Retail’s biggest challenges (and why AI is the answer)By Jon Taylor on March 19, 2018
At first glance, you could be forgiven for thinking that the retail industry hasn’t enjoyed the best start to 2018.
The unfortunate plights of Toys R Us, Maplin et al have dominated the headlines in recent months, leading many to believe that it’s all very much doom and gloom across the sector at the moment.
However, it pays to be positive, and although some UK retailers are going through some tough times, this provides valuable lessons that other businesses can learn from. It’s now more apparent than ever that those retailers who don’t change and adapt to the changes taking place in their industry will struggle. It’s 2018 – and it pays to be smarter.
We’re living in what we like to call the ‘data economy’, where insights-driven retail businesses (think Amazon, Asos, Boohoo etc.) are thriving. Across the industry, artificial intelligence is being applied in new ways across the entire product and service cycle, from assembly to post-sale customer service interactions. The ability to acquire data, and to leverage it using the power of AI, allows businesses to not only be competitive, but enables them to overcome some of the toughest challenges in retail.
So, what are these challenges? Let’s take a look…
Understanding the customer journey
Consumer’s relationships with brands are changing; customers are frequently hopping between different channels and devices, but expect personalisation at every touch point, whether that’s in store, on a website or on social media. The customer journey is more complex than ever, and this is a serious problem for the majority of marketers – in fact, only 8% of retailers are currently using full-cross personalisation.
Retailers may have access to a plethora of useful data, but it’s more often than not highly fragmented, isolated and disjointed – making it difficult for marketers to get a full picture of their customer and deliver the perfect customer experience.
That’s where artificial intelligence comes in to save the day. By leveraging data across different sources, retailers can join the dots between all online and offline activity, creating a detailed single customer view. With this data, retailers are able to deliver the hyper-personalised experience that the customer expects and deserves.
Supply chain risk monitoring
As KFC’s ‘chickengate’ incident proves, risk is inherent to the supply chain, regardless of how big or famous your business is. Successfully being able to anticipate and manage these kind of mishaps has been an issue for businesses of all industries for a long time, and while there are traditional methods in place that can help, it’s still difficult for companies to spot potential issues before it’s too late.
With AI, though, you’re able to dig deeper into your data, spotting all kinds of probable risks or disruptions well ahead of time. Artificial intelligence is incredibly handy when it comes to drilling down into your data pools, cleverly locating that one tiny piece of data that could make all the difference and save you copious amounts of time, money and resources. Let’s face it, at the end of the day, the people need their fried chicken.
Uh oh. This is a big one – these four little letters are a cause for concern for a lot of businesses. It’s a hot topic at the moment, and complying with the incoming EU-wide General Data Protection Regulation is absolutely essential for all businesses that hold and process customer data.
Retailers are now under pressure to know exactly where their data is, and what it’s being used for; they need to be able to show that they’re maximising their data security and are being completely transparent with their customers regarding how their personal data is being used.
Although GDPR is undeniably a challenge for retailers, it also presents a fantastic opportunity to get organised and uncover some of the potential locked inside your data – you have to be careful with what data you’re keeping, so if you’re keeping it, why? What could you use it for?
AI is a big help here – we’ve built an automated solution, powered by machine learning, which helps retailers get on the right track towards GDPR compliance. It identifies what personal data you have at a much quicker rate and to a higher degree of accuracy, avoiding human error. It works across legacy systems and siloed data, too. Speaking of which…
We’ve touched on this already, but a big issue that retailers have when it comes to data is its fragmented nature. You’ve more than likely got an incredible number of insights right there at your fingertips, but if it’s disjointed and spread across 25 bricks and mortar stores and extinct loyalty card schemes, how do you make the most of it?
Using AI allows you to bring everything together in one nice neat package. Rather than digging aimlessly into a multitude of different datasets, you can take a step back, think about what business problems you actually want to solve and pick out the data that can help you do precisely this.
Where do I start?
All sounds good, right? But where do you begin? The vast majority of retailers out there know they need to be doing great things with data and artificial intelligence, but aren’t sure what, or how. For many, the idea of overhauling the way they manage their data and generate their insights can be somewhat overwhelming – but it doesn’t have to be.
Peak are the pioneers of artificial intelligence for businesses, providing a service on a subscription basis that plugs straight into your business systems, streaming all of your data into one place and delivering invaluable insights. It’s risk-free, there’ll be no disruption to your business-as-usual, and if you’re not getting value from it, you simply switch it off.
Insights-driven businesses have been proven to win customers and grow eight times faster than global GDP. Those who don’t take this leap into the future are setting themselves up for failure, and the woes of the Toys R Us of this world only further reaffirm this view. We’re firm believers that retailers need to be using AI not just to compete, but to survive.