Shahid Hanif is the Chief Technology Officer and Founder of Shufti Pro, a biometric identity verification (IDV) solution.
Data is predominant in our current digital infrastructure. A report by the United Nations Conference on Trade and Development (UNCTAD) notes the increasing importance of data in our digital economy by highlighting its positive impact on our global inclusive trade and development.
The world has seen a massive surge in data science technologies. Machine learning, artificial intelligence (AI) and big data are leading technologies in this sector. Integrating them into general business processes can help sustainable growth. While many businesses still rely on manual data processing mechanisms, revamping our tech infrastructure can help upscale business processes.
Navigating A Consumer-Centric Market
Our current digital market is primarily consumer-centric. SaaS providers are moving towards niche-specific solutions instead of providing a whole suite to the consumer base. For this purpose, businesses should create consumer-centric products that accurately target consumer sentiments, improve engagement and meet consumer needs.
Data sets are collected and refined through data cleaning/refining processes, which are then processed into consumer data. This includes structuring unstructured data into organized forms, identifying similar values in a dataset and categorizing them in their specific category. Consumer data is paramount for this purpose because it gives businesses the necessary insights to develop effective strategies.
The Importance Of Tracking Consumer Behaviors
Monitoring consumer behavior is one of the main applications of data analytics. The first aspect is identifying how consumers act when subjected to various interfaces. The datasets gathered from this information are then refined and used to develop patterns. These patterns are then often used to create personalized solutions. Another primary application of tracking consumer behaviors is predictive analysis. In predictive analysis, the data gathered on users is used to design proactive strategies to avoid potential problems.
By effectively tracking consumer behaviors, businesses can better improve their conversion rates. Netflix, Amazon and Spotify track consumer behaviors and use them to sell their services better; they are prime examples of a consumer-centric marketing strategy. They gather data on watch histories, preferred genres and browsing histories, which are then used to generate personalized recommendations for individuals. Approximately 80% of users trust the recommendations made to them by these algorithms.
Setting Up Integrations To Compliment Data Dynamics
Now that we know the importance of data, let us discuss a few ways businesses can utilize emerging technologies to promote business growth.
Managing and organizing large amounts of data is a prevailing challenge. Cloud computing offers businesses a scalable and resource-friendly method for data storage. Along with storing large amounts of data, this process also helps businesses safeguard sensitive information. Spending on worldwide public cloud services is expected to grow by 21.7% in 2023, reaching $597.3 billion.
Integrating cloud computing processes into your business models requires identifying intricate details regarding your company. Identifying your specific needs and scaling your processes accordingly is crucial. Once a cloud computing process is integrated with your processes, training the employees to use it efficiently must be your top priority.
Artificial Intelligence Automation
To successfully implement an AI automation system, businesses must first ensure data fluency and proper processing of all data sets because AI is totally reliant on data. Before adopting AI automation solutions, business owners must assess the capabilities and infrastructure of their organization, which is then 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 function. To overcome this hurdle, businesses can leverage automation technology. Data science has combined ML and AI technologies to create independent automated processes. Automation technology can be applied to processes as simple as data entry to large-scale tasks such as manufacturing.
Identity Verification And Cybersecurity
Besides storing and managing datasets, ensuring their safety is crucial to a business’s success. As of 2023, the average data breach cost in the United States amounted to $9.48 million. Verification checks require flexibility and versatility, as these requirements are constantly changing.
IDV technology can help businesses avoid potential losses by safeguarding their sensitive data from cybercriminals. Compliance is an essential aspect as well; these solutions are automated and possess the ability to perform independent compliance checks. Automated reports help businesses stay compliant with the rules and regulations of their country or jurisdiction.
When using IDV technology, be sure to gather feedback from users and adapt your tech based on their experiences and suggestions. This iterative process can help improve the technology’s effectiveness and user satisfaction by understanding key questions. Are the steps clear? Is the process too time-consuming or complex? Does it cause frustration or confusion? Understanding these aspects helps refine the user experience.
To successfully adopt the IDV technology, users need to establish clear objectives and goals that they intend to achieve with the adoption. This ensures the integration aligns with the organization’s business model and infrastructure. Collaborative teams and departments that promote effective internal communication and data management need to be established. Without streamlined internal communication and processes, the effectiveness of the IDV processes can be hindered. Moreover, gathering customer feedback and key IDV metrics such as accuracy, fraud detection and false positive rates contributes directly to improving a company’s IDV processes by ensuring continuous monitoring.
Upscaling Businesses: Adopting A Proactive Approach
Adopting modern data processing technologies and complimenting them with AI and ML technologies is a unique and powerful blend. It has allowed better decision-making and has aided in upscaling businesses significantly. With a holistic view of industry trends and consumer data, business owners can make informed business decisions. Moreover, predicting growth patterns is also relatively easy now, as predictive analysis is accessible to businesses in the market.
In other words, business processes are now more efficient than ever, and technologies complement data dynamics to free up resources that can be utilized in other business areas. Human resources and finances are used effectively, which nurtures growth. It’s important for tech giants and leaders to understand today’s modern technologies and how these innovations might be integrated into their operations.
The global markets are evolving at an unprecedented rate, and consumers move from one service to another in seconds. It only takes a single inconvenience for them to change services. Elevating business processes by understanding data science technologies can lead to a pleasant experience for both consumers and providers.