Digital future
What’s good about big data and/or AI? What’s not?
Benefits of big data and AI: Better decision-making, Increased productivity, Reduce costs, Improved customer service, Fraud detection, Increased revenue, Increased agility, Greater innovation, Faster speed to market.
Disadvantages: Need for talent, Data qualityNeed for cultural change, Compliance, Cybersecurity risks, Rapid change, Hardware needs, CostsDifficulty integrating legacy systems.
Does it have limitations? If so, what are they?
Data utilization is one of the significant restrictions of Artificial Intelligence.If we implement AI into a program, the software robots need some cognitive aptitudes to become more intelligent with time. There are likewise robots with cutting-edge cognitive aptitudes that utilize technologies to extricate the significance of data restricted in the documents. What’s more, AI lacks emotional intelligence as it cannot classify human sentiments and mindsets into one of a kind data points or profiles. Nevertheless, AI activities that aren’t planned at a strategic level, failure to address strategic business goals and don’t fit inside a company’s overall actions for development and business development.
Can we trust every bit of data we get?
There are many problems with data we get that related to: Data completeness and accuracy, Data credibility, Data consistency, Data processing and algorithms, Data validity. For all these reasons, Big Data is necessarily at best a fuzzy source of truth — but that does not mean that it cannot be used for important business decisions. Here are solutions: Define the ROI for Big Data quality, Robust governance, Transparency, Training, and Ethics.
Is AI as good as human to human interaction when it comes to customer service?
All customer service interactions are on a spectrum that has two axes: emotion and urgency. New AI tools are rapidly emerging in the support space that can address high-urgency situations quickly, but when it comes to high-emotion scenarios, no AI can replicate human empathy, so there’s still a distinct advantage to having a real person help a customer.
Is data alone enough to make a marketing decision?
If data and analytics leaders simply provide access to data and tools alone, self-service initiatives often don’t work out well. This is because the experience and skills of business users vary widely within individual organizations.
How do bots and “fake” accounts factor into the accuracy of data?
The difference between “good” bots and “bad” bots are: More than half of internet traffic is bots, Accessibility attracts bots and fake accounts, Bots are programmed to perform simple internet tasks repeatedly, The Internet Research Agency is where many Russian bots come from, Bots don’t just spread fake news — they can create it; thus they influence the accuracy of data.
Can we make future marketing decisions based on past behavior the data provides?
The problem of customer behavior analysing that from a psychological perspective, there is little validity to this assumption. In today, we can leverage advanced user-experience technology to evaluate and micro-monitor on-page visitor behavior. Based on this, we should be personalizing according to each individual’s mindset, affect and level of suggestibility.
Will personal privacy controls affect the accuracy of big data?
Data analytics are not 100% accurate. The data files used for big data analysis can often contain inaccurate data about individuals, use data models that are incorrect as they relate to particular individuals, or simply be flawed algorithms. These risks increase as more data is added to data sets, and as more complex data analysis models are used without including rigorous validation within the analysis process.
