Skip to main content

How Comfort Is Becoming More Important Than the Brand in AI

 All of the large technology companies are currently competing for the best

personal assistant. The field is lucrative as people with a personal assistant

will spend even more time on their mobile and thus both income from

advertising and device sales can increase. The search for keyword terms, via

Google for example, will presumably disappear in the long run in the scope

of this development. Instead of that, purchasing decisions will be made in

conversation with the digital assistant. Product recommendations in social

networks may also lose significance. It is probable that products suggested by

the persona assistant are a better match for the users than ever before, as the

persona assistant avails of a larger amount of information than what personalised advertising is based on. If more products are presented to the consumers that are much more tailor-made to his or her needs, it is probable that in

sum, more products will be consumed.

For a brand or a company to be successful in the future, it is thus important that the respective products and services are taken into consideration by

the personal butler’s algorithm. If a user then wants to order flowers, book a

hotel or buy a coat, the personal assistant will only consider those companies

that are present in the network of the algorithm. For personal assistants of

Google, on the other hand, the ranking of the results in the Google search

can play an important role. In the future, the focus of customers will be less

on the brand than on convenience. This means that companies that understand how to be connected to the relevant personal assistants will win.



Amazon, for example, could soon offer own labels via comfortable ordering processes without having to surrender margins. The first step in this

direction is the Amazon Dash Button, a button that is placed on devices to

order goods to be refilled at the press of a button such as washing powder

or toilet paper, which was introduced in 2016. The team behind Viv 1 is still

trying out various business models, but one could involve a processing fee

for every enquiry.

Comments

Popular posts from this blog

Possible Limitations of AI-Based Bots

 The examples above already show the present-day potential of AI-based bots. At present, these systems are still in an early stage and still have certain limitations and potentials for optimisation. Twitter Bot Tay by Microsoft Most bots at present are reactive service bots. Engagement bots that actively interact with the users as market and brand ambassadors go one step further. The most famous example here is the chatbot Tay by Microsoft. Microsoft removed Tay from the web apologetically within one day. The example shows that the uncontrolled training of bots by the community can lead to fatal consequences. AI systems still have to learn ethical standards. It thus becomes apparent that even bots require a kind of guideline. Like a journalist has to observe editorial guidelines, bots have to observe certain standards. The next generation of AI-based bots must control and create the possible room for communication. IBM Watson has been able to celebrate quite a few respectable resul...

What is Machine Learning

 The term machine learning (ML) as a part of artificial intelligence is ubiq- uitous nowadays. The term is used for a wide number of various appli- cations and methods that deal with the “generation of knowledge from experience”. The well-known US computer scientist Tom Mitchell defines machine learning as follows: A computer program is said to learn from experience E with respect to some class of tasks T and performance measure P, if its performance at tasks in T, as measured by P, improves with experience E (Mitchell 1997). An illustrative example of this would be a chess computer program that improves its performance (P) in playing chess (the task T) by experience (E), by playing as many games as possible (even against itself ) and analysing them (Mitchell 1997). Machine learning is not a fundamentally new approach for machines to generate “knowledge” from experience. Machine learning technology was used to filter out junk e-mails a long time ago. Whilst spam filters that tack- ...

What is Data Protection and Data Integrity

 As a matter of principle, when it comes to data protection, a differentiation must be made between personal data and data involving companies. As soon as inferences can be made to a specific individual and single data levels are being worked at, a moment has to be taken to consider: What is being processed? Is there already a business relationship? Which permissions or legal consent elements are at hand? Customer data may not be collected without permission and may also not be resold. Anybody who acts carelessly here can quickly render themselves liable to prosecution. In principle, the following applies however: Almost anything is possible with the customer’s consent. This is the reason why Facebook can act with the data to such an extent, because consent has been given, even if only few users have probably fully read and understood the Terms of Use. Likewise, a relatively far-reaching data processing in the scope of an ongoing customer relationship under the motto “for our own p...