We’ve been tracking 18 different categories in the Retail Online to Offline (O2O) space.
Here is how Retail 2.0 is shaping up:
Local Daily Deals: Companies that sell locally available, pre-paid vouchers for steeply discounted goods and services. This category also includes daily deal aggregators.
Point of Sale 2.0: New point-of-sale solutions that create frictionless consumer transaction experiences and also enable retailers to collect data about their customers that can be leveraged for marketing and CRM purposes.
Online to Offline Payments: Technologies and services that are changing the way we pay for goods. In addition to payment execution, this also includes companies that provide consumers with a mobile wallet (e.g. payment information, loyalty cards) or other digital storage functionality (e.g. receipts).
Loyalty Programs: Products that provide or power a merchant’s reward / loyalty program. Examples include digital frequent shopper cards, tailored rewards based on spending, etc.
Social Discovery: This category includes companies that allow for discovery through location check-ins and social sharing of ideas, products, companies, brands, etc.
Coupons: Companies that focus on both traditional and digital merchant coupons.
Local Incentives: These companies help stores increase loyalty, customer base, and revenue from both new and repeat customers through deals, local offers, discounts, frequency rewards, gamified badges, and other techniques.
Marketing Platforms and Customer Relationship Management: Products that enable merchants / brands to engage with their customers across social media channels, and execute and manage marketing campaigns. This category also includes customer relationship management tools used to improve customer communication, tracking, and overall relations.
Infrastructure and Enablers: Products and tools designed to help developers increase functionality in their existing products (e.g. payment integration), create applications (e.g. mobile apps, websites), etc .
Physical Store Analytics: Using sensors, cameras, and mobile devices to provide retailers more data about customer behavior in-store such as window conversion rate, customer dwell time, optimal shelf placement, and ideal store hours. These companies help retailers optimize the customer experience to increase revenue.
Local Advertising Technology: Companies that alert the consumer of a retail product or service. The advertising models in the O2O market often center around targeted ads, real-time mobile ads, retargeting, dynamic ads based on proximity to clear inventory, ads targeted based on check-ins or social comments, and in-store up-sell ads.
Data and Analytics: These companies help with the acquisition, organization, and distribution of data that companies can then utilize to enhance their applications and service offerings.
In-Store Experience: Companies that are innovating with in-store navigation, mobile-enhanced shopping lists, monitoring friends and family in-store, real-time customer relationship management, and “looking” inside venues to see product offerings and clientele demographics before making a purchase.
Convenience as Marketing: Much of the value proposition of these services is that they allow for the more convenient selection and purchase of goods or services.
Gift Cards: This category includes both physical and digital stored-value and prepaid cards.
Search and Local Availability: The companies in this category provide the means by which consumers can search and/or compare local availability of products and prices. This includes innovations such as store-level inventory searches and local comparisons.
Price and Feature Comparison: Services that empower consumers to compare product prices at different outlets or compare features across similar products (e.g. scan and engage capabilities for QR codes, bar codes, or physical items to bring up product information and comparisons in real-time).
Retail Augmented Reality: Companies that enable consumers to interact with products using augmented reality (e.g. virtual manipulation)
Automation A Necessity in the Future Of Retail to Drive Revenues ( 300–500 Basis Points ) — Are we falling behind
- New Realities — The Evolving Market Perspective :
a. Retail is under pressure. Margins are stressed from all sides: higher costs to manage e-commerce supply chains, growing demands from suppliers to pass on raw-material cost inflation, higher investments to match new competition, and steadily rising labor costs. At the same time, the customer’s expectations continue to surge as digital natives and disruptors alike raise the bar for personalized service — on the back of what, at times, is an advantaged cost structure. As retailers struggle to adapt, and even to survive, they increasingly pursue automation to address margin strain and more demanding customer expectations. Automation however is a new capability for all but digital natives and the sophistication in approach varies accordingly. Automation will reshape retail business models and the broader value chain, creating organizations with fewer layers and better trained and trusted workforce empowered by real time data and analytics. The winners in the sector will be those who understand these implications and act quickly to address them.
