Just a moment, I have to check…
Making a great shopping experience can happen in seconds, but can also fail just as quickly. The customer who is ready to buy a desired article is often left standing in the aisle, being asked by the shop assistant to wait. He/she goes off to search for the article in the stockroom, perhaps call another location or check with the manager. If the article cannot be found, the sales interaction usually comes to an end with something like “Sorry, we don’t have it.”
The possibility that the desired item, say a skirt in size S, could be available in another store is something that the customer has to find out for themself. Of course they could try their luck online, and maybe even order it in the online shop if it’s still in stock.
That’s a shame. All that just happened because the shop assistant did not have the right information.
Lacking item visibility is a massive problem in the fashion industry, and almost all retailers suffer with lost profits because of it:
- If the article is not on the sales floor, it cannot be sold
- If no one knows that the article is in the stockroom, on display in the shop window or in the changing room, it cannot be sold
- If the sales person cannot give the customer information on the availability of an article immediately, a sale is missed and the customer is disappointed
- If the click & reserve inventory is not kept in sync with the store inventory, the reserved article cannot be sold
- If the article surprisingly “reappears” during inventory, for example someone finds it in an unopened box, it’s too late
- If there’s no item visibility in the individual channels, then flexible redistribution will not work
Getting the merchandise to where it is needed most
It’s the dream of every retailer: the merchandise offered is presented to precisely the customer who would like to buy it. With 5,000 articles in 700 stores in a variety of sizes, even the most experienced retailer can no longer make decisions by gut feeling.
- Sizes should not be evenly distributed among all stores
- Buffer stock should not clog up the stockroom
- Excess inventory that later has to be written off should simply not exist
Intelligent Merchandise Distribution
One is always wiser after the fact, for example at the end of the fiscal year or of a collection season, retailers know which items sold well in different stores and which did not. But then it’s too late. The merchandise ends up in the factory outlet store and eventually sold at discounted prices, the amount written off remains high, sales stagnate, etc.
However, retailers should immediately know which articles are sold well in which locations. Also, information on items that need to be reordered as well as the prevailing aging structure of articles at item-level per store is needed. To take the right decisions, it would be wise to have access to reliable real-time data in forms of dependable analysis and clear recommendations.
Actively manage your network of stores using real-time data:
- Real-time control over inventory and more efficient replenishment
- Quicker reordering
- Reduction in reserve stock
- Less merchandise in the channels, combined with greater inventory accuracy
- Smaller lot sizes, more precise control over the flow of merchandise
- Selling out collection merchandise at the planned margin, not via outlet sales
- Fast recommendations for activities to optimise the store
- Real-time dashboards promote the right decisions being made
- Rapid relocation of sale merchandise between the 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.
In fact, with the help of new technology, in particular, AI brick and mortar stores can take lessons from e-commerce and bring new innovations into the physical store. A study by Capgemini found that around 68% of pure-play online retailers have implemented artificial intelligence in some fashion, compared to only 10% of brick and mortar stores. Utilising new technology can often be the key to growth, so perhaps it’s no surprise that online retailing is growing at such a faster rate. This is beginning to change however, as physical stores are learning to adapt.
AI-assisted cross-selling in the store
The ability to cross-sell using AI is a huge strength of online retail. Online stores use machine learning to make intelligent and tailored product recommendations to customers while they are shopping This naturally increases sales, but does so relative to the quality of the product recommendations, hence the use of AI to perfect the process and make more successful recommendations. Brick and mortar stores have traditionally never been able to make use of cross-selling like this, having to rely on in-person customer service to drive sales. But as technology has improved, they can now make use of both.
The main reason for this is the emergence of chatbots as a mobile platform for in-store product recommendations. Whilst chatbots themselves originate from online, certain retailers now implement them in their stores to assist customers. Their primary function is often to assist customers if store associates are all occupied. Chatbots can help customers locate items, find more information on products and check stock availability, all through their smartphones. Intelligent AI-powered chatbots will then be able to recommend products similar to the item’s customers were searching for, not only increasing sales but improving the customer experience.
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.
Retail software specialists, Detego, have presented their ground-breaking methodology for in-store product recommendations, helping bring the same quality of cross-selling over from e-commerce and into the physical store. The new AI-based recommendation engine will enable retailers to provide personalized product suggestions utilizing data unique to store locations and point of sale information, without the need for identifying customer profiles.
