Skip to main content

Artificial Intelligence Marketing Matrix

 Nowadays, there already is a multitude of potential applications for marketing based on artificial intelligence. These potentials can, in principle, be

subdivided into the dimensions “automation” and “augment” as well as on

the basis of the respectively associated business impact. In the case of the

augment applications, it is especially a matter of intelligent support and

enrichment of complex and creative marketing tasks that are currently still

performed by human actors. Artificial intelligence can, for example, support the marketing team in media planning or in the generation of customer insights (see the practical example  “The Future of Media

Planning—AI as a game changer”). First and foremost, the augment potential is already more strongly developed in those companies that reveal a high

degree of maturity in the AI maturity model. Planning and decision-making

processes are also supported or already performed here by artificial intelligence. With regard to the automation applications, it is hardly surprisingly

noticeable that with them, both the degree of maturity and the distribution

are significantly more developed in comparison. There are many automation

applications, for example, that already have a high degree of maturity and

use in practice today. This includes marketing automation or real-time bidding, for example (Fig. 3.11).

There are, however, applications that are used comparatively little in practice today despite their high degree of maturity and high business impact.

One area of application this phenomenon applies to is the principle of

lookalikes that can be used for lead prediction and audience profiling. In the

B-to-C field, this can easily be put into practice with Facebook Audiences

(https://www.facebook.com/business/a/custom-audiences).

This principle can also be easily applied in the B-to-B area (see practical example Sect.“Sales and Marketing Reloaded—Deep Learning

Facilitates New Ways of Winning Customers and Markets”). Behind this

is the possibility of strategically identifying new potential customers on the

basis of the best and most attractive key accounts of a company, who are

similar to the key accounts in such a way that it can be presumed that they

are likewise interested in the company’s products.



The way it works is easy to understand: Customers—in the B2B area,

these are companies—can be characterised on the basis of various aspects.

Besides classical firmographics such as location, business sector and the

company’s turnover, these also include information about their development, digitality and their topical relevance. In times of big data, this enormous amount of information can be mainly acquired from the companies’

presences on the web, because every day, up-to-date posts about new prod-panies that have the same DNA—the so-called lookalikes—can be identified 

ucts, changes within the company as well as on other subjects are published on the website and on social networks. On the basis of these aspects,

all companies can be characterised comprehensively, on the basis of which

a generic customer DNA is generated. In a subsequent step, further companies that have the same DNA—the so-called lookalikes—can be identified on the basis of this generated generic customer DNA. The result is a

pool of potential new customers, the approaching of whom offers promising

opportunities.

Comments

Popular posts from this blog

Customer Engagement with Chatbots and Collaboration Bots: Methods, Chances and Risks of the Use of Bots in Service and Marketing

 Relevance and Potential of Bots for Customer  Obtaining information, flight check-ins or keeping a diary of one’s own diet—all of this is possible in dialogue today. Customers can ask questions via Messenger or WhatsApp or initiate processes. This service is comfortable for the customer, available at all times via mobile and promises fast answers or smooth problem-solving. A meanwhile strongly increasing number of companies is already relying on this means of contact and the figures on chat usage speak in favour of this means supplementing or even replacing many apps and web offers in the future. The reasons for this are manifold. Figures of the online magazine Business Insider 1 reveal a clear develop- ment away from the public post to the use of private messaging services such as Facebook Messenger or WhatsApp. Facebook meanwhile has a user base of around 1.7 billion people worldwide; 1.1 billion people use WhatsApp, and Twitter can nevertheless still record 310 million us...

Robot Journalism Is Becoming Creative

 Algorithms are able to automatically search the Web for information, pool it and create a readable piece of writing. In addition, data-based reports in the area of sport, the weather or finances are already frequently created automat- ically today. Recently, for example, merely a few minutes after Apple had announced their latest quarterly figures, there was a report by the news agency Associated Press (AP): “Apple tops Street 1Q forecasts”. The financial report deals solely with the mere financial figures, without any human assistance whatsoever. Yet, AP was able to publish their report entirely via AI in line with the AP guidelines. For this purpose, AP launched their corresponding platform Wordsmith at the beginning of 2016, which automatically creates more than 3000 of such financial reports every quarter, and which are pub- lished fast and accurately. It is no longer that easy to distinguish between whether an algorithm or a human has written a text. Another exception of rece...

Sales and Marketing Reloaded—Deep Learning Facilitates New Ways of Winning Customers and Markets

 Sales and Marketing 2017 “Data is the new oil” is a saying that is readily quoted today. Although this sentence still describes the current development well, it ides not get down to the real core of the matter; more suitable would be “artificial intelligence empowers a new economy”. The autonomous automation of ever larger fields of tasks in the business world will trigger fundamental economic and social changes. Based on a future world in which unlimited information is available on unlimited computers, ultimate decisions will be generated in real time and processes will be controlled objectively. These decisions are not liable to any subjectivity, information or delays. In many sectors of the economy, e.g. the public health sector or the autonomous control of vehicles, techniques of artificial intelligence (AI) are applied and increase the quality, availability and integrity of the services offered. The same development can be observed in the field of sales and marketing. Today, ...