2. Threat :
1. A online-only startup retailer or brand doesn’t have a physical store to manage or employees to manage.
2. They will have a small number of employees and become a large retailer with digital labor.
3. While there are a lot of human skills that cannot be digitized, there are definitely areas that can be automated.
4. These startups introduce a threat to retailers, and automation cuts a huge portion of the cost it takes to become very competitive.
5. There’s a lot going on right now with physical robotics. The questions that retailers need to ask are: How brittle are these tools — meaning, how prone are they to break while in situ? And do they function in the ways that the vendors are saying they are? In terms of AI, retailers and brands must understand the multiplicity of technologies that are out there. AI isn’t one technology; it’s a complete “sense, think, and act” in how AI can solve problems. There is lots of value in disaggregating our knowledge of AI into actual, specific technologies — like machine learning or computer vision or sentiment analysis — and becoming familiar with what’s out there and what other businesses are piloting and implementing — including in the travel, healthcare, and financial services sectors.
3. The Study :
a. The IBM institute for business value and Oxford Economics surveyed 1900 retail and consumer product leaders in 23 countries. Participants included executives in supply chain, store operations, merchandising, product design finance, sales and marketing and customer focused areas. Following five broad areas were addressed :
i. How can you better understand intelligent automation capabilities, and what steps is your organization taking to communicate its capabilities and implications across the value chain?
ii. How do you plan to educate, train and prepare executives and employees to adopt this capability? The traditional HR model is obsolete as most of the HR people are not even aware of the exponential technologies that are redefining competition. Hence the skillsets they lookout for will not take an organization to the future. How HR needs to be totally revamped to pursue the talent of the future beyond the traditional bureaucracies of the legacy organizations ?
iii. What steps can you take to assess, identify and prioritize the strongest opportunities for using intelligent automation to engage with consumers and improve the customer experience, while ensuring back-end processes across the supply chain can deliver the brand promise?
iv. How do you plan to integrate intelligent automation across your existing tools to engage with consumers and processes, and deliver the products and service consumers demand?
v. How do you plan to build an enterprise approach for intelligent automation that can deliver compelling brand experiences throughout the customer journey?
vi. How are you reinventing the last mile to make it completely electric and digital ?
3. Findings : The findings are alarming. The change will be less about the job loss and more about the evolution of jobs, the creation of new ones and reskilling.
a. Purchase phase is the most stressful and painful one.
i. Waiting in long lines at checkout is one of the reasons why shoppers are turning to online shopping: it is no wonder the first thing retailers are innovating is the phase of the purchase. They hope to increase visits and sales in store and contain the race to online shopping.
b. Common Goals :
i. All successful retailers around the world have a common goal: low cost, great convenience, speedy response, and a memorable experience. While this may seem simple, many large retailers have closed down after failing to implement this. Two in five retailers are already working with intelligent automation today, the study found, and that number is expected to double in the next two to three years. Retailers are primarily using AI to automate processes along the supply chain. With AI, retailers can start to consume huge amounts of data, see patterns and then automate the necessary actions, like rerouting trucks due to developing bad weather conditions or reinventing the last mile. AI and automation are typically used to drive efficiencies and lower costs; one thing from the study that is surprising is how AI is helping people make better, faster decisions — and execute them faster as well. These technologies don’t just manifest in lower costs, these are actually revenue drivers. The research showed many retailers and CPG companies thought the revenue potential for intelligent automation would be even higher than the cost savings. Food and grocery stores are where the highest number of automated processes examples are visible.
c. Need to change or get disrupted — Physical retail isn’t dead. Boring retail is :
i. Physical stores still account for majority of the sales today. However, brick and mortar stores all over the world are evolving their traditional one-size-fits-all stores into immersive experiential stores that focus on personalizing each shopper’s experience. Stores are evolving to be environments that entertain, educate and rediscover rather than just being transactional entity.
