Published by FirstAlign
The application of Artificial Intelligence has boosted popular products and services like Netflix, Google, and Amazon to huge successes. A vital reason for its popularity is intelligent marketing. AI in Marketing involves making use of customer data, machine learning and other computational concepts to predict a customer’s habits and wants, hence, improving the customer experience.
The development of big data and analytic solutions allows marketers to gain a clear idea of their target audiences. Intelligent marketing helps digital marketers boost their campaign’s performance and return on investment with the help of these data insights. AI can quickly analyse large amounts of data, categorize and then break it down to create personalized content for their audiences.
AI helps businesses to create advanced marketing analytics techniques to target the right customers for their products. Therefore, digital marketers are able to reach customers through the right channel at the right time.
Let us dive into the various AI-powered services that augment marketing.
Marketing using Predictive Analysis
Intelligent marketing makes use of Predictive Analytics, which in turn plays a crucial role in marketing success. It is the use of data, AI-systems, and statistical algorithms that predict possible future outcomes.
Predictive Analytics makes use of data to determine, what customer category will be the aptest to reach, and create effective actionable insights. In this way, predictive analytics optimizes marketing campaigns. It provides an accurate report which allows marketers to optimize areas where they may seem to fall short. Thus, a groundwork for effective strategical practices is laid, not only for marketing but for sales and business decisions too.
Predictive analytics is also used to forecast a customer’s behavior. Techniques powered by AI and Machine Learning builds predictive models that assess future customer behaviors. It does this by identifying patterns between variables in the data. Models can identify correlations between customer’s past purchasing habits to determine the probability of future purchases. These models are capable of identifying dissatisfied customers whom the brand might risk losing, as well as excited customers who are ready to purchase the brand’s products.
In this manner, running customer data through predictive models can help marketers to anticipate customer behavior better, and plan better marketing strategies.
Programmatic ad targeting
Programmatic ad targeting is the automation of the ad-buying process using software-driven technology. Intelligent marketing makes use of data from the cookies of mobile applications and websites, visited by customers to target them with advertisements that match their demographics. Age, gender, location, etc. are all common factors. If the advertisements do match, the ad-buying system will bid on the impression and display targeted content.
Customers in this day and age are familiar with the personalization of content and product recommendations from companies like Netflix, Spotify, or Amazon. Therefore, they expect more brands to provide the same, customized experience. The optimization of ad targeting based on key insights and in-depth analyses helps to connect with customers better, and show them relevant content.
Through catering to their needs, by displaying relevant products, customers will be engaged with the business, providing marketers with a deep knowledge of their customers’ preferences. This way, programmatic ad targeting will enable companies to deliver the right content to the right person at the right time.
Relying on ChatBots
Customers can reach out to companies with the help of messaging apps such as Facebook, Whatsapp, Viber, or Kik. These apps provide a route for customers to pose inquiries or complaints. Responding to each and every customer inquiry would be a herculean task for human employees. Here is where ChatBots provide a solution.
ChatBots are AI programs that can simulate a conversation with customers through the help of natural language processing. Companies can set predetermined answers to FAQs or help customers find and buy a product that they like. ChatBots have the ability to incorporate location-specific requests, detect patterns, identify repetitive problems, and predict the cause of issues for a particular customer. This significantly increases speed of response and cuts down the need for human intervention, thus, saving time and cost.
Below is a video displaying Sephora’s Kik bot that provides a mini-quiz about the user’s makeup preferences.
Sephora’s example shows how AI-powered ChatBots can provide advice during customer research and discovery, therefore, paving a way for a new form of marketing. Intelligent marketing shows that ChatBots’ abilities aren’t limited to direct customer service interactions; they can act as proactive advisers for every online visitor.
Many businesses are well aware of the importance of the implementation of AI. According to a recent research by Dressner Advisory Services, 40% of marketing and sales teams say AI and machine learning is critical to their success as a department.
Intelligent marketing will provide an increase in customer satisfaction and a higher return on investments. In this technological era, with the quantity of online content and user consumption rates, intelligent marketing will help brands maneuver through, and find the perfect set of target audiences.
AI’s integration into marketing will provide brands with a competitive edge and increase their revenue by reaching more relevant customers with relevant content.
- @Emarsys: What Is Artificial Intelligence Marketing & Why Is It So Powerful?
- @AI News:3 fascinating case studies of AI success in Content Marketing
- @Mageplaza: AI Marketing: What, Why and How to use Artificial Intelligence in Marketing
- @AI News: Decoding the 3 potential advantages of big data
- @Content Marketing Institute: 8 Ways Intelligent Marketers Use Artificial Intelligence
- @Forbes: How AI And Predictive Analytics Drive Marketing Success
- @Towards Data Science: Predictive Analytics for Marketing: What It Can Do and Why You Should Be Using It