Cross-selling through related product recommendations has always been a huge strength of e-commerce, with 35% of Amazon’s revenue generated by its recommendation engine (source). In recent years, innovations in RFID-based solutions such as smart fitting rooms and mobile chatbots have opened the doors to automated product recommendations within physical stores. Whilst the technology is now available, there is still one more hurdle between Brick and Mortar stores and effective cross-selling. This is namely the fact that the best recommender systems require vast amounts of both personal and aggregated data to provide effective suggestions, and whilst this is at a surplus in e-commerce, physical stores traditionally struggle with data being limited as well as sparse.
Speaking at the ACM UMAP 2019 in Cyprus in June, data scientists from Detego, who specialise in RFID-based software solutions for retailers, presented their proposed method of data-manipulation for in-store recommender systems with a paper titled: ‘Beggars Can’t Be Choosers: Augmenting Sparse Data for Embedding-Based Product Recommendations in Retail Stores’. The approach involves an alternative algorithm that leverages shopping-baskets and common-item combinations combined with point of sale information. Detego says this allows retailers to provide targeted recommendations with a 6.9% increase in quality, aimed at individual stores, without having to maintain separate models for each location. When combined with the technology to deliver these product recommendations, retailers could see a substantial increase in sales in Brick and Mortar stores, whilst customers will see a more connected and engaging in-store experience, as Detego continues to bridge the gap between online and the physical store.
“Customers who bought this also bought…” is no longer a phrase reserved exclusively for customers of e-commerce platforms. Due to the adoption of RFID-based technologies, such as Detego’s Smart Fitting Room, personalised recommendations can also be presented to customers of brick and mortar stores. Moreover, Detego’s AI-based recommendation engine is tailored towards the specific requirements of fashion retail stores, such as fast-changing and varying product assortments.’ says Matthias Wölbitsch, Detego data scientist.
With Detego now successfully rolling out the Smart Fitting Room application alongside their real-time inventory management software, this latest improvement is another opportunity for retailers to evolve their stores for the future.
This webinar discusses intelligent planograms and how they enable an individual size distribution for fashion retail stores and make sure that products are available on the sales floor in the appropriate sizes.
It provide insights into how the self-learning system adapts to possibly changing conditions and continuously optimises the plan – with a direct impact on the store revenue.
Detailed analysis by retail tech specialists at Detego has confirmed that the average retailer’s data is only about seventy-five percent accurate when it comes to knowing exactly what inventory is actually in stock at any particular time. The problem is often compounded by retailers continually managing stock across multiple channels and increasingly having to stay on top of consumer demands for up-to-the-minute, reliable information. Detego, which has been monitoring its own chatbot service that allows consumers to engage with retailers via their smartphones, found the most common enquiries to be about stock availability. It found data inaccuracies around inventory to be most of an issue in fashion retail where ever shorter product lifecycles, fast turnarounds of stock and multiple style, size and colour combinations can play havoc with the supply chain and in-store operations.
“Customers, above all, want instant and accurate information on product availability,” says Dr. Michael Goller, CTO at Detego. “If you’re shopping for clothes, you want to be sure of getting the exact size and style you’re looking for. But many retailers fall by the wayside here – their systems might tell them that a particular size is available; yet, there’s a one in four chance that this isn’t the case.”
According to Goller, continually relying on manual processes for something as vital to the retail business as stock – usually by shutting up shop once or twice a year for store or warehouse staff to do a stock-take – is madness. And especially given that smart technologies abound, including RFID and mobile devices which ensure continual monitoring and lead to near hundred percent accuracy and operational excellence in the stores.
Research by the University of Parma in Italy has shown consistent sales increases in RFID-managed apparel stores and deduced that “RFID item-level tagging is a powerful tool for improving inventory accuracy, which is a prerequisite for both omni-channel strategies and store floor replenishment from the backroom.”1
Thanks to technology that helps increase the availability of products on the shopfloor – such as using wearable devices that rely on alerts and images to guide staff and speed up the replacement of missing articles and gaps on the shelves – the industry is starting to see a gradual shift towards more connected technologies in retail. IDC Retail Insights predicts that eighty percent of retailers are due to spend on visibility platforms powered by RFID and IoT2 over the next few years.