ii. Overcoming the physical/digital divide is an overarching trend we are seeing in every vertical.
iii. Retailers in general are pivoting to customer-obsessed, omnichannel experiences.
iv. This means being able to order online and pick up in-store or returning an item bought online to a store, so a lot of back-end automation — software, mostly — helps these processes.
v. But this also changes the dynamics of inventory: There are carrying costs to stores for holding on to lots of products. Retailers are moving toward a world of short-term replenishment; instead of replenishing in bulk weekly, some are moving to a faster, even daily approach. All of these changes require automation and intelligence.
d. Today’s customers no longer seek products, but experiences.
i. 41% of customers demand the personalization of their shopping experiences.
ii. There has been a big transition in the behavior of next-generation shoppers. They have gone from viewing shopping as an “activity” to a holistic, entertaining experience that is comparable to other valuable experiences of their lives. With the advent of the experience economy, omnichannel marketing and innovative retail concepts, we know one thing.
iii. The future of retail is entertainment.
iv. Being able to provide experiences that are customized, thoughtful and memorable must be prioritized over anything else to retain shoppers.
e. Margin pressure has made automation a requirement, not a choice
i. Retail-margin pressure is mounting, driven by more intense competition, investment in e-commerce, and pressure to increase wages. While these cost pressures are not new, many retailers have already exhausted traditional cost-reduction levers. Unable to pass on costs to their customers in this hypercompetitive environment, retailers are using automation to support and bolster margins. These pressures are consistent across retail subsectors.
ii. Mckinsey analysis suggests that typical grocery and hypermarket retailers face 100 to 150 basis points of margin pressure.
iii. Typical specialty apparel or department stores face 350 to 500 basis points. A comprehensive automation program can significantly offset these headwinds.
iv. Automation initiatives across store, supply-chain, and headquarter functions can generate 300 to 500 basis points of incremental margin, which retailers can reinvest in their growth opportunities.
f. The bottleneck to automation is internal, not external
i. An assessment of available automation technologies shows that they can already operate a typical retail grocery store with up to 55 to 65 percent fewer hours.
ii. The critical components include electronic shelf-edge labels, self-checkout terminals, shelf-scanning robots, and partially automated backroom unloading. These technologies have been proved at scale and offer internal rates of return higher than historical retail hurdle rates — yet few retailers are moving quickly to implementation.
iii. Retailers struggle to break free from the soft tyranny of budget cycles and the replication of last year’s capital spending. In some cases, the bottleneck is a lack of skills and capabilities.
iv. But one of the biggest challenges is the inertia of the business. Retailers struggle to break free from the soft tyranny of budget cycles and the replication of last year’s capital spending.
v. Mckinsey’ s corporate-finance research suggests that two-thirds of companies fall into this trap. For these players, more than 90 percent of a given year’s capital expenditures simply reprise those of the preceding year.
vi. Only one-third of companies are dynamic reallocators, consistently shifting 30 to 40 percent to different business units or new uses over five to six years — that is, a reallocation rate of 5 to 6 percent a year.
vii. Dynamic reallocators enjoy disproportionate rewards: growth in total shareholder returns nearly three percentage points higher than those of other companies over an extended time period.
g. Automation democratizes functions, thus reducing dependencies and delays in the pipeline while at the same time ensuring that a constantly improving process is in place. It benefits both the retailer and the shopper.
i. Intelligent Retail Automation allows a lot more people to access what used to be an exclusive experience, bringing in more people to the economy. Today, automation is about leveraging the power of data. The amount of data that needs to be processed from a plethora of data points makes automation a necessity, not a luxury. Especially in an industry like retail where each customer can have several touch points through multiple channels, automation is extremely important to keep up a high level of customer experience. Failure to automate can even lead to retailers missing out on capturing data completely. And in a data driven economy, this can have dire consequences. There is a constant need to create, use, analyze and distribute data in a timely manner for instant contextual decision making and value creation. This can only be done with automated systems capturing data across different touchpoints and channels.
h. The Millennial : .
