There is a fundamental shift happening in the retail ecosystem, which has now become a hypercompetitive battleground where both brands and retailers are in a race vying for attention and striving to provide more personalised and differentiated experience to their customers.
By Google Cloud JAPAC Director Retail & Consumer Sameer Dhingra.
Eighty-three per cent of customers say they want their shopping experience to be personalised in some way, and effective personalisation can increase store revenues by 20% to 30%. In addition, the ongoing pandemic has further complicated purchase journeys as shoppers experiment with new store formats and categories, and become accustomed to digital platforms and various fulfilment options. Many have tried these for the first time, and most intend to continue with them, according to a recent McKinsey study.
As these shopper purchase journeys evolve further, one thing is for sure – customers now have higher expectations of retailers as they look for relevant products and experiences in line with their individual preferences and needs. This means retailers need to up their game and have the ability to proactively engage with their shoppers, from anticipating and predicting their needs to create more personalised experiences.
Unlock data to drive personalisation
Becoming data-driven is key to understanding consumer behaviour and preferences which is the foundation for personalisation. Modernising your data warehouse, leveraging a big data platform, processing and analysing streams of data in real time are now essential building blocks for your data foundation. Making this data accessible with business intelligence platforms makes it easy to consume information, ensuring that the power of insights is available for wider adoption.
By bringing multiple datasets across an organisation together, you can improve shopper experiences and customer lifetime value by optimising in-store/on-site operations. Large retailers like Bed Bath & Beyond are working on establishing a single view of customer data across their portfolio with a view to drive personalisation, enhance fulfilment capacity, and optimise merchandise planning and demand forecasting.
Another great example would be Zulily as they have leveraged their data platforms to build real time analytics capability enabling better understanding of their consumer behaviour, improved collaboration with their suppliers and smarter decision making. In addition, technologies like Recommendations AI can provide personalised recommendations based on search and changes to product ranges, pricing and offers. The ideal solution architecture should enable collection of on-site as well as in-store transaction data along with customer event data which then can be streamed in near real time to a common data platform for targeting, optimisation and personalised recommendations.
Unlocking your data to drive personalisation can dramatically improve customer engagement and experience, enhance transaction conversation rates and drive revenue.
What is your innovation agenda?
Defining your innovation agenda is dependent on digital maturity and business priorities. Irrespective of the need, the logic demands careful consideration and prioritisation of the solution areas based on business impact, strategic importance and execution complexity. More often than not, getting real time visibility of data across your retail value chain is the first step before you can begin to optimise the information in order to personalise the experience.
Building a strong data foundation across multiple silos of information is the first step in this direction. At the same time, having the technology is not enough. It is critical for you to leverage your data and analytical capabilities to establish a System of Insight which you can then use to power data-driven decision making within the retail ecosystem.
What’s clear is that data will be the new driver of improved customer experiences. Retailers that make it easy, personalised and enjoyable for customers will win in the new normal. This capability however is still nascent as retailers adopt and build strong data foundations to create more personalised experiences – a huge area of focus as you work to recreate what “shopping” looks like now and in the future.
