This article was contributed to TechCabal by Stefan Gerber.
As the world transitions into the information age, data-driven insights, automation, and data management are becoming increasingly vital for business survival. For retail businesses, whose success depends on maintaining a healthy customer base, data-rich loyalty programs are essential tools for achieving this goal.
In May 2024, the market research firm BrandMapp and consultancy Truth published their 2023/24 Loyalty Whitepaper, which revealed that 76% of South Africans now use a loyalty program in some form or another. The study also revealed that 30% of the respondents indicated they were using loyalty programmes more than the previous year, revealing that consumers were becoming more desperate for any discount or deal against the backdrop of rising cost of living.
The demand by the consumer class for more financial relief from loyalty programmes is increasing and provides a golden opportunity for businesses that manage these data-heavy systems. As digital technology rapidly evolves, so is how companies—retail or not—manage their data and the systems they use to leverage it.
Businesses are now seemingly rushing to integrate artificial intelligence into their operations to streamline business processes without pausing for thought on the current condition of their data management systems. Before one can even think of advancing their systems into the age of intelligence, one must adopt the principle of effective data management. If one were to simply skip this and input garbage data into their AI applications, garbage data is bound to be the product.
This justifies the need for businesses that are heavily reliant on data to avoid scrambling to collect it on an ad-hoc basis. To leverage AI to its true potential, businesses need to begin with data warehousing. Without further delay.
A data warehouse is a centralised depot that stores data from numerous sources in a single location, making it easily accessible and crucial in supporting business intelligence and analytics. To make this more relatable, imagine a big library with countless books, with each book representing a different type of data, such as sales, customer information, or website engagement. A data warehouse is like a catalogue that collects and organises all these books into one place, enabling the user to find specific information more easily, see relationships between different data points, and gain valuable insights.
The work of a data warehouse is complemented by the functioning of a customer data platform (CDP), a software application that collects, unifies, and organises customer data with the primary purpose of providing a single, comprehensive view of each customer, allowing for personalised marketing, sales, and customer service. In simple terms, think of a CDP as a magic scrapbook that collects and combines all the relevant information about each customer from various sources.
The data warehouse is the repository for all data, while the CDP uses this data to create a personalised view of each customer. But how does this practically work?
As we progress further into the online shopping dynasty, the demand by customers for more personalisation in their online shopping experience is overwhelming. This requires businesses to have systems in place that can operate at scale. Picture a customer who purchases a Nikon camera online. With the help of data warehousing and CDP systems, an online store can catch their customer before checking out and provide various recommendations, in real-time, based on different data sets, such as a camera lens of the same brand of camera they picked, products within the same category as the camera they chose, or other products associated with other customers who demonstrated a similar purchasing behaviour. This experience can easily be replicated with loyalty programmes for customers still shopping at physical stores.
Omnichannel experiences are also particularly important, and refer to integrated customer experiences across multiple channels and touchpoints, whether online or offline. The goal of an omnichannel approach is to provide a consistent and cohesive brand experience for customers, regardless of how or where they interact with a business. An example of an omnichannel experience in retail would include the process of a customer browsing for a product online, checking in-store availability, and then picking up their purchase at the physical store.
On top of personalisation and omnichannel experiences, data warehousing and CDP systems also help businesses satisfy another desire of today’s digital consumer: instant responses and feedback. If you can use these tools in a manner that leverages AI-based analytics, you can guarantee a rapid transformation that will make your company far more competitive in the South African (and even global) market.
This is exactly what makes a retail giant like Shoprite so successful, especially when executed through its various loyalty programmes. With the right data management systems in place, aided by machine learning infrastructure, any business has the potential to build a data kingdom like Shoprite and retain customer loyalty through personalisation and instantaneous feedback.
While these systems likely sound costly for the little guy, there is an opportunity to start by targeting low-hanging fruits at a reduced cost while gaining most of the benefit for your business. Working with local experts can help you learn about the easiest ways to get started on your data journey by building systems specifically catering to your needs.
Regardless, the goal of leveraging cloud technology, data warehousing, and CDPs is to achieve rapid business transformation, enabling your business to gain a competitive advantage, improve project timelines, secure funding, and strengthen stakeholder relationships.
In the age of intelligence, where data is the new currency, businesses that prioritise effective data management and leverage AI-driven insights will be the ones to reap the rewards of loyalty, retention and ultimately, reign supreme in the market.
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Stefan Gerber is the co-Founder of Tregter, a South African data-management agency.