i. Among Millennial there is a growing desire for control of every aspect of their shopping, payment included. Long gone are the days where you needed to depend fully on a sales assistant to request new sizes or to ring you up. Obsession for saving time, avoid stressful situations, control over the shopping processes, privacy and anonymity make the introduction of automation instore almost inevitable.
ii. According to an iResearch study of the Chinese market, 8.5 percent of the country’s consumers prefer to make purchases from human cashiers, while 23.7 percent prefer to scan a code as they leave the store. Beyond this, 29.8 percent prefer to pick up goods from a smart settlement basket that they retrieve at the exit, while an overwhelming 39 percent would prefer to simply walk out with their groceries in a form of automatic settlement.
i. The Power of Data : Flow of Data in Fashion Retail
i. Retailers have understood that as much as online ecommerce is gaining momentum, offline stores have the advantage of offering a ‘unique in-store experiences’. Stores today specializing in immersive retail have themed areas where people shopping for different occasions such as work wear, beach/vacation wear etc, can experience their attire in the respective setting offering them a unique perspective on how their outfits go with their surroundings. Apparel and beauty stores are bringing in Augmented Reality and Virtual Reality technology which helps customers to virtually try on clothes, style it with accessories, check how a particular shade of lipstick complements their outfit. But how can brands create these seamless customer experiences both online and offline, and do it successfully at scale? If experiential retail is the jet that will propel retailers to new heights, data is the fuel powering this jet! Data is well on its way to becoming its own currency, and that is why retailers need to be front and centre in its creation, its management and its deployment. Data also forms the foundation of inventory management. From the moment inventory lands at the warehouse to when buyers place orders for the season to come, data is the crucial link that connects the inventory management cycle and leads the decision making process. Data accuracy is necessary from the start of this process to ensure that subsequent decisions are taken in an appropriate and timely manner. 2.5 million quintillion bytes of data are generated every single day. Data needs to be both precise and accurate to aid in every step of the retail process. But a team creating and managing this data makes it susceptible to human error and inconsistencies. This where AI comes into the picture.
j. Intelligent Retail Automation
i. AI-powered Retail Automation ensures that this data creation, in the form of automated product tagging as well as collating individual customers preferences. Using AI in Retail additionally ensures the creation of an accurate database that is completely unique to the retailer’s business and customers. This database, when distributed across the retailer’s decision makers, is a proverbial goldmine. Not only does it provide cues for visual merchandising, but it also facilitates styling decisions and impacts buyers’ decisions for buying inventory for the season to come. Most significantly, this unique database is the key to cracking the most difficult piece of the retail puzzle, the customer.
ii. AI and Automation can help retail teams across the globe improve efficiencies across their workflows. Automation processes help brands with accurate data creation and helps provide context around shoppers’ needs and behaviors. By getting access to this accurate data and using it across personalization, styling and customised-marketing, brands can levegrage this information to curate experiences that are meaningful and valuable to the shopper
k. Intelligent Retail Automation
i. If one were to look at the customer journey along a retail chain, then automation can lead-in right from product discovery which can be boosted through “) automated catalog management, leading to enhanced product visualization, be it in terms of “); on-model imagery and an AI stylist, both of which can truly help customers visualize product in context. Leveraging this context and adding to this the power to be able to provide each shopper a bespoke, custom experience where they are capable of making choices on a shopper journey that is shaped entirely on the basis of their unique preferences. This now gives retailers the ability to understand shopper intent in real-time, thus leading to increased engagement and conversion. From a merchandising point-of-view, most retail teams spend a lot of time and resource in presenting their products on-site and in-store in a way that product discovery as well as associated products as discovered quicker by the relevant demography. Brands and companies worldwide are utilizing automation to generate on model images of their products, circumventing the need for traditional fashion photography and while controlling the custom needs of audience segments in accordance to their respective dress sizes, gender, styling preferences and need for accessorization. Retail teams today spend many hours doing work that, if automated, can be done in a few minutes. This lowers the productivity, morale and efficiency in a highly competitive market. With the power of data, AI can completely transform how retail teams function. Automation not only simplifies work but it also lowers costs, improves scalability, minimizes errors and increases efficiency. Automation democratizes functions, thus reducing dependencies and delays in the pipeline while at the same time ensuring that a constantly improving process is in place. It benefits both the retailer and the shopper.Intelligent Retail Automation allows a lot more people to access what used to be an exclusive experience, bringing in more people to the economy.
