Skip to main content

The Right Use of Ai Algorithms in Marketing

 As suggested by the afore-mentioned negative examples, certain risks are

lurking in the background for companies that use algorithms in marketing.

It is thus essential for companies to fully understand the algorithms applied

and their limitations and for the algorithms to be used wisely. In addition,

algorithms have to be supervised and controlled so that they are in harmony

with the principles of the company and the image of the brand.

Another aspect is the ever-increasing concerns of customers regarding

their privacy, which can arouse mistrust of the use of algorithms. If the

customer sees too much personalised advertising, this can be perceived as

creepy, especially if the advertising is based on very deep insights into private information. This is also called overkill targeting and can reduce the

success of the marketing strategy, The creepiness that the customer can

experience emerges from an imbalance in the distribution of the information. The company advertising knows more about the customer than the

other way round.



Companies also need to be aware that by the collected and analysed data,

they have an advantage over the customer and can thus manipulate and

misguide their perception. If consumers are only shown pre-sorted information, they have no chance of obtaining an overall view. There is thus the

risk that individuals exploit algorithmic marketing without heeding any ethical aspects. For the trust of the customer to be gained, the marketers must

ensure that the algorithms adhere to the codex of digital ethics and privacy,

and observe manipulation and selection of information as well as communication behaviour.

For a successful application of algorithms in marketing, it must also be

considered that not all factors are analysed in context. The customer’s mood,

the weather or the presence of other people, for example, can influence the

customer’s purchasing behaviour. For this reason, an algorithm should con-

tain as many variables as possible but also elements of surprise and chance,

in order to not be too predictable. Another disadvantage of algorithms is

that they are often restricted in their ability to analyse why a customer made

a certain decision. As suggested by the afore-mentioned negative examples, certain risks are

lurking in the background for companies that use algorithms in marketing.

It is thus essential for companies to fully understand the algorithms applied

and their limitations and for the algorithms to be used wisely. In addition,

algorithms have to be supervised and controlled so that they are in harmony

with the principles of the company and the image of the brand.

Another aspect is the ever-increasing concerns of customers regarding

their privacy, which can arouse mistrust of the use of algorithms. If the

customer sees too much personalised advertising, this can be perceived as

creepy, especially if the advertising is based on very deep insights into private information. This is also called overkill targeting and can reduce the

success of the marketing strategy, The creepiness that the customer can

experience emerges from an imbalance in the distribution of the information. The company advertising knows more about the customer than the

other way round.

Companies also need to be aware that by the collected and analysed data,

they have an advantage over the customer and can thus manipulate and

misguide their perception. If consumers are only shown pre-sorted information, they have no chance of obtaining an overall view. There is thus the

risk that individuals exploit algorithmic marketing without heeding any ethical aspects. For the trust of the customer to be gained, the marketers must

ensure that the algorithms adhere to the codex of digital ethics and privacy,

and observe manipulation and selection of information as well as communication behaviour.

For a successful application of algorithms in marketing, it must also be

considered that not all factors are analysed in context. The customer’s mood,

the weather or the presence of other people, for example, can influence the

customer’s purchasing behaviour. For this reason, an algorithm should contain as many variables as possible but also elements of surprise and chance,

in order to not be too predictable. Another disadvantage of algorithms is

that they are often restricted in their ability to analyse why a customer made

a certain decision.


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...

A Bluffer’s Guide to AI, Algorithmics and Big Data

 Big Data—More Than “Big” A few years ago, the keyword big data resounded throughout the land. What is meant is the emergence and the analysis of huge amounts of data that is generated by the spreading of the Internet, social media, the increasing number of built-in sensors and the Internet of Things, etc. The phenomenon of large amounts of data is not new. Customer and credit card sensors at the point of sale, product identification via barcodes or RFID as well as the GPS positioning system have been producing large amounts of data for a long time. Likewise, the analysis of unstructured data, in the shape of business reports, e-mails, web form free texts or customer surveys, for example, is frequently part of internal analyses. Yet, what is new about the amounts of data falling under the term “big data” that has attracted so much attention recently? Of course, the amount of data avail- able through the Internet of Things (Industry 4.0), through mobile devices and social media has ...