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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.


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