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How have consumer expectations changed over time? What can retailers do with all the data they collect? Is data science, analytics and technology the key to success?
In this episode, we discuss how retailers can drive value from data with Andy Tudor, CEO of Clekt. Andy has an in-depth knowledge of retail, including what it takes to succeed in a challenging market. Before co-founding Clekt in 2020, he held senior roles with retailers like WHSmith, Monsoon Accessorize and Debenhams.
Consumers are demanding fresh, engaging experiences.
Customer expectations are ever-changing. Not only this, but consumers assume retailers will adapt quickly to offer fresh, new experiences that keep them engaged.
Crucially, customers are seeking out personalised experiences. They want brands to treat them as individuals, with propositions tailored to their needs. Retailers need to be in tune with one-to-one relationships with their customers. Do they expect your brand to be ethically minded? Environmentally responsible? Sustainable?
We’ve got the world in the palm of our hands.
Why exactly are customer expectations changing? Instant gratification is a key driving force.
Technology means information is just a tap or a click away – we’ve essentially got the world in the palm of our hands. Now customers expect the same from online retail interactions; from buying products to booking appointments.
The likes of Google and Amazon have set the bar high. However, it’s difficult for all brands to replicate the same level of immediacy – and there’s a feeling of dissatisfaction if these high expectations aren’t met.
Data is an asset.
In the modern world, data is arguably retailers’ most important asset. The sticking point is understanding how to leverage its power.
Historically, technology has been an expensive investment and implementing targeted analytics has been challenging. Businesses at various stages of data maturity have often struggled to translate objectives into a coherent data and technology roadmap.
However, times are changing, and data presents a huge opportunity for retail – especially when it comes to changing consumer expectations.
The flywheel effect.
Well-established retailers have oodles of data flowing around their organisations. However, it’s often siloed in operational systems and databases, despite being a source of untapped value.
Bringing data together from different sources helps retailers find out more about the way customers are interacting with their brand. Think of it as a ‘flywheel’ effect: a virtuous cycle triggering business growth (see Peter Thiel’s book ‘Zero to One’).
However, analytics shouldn’t be treated as a one-time project. Ideally, it should be embedded into business processes for ongoing decision making. Doing so means retailers can start applying insight across the business – from new product development to operational efficiency and marketing.
Over the last couple of years, technology has become more affordable – so being a data-driven business is no longer inaccessible.
Technology is a tool for better decisions.
Traditionally, retail decisions have been made based on experience and gut feel. However, in the information age, retailers collect too much data for humans to process.
Technology isn’t replacing highly knowledgeable team members – instead, it’s giving them the tools they need to make better, informed decisions. It’s automating routine tasks so employees can apply their expertise in other areas where they can make a bigger difference. It’s arming them with insight so they can make better decisions about which products to buy and how to merchandise them in physical stores or on a website.
Similarly, recruiting technical talent is tough – such as data scientists, data engineers and data architects. This is where data science agencies and software come in. No-code platforms are democratising access to data and insight – enabling retailers to take advantage of complex, sophisticated analytics in a point and click environment.
Data empowers teams with knowledge and insight.
Investing in data and analytics has a financial upside – such as increased profitability and reduced operating costs. It also encourages a cultural shift; by creating a single source of truth and focusing business operations and customer interactions around it.
Crucially, it empowers teams with knowledge and insights, so that they can make better commercial decisions and pinpoint areas to optimise and improve.
Are you wondering where the power of data science, AI and decision intelligence could take your retail business? Contact us to find out more about how we can help you make better assortment, pricing, media, eCommerce and supply chain decisions.