AI in digital marketing - key uses
Five ways that AI and machine learning are being used in digital marketing include content curation and search optimization, predictive analytics and sales forecasting, chatbots and data learning, profitable dynamic pricing model, and computer vision for product recognition.
- AI or artificial intelligence is the teaching of computers to do things that ordinarily are done better by humans and this is achieved through computers acquiring knowledge and learning how to apply them,
- Machine learning, on the other hand, has to do with algorithms that acquire knowledge or skill through experience to look for the pattern learned.
AI Uses In Digital Marketing
#1 Content curation and search optimization
- Content is considered the deciding factor in any successful marketing model and this is achieved through the application of AI to curate content according to targeted customer segements.
- AI algorithms utilize data on user habits, interactional patterns, and buying behaviors to select targeted customer's interests before presenting recommendations for them. AI raises the probability of conversions.
- A typical example would be Netflix, the world's largest media service, which uses AI to suggest video content for its subscribers or users.
#2 Predictive analytics and sales forecasting
- This practice involves the extraction of information from data sets to predict future trends by combining data mining, sales modeling, and statistics.
- Predictive analysis can help online entrepreneurs score leads with better maturation, nurture campaigns from demographics and behavioral data, and increase bottom lines while allowing detailed research on preferences of customers.
- Retail giant Walmart, observed a 10-15% increment for online sales for $1billion while utilizing AI sales prediction.
- Also, FedEx and Sprint use predictive analytics to pinpoint flight risk customers.
Both Artificial Intelligence and Machine Learning
#3 Chatbots and data learning
- With AI, chatbots now have a more significant role as digital marketers can have unmanned customer support that increases engagement, improve sales and reduce business costs.
- They assist online businesses to run a 24/7 customer support service that tends to basic inquiries in real-time, generating unique content for emails, tracking behaviors of customers and providing recommendations.
- Chatbots are now capable of giving human-like replies to difficult queries using AI and machine learning. By using natural learning processing to analyze keywords and influence buying decisions in customers, AI can answer complex queries.
- An example would be Starbucks, which utilizes AI chatbot for its Facebook messenger to take complex orders from customers. In an FME infographic compilation, by 2022, chatbots will help save $8 billion.
#4 Profitable dynamic pricing model
- The success of any business lies in the price settings on the products or services being offered.
- Businesses offer flexible prices for products and services they offer by utilizing dynamic pricing strategies. It is a common model in hospitality, entertainment industry, travel, and the retail industry.
- The strategy helps segment prices based on customer choices. There is a relationship between dynamic pricing and real-time pricing which is when the value of goods is based on market conditions.
- Machine learning makes it easier for businesses to efficiently implement a dynamic pricing model.
- Machine learning utilizes regression techniques to make market predictions.
Machine Learning Uses in Digital Marketing
#5 Computer vision for product recognition
- Using a software called GumGum, machine learning for computer vision was used to assist brands to recognize their products in videos and images online.
- A company called Miller Lite utilized a machine-learning algorithm to scan through user-generated content on social media. It searched for images without relevant text to find posts related to the brand and tracked information about competing brands and influencers.
- The results of the data collected by the software include 1.1 million total posts found, 3.2% irrelevant text posts scanned found, and 575 promoters found. This would have been almost impossible for a human to carry out such a task.
We searched relevant sources to come up with all of our findings and achieved the desired results. We did not need to triangulate to answer the client's request as all findings were easily obtained via the public space. We consulted sources with relevant and credible information as regards the uses of AI and machine learning in digital marketing and was successful at achieving all the above findings.