AI and business strategy go hand in hand in the modern retail era, with 72% of retailers well aware of the practical application of AI in their business, and a huge 79% of retail executives planning to invest up to $1.3m in the technology. This begs the question, therefore, that if the benefits of an AI implementation strategy are well-known by all, why isn’t everyone in retail doing it?

Generally, the answer is that they haven’t quite figured out how to execute their AI strategy yet, or are still undecided on the steps they need to take to first introduce AI successfully. However, the clock is ticking, and businesses need to move now before they miss out on the advantages of being an early AI adopter.

What is an artificial intelligence strategy?

If you’re not 100% sure what an AI strategy looks like, you’re not alone. But don’t worry – here are some key steps to set you on your way to becoming AI-driven and boosting your revenues and profits…

Start small, think big

It’s important to outline what you want to achieve with AI from the outset, but take small steps to start your AI journey – don’t dive in head first at the beginning! The pace of the technology’s advancement means that what might be a “oh, that’s a cool idea” today will be a commercial reality by tomorrow; you need to focus on what you can achieve now, but also understand how this will roll into a game-changing, market-leading piece of kit in the near future. Put the right structures in place to accommodate this scale from the beginning – such as team training, upskilling, and change management processes.

Avoid point solutions

Your business is made up of multiple connected parts, and it’s important to understand and acknowledge how AI can be used across the entire enterprise; not only in terms of top-line growth, but also in terms of establishing new, positive links between teams and different business areas. This will drive a real, positive change across your business. In Peak’s experience, we’re seeing the biggest value from AI when businesses are making smaller gains across multiple business areas and functions, coming together to create a significant total AI opportunity.

Collect data – and lots of it!

Think about the masses of data your company has at its disposal – whether it’s customer, transactional, or supply chain data. No matter the business system or where it’s stored, your business is gathering data all the time. A key first step in your AI journey is collecting as much data as you can – and don’t worry if it’s not perfect or a little messy; AI can handle it!

AI strategy implementation

So, now you know more about what an AI strategy entails and some of the points your business should consider during the AI research and development phase. But how do you go about actually implementing your AI strategy framework?

Define success and measurements

One piece of advice that we give here at Peak is to brainstorm and rank your ideas in terms of the value they could ultimately offer and how difficult they will be to deploy successfully into your organization. You need to define what success looks like and how it will be measured, focusing on tangible outcomes and a demonstrable ROI – this helps when it comes to internal stakeholder buy-in, too.

You need to remember that introducing AI isn’t like getting a new CRM or ERP system, or even a shiny new data warehouse. It needs to be deployed with the intention of delivering real business change – which means you can attribute the benefits it has brought to your business in a really effective and transparent way.

Understand your data landscape

As we’ve said already, your data is key to the success of any AI project you embark upon. You should engage and empower all of your teams to get everyone on board with your plans for becoming AI-driven – even some of the teams you might not think of as being potential AI beneficiaries at first. All teams produce and store a lot of really valuable data, and the more you give your AI solutions to work with, the better the results will be. Simply put, always think of your data as the building blocks and foundation of your AI business strategy.

In conclusion, here’s a reminder of some of the key steps when it comes to planning and executing an artificial intelligence strategy in retail:

• Think big, take small steps, but make sure you act now
• Focus on outcomes and a clear ROI
• Consider the value of AI across your entire business – think of all that lovely data you have just sat there waiting to be leveraged!

Today, customers are switched on 24/7, 365 days a year. They have the power to like, follow, and buy from their favorite brands on their own terms, in the way that best suits them. In short, the modern shopper is more demanding of retailers than ever before. The key to keeping them happy, we believe, is to provide a connected retail experience – one that is powered by data and AI.

The rise of connected retail

The notion of ‘connected retail,’ also often known as ‘unified commerce,’ is becoming increasingly talked about by both analysts and retailers.

Those retailers who are successfully providing unified commerce solutions and a connected retail experience to customers are connecting three key elements of the customer journey; referred to in Adyen’s retail research report as context, convenience, and control. We believe that the only way to truly achieve this is by using AI to generate value from a retailer’s vast amounts of data.

Context refers to a customer’s desire to be treated as an individual. They have an expectation of brands to provide them with a truly personalized, one-to-one experience. Complete personalization is only possible by making the most of data – data on a customer’s brand and style preferences, shopping habits, or transaction history, for example. With AI, you can scale this personalization to talk to millions of customers on an individual basis, ensuring that you’re delivering customers the right message at the right time, via the right channel.

Convenience is, naturally, extremely important to customers. They expect to be able to browse and buy when, where, and how it best suits them – and they want to know that the items they want are in stock, in their size, ready to ship. However, for retailers, delivering convenience to customers can be tricky. With hundreds of stores, thousands of SKUs, and millions of website visitors, ensuring that the right products are in the right place is only achievable with AI. It crunches the billions of possibilities around stock allocation, merchandising, markdowns, and buying to reduce complexity and enable more intelligent decision-making.

Control is all about customers being able to engage with retailers on their own terms – with no concerns around payment options, delivery windows, or returns processes. However, this can be challenging when your retail business is dealing with thousands of orders a day and complex distribution centers. With AI, you can optimize the flow of products to and from customers, streamlining your supply chain to help warehouse operations and logistics processes run more smoothly.

By its definition, connected retail should be focused on keeping the customer happy at all times, providing them with a truly personalized experience whether they’re shopping on their phone, in the office, or in-store. But what does a connected retail journey actually  look like?

