Making use of AI in retail
Becoming a data-driven organisation is consistently topping the agenda for businesses within the retail sector. Yet, historically, many retailers have been prevented from achieving this due to a lack of skills and budget to implement the technologies needed to turn their data into actionable insights. Now, with the availability of retail solutions that integrate artificial intelligence (AI) and machine learning (ML) capabilities, that all stands to change.
The increasing democratisation of these technologies means it is now easier than ever for businesses of all sizes to implement them without needing to hire a team of data scientists. In doing so, they can expect to gain the significant benefits offered by AI and ML for retail, ranging from increased efficiency to more effective supply chain management and providing more personalised customer experiences.
But, before implementing these technologies, there are a number of considerations for retailers to ensure that they deliver real value – starting with getting their data in order.
Data as the foundation of AI retail initiatives
As with many business initiatives, data is the starting point for AI adoption. However, many organisations still do not know how to obtain the quality and quantities of data required to feed AI models. Fortunately, the use of an enterprise – or smart – data fabric, a new architectural approach that speeds and simplifies access to data assets across the entire business, can help to overcome this obstacle.
Smart data fabrics interweave data from multiple sources and different formats, using a multi-tier approach that cleans data and employs an integration layer to make it usable. The fabric does this while leaving the data where it is, with lineage tracked for every item, enabling users to see where it has come from. Machine learning incorporated in the fabric enables dynamic queries and data analytics, along with API management capabilities.
This will help retailers to more easily gain critical insights from their data which they can deploy for a wide range of purposes including new service offerings and products. By allowing existing applications and data to remain in place, the smart data fabric approach enables retailers to gain business value from all their data sources quickly and flexibly so they can power their business initiatives.
Taking this approach of implementing a smart data fabric will give retailers the clean, dependable data they need for more advanced applications that meet the evolving demands and expectations of today’s consumers. These applications will use the data to adapt services to each customer’s preferences, history, and potential, optimising interactions and streamlining processes.
Slow and steady adoption
For many retailers, tight budgets mean hiring a team of data scientists straight away is out of the question. Yet, this doesn’t mean they can’t begin to reap the benefits of AI.
For these businesses, the most effective approach to implementing AI is to start small and introduce the technology incrementally. They can do this by identifying the business needs that would most benefit from the use of AI, whether that be forecasting or customer experience, for example. Taking this approach will allow them to experience some of the benefits of AI adoption and garner any learnings before moving on to the next business need.
What’s all the fuss about?
In a world where consumers demand increasing personalisation of services, AI holds enormous potential for retailers to deliver. So, to be competitive, more organisations should be using the technology to provide a customer experience that steps beyond what is now commonplace, into a more intelligent understanding of people’s needs and how to meet them. The use of AI will enable them to offer far greater personalisation and more persuasive targeting with offers, recommendations, guidance, and advice, to ensure they stand out within their market.
Additionally, AI has the potential to transform decision-making, giving retailers access to hard evidence and new predictive capabilities based on reliable data which can be used to further functions such as supply chain management and scheduling. This will help to streamline processes and increase efficiency across the business.
Delivering value for the business and customers
Ultimately, the potential for AI within the retail sector is huge and retailers should no longer be held back by a lack of skills or data-related challenges. The combination of a modern, smart data fabric approach to data management and the use of AI-enabled tools will help these businesses to capitalise on these technologies without significant investment, allowing them to deliver enhanced customer experiences, gain a competitive advantage, and improve business processes.
Andrew Tunstall, Sales Manager, InterSystems