An extraordinary four-month project sprint for 500 adidas stores in Russia has been successfully completed. The goal: Boost store KPIs such as inventory accuracy, article availability and consumer service to the highest levels. The means to achieve that: Extremely fast, error-free stock taking of 45 million articles per year through real-time in-store processes that are more efficient and intuitively managed, using decision-relevant analytics. The end-to-end integration was accomplished in just four months. The interdisciplinary project team consisted of business, IT, logistics and retail experts coming from five different countries – all working together across ten different time zones. The result: 99% inventory accuracy and the highest on-floor availability that adidas wanted for its stores. The winner: The adidas end customer.
The future? Athletic.
99% Stock accuracy
98.5% product availability
2000+ sales employees trained
Although the customer leaves an invisible data trail in the store, brick-and-mortar retailers barely use them to improve customer service. Dr. Michael Goller, CTO at Detego, explains why things need to change in the future.
Online retailing has not only created a new way of shopping, but also has a powerful toolbox to measure its results – with the overall objective to meet the customer’s expectations at all times. For that reason, online retailing has become the highest standard when it comes to measurement and evaluation in fashion retail. There is almost nothing that is not being evaluated while surfing the web shop. Conversion rate, click through rate, average order value, relation between new and returning visitors, bounce rate and retention time are just some of the KPIs that measure the success of online shopping activities. The really powerful thing about this is that analysis is always followed by action – usually fully automated.
And what about brick-and-mortar retail? It is about time to take some lessons…
The need for real-time data
For years, brick-and-mortar retailers have been complaining about imprecise stock-figures and unreliable historical data. Unhappy with its purchasing decisions based on last year’s sales figures, retailers would prefer to have real-time data and inventories that allow for reliable and economically viable decisions. After all, it is important to avoid high security stocks in order to reduce capital tie-up.
But why do we actually have this problem? Are the datapoints offered by the ERP systems not enough? Unfortunately not – it is not unusual that the ERP system shows higher stock than actually available on the sales floor. This so-called “ghost stock” is the cause for various problems in sales, e.g. the ERP system says a certain article, for example a red skirt in size S, is in stock, but in reality it is not. It can neither be sold nor refilled from the central warehouse – a classical out-of-stock situation. Or vice-versa, the ERP displays a lower inventory level than is actually available. The reason for these deviations is insufficient accuracy in individual processes that dangerously sum up over time.
Today’s intelligent article management is based on three pillars: fast, RFID-based article identification on item-level, tracking of every movement in real-time and proactive analysis with concrete recommendations for actions to take for the sales personnel. This is the foundation for optimum customer service and efficient processes.
Meaningful KPIs in the store
When measuring KPIs, the practical benefits for retailers are paramount. Three areas of data in the store can be distinguished:
- KPIs for inventory accuracy and product availability
- KPIs for campaign performance measurements
- KPIs on customer engagement and service quality
How KPIs are defined depends on the size and number of stores, the assortment depth and the flow of goods. Predefined objectives also play an important role: Whether five or 800 stores, KPIs for measuring inventory accuracy are significant for every retailer and still represent one of the main challenges in today’ business. Retailers, on average, can actually make accurate statements on just about 75% of their inventory (based on SKU level). However, this is not enough to meet customers’ expectations for omnichannel services. Therefore, inventory transparency and corresponding KPIs are essential for retailers´ success.
Product availability on the sales floor, also known as on-floor availability, is the second central parameter. Initially, it is less about the exact position and more about the fact that the articles are on the sales floor – after all, only items that are actually available can be sold. This key figure can be combined with an alert system that makes sure not to fall short of the defined minimum availability. Complementary to classical ERP-systems, an RFID-based merchandise management takes the data granularity to the next level, by knowing exactly at each moment in time if products are really on the salesfloor or still lingering in the backroom of a store. Having data on item level, store managers are also given important information on the dwell times of articles on the sales floor to gauge whether they are corresponding with the sales plan. One of the most famous KPIs in e-commerce is the conversion rate that describes the ratio between purchases and website visitors and also provides information on certain items that were already in the shopping cart, but for some reason have not been purchased in the end. Specifically this aspect was incredibly difficult to measure in the store for a long time but can now be measured in fitting rooms using IoT and RFID technologies. This provides meaningful insights into how many, and above all, which articles does a customer take into the fitting room and which one does she/he actually buy?
