for future campaigns in other to increase chances of success.
Here we will introduce some of the fascinating applications of AI technology in digital marketing, by also showcasing some of the tech giants that have taken advantage of the technology
Google has implemented AI in many areas, ranging from human-like data processing to smart form of Youtube video ads suggestions (https://www.forbes.com/sites/bernardmarr/2017/08/08/the-amazing-ways-how-google-uses-deep-learning-ai/#3a059a583204). Advertisements Videos are been suggested to viewers based on the past history of their views using a machine learning algorithm. A personalized collection of videos that individuals may be interested in watching next is displayed at the right side of the watch page. Google uses a recommendation system architecture funnel where candidates’ videos are retrieved and ranked before presenting it to the viewer. Therefore, the algorithm is usually a “real-time feedback loop tailors’ video the interest of each viewer
(https://blog.hootsuite.com/how-the-youtube-algorithm-works/)
Personalized and data-driven marketing
AI has been applied in personalization by categorizing the data sets of different customers and extracting valuable insights from it. Forbes
(https://www.forbes.com/sites/bernardmarr/2017/10/30/the-amazing-ways-spotify-uses-big-data-ai-and-machine-learning-to-drive-business-success/#147d2d004bd2) explained how Spotify uses big data, AI, and machine learning to drive business, they recently use customer data to enhance the user experience. Every Monday a personalized list of thirty songs are presented to individual users, the recommendation is generated based on the user search pattern and music preference. This endears customers to return back to the platform and provides greater exposure for the artist that may not be searched before.
Video marketing
Most brands believe that the best way to pass information regarding their products is through video advertisements. A recent survey has shown that most people spend approximately 90 minutes on their phones every day, which added up to 23 days in a year (http://www.mobilestatistics.com/mobile-news/23-days-a-year-spent-on-your-phone.aspx.). It is also a known fact that video graphics have an excellent recall value for consumers, compared to text.
According to cisco annual internet report,
(https://www.cisco.com/c/en/us/solutions/collateral/executive-perspectives/annual-internet-report/white-paper-c11-741490.html). 74% of all internet traffic are from videos. With the assistance of AI, a video marketing strategy can achieve a greater height, providing your customers with tailor-made content. AI data can be used by video developers to predicts customer's interest, preventing marketer form producing redundant video.
Application to AI chat bot
AI chatbots has enabled the developments of Language processing, AI semantic recognition, and voice conversation, delivering AI customer service with a better service. AI chatbots enable and delivers one-to-many, delivering and providing support to many customers at the same time with different time zone, even during off duty hours. Google uses Dialogflow platform as an advanced development suite for creating conversational AI applications. Dialogflow is a natural language understanding platform that makes it easy to design and integrate a conversational user interface into your mobile app, web application, device, bot, and so on
(https://cloud.google.com/dialogflow/docs).
Starbucks have leverage on the power of Chatbot AI to help customers order their favorite coffee, what is required from customers is to order through the Starbucks Barista bot for messenger and wait for their coffee and snacks to be delivered at their doorsteps.
(https://www.topbots.com/project/starbucks-barista-bot-mobile-app-review/)
AI Analytics
Marketers have access to more tools than before, and they need to constantly update their skills on those tools. Ai marketing analytics span from everything from social media analytics to automated decision making. This is usually made possible by merging different data gotten from different sources to gain insights and predict the future, thereby making the marketing analyst job to be much easier. Google web analytics has helped marketers to get a deeper understanding of their customers. Google analytics has given you free tools needed to analyze data for your business in one place.
(https://marketingplatform.google.com/about/analytics/)
AI in email marketing
Recently, AI has help brands or companies to personalize email marketing based on user behavior. Therefore, AI has helped marketers to better personalized content. Airbnb has leverage on these possibilities by sending relevant emails to customers inboxes, based on the suggestive
power of the recommendation algorithm factoring in their buying history. The company, like phrases (https://phrasee.co/), has created a new rule book for marketing in the digital age. They
Collaborate on the right tone and messaging based on data-driven insights and not human instinct, helping them to say the right thing by not saying the wrong thing in sensitive times.
Ultimately, AI has helped email marketers to reach a specific customer at the right time, making sure that the messages sent out is relevant and engaging.
In conclusion, as AI continues to shape digital marketing, we may not have to search further for the future, we can, however, say the future is here. keeping up with digital trends cannot be a matter of choice but a necessity for businesses to compete favorably in the new-age technology era.
Written by :
Olanipekun Ayorinde.
I am an AI expert, using machine learning and data science tools, to build a predictive model and develop a creative AI/ML solution for tech industries. I have carried out several research works in the area of Machine learning.
