DCM

Volume.Increasing data volumes

Speed.Data is generated enormously fast

Variety.Diversity of data generated: structured, numerical data from traditional data bases

• In contrast to structured data, unstructured data has no predefined format and no formalised structure.

•  

• Examples of unstructured data that must be processed before it can be evaluated are text data (e.g. emails, customer reviews, forum posts, etc.) or image data that may arise during production, for example, to ensure production quality.

• A data lake is therefore much less restrictive in storing data and therefore offers greater flexibility.

• On average, each person generates about 600-700 megabytes of data per day

• With "Industry 4.0", big data is also being created in industry. Sensors produce data

  that measure their surroundings via the internet.

• Huge data is also generated by social media platforms that stream videos, music and photos.

• These are just three examples of multiple data sources that lead to an enormous information overload for companies.

  The question is how to create value from this data.

• According to the "father" of artificial intelligence John McCarthy, it is "the science and technology of making intelligent machines, especially intelligent computer programs" (1961).

• Artificial intelligence is a way of making a computer, computer-controlled robot or software think intelligently, much like intelligent humans think.

• Artificial intelligence is achieved by studying how the human brain thinks and how people learn, decide and work while trying to solve a problem, and then using the results of this study as the basis for developing intelligent software and systems.

• An important area of research in AI is neural networks. These are inspired by the natural neural network of the human nervous system.

• The inventor of the first neurocomputer, Robert Hecht-Nielsen, defines a neural network as:

• "...a computer system consisting of a number of simple, highly interconnected processing

  elements that process information through their dynamic state response to external inputs."

Medical: cancer cell analysis, EEG and ECG analysis, prosthesis design, transplant time optimisation.

Speech: speech recognition, speech classification, conversion of text to speech.Telecommunications: image and data compression, automated information services, real-time

translation of spoken language.

Transportation: Truck brake diagnostics, vehicle planning, routing systems, ANNs are often used to make steering decisions of physical vehicles.

Software: pattern recognition in face recognition, optical character recognition, etc. Signal processing: Neural networks can be trained to process an audio signal and filter it

accordingly in the hearing aids.

Anomaly detection: Since ANNs are experts at recognising patterns, they can also be trained to produce an output when something unusual occurs that does not fit the pattern.

• Natural Language Processing (NLP) refers to the AI method of communicating with an intelligent system using a natural language such as German or English.

• Natural language processing is required when you want an intelligent system such as a robot to work according to your instructions, when you want to hear decisions from a dialogue-based expert clinical system, etc.

• The field of NLP involves the production of computers that perform useful tasks with the natural languages that people use. The input and output of an NLP system can be:

• Language
• Written text

• Threat to privacy: An AI programme that recognises speech and understands natural language is theoretically able to understand every conversation on emails and phones.

• Threat to human dignity: AI systems have already started to replace humans in a few industries. It should not replace humans in the sectors where they hold dignified positions that have to do with ethics, such as doctors/caregivers, security agencies, justice, etc.

• Threat to security: The self-improving AI systems may become so effective that it could be very difficult to prevent them from achieving their goals, leading to unintended consequences.

• Consistent orientation towards the human personality.

• Basic explanation of how relationships come about and persist.

• Explains different phases of a relationship.

• Also explains the inclusion of alternatives in customer considerations.

• Explains values and differentiation in relationships.

• Data "give and take" is understood as a reciprocity principle.

• Empirical verification largely possible.

Attention

Trust

Connection

Why

How

What

eyecatcher

copy

reason why

• the right customers
• with the right offer
• at the right time
• via the right channel/at the right touchpoint.

• Campaigns for the introduction of new products / services

• Campaigns to win new customers

• Campaigns to work with existing customers (cross- and up-selling)

• Campaigns to win back customers

campaign trigger

• CONVERSION!

• Number of clients reached through the campaign

• Number of clients opening the campaign

• Number of customers who obtain more information (e.g. online or in the shop)

• Number of buying customers

• Contributionmarginofnewcustomers

• Campaigncostsuntilpurchase

• Number of contacts during the campaign

• Turnover on first purchase after the campaign

• Increase in turnover through the campaign

• Performance of the control group

• Ensure positive customer experiences

• Ensure that the company is accessible

• Enable differentiated customer service

• Relieving sales staff of standard tasks

• Cost control in service

• Avoiding work backlogs through industrialised services

• One Face to the Customer - uniform access of the customer to

  the company

• Implementation of corporate identity

• Professionalisation of contact management

Customer enquiries can be divided roughly according to the 80/20 rule:

80

• • • • •

% of the volume are simple enquiries: highly standardised,

quick solution,
low qualified staff to solve so-called "FIRST LEVEL SUPPORT". here applies: Time is Money!

February 2023

20 % of the volume are complex requests:
• individual enquiries (some of them potentially very good

customers!)
• complex solution by
• partly highly qualified personnel (e.g. technical specialists) • so-called "SECOND LEVEL SUPPORT
• Success factor: Listening and customer-specific solutions

• Organization of special sales events only for participants

• Commission through participating partners

• Sale of advertisements in the participant magazine

• Sale of «Special Editions»

• Participation fees (e.g.Amazon Prime)