What exactly is AI, or “artificial intelligence”?
The term “artificial intelligence” (AI) is used to describe the process of teaching robots to reason and learn like humans. The most well-known subfield of AI is Machine Learning, although the technology has numerous other uses throughout sectors and specialised professions as well.
Common marketing uses include targeting certain demographics, improving the efficiency of message delivery, and coordinating advertising efforts across multiple channels.
Analysis using artificial intelligence – The field of marketing analytics is ripe for the usage of artificial intelligence. For some, it’s all about mining client data for fresh insights that may be used in their outreach efforts. Natural Language
Processing (NLP) is one type of AI that can be put to use in this way by gathering information about a customer’s reaction to a brand’s communication with them after a particular engagement. Others look at historical data to figure out which mix of marketing activities produced the most positive change in a key performance indicator.
Effective use of AI for campaign development – From the dynamic discovery of consumer categories with similar characteristics to the selection of campaign material, AI is being used across the entire process of creating campaigns.
Marketers can use AI algorithms to find new audiences or segments of existing ones that are reacting well to a communication and then tailor future efforts to those groups. Similarly, AI can help marketers decide in real time the content each client should see based on their specific profile. As an illustration, a product suggestions algorithm can be used to update the featured products on an online storefront in real time.
Artificial intelligence (AI) in campaign orchestration – Campaign orchestration is the process of determining which of several campaigns can be sent. AI is essential in this area if personalised consumer experiences are to be achieved. AI makes it possible for marketers to increase the number of campaigns and journeys they design without increasing the number of campaigns sent to each individual customer. In order to improve marketing automation, AI models may instantly identify all applicable campaigns for each consumer and recommend the best course of action.
AI in Marketing
As was seen above, marketing is only one field where AI may be put to use. Therefore, businesses and its marketers need to decide which AI tools will be implemented first depending on the potential benefits they would provide. In marketing, some common uses of AI include:
Insights from the Data – AI can be utilised as a tool to deliver data insights, especially for marketing teams that don’t have access to data engineers. Patterns in customer data can be used by AI models to automatically group clients into similar categories. By fueling analytic models like marketing mix modelling and multi-touch attribution, AI may also lend a hand with result analysis by revealing the effect campaigns have on various KPIs.
One of the most common applications of AI in marketing is in the area of personalisation. Artificial intelligence models are especially useful when trying to scale up efforts to determine user tastes and tailor content in real time. Applications of artificial intelligence (AI) in personalization include recommendation models for products, interactive websites, self-optimizing campaigns (in which the model determines the best treatment from a multivariate test for each individual customer), and chatbots that provide customised communication.
Campaign Recommendations – AI can also be used to recommend content to marketers as they create their campaigns. The application’s use cases centre on recommending and reviewing voices and images in a given tone of voice. Campaigns that are inefficient or have a major influence on customer lifetime value can be identified and optimised with the use of
AI, and a subsegment of targeted customers that responds better to the campaign can be identified and targeted.
One of the most common applications of AI in marketing is scheduling, which may be seen of as a special case of Campaign Recommendations. With each consumer preferring to receive communications at their own time, and based on each individual’s open and click tendencies, send time optimization algorithms have become a prominent capability in marketing automation software.
Using AI for programmatic advertising can yield significant benefits for digital advertisers. Predicting campaign success for various demographics, optimising bidding tactics for maximum return on investment, and better matching content to viewers are all possible thanks to AI models’ ability to analyse data in real time.
Artificial intelligence (AI) has come a long way in the field of marketing, with the most recent use being next-best-action decision making. Instead of relying on predetermined automations established by marketers, AI can be used to identify the optimal campaign for each customer. Marketers create the campaigns and client segments (which can be assisted by AI, as mentioned above), and the algorithm chooses which one to send to each individual customer.
A Definition of Marketing Automation
The term “marketing automation,” or “MA” for short, is the practise of utilising computer programmes to speed up and streamline various aspects of the marketing process. Marketing automation helps professionals streamline and improve the efficacy of their marketing operations. Pre-scheduled marketing campaigns delivered via email, social media, and text message are examples of the kind of tasks that can be automated. Multi-step campaigns (sometimes called customer journeys) are another common feature of marketing automation software. These campaigns allow marketers to predefine a sequence of campaigns to be executed in response to a given consumer behaviour. Some marketing automation technologies are multi-channel, or “channel agnostic,” meaning they can automate across a variety of marketing channels. Those that specialise in a particular channel, like social media, will have access to channel-specific tools that offer advanced automation features, such as social listening notifications. Last but not least, the majority of marketing automation systems will come with reporting and dashboarding features to help marketers evaluate the efficacy of the automations they’ve implemented.