Artificial intelligence (AI) is a rapidly growing field. It promises to provide benefits to nearly every business. This field has risen to prominence with the increase in big data, cheap computing, and fast internet.
As most businesses move to a digital model, customer data becomes increasingly accessible. This provides a valuable new opportunity for marketers to understand, predict and influence customer behavior. This trove of data offers insights that marketers can use to inform and direct campaigns.
AI offers insights in a way that traditional analytics cannot. By allowing machines to learn from complex datasets, AI marketing can identify complex trends and patterns. These insights can inform marketers about the effectiveness of different campaigns. AI makes it possible to simplify big data into actionable strategies.
Here we discuss 10 powerful ways you can use AI in your marketing campaigns.
Personalized Product Recommendations
Product recommendations are one of the earliest applications of machine learning (ML) to marketing. Companies began clustering the behavior of customers in order to predict their future shopping habits over 20 years ago.
This use of AI is now essential to the online experience. Users expect curated content and targeted marketing. Showing customers the products they are more likely to want first lets marketers grab shortening attention spans.
Personal suggestions are now an expected part of online shopping. Companies from Amazon to Hulu use these techniques.
Natural language processing (NLP) is the field of AI that enables machines to interpret human languages. Many people encounter this tech daily. Smart home devices use NLP to interpret commands.
It would be nearly impossible to read all of the written reviews and feedback provided for many products. Random reviews do not capture the full picture. AI allows marketers to explore the way real people perceive their brands and products. By combining reviews and data from social networks, sentiment analysis can reveal large-scale trends in popular opinion.
Prices change regularly in just about any market. Changes in demand and competition influence the price a product can sell for. In traditional stores, products would sell for different prices in different markets.
In an online context, these market changes are rapid. This can be hard to keep up with. Instant online shopping allows customers to find cheaper products right away.
AI can enable marketers to respond to these changes rapidly. AI can track changes in competitors’ prices and respond in real-time. In addition, it can change pricing depending upon the user. The different markets can be different groups of consumers that may be willing to pay higher prices for the same products. These techniques are being used by companies like Amazon, Uber, and Airbnb.
Predictive analytics is one of the largest applications of AI and ML. These strategies allow marketers (and others) to make informed guesses about the future. This helps inform decisions, allowing teams to get ahead of change.
Marketers can use predictive analytics in many ways. By tracking customer behavior, ML algorithms can predict purchases, conversions, and losses. This allows marketers to respond to customer behavior. They can identify how to most effectively leverage advertisements, outreach, and support.
Another use of predictive analytics is forecasting sales. By learning from past trends, AI can help businesses predict changes in demand. By predicting both short and long term performance, marketers can plan their campaigns to maximize outcomes.
AI can help businesses provide a targeted experience beyond their websites. Marketers can pair programmatic advertisement bidding with AI. This allows marketers to use bots to direct their campaigns based on audience, time of day and more.
AI can bid on ad placements that are more likely to result in conversions. This can save advertising costs and lead to higher overall performance.
Chatbots are a classic example of AI. These programs replicate a very human behavior, communication. This makes them a popular poster-child for AI. The classic Turing Test identifies ‘true’ AI through a chatbot. Today this is only one small part of what we call AI. However, it is still a gold standard.
Many AI-powered chatbots exist for websites today. These chatbots certainly would not pass the Turing Test. However, that doesn’t make them useless. Chatbots can save time for many companies by providing support suggestions and pointing users in the right direction. For example, chatbots help decrease support tickets, enabling customer success teams to service more customers per person. Another example of how chatbots are used in business is to capture and qualify leads for marketing & sales.
These tools use natural language processing to understand users’ questions. They can identify solutions more effectively and naturally than a traditional search engine.
Computer vision (CV) is one of the most popular fields in AI. This field has been at the forefront of ML for decades. Because of this, many image classifiers and object recognition algorithms perform incredibly well. They can be trained to identify everything from individual zebras to dragons.
CV has many applications in marketing. One of the most obvious uses is visual search engines. These technologies allow users to find products based on visual similarity.
These same technologies can be used by marketers to identify their products and competitors in social media photos. This can enable marketers to track popularity and make predictions.
Another use of CV is real-world personalization. McDonald’s is using cameras in their kiosks to make decisions about the content served to customers. These kiosks use cameras to guess demographic information. They then select the products to advertise. Real-world uses of AI are becoming increasingly common.
Personalized Web Experience
A/B testing is just the tip of the iceberg when it comes to website optimization. Rather than simply testing two design choices, AI can be used to dynamically change web experiences. This could enable websites to respond in real-time to changing performance. It also allows marketers and web developers to test many design changes at the same time. They can then identify the best designs for each customer segment.
Customer Insights and Segmentation
A personalized online experience requires an understanding of the different groups you are targeting. Traditionally, this was done using only demographic data. AI allows marketers to cluster customers based on their online behavior.
This allows advertisers to segment their customers into useful and specific categories.
One of the hottest areas of AI marketing is to use AI to streamline the actual creation of content. Though this is still in early stages, companies are beginning to release products that write using AI.
Elon Musk’s AI-research lab OpenAI has created an algorithm capable of generating written English text. OpenAI has restricted the release of this software due to concerns it would be abused. Though this may just be a way to build hype, the results of the algorithm are impressive. Try it out here.
AI may be used for other forms of content creation in the near future. Generating advertisements by combining text and images to match different audiences and products is another application. Though this technology may threaten the jobs of some advertisers, it can also allow marketing teams to focus on other areas. The uses and implications of AI generated creative content are vast.
As the field of AI grows, so do its marketing applications. Researchers are constantly developing new techniques. Many of the applications of these technologies have not yet been imagined. However, one thing is certain, AI is changing the way marketing works on a fundamental level.
We invite you to visit our new website and learn more about our how we can help you address your marketing needs and integrate AI into your workflows through our conversational interface and our recently launched Live Chat!
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