As a major force in many markets, Gen-Zs shun slow and non-personalized service. How can organizations tool up to placate them?
As Gen-Zs youth overtake baby boomers and millennials as the major consumer market, businesses that cannot keep up and exceed these digital natives’ rapid responses and expectations will not stay competitive for long.
Businesses will find that the better the experience they deliver, the better the returns that can be expected. Investing in data technologies will provide the right insights to adapt, improve revenue generation and address operational problems such as UI and UX challenges.
Big, technologically progressive names such as Macquarie Bank, Meesho, Tokopedia, Grab and so on, have embraced such technologies and even turned into industry disruptors with their ‘always on’ customer engagement. Their ability to leverage real-time data is a major reason for this.
Harnessing data at rest and in motion
Organizations that want to make better decisions quickly need the discipline to apply logic and mathematics to data for the right insights. This requires mastery in collecting and using both data at rest and data in motion, from a variety of sources such as transactional data, GPS, website, social platform data, and more — to engage customers in the moment with unique customer personalization and recommendations; and engaging real-time customer experiences.
Real-time data can be used to improve existing critical processes such as inventory management, fraud detection and fleet monitoring. Unfortunately, many organizations have been held back by:
- complex data infrastructure and architectures
- legacy application silos
- poor data warehousing
- pools of unstructured data
Consequently, businesses are unable to support the needs of present-day and future customers.
Due to data siloing, collaboration and development of desirable customer offerings get stunted — especially because stored data becomes quickly obsolete and are only batched analyzed using archaic processes — resulting in insights that are no longer relevant.
Real-time cloud-based data
When real-time data is centralized, the detriments of siloing are reduced. At the same time, cloudification of real-time data also requires a brand-new approach and data architecture.
The higher capacity and dynamic elasticity of cloud data infrastructure will result in more agility and speed in terms of settings, computing power, storage, and network options.
And because the cloud itself is decentralized, data and information are also subject to lower risks of data loss, protected with industry-level security while maintaining ease of access for all stakeholders.
Also, moving real-time data to the cloud can be adopted in increments, trialed and fine-tuned using ‘pay-as-you-go’ models instead of large capital investments upfront.
Beyond Gen-Z expectations
With Gen-Zs becoming the primary audience on digital platforms today, organizations can no longer ignore the need to get up-to-speed in customer engagement.
If data siloes and suboptimal data intelligence are impeding how an organization extracts the right insights and engagement strategies instantly and fluidly, this should call for measures to leverage cloud computing and real-time data analytics.
It is either play ball, or you are out.