When it comes to digital transformation, RFID (Radio Frequency Identification) has been the hype in retail for several years now. It has, however, been a bumpy road to success. In the past, stories of failed implementations and botched rollouts were far too common and kept many retailers from taking the plunge. Thankfully these days the picture is much more encouraging. We are now spoilt for case studies and examples of retailers having enormous success with the technology to digitise their inventory and processes for the modern retail environment.

So, what makes the difference between failure and success?

Ultimately it comes down to a combination of knowledge, technology and price. Improvements in all three of these areas have evolved the technology into a vital component of any digital transformation journey in retail. But as with any transformative project, getting the detail right is vital. The approach to implementation and suppliers you choose to engage with will have big implications on ROI.

A best-practise approach is easier said than done, so you need to surround yourself with a team of experts who have skin in the game and ensure the solution you choose to implement has the capabilities to lead your digital transformation for years to come.

 1.   Understand the problems you want to solve and clearly define the KPIs

The first step in any new tech investment is to be sure that you have clarity around what problems you are hoping to solve. This will often require some hard-hitting questions and honest auditing of current processes and data to understand where you and your customer’s biggest pain points are. Customer feedback surveys are always a good way to gain insight into this.

What common retail problems can RFID solve?

• Stock inaccuracy leading to out-of-stock situations
• Poor product availability on salesfloors and webshop resulting in lost sales
• Labour costs and operational inefficiencies
• Reduction in excess/safety stock
• Inventory visibility and supply chain traceability

Luckily, these problems all have clear KPIs related to them and can be used as a great measurement tool to understand your current position and build a business case for the investment.

2.   Choose a software partner that will help you achieve more

Once you have clearly defined RFID as the technology you want to implement, it is then vital to choose the right partners to go on your digital transformation journey with. Within the RFID market, there are generally three partner types – hardware, labels and software. The software component is the most important aspect as this must be able to process all the data, integrate with existing systems and empower employees with user-friendly applications to improve daily processes. Choosing the best-suited partners will make all the difference to ensuring you have a scalable and future proof solution for the next 5+ years.

What to look for in an RFID software partner?

• Credibility in the market – do they have proven RFID deployments with reputable brands in your sector?
• Future-proofed services – do they have a product roadmap that inspires innovation and constant improvement?
• Scalability and flexibility – does the solution fit your business needs and implementation roadmap?
• Industry expertise – do they have deep industry knowledge to understand your specific business requirements and help you think through these challenges?

5.   Full omnichannel enablement

After securing the foundations of stock accuracy and on-floor availability in stores, the next step is to connect the online and offline business. Omnichannel services such as click & collect (aka BOPIS) and Ship-From-Store are expected in the modern retail environment as consumers demand to shop anywhere, anytime and any way they want. However, it’s important to ensure you can deliver on these retail experiences so that customers don’t end up disappointed. Enabling this requires connecting inventory from your store networks with your distribution centres and webshop to create a single and transparent view of stock.

 What’s required for Omnichannel retailing?

• Transparent view of stock across all stores made available to the online store
• Automate warehouse processes with RFID tunnel and outbound processes
• Offer new services such as click & collect, ship-from-store etc.

At Detego we know retail and we know RFID. This combination has enabled us to develop the most innovative RFID software solutions on the market, alongside major global fashion brands. With RFID now on almost every retailer’s roadmap, we have the answers for any step of the journey, anywhere within your operations.

Everyone has to start somewhere, which is why we have out-of-the-box solutions to quick-start your RFID journey. Alternatively, if RFID is well and truly ingrained in your business, then talk to Detego about how we are using AI and innovative new practices to take real-time decision making to the next level.

Visual Merchandising’s Data Problem  

Visual merchandising is one of the ‘dark arts’ of retail. For the uninitiated, it’s the practice of designing visually appealing sales floors and store fixtures that attract customers and ultimately sell the products on display. It’s a subjective and artistic means of delivering a concrete KPI – sales.

One of the challenges of visual merchandising is data, experimentation & design is all well and good, but not if you have no way of knowing what does and doesn’t work. Sales data is always a good place to start, but there are so many other factors at play that it’s often unwise to attribute visual merchandising to an increase or decrease of sales to a single product. You have to go one step further…

What is Money Mapping? 

So, how do you measure the sales performance of a store based on its layout and design? 

First, you map out the sales floor with the exact location of products. Then you break the map of the store into ‘zones’, typically around certain fixtures, shelves and displays. These zones can consist of several different items, grouped by either category or style depending on the design of the store. 

You then collate the sales of every item in this zone and compare it to others in the same store. The result? An impression of shop floor sales broken down by areas of the store.  

This is called ‘Money Mapping’ and allows retailers to visualise and analyse which areas of a store are ‘hotspots’ and which are ‘cold’ in terms of sales. This gives an initial view of which areas and fixtures are selling products and which aren’t.

To account for other external influences on sales, best practise is to swap items between fixtures or observe a ‘money map’ over a long time, as collections and merchandise changes between seasons. This way, if the localised sales data remains relatively similar even after products have rotated, then it’s clear the design or locations of the fixture is having an impact.

What are the benefits of Money Mapping?