ii. At the heart of new retail is data, and ways it can be used to reduce pain points for consumers and merchants alike in traditional retail settings. Market analysis indicates that early efforts to remove human workers from retail have been met with mixed reactions from consumers. Nevertheless, the output value for such ventures in China is predicted to rise from RMB 20 billion in 2017 to RMB 65 billion in 2020, driven mainly by rising labor costs, offline operating costs, and consumer demand.
a. Skill Sets :
i. Employees will need new skill sets and knowledge on how to work with these new technologies.
ii. We will need to hire people (e.g., omnichannel experts) who can trace the entire business process and execute the move from brick-and-mortar to something more holistic of digital and in-store.
iii. Managing multiple chains of automation — from pick-and-pack robots in warehouses to inventory monitoring and management to software bots that help execute supply chain management — will require new skills from employees.
iv. Retailers will have to skill and reskill at scale.
v. Talent acquisition strategies require and upgrade.
vi. Automation and AI will fundamentally reshape activities and skills.
b. Technology :
i. The issue with analytics is true for anybody — you have data silos that don’t connect.
ii. You can send bots out to collect data and bring it back. For chatbots, the front ends are dumb and don’t do a great job currently.
iii. A robotic process automation (RPA) bot can sit behind a chatbot and execute certain tasks, such as taking on the role of an FAQ chatbot in the back end.
iv. Every business process will need to use software algorithms to solve problems.
v. Everyone has an IT department. RPA bots can help people in call centers do their jobs better and faster by connecting all queries in the back end to respond to problems more quickly.
5. Relevant Use Cases :
a. In-Store Automation — The key to competitive differentiation
i. Today’s retailers are placing an increasing focus on in-store automation. Where bricks-and-mortar stores are having to reinvent themselves to survive amidst a thriving online landscape, in-store automation has the power to entice new customers and keep old customers returning. By enhancing shopper convenience, it enables businesses to differentiate themselves and deliver a seamless omnichannel experience.
b. Using technology to increase customer convenience
i. When it comes to improving customer experience, savvy brands are getting ahead of the curve and investing in automation technology to solve in-store issues; particularly those centered around time and convenience. In the eyes of the customer, retailers that deliver a high quality, convenient experience leave a lasting impression and this is what differentiates one brand from another.
ii. Augmented reality (AR) is being utilized to superimpose digitally generated images over real-life view. Furnishing giant IKEA uses AR in this way, enabling its customers to use their smartphones or tablets to see what furniture looks like in their home. This removes the time and effort needed to visit a store, queue to pay and arrange for delivery — amongst a whole host of tasks required for in-store shopping.
c. Fast fashion gets even faster
i. Trying on clothes can be an arduous task. To alleviate this, many stores now offer ‘magic mirror’ and AR technology in dressing rooms, allowing shoppers to try before they buy. Earlier this year, fashion brand Mango’s new Westfield London store teamed up with Vodafone to roll out new smart mirrors in their fitting rooms. Shoppers can now digitally visualize what outfits will look like on — again saving the time needed to physically change.
ii. Along with magic mirrors, self-checkouts have been around for a few years. In a bid to make “fast fashion” even faster, wireless technology has been added to the equation, that removes the need to scan items. In addition to regular cashier desks, some Zara stores offer a self-service checkout area that automatically identifies items being purchased. Customers simply confirm items using the touchscreen before paying via card or mobile phone, to complete the transaction.
