The minds behind the development of artificial intelligence (AI) have always wanted a technology that could replicate human intelligence. Yet in the wake of big data and analytics, AI has far surpassed any human ability to process information from these sources.
Companies in various industries have been able to leverage the knowledge and information from big data thanks to AI technologies. Perhaps one of the biggest groups that continue to benefit from the superhuman capabilities of artificial intelligence and machine learning (ML) are the marketers.
What is AI marketing and machine learning marketing all about? Are they one and the same or do they differ from each other?
In this post, we’ve prepared a primer that will help you understand AI and ML and how they are being used in the field of marketing in real life.
Artificial intelligence in marketing is about using both online and offline customer information combined with AI concepts like natural language processing, social intelligence, and machine learning. It uses these methods of data analysis to assess the future actions of target markets.
AI is the foundation of everything that involves the intelligence in machines and machine learning is a subset of it.
With artificial intelligence, marketers can pinpoint specific users and use the appropriate messaging at the right time to drive them through their desired marketing funnels.
As mentioned earlier, AI in marketing can provide marketers with in-depth customer data for analysis. Such capability can help marketers influence consumer behavior and drive conversions to their brands.
Although artificial intelligence became an official term in 1955, experts had been trying to implement it as early as 1939 especially during the war.
Alan Turing, a theoretical computer scientist and the father of AI, was able to develop a machine that could understand and decode German enigmatic messages. The apparatus can be considered the very first implementation of machine learning despite its archaic form.
Compared to AI, machine learning in the field of marketing uses statistical methods and algorithms to make forecasts. Its algorithms work to learn from the data provided to it so it can perform actions that result in better outcomes.
Some areas where machine learning is being used in marketing nowadays include churn prediction, personalization, and segmentation.
Now that we’ve discussed the basics of AI and ML, let’s take a look at examples of how these two are being used in marketing.
Perhaps the most popular application of artificial intelligence today can be found in the form of conversational AI. The prominence of such technology is primarily because of the rapid adoption of digital assistants and chatbots in various industries.
Digital assistants are increasingly being used by major brands like Apple, Amazon, Microsoft, and Google to optimize their voice search content and ensure their customers get the best experiences.
Meanwhile, chatbots are currently being used to provide immediate responses to customer service needs. These bots are capable of interacting with users conversationally, making people feel that they are chatting with a human agent.
Personalization is a priority in business and its foundation lies in one’s ability to accurately segment their audience. With traditional segmentation, the criteria available are extremely restricted to just the demographic, geographic, and psychographic characteristics of users. Compared to machine learning-driven segmentation, marketers can separate their audience in a more granular manner.
For instance, rather than just base users on subscription data and product usage, you can pinpoint which customers are no longer using your services. With this data, you can initiate a retargeting campaign to bring them back to the fold.
Although you can’t find artificial intelligence that is capable of writing editorial articles or opinion pieces just yet, major progress has already been made to enable technology to come up with data-centered content.
There are AI marketing and content creation tools available that have found success in producing industry reports and news stories. You may even one day stumble upon an AI-generated sports or financial report one day that sounds cohesive and coherent.
Another aspect where AI is present in content creation is copywriting. You can find a few AI providers today that have models that can produce email subject lines and Facebook ad copies.
The foundation of being able to identify those who are no longer using your products can be found in predictive analytics. This is because predictive analytics uses customer data to allow machine learning models to predict behaviors and future actions.
When combined with big data, an ML algorithm can create a prediction model that can forecast outcomes. It can also be used to predict churn or help in finding opportunities for upsells and cross-sells.
The caveat here is that the quality of data provided to such an algorithm has to be top-notch. If the information is prone to errors, then you can’t expect its output to be accurate.
One of the biggest benefits of using AI in marketing is helping marketers optimize their ad budget. Since ad optimization is an iterative process, artificial intelligence can help you through:
The ideas provided in this post should help give you a basic understanding of how machine learning and AI marketing works.
If you plan to leverage artificial intelligence for your marketing campaigns, it’s best to start with the fundamentals. From there, you can experiment and do some testing before you decide to scale.
Since personalization has become a vital aspect of the marketing world, you can use AI as a facilitator to ensure your approach and brand messaging are personalized to meet the needs of your target market.
To learn more about AI Marketing check out our Ultimate List of AI Marketing tools.