• Insight on consumer experience
• Provides valuable data for visual merchandisers
• Breaks down areas of sales floor by sales performance
• Can be used to optimise store layout
• Drives Sales
• Can compare Product Placement & Visual Merchandising
• Can be used to conduct A/B tests

This all sounds great, so why doesn’t every retailer and every store do this already? The simple answer – the process of matching the sales data to specific locations on the sales floor, manually for every item and every store, is logistically a big ask. This means, if this can be done at all by visual merchandisers, it can only be done in a small number of stores.

How does AI change money mapping?

So how can we solve this data problem for visual merchandisers and make ‘Money Mapping’ easier and more accessible for retailers?

The first issue is having an accurate map of a store which includes exactly where every single item is sold from. Traditionally this would have to be done manually, and then have the sales data of items cross-referenced with their location in a store.

The solution: Using RFID (Radio Frequency Identification) and AI localisation techniques, we can now create a map of a store as part of the daily or weekly stock count.

This is done by adding ‘reference’ RFID tags into the store. Small tags just like ones that go on products are placed on fixtures and walls in the store. Because these never move, we can use the signal strength (relative to the fixtures) from stock counts to map exactly where items are in the store and what items they are grouped with.

This location info is then integrated with data from point of sale to generate an automated Money Map of a store, as part of the regular reporting and analytics function of the store. This can be done for as many stores as desired. With the data collection automated, visual merchandisers can focus on using the data to optimise product placement and store design across stores.

With larger data sets to work with, this also opens up the potential for more detailed analysis and experimentation such as A/B testing product combinations and store layouts!

What’s the process for AI Money Mapping?

• Attach reference RFID tags to walls and fixtures within the store
• Perform regular RFID stock takes as normal
• Software uses machine learning to ‘map’ out item locations within the store
• Integrate point of sale data with RFID software
• Software produces ‘heat map’ of the store based on sales
• Visual merchandisers can use data to inform strategy and measure results

Conclusion

Visual merchandising is a subtle but valuable process for retailers. Done properly it has a huge impact on both sales, customer experience and brand image. The only problem with this is visual merchandisers often don’t have enough data to measure performance and identify where their attention is needed most. The data they can collect is either time consuming, expensive or inaccurate.

Artificial intelligence changes the game for visual merchandising. By utilising RFID tags and Machine Learning, it is possible to ‘map out’ the location of items in a store, and more importantly, the sales distribution of the shop floor. These ‘Money Maps’ tell visual merchandisers what areas of the sales floor are ‘hotspots’ for sales and which are underperforming. Using this data, they can then focus their attention on improving the design or layout of certain areas.

Additionally, with this data stores can look to leverage their sales hotspots either by prioritising the best locations for best-sellers, high-value items or items that are due to go out of season.

Either way, AI-enabled Money Mapping is another important evolution in retail data and analytics. Providing retailers with unprecedented insight into exactly what goes on in Brick and Mortar Stores.

The retail industry has been subject to enormous change in recent years, a trend that looks likely to continue even now retail has found its feet in the digital age. This significant shift in the landscape coupled with the collapse of numerous household brands naturally created something of a panic in the industry and a fear an impending ‘retail apocalypse’. So, has this taken place and are brick and mortar stores heading toward extinction in the age of online shopping? The short answer: no. Retail sales, in general, are increasing, and whilst online sales are certainly growing at a faster rate than in stores, in the UK market Brick and Mortar stores make up roughly 84% of all sales, a trend that applies globally.

The fashion industry has taken this concept even further with the use of smart mirrors. Smart mirrors use advanced tagging technology (RFID) to sense the items that a customer brings into a fitting room. It will then display the products on the mirror and, like a chatbot, assist customers by providing information on other available sizes and colours and recommending products that are often bought with the ones being tried on. Most smart mirrors also have a feature that calls store staff to assist the customer, either providing face-to-face support or bringing the recommended items the customer has chosen to the fitting room. Smart fitting rooms are the epitome of the merger of the digital and physical in brick and mortar stores.

AI-powered in-store business intelligence

Artificial intelligence can also go a long way to revolutionising traditional brick and mortar store processes. One of the best examples of this is the use of AI assisted planograms. A planogram is essentially a plan of where items should be displayed on a shop floor to maximise customer purchases. In certain sectors such as fashion, planograms must be even more detailed and include the optimum display quantities of each different size and colour.

Artificial intelligence can revolutionise the planogram, using machine learning to constantly optimise not only the positioning of merchandise but the most efficient quantities of different articles to display on the shop floor. The advantages of this process being performed through AI are huge. Not only does it largely automate the process, saving time for staff, but it will constantly adapt and improve and can personalise and optimise the planogram on an individual store level.

The future of retail, online and in-store

To conclude, the impact of digital technology on the retail industry, in particular brick and mortar stores, has been significant but not actively catastrophic as many feared it would be. The emergence of ecommerce has gone from a threat to a strength for some physical stores. Not only has omnichannel retailing (something we did not have time to explore, but we go into detail on here) allied the different methods of shopping, but brick and mortar stores have now begun to incorporate certain technologies from online.

AI technology, originally something only online retailers could really utilise, is now finding its way into brick and mortar stores and improving both store processes and customer experience. We are also just scratching the surface of AI’s uses in retail and as more retailers choose to adopt the technology more benefits will be discovered.  So, in reality brick and mortar stores are far from going extinct; they are in fact evolving and will continue to do so.

(Originally published on AI Business.com)