Global Data Science Forum

AI and Big Data: Even More Information about Your Customers

By Mira Stone posted Wed July 15, 2020 05:24 PM

  

As technologies that take and analyze data proliferate, so, too, do businesses' experiences to contextualize data and draw new insights from it. Artificial intelligence is a critical tool for data capture, analysis, and collection of data that many businesses are using for a range of designs, including better understanding day-to-day operations, making more informed business choices and learning about their clients.

Customer information is a focus field all its own. From customer behavior to predictive analytics, organizations regularly capture, store, and analyze large volumes of quantitative and qualitative data on their customer base every day. Some organizations have built an entire business model around customer data, whether they're businesses selling personal data to a third party or creating targeted ads. 

Here's a look at some of the methods businesses capture consumer data, what they do with that data, and how you can use the same methods for your own sales purposes.

Anything users do online, from buying to likes and subscriptions, is there forever. This large volume of information is named big data. It is of great importance for business. We will understand how big data and artificial intelligence help collect information about clients, raise companies’ income and change the system.

Big Data and Clients: Tons of Data for Sales Growth

Big data points to the large volumes of information on an object or phenomenon, collected from numerous online references by using a special technology. Big data can be both structured and disorganized. For example, big data on consumers may include: 

  • Personal data, i.e. name, email, telephone, gender, age, location;
  • Time used online and hours of the most important engagement;
  • Most visited places, i.e. shops, cafes, offices; fields of interest;
  • Social network activity, i.e. subscriptions, likes, comments;
  • Search queries; 
  • Number of visits to websites and applications;
  • Purchase history;
  • Information on users’ movements on foot, by car, public transport or taxi. 

This is not an exhaustive record, but imagine the window of possibilities for sales and opportunities offered to business by big data analysis with the help of AI. The importance of personal data goes to a new level and needs new technologies.

AI in Big Data: Collaboration for Best Results

The mystery of such rapid evolution of big data methods lies in the use of AI. With the help of machine learning, big data gets more and more information and delivers greater accuracy for its review with each passing day. 

Use of AI solves the difficulty of personal data research: “smart” algorithms cannot acknowledge and identify a person. Computer programs gather vast amounts of personal data, but they are “impartial”, which serves to maintain confidentiality. Big data technologies resolve two matters at once: getting as much as possible about clients and protecting their privacy setting while shopping online in the meantime. AI is so much better in it than any human is.

Big Data Tasks in Customer Relations

The central plank of big data is that the more you know about something, the more comfortable it is to manage it happily and to predict what will occur next. In the meaning of customer relations, it means performing the following tasks: 


  • Building an actual profile of the target users;
  • Knowledge of their interests, choices, complaints, and wishes; 
  • Providing specific advice based on personal data analysis;
  • Detecting client categories for relevant goods and services; 
  • Defining dates of products produced with a focus on profits maximization. 

Big Data Analyst: In-House vs. Outsourced

Big data investigators are professionals who process big data. Such specialists can be both in-house or outsourced. For example, if a company receives data using its own system framework, it needs in-house investigators. In case it works with a ready-to-use structure, outsourcing will do.

Big data and AI technologies have a possible effect on business. 

Data privacy regulations

So much user data has been captured and analyzed that governments are crafting strict data and user privacy regulations designed to give somebody a modicum of control over how their data is used. The European Union's General Data Protection Requirements (GDPR) lays out the laws of data capture, storage, usage, and giving for companies, and GDPR regulation and agreement doesn't just matter for European peoples – it's a law applicable to any company that targets or collects the personal data of EU citizens. Businesses that ignore GDPR compliance and fail to abide by their legal duty to uphold consumer privacy may face fines of up to 20 million euros or up to 4% of annual income, whichever is higher. 

Data isolation has made it to the U.S. in the form of the California Consumer Privacy Act (CCPA). The CCPA is, in some ways, related to GDPR regulation but changes in that it requires buyers to opt out of data collection rather than placing the onus on service providers. It also describes the state as the entity to develop appropriate data law rather than a company's private decision-makers.

Data privacy laws are changing the way companies capture, store, share and interpret customer data. Companies that are so far untouched by data privacy laws can require to have a greater legal responsibility to protect consumers' data as more customers demand privacy preferences. Data gathering by private companies, though, is questionable to go away; it will simply change in form as businesses adjust to new laws and regulations.


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