Shahid Hanif is the Chief Technology Officer and Founder of Shufti Pro, A biometric identity verification (IDV) solution.
Data is central to our current digital infrastructure. A report by the United Nations Conference on Trade and Development (UNCTAD) highlights the growing importance of data in our digital economy, highlighting its positive impact on global inclusive trade and development.
The world has seen a huge surge in data science technologies. Machine learning, artificial intelligence (AI) and big data are the leading technologies in this field. Integrating them into normal business processes can help sustainable growth. While many businesses still rely on manual data processing mechanisms, improvements in our technological infrastructure can help advance business processes.
Navigating a Consumer-Centric Marketplace
Our current digital market is primarily consumer-centric. SaaS providers are moving toward niche-specific solutions rather than providing entire suites to the consumer base. To this end, businesses must create consumer-centric products that accurately target consumer emotions, improve engagement and satisfy consumer needs.
Data sets are collected and refined through data cleaning/refinement processes, which are then processed into consumer data. It involves structuring unstructured data into organized forms, identifying similar values in the dataset, and classifying them into their specific category. Consumer data is paramount for this purpose as it gives businesses the insights needed to develop effective strategies.
Importance of tracking consumer behavior
Monitoring consumer behavior is one of the main applications of data analysis. The first aspect is to identify how consumers act when subjected to different interfaces. The dataset collected from this information is then refined and used to develop patterns. These patterns are often used to create personalized solutions. Another primary application of tracking consumer behavior is predictive analytics. In predictive analytics, data collected on users is used to design proactive strategies to avoid potential problems.
By effectively tracking consumer behavior, businesses can better improve their conversion rates. Netflix, Amazon, and Spotify track consumer behavior and use it to better sell their services; They are prime examples of consumer-centric marketing strategies. They collect data on watch history, favorite styles, and browsing history, which is used to generate personalized recommendations for individuals. Nearly 80% of users trust the recommendations given to them by these algorithms.
Setting up integrations to compliment data dynamics
Now that we know the importance of data, let’s discuss some of the ways businesses can use emerging technologies to boost business growth.
cloud computing
Managing and organizing large amounts of data is a prevalent challenge. Cloud computing provides businesses with a scalable and resource-friendly way to store data. Along with storing large amounts of data, this process also helps businesses keep sensitive information secure. Spending on public cloud services worldwide is expected to grow by 21.7% to $597.3 billion in 2023.
Integrating cloud computing processes into your business model requires identifying complex details about your company. It is important to identify your specific needs and enhance your processes accordingly. Once the cloud computing process is integrated with your processes, training employees to use it efficiently should be your top priority.
Artificial Intelligence Automation
To successfully implement an AI automation system, businesses must first ensure data flow and proper processing of all data sets as AI is completely dependent on data. Before adopting AI automation solutions, business owners should assess their organization’s capabilities and the infrastructure used to scale accordingly.
Data processing is a revolutionary technology; Its only problem is that it is time and resource intensive. Small businesses, especially startups, cannot afford to hire staff and integrate individual processes to refine data sets for a specific task. To overcome this hurdle, businesses can take advantage of automation technology. Data science combines ML and AI technologies to create independent automated processes. Automation technology can be applied to simple processes such as data entry to large-scale operations such as manufacturing.
Identity Verification and Cyber Security
In addition to storing and managing datasets, ensuring their security is critical to the success of a business. By 2023, the average data breach cost in the United States was $9.48 million. Validation checks require flexibility and versatility, as these requirements are constantly changing.
IDV technology can help businesses avoid potential losses by protecting their sensitive data from cybercriminals. Compliance is also an essential aspect; These solutions are automated and have the ability to conduct independent compliance checks. Automated reports help businesses comply with the rules and regulations of their country or jurisdiction.
When using IDV technology, be sure to seek feedback from users and adapt your technology based on their experiences and suggestions. This iterative process can help improve the effectiveness of the technology and user satisfaction by understanding key questions. Are the steps clear? Is this process extremely time consuming or complicated? Does this cause frustration or confusion? Understanding these aspects helps refine the user experience.
To successfully adopt IDV technology, users need to establish clear objectives and goals they want to achieve with adoption. This ensures that the integration aligns with the organization’s business model and infrastructure. There is a need to establish collaborative teams and departments that promote effective internal communication and data management. Without streamlined internal communications and processes, the effectiveness of IDV processes can be hindered. Additionally, collecting customer feedback and key IDV metrics such as accuracy, fraud detection and false positive rates directly contributes to improving a company’s IDV processes by ensuring continuous monitoring.
Transforming Business: Taking a Proactive Approach
Adopting modern data processing technologies and combining them with AI and ML technologies is a unique and powerful mix. This has allowed better decision making and has significantly helped in growing businesses. With a holistic view of industry trends and consumer data, business owners can make informed business decisions. Furthermore, predicting growth patterns is also now relatively easy, as predictive analytics is accessible to businesses in the market.
In other words, business processes are now more efficient than ever, and technologies complement data mobility to free up resources that can be used in other business areas. Human resources and finance are used effectively, which promotes growth. It is important for tech leaders and leaders to understand today’s modern technologies and how these innovations can be integrated into their operations.
Global markets are evolving at an unprecedented rate, and consumers move from one service to another in a matter of seconds. The only inconvenience they face is in switching services. Enhancing business processes by understanding data science technologies can lead to a pleasant experience for both consumers and providers.
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