Let’s take a look at an example of an AI-optimized, ominichannel connected retail/unified commerce experience…

At Peak, we work with a wide range of retailers, helping them to rapidly leverage their data with our AI System and our suite of unified commerce-enabling solutions.

With AI, we help brands utilize personalization to target and acquire new “ideal” customers, improve productivity and forecasting in merchandising and buying functions, and streamline the supply chain to drive efficiencies and reduce costs.

If you’re interested in finding out more about the potential AI opportunity for your retail business, we’d love to hear from you.

Why? Because customers care. In fact, a whopping 93% of global consumers expect the brands they use to support social and environmental issues.

So, how can businesses take that step towards becoming more environmentally-friendly and driving retail sustainability? What can they do to meet the growing expectations of their customers? Smaller changes, such as paperless receipts and the phasing out of plastic bags, are becoming more and more commonplace, but there is more that can (and should) be done.

One area of critical importance when it comes to sustainable practices in retail is the supply chain. With thousands of SKUs and hundreds of stores, maintaining an efficient and eco-friendly supply chain in retail is one of the biggest challenges facing brands looking to take steps to reduce their retail carbon footprint.

Thankfully, like in most cases, the answer to this problem is hidden in a business’ vast amounts of data. When that data, whatever shape it’s in or wherever it’s stored, is leveraged by artificial intelligence (AI), it can be used to draw predictive insights that can help retailers streamline their supply chains and take steps towards meeting their sustainability targets. Let’s take a look at two specific areas in which AI can be an important asset when it comes to tackling sustainability issues in retail…

Waste reduction

While data has traditionally been used to look back at past performance, the predictive powers of AI and machine learning mean that it can be used to significantly improve how you forecast and anticipate demand. More accurate forecasting leads to more intelligent merchandising, buying and manufacturing decisions – having just the right amount of stock, in the right styles and sizes, in the right locations can significantly reduce the amount of excess products you’re holding and minimise unnecessary wastage.

Not only does this equate to significant financial savings, it reduces the amount of extra material, products or unsold garments being produced that would otherwise go to waste. Let’s leave this rather infamous example of Burberry burning over £19 million worth of unsold garments here…

Logistics optimisation

AI can play a key role in optimising life in the warehouse, which in turn has a positive knock-on effect on your logistics operations, both in terms of moving goods between distribution centres and delivering to customers. Better forecasting means more efficient processes throughout the supply chain; you can anticipate and cater for demand by having the right products at the front of the pick-face at the right time, ready and waiting to be loaded onto your delivery trucks.

With a more accurate view of what needs to go to where (and when!), space on your logistics fleet can be maximised, reducing the number of unnecessary journeys and maximising truck capacity. What’s more, you can use AI’s insights to plan the most efficient, eco-friendly delivery routes to customers, as well as streamline journeys between distribution centres. The environmental impact of fewer, half-empty trucks on the roads speaks for itself, and is just one of many ways AI can positively impact your supply chain and drive retail sustainability.

1) Personalisation

The fact that companies now have ‘more data than ever,’ allows your business to hyper-personalise your customers’ experience of your fashion brand, by engaging that customer with the content that matters to them, in their preferred format.

2) Being able to respond to changes and trends that are driven by the customer

This is all about adaptation, and being able to react to fashion trends by getting the right product to the right location, in front of the right person at the right time. The only way to do this effectively and efficiently enough is using AI thanks to its predictive capabilities.

3) Sustainability

Here, Mylo runs through how it is easy for a fashion company ’s supply chain to become very complex very quickly. However, using AI, this complexity can be reduced through more intelligent inventory management and forecasting techniques. This can help to reduce wastage and allows you to portray your business as one that has a clear focus on sustainability – which is increasingly-demanded by modern customers.

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Footasylum’s Tom Summerfield joined our retail customer success manager Mylo Portas on stage for a “fireside chat” to round off the one-day conference. They discussed the importance of omnichannel for the footwear retail giant, their journey to becoming AI-driven and some of the successes they have enjoyed from working with Peak.

If you found this video of interest, don’t forget to subscribe to our YouTube channel for more vlogs and to find out what’s going on behind-the-scenes at Peak.

Bottom Lines

IDC research suggests retailers, in particular, are seeing the impact of improved technology and more sophisticated uses of data on their bottom lines. Marketer respondents to its 2017 Online Marketing Survey expect to see advertising language, layouts and creative being personalised in real-time increasingly, further driving sales as a result.

Lead Scoring

On the sales side, we know from our own work that applying AI to customer and pipeline data can drastically improve the accuracy of lead scoring. It’s a fact that was being touted by the likes of Marketo as far back as 2014, and was backed up more recently by HubSpot’s Radhika Ramachandran, who explained, “Adding artificial intelligence to lead scoring can help companies increase sales by better prioritising customers and aligning sales messaging and resources with customer experience.”

A lot of brands are already harnessing their data to improve customer experience. By simply analysing their emails and tweaking them towards the preferences of recipients, Virgin Holidays saw a two percentage point increase in open rates, which translated to an increase of several million pounds in revenue. 

This handful of examples is undoubtedly just the tip of the iceberg, but it shows the potential value of data and that this value spans the sales journey. It shows that not only is there more value locked inside your company’s data than you realise, but that others will use data to gain a competitive advantage regardless of whether or not you do.

Here at Peak, we’re focused on helping businesses make the most of their data. Despite what you might think at first, your data is good enough, and can be used to improve your business processes and profits. You just need to know how to leverage it in the most efficient way possible – and that’s where Peak’s Connected Decision Intelligence system comes in.

To get started on your data and AI journey, arrange a quick, no-obligation chat with our team. We’d be happy to help.