Okay, so maybe my title is slightly over the top. But my musings and meetings in the weeks since attending Retail Week’s Tech. in London, have led to this being my key event takeout.
Underlying the exciting and varied session themes, and speakers from all walks of retail, was the feeling that the industry is in a major period of experimentation. In a search for the next big thing in consumer engagement, retailers are looking at a vast range of new technologies in a race to survive.
We heard from retailers already trialling voice, artificial intelligence, robots, augmented reality, automated chat, and blockchain. And then we heard about the potential of more futuristic technologies, including mixed and virtual reality devices to enhance in-store shopping experiences, biometrics to enhance payment security, and self-driving vehicles for delivery.
For me personally, voice is a really interesting case study about user adoption. Voice technologies have been around for a few years now, but devices such as Amazon Echo are only just starting to really take off. What this lag time between launch of new technologies and mass market adoption means for retailers trialling the next wave of technologies, particularly in advanced machine learning and AI, will be interesting to observe.
Forward-thinking retailers like Amazon and Walmart today leverage the vast amounts of new data these technologies possess, and build analytical muscle to enable targeted marketing, tailored assortments, and effective pricing and promotions. Gathering and analysing data to understand the needs, preferences, and attitudes of growing consumer segments, will be especially important, as will understanding individual consumers and customising offers on a one-on-one basis.
Some of the challenges of implementing advanced machine learning and AI technologies to revolutionise the retail experience and build customer loyalty, are the limited capabilities, prohibitive costs, and long lead times in experimentation, not to mention potential disruption to the business. So how can this challenge be addressed?
Retail leaders must assess their investments in advanced data analytics to ensure that they are bringing new actionable insights to the biggest business problems; what steps is the organisation taking to turn data into practical actions to increase revenues, reduce costs, or free up capital; and what capabilities is it building to become more analytically driven?
To really accelerate advanced analytics activities now, retailers must continue to move towards data-driven experimentation, which involves using a variety of existing and new data sources to test innovative concepts in a secure analytical ecosystem. Identifying an analytics industry partner can help define a key business problem to investigate – be that promotional strategy, customer segmentation, or channel shifts – and to ‘time-box’ the investigation. By using sprint-based delivery principles, opportunities (and mistakes) can be identified early, and these learnings can be built into the process.
And bringing these aspects together to develop and scale the right analytical asset – whether a Chatbot to enhance customer service capabilities, or a machine-learning personalisation algorithm to deliver true one-to-one customer experiences – and is the key to avoiding extinction.