d. Reducing out of stock instances with Smart Shelves
i. Another common shopper pain point is dissatisfaction due to out of stock items. In answer to this, Sunglass Hut and fragrance maker Jo Malone are investing in smart shelves that use laser and motion sensors to detect when a product is picked up. Using real-time data, the retailers are able to monitor stock levels and receive automated alerts when levels drop — reducing out of stock incidents and creating a more seamless experience for customers. Jo Malone also has the ability to personalize the customer experience; when a shopper picks up a product, they are shown an interactive display offering a complementary fragrance.
e. The Importance of Personalization
i. With the advent of so much new technology, it is essential to remember the importance of the human touch. While fast fashion retailers, in particular, are focusing efforts on speeding things up even more, automation can also be leveraged to further personalize and enhance the in-store experience. Rather using technology to reduce staff numbers, retailers can alter the role of staff. Automating manual and mundane tasks can free up staff time to focus on delivering an attentive, 1–1 service such as styling, assisting with queries, and offering expert product knowledge and advice.
f. Automation has the power to completely shift the way consumers shop, by placing more control into the hands of the customer. By tackling both personalization and convenience, retailers can utilize automation as a way to stand out from their competitors whilst addressing the challenges that come with in-store shopping.
6. Examples of how automation is already changing the retail industry are :
a. Retail and CG :
i. Amazon Case Study : Amazon, which has made headlines with its Amazon Go retail concept, has been the most prominent disruptor. Amazon Go amplifies the meaning of what has traditionally been called a “convenience store.” To be able to shop in the store customers must download the Amazon Go app. In the store technologies as computer vision, sensors, cameras and learning algorithms are used to automate the purchase process allowing people to check out without passing from the cashier. Weight sensors on shelves and cameras on the ceiling detect when the customer takes a product and add it on the person’s virtual cart. Upon entering by scanning an app-generated barcode that essentially opens a tab, Go tracks the items removed from shelves for you and any of your guests who enter with you. At the end of the shopping spree, you simply leave the store with your legitimately gotten merchandise and have them charged to their Amazon Prime account. The food and sundries available at Amazon Go aren’t the kinds of products typically associated with the retailer that one might find at one of its bookstores. These stores represent a futuristic but ultimately fractional part of the retailer’s push into groceries, the massive market that is developing into its fiercest battlefield with Walmart. Of course, its main incursion is via its Whole Foods supermarket acquisition. For now, Amazon seems more focused on reducing prices at the organics-focused chain. But the number of Go stores may soon rival or exceed the number of Whole Foods’ markets, as Amazon has announced plans to open thousands of the 7-Eleven competitors in the coming years as it contemplates smaller and larger versions that can accept tons of greenbacks. The company now operates Amazon Go stores, in US cities, and the tech giant has ambitious expansion plans: 3,000 stores by 2021. Mckinsey’ s outside-in analysis of the profit-and-loss impact of Amazon Go technologies hints at a high return on investment (ROI). Amazon can expect a 5 to 10 percent top-line improvement thanks to additional transacting traffic from reduced wait times and the use of customer insights to optimize assortments and personalize promotions. Reducing labor costs and deleveraging the fixed-cost base can drive a 2 to 4 percent increase in earnings before interest, taxes, and amortization — to say nothing of the further potential from commercializing customer data and insights .