On an operational side, KPIs can also be used to manage the service quality. The replenishment rate, for example, states how quickly articles are replenished on the sales floor. On the other hand, the fitting room response time describes how quickly sales personnel handle customer requests coming from the fitting room.
The KPI “Conversion rate per campaign” shows the success of a campaign and if campaign-specific countermeasures are necessary / ©Detego
Turning data into actions
What else can brick-and-mortar retail learn from the web shop? Turning data into actions. Since nobody needs a data graveyard, any analysis of data has the goal to take immediate actions to improve. Today’s systems help the management team as well as the store personnel with concrete and automated recommendations for actions to take. This saves time in the decision-making process, unburdens the sales personnel, and enables them do the right things at the right time.
KPIs should be suitable for everyday business use. Presented visually and self-explanatory, they need to be linked to clear recommendations for actions to take. This frees up store personnel time and provides a data-driven way of optimization. Examples range from simple in-store replenishment advices, i.e. “The minimum stock for article #47699-0010 has been reached – please refill three pieces” to more advanced topics, e.g. to choose a different placement in the store for a specific article when the dwell time on the sales floor is too high compared to other stores.
Brick-and-mortar retail definitely needs support and an update to the toolbox when it comes to analysis and measures. Not only does the sales personnel benefit from intelligent recommendations for action, but the management team also gains efficient control mechanisms across the entire store network. Decisions are made on the basis of real-time data and therefore allow timely action. Ultimately, the end customer is pleased about a first-class service, which – thanks to the individual and informed advice through the sales personnel – even exceeds the standards of the online retail.
Why should fashion retailers deal with IoT? What problems could be solved in the stores? What results can be expected? As a retail decision maker you need to deal with IoT if increased article availability, exact inventories, interaction with customers and operational excellence in your stores are set as objectives. This practice-oriented guide sheds light on the triangle of “customer”, “processes in the store” and “deployment of new technologies” and shows how the use of IoT benefits retailers and ultimately the customer. The whitepaper reveals the formula for the perfect customer relationship, based on the right technologies and processes and shows how retailers can apply them to their business.
Detego, a market leader in real-time business intelligence for the fashion retail industry, is releasing its latest whitepaper, providing valuable information on the use of Internet of Things (IoT) in fashion stores. Titled as “The perfect customer relationship – How fashion stores leverage Internet of Things (IoT) technologies to put the customer in focus of all activities “, fashion retailers get a practice-oriented guide that highlights the most important aspects such as: Why should fashion retailers deal with IoT?, What problems could be solved in the stores?, What results can be expected? Retail decision makers need to deal with IoT if increased article availability, exact inventories, interaction with customers and operational excellence in the stores are set as objectives. The 35-page guide sheds light on the triangle of “customer”, “processes in the store” and “deployment of new technologies” and shows how the use of IoT benefits retailers and ultimately the customer. The whitepaper is available for download on the Detego website.
Detego discusses the various IoT technologies as a way for retailers to realize the perfect customer relationship. Based on customer’s needs, the practical tips are divided into 1. Self-service in the store: The customer as the main actor, 2. Brand Ambassador: The customer as influencer, 3. Co-Value Creation: The customer as partner and 4. Predictive Analytics: The Customer as creator of the future. All four subchapters describe what retailers can do to connect with the customer and enable an interaction in the store.
In addition, infrastructural prerequisites such as the optimal process support through IoT technology and in particular support for the sales personnel are discussed. With the help of IoT, retailers and their store personnel gain valuable data that is translated into recommendations for concrete action to take. In addition to the operational excellence in the store, it is primarily about the new shopping experience for the customer. The whitepaper reveals the formula for the perfect customer relationship, based on the right technologies and processes and shows how retailers can apply them to their business.
The one-size-fits-all sales approach is outdated. In the store, intelligent systems are needed to provide the customer with a personalised experience. Key elements for this are individual and personalised recommendations from the current product range and simplified processes that give stores associates more time for the customers.
In this webinar you find out how “Data Driven Empowerment” activates cross-selling potential, increases the number of articles per receipt and finally leads to satisfied customers and happy retailers.