What is marketing that changes with AI / machine learning?
In the world of shogi and go, AI has surpassed humans, and we are also conducting a practical test of autonomous driving by AI. In recent years, we have heard the word "AI" in every field.
Why? "AI" itself is a concept that has been around for decades, but its use has been limited. However, when technologies and environments such as "deep learning", "development of the Internet", and "establishment of big data technology" are in place, when a large amount of data is learned, complicated judgments and recognition such as image recognition can be performed by AI. Proved to be able to do. As a result, we are exploring ways to utilize AI in various scenes around the world. Business is no exception. For example, in the human resources field, matching is performed with companies and occupations that enable the person to continue working and maximize their abilities.
Of course, "AI" is also used in various places in the marketing field.
This time, we will introduce these "examples of using AI / machine learning in the marketing field".
"AI / machine learning" has already been introduced in the marketing field
One way to utilize AI is to "predict what is not yet visible" from "visible data". For example: It may be relatively well known that these are done by AI / machine learning.
By using such machine learning, it becomes possible to find out the rules buried in a large amount of data that humans do not notice, and to finish office work that takes a huge amount of time for humans in an instant. For example, on EC sites, products that customers may judge to like from purchase history and operation history are displayed as recommendations, which are already being used.
In addition, by going one step further from machine learning and combining advanced computers with special networks such as the human brain, a method of discovering while learning complex patterns hidden in a large amount of data has appeared, and deep It's called learning. Deep learning is also learned based on teacher data, but in general, the difference between machine learning and deep learning is that features are automatically found.
Nowadays, technologies and ideas that artificially reproduce human intelligence with machines are called AI (artificial intelligence), and machine learning and deep learning are one of the methods included in them.
AI / machine learning marketing methods that should be suppressed
AI and machine learning are being used in various fields against the backdrop of labor shortages, higher computer performance, and network development, but they are also being introduced into the fields of marketing and retail. Already, in the field of digital marketing, there are an increasing number of cases where AI is being adopted to produce results. The following are examples of actual marketing where AI / machine learning is used.
Recommendation
This is a technique we have seen for a long time. Not only recommendations based on past purchase / browsing history, but also recommendations for similar products are possible. Next, you can expect the effect of inducing buying and raising the average customer price.
Maximize advertising effectiveness
Automatically purchase ad space that can be expected to be effective and place ads. Allocation of advertisements and channel selection are all calculated with the goal of achieving KPIs.
The use of AI is progressing even in real stores. By capturing the customer's flow line with a sensor such as a camera and letting AI learn it together with the purchase data, the optimization of the store layout and the placement of the clerk are improved, and the customer's staying time and purchase unit price are improved.
In this way, the use of AI and machine learning has been promoted in the field of marketing as well. Recently, with the attention of digital marketing, a wide range of utilization methods are being sought. There may be some people who have used AI-based chatbots.
Bring MA tools
closer to one-to-one marketing with AI
One of the things that is attracting attention in digital marketing is the MA (MA: Marketing Automation) tool. The MA tool automates the one-to-one approach by setting scenarios. However, it is not enough to leave marketing to MA tools, and scenario design of "when", "who", and "what kind of approach" is left to the know-how of marketers. Therefore, the use of AI is attracting attention in MA tools as well.
For example, the following usage examples can be mentioned.
Automation of lead scoring ...
[Trouble] It is difficult to find highly accurate leads from a huge number of leads
In companies that handle products that involve sales negotiations, such as BtoB, the role of marketers is to hand over promising leads to sales. However, it is difficult to narrow down the most accurate leads from the large number of leads obtained from promotional activities. The MA tool uses a function called "scoring" to evaluate the quality of leads, but the question of "what kind of customer behavior" should be given "how many points" is a source of concern for marketers. .. Therefore, efforts are being made to improve the accuracy of scoring by utilizing AI.
Applying AI to lead scoring
・ Learn behavior data such as past sales performance, reaction of promotion activities, and web access history ・ Give a
score for each lead based on the learning model ・
Develop measures according to the score (DM focusing on leads with high scores) , Implementing measures such as telematics)
In addition to this, there are cases where AI is used to analyze customer purchasing behavior, predict who should approach which product and when, and use it as a scenario for MA tools. ..
In this way, by applying AI to MA tools, we can approach customers efficiently.
It is extremely difficult to extract meaningful information from a large amount of data, identify the needs of subdivided customers, and draw detailed scenarios for training and contracts tailored to each customer. And it's clear that it's difficult to cover that with just the resources of a marketer. However, on the other hand, there is a strong demand for a shift from mass marketing to one-to-one marketing. Therefore, we will ask AI to help us and realize effective marketing activities.
・ Shortage of marketing personnel
・ Implementation / evaluation / improvement of continuous measures
It is possible to solve such a big marketing problem by using AI.
Summary
With the spread of big data and IoT, the importance of data utilization in marketing will increase in the future. In addition, there is a strong demand for a shift from mass marketing to one-to-one marketing. However, it is difficult to grasp the needs of individual customers in real time from a large amount of data. Therefore, it is expected that AI will repeat learning from a large amount of data and automatically predict customer needs.
Utilization of AI for marketing is being tackled in various industries and issues. Those involved in marketing must always be aware of the ever-evolving “what AI can do”. With the evolution of AI, perhaps in the not too distant future, AI may discover new marketing perspectives and perspectives that we didn't realize.
AI-related solutions
Membership management
0 Comments