ii. Alibaba Case Study :
1. Hema stores changing the supermarket experience : Blending offline with online, Alibaba’s ‘Hippo Fresh’ stores showcase how technology can transform retail, including through an in-store robot restaurant. Chinese ecommerce giant Alibaba has gone all in on its New Retail play, taking the online shopping experience to bricks-and-mortar stores, starting with its own backyard.According to Hema CEO Hou Yi, technology has brought a lot of transformation into the retail experience, and there is no reason why a customer can’t have the same experience in-store as they do online. Alibaba opened its first Hema — Hippo Fresh — store in January 2016 and as of next month, there will be over 100 peppered across China. Products can be bought both online and offline from Hema, with Hou touting the idea as allowing customers to order food for the night on their commute home. Delivery is guaranteed for 30 minutes after an order has been placed if the customer lives within a 3km radius of a Hema store. Alibaba said house prices have soared in the delivery radius where Hema has a store presence. Hema has gained popularity in China for its mobile-first approach to grocery shopping. In the bricks-and-mortar shop, customers use a mobile app to scan items as they shop to get product information. All information, such as pricing, is updated live to the online store, which customers can also use to shop.Each store serves as its own 24-hour fulfillment centre, backed by Alibaba’s warehouse tech. Alibaba’s Alipay is also used for checkout both online and offline, with the company saying its artificial intelligence technology uses information about previous purchases to serve up personalised recommendations for shoppers. “We must blaze the trail and be the pioneer of New Retail so our partners, such as the farmers, brands, real estate firms, restaurant operators, and even our cohorts can learn from our experiences,” Hou said. Nestled inside one of Alibaba’s Hema stores in Shanghai is the company’s robot dining experience, Robot.He. When a customer arrives they check-in to a kiosk to book a table. The customer scans the QR code on their app to organise a seat. The customer then chooses the food they want to eat from the Hema supermarket, which, after purchase, is sent to the kitchen for cooking using ceiling-mounted conveyor belts. The belt takes the bag to a robotic arm that transfers it to a refrigerator until the food is ready to be prepared. While seated, the customer can order additional food through the app. Once the food is cooked, robots deliver the food to the diner’s table.
2. Alibaba — From New Retail to Unmanned Retail : Alibaba recently unveiled an experimental 80-square meter installation of its new Tmall Future Store. Inside, they were able to browse for food, snacks, and beverages while getting help as needed from a digital T-guide assistant, then settle their bills by simply exiting the premises thereby its Alibaba’s Taobao Technology Department laying foundation of unmanned retail. While Tmall’s unmanned Future Store presents an entirely new paradigm for shopping, it is only one part of a broader movement to upgrade offline shopping through new technologies, business models, and channels, known together as ‘new retail’. At the most basic level, new retail ranges from vending machines that accept mobile payments to the cheap, open-shelved mini shops many workplaces now offer thanks to digitalized business models that expedite stocking and reduce overhead. On a larger scale, it also encompasses supermarkets like Alibaba’s Hema that combine features of online and offline commerce, as well as cooperative ventures with independent retailers like Starbucks. With technology now able to support the truly futuristic experience the Tmall Future Store captures, unmanned retail can focus on giving consumers a whole new way to shop, rather than simply upgrading existing options. Having cleared the initial hurdle of cultivating demand for experiences like the Tmall Future Store, Alibaba has since been able to focus on the ways its new model can enhance business for its partners, as well as the efficiency of labor in the broader marketplace.
3. In one instance, moving the group’s Alicool souvenir shop to a completely automated framework increased annual turnover by 75 percent and sales volume by 20 percent, attracting 56 percent more consumers than during the previous year. At just 120 square meters, the store is now able to handle as many as 2,300 visitors per day, largely owing to the average 4.5 seconds it takes shoppers to complete automatic settlement when exiting.
4. In another example, Alibaba collaboratively renovated the Zhida Bookstore in Shanghai to enable automatic facial recognition-based settlement, greatly increasing the store’s daily turnover. Notably, Alibaba was able to apply findings from previous efforts to complete the installation of the new facilities in just 53 days, raising the store’s daily turnover by 78.3 percent.
5. With the Tmall Future Store, Alibaba has entered a phase it calls ‘unmanned retail 2.0’, significantly expanding on the capabilities Alicool and the Zhida Bookstore demonstrate. As well as a technical upgrade, the new phase involves a shift of emphasis from impressing customers to attracting existing merchants to the concept.
6. Technically, the key advance captured in the Tmall Future Store is computer vision. Upon first entering the shop, customers scan a code with their phones to establish their virtual presence there. Once they have done so, a series of roughly 100 screens will respond as they move through the store, making personalized recommendations and providing directions to help locate items. At shelves, the system uses gravity sensors and built-in cameras to identify and add goods to customers’ virtual shopping carts. This enables customers to simply leave when ready, as the system will automatically collect payment for any items which have not been returned as they exit. To document these transactions, the system generates a virtual bill which appears in customers’ Alipay or Mobile Taobao accounts, and the items in the virtual bill will also include links for repurchasing if they are available online. As a whole, this user experience traces the interaction of three core systemic capabilities: global tracking, product identification, and user-item matching. The last of these is by far the most critical, as any confusion that results in a payment being deducted from the wrong customer can invalidate the idea that automation can replace human services.
7. In an example of how this can happen, visitors occasionally cross arms reaching for items, swapped items, or offered to help each other return items, challenging the algorithm to sort out conflicting digital impressions. The best solution to such problems is prevention through the effective digitalization of offline behavior, presenting an ongoing challenge for developers as they seek to make these novel capabilities fully marketable.
8. In its present state, the Tmall Future Store introduces a coherent “6+1” technical architecture, in which five processing ends and a local gateway interact together with a coherent set of business priorities — namely transaction, processing, operating, and data storage in the cloud. While anyone hoping to open a store could work from this architecture, preparing it for widespread marketing still requires the targeted improvement of algorithm capabilities, reduction of hardware costs, and reduction of deployment costs. One current example of an algorithmic limitation is the need for customers to cooperate with sensors by standing still while selecting items or completing settlement. Ideally, scanners should be equipped to handle some amount of motion or other variations, presenting a complex deep learning problem for optimization. Further, the system’s facial recognition component uses an initial scan image of each customer as a “one-off” point of reference. As even human observers may struggle to tell whether two images from different angles show the same person’s face, refining the recognition algorithm poses formidable challenges.
9. Another outstanding challenge is to make algorithms more adaptable across environments, as each new unmanned store requires deploying and training the model to work within its specific dimensions and conditions. The key to doing so is separating the tuning of specific parameters from the model, which can be done using information gathered through the repeated deployment of its environmental sensors in different environments. In terms of market entry barriers, hardware costs remain preventive, not because they must be high but because the processing challenges developers currently face place heavy demands on equipment. Moreover, transforming a traditional brick-and-mortar shop into an unmanned store takes up a great deal of time, as engineers need to work on a by-case basis to update devices and systems one by one.
10. To reduce costs, Alibaba is working to narrow down the functionality of devices. Because the cost of increasing computing power is not linear, boosting central server power to cover more end functions is not viable in the age of edge computing. To counter this, cameras and screens deployed in unmanned stores will need upgrades to their own computing power. Another cost reduction approach in the works is device standardization. By making all devices replaceable, repairable, and consistent, developers hope deployment and maintenance processes can be streamlined and standard procedures enabled. This would allow for a robotic approach to off-hours maintenance and inspection for both hardware and AI. With the ultimate goal of establishing a device management system, developers are seeking applications for an Alibaba Cloud product called Linkedge, which can be used to develop a hot-swappable HAL layer for the framework that uploads and downloads device information for monitoring. In effect, this means the system will be remotely upgradable, deployable across different devices, and primed for the addition of new functions — in short, perfectly suited to the mobile era.
11. Tmall Future Store, is an offline Taobao designed to be as interactive as the mobile phones that shoppers carry in with them. Like the first wave of online commerce that Taobao emerged with, it is offering new ways to study people’s habits and preferences as shoppers, making stores both a laboratory for understanding economic activity and a setting for putting that knowledge to use. Some of the many ways data from unmanned retail stores can help merchants thrive. With the rise of e-commerce, many have voiced fears that platforms like Taobao will eventually make offline retail obsolete. With its Tmall Future Store, Alibaba is showing how the technology enabling it might instead be used to improve business for offline merchants, helping them to make smarter choices and better returns on investment. As a first step in unmanned retail, its
iii. Café X : Cafe X has popup versions even closer. Entering the storefront, you are greeted with a friendly wave from the barista, but that’s where the conversation ends, as all Cafe X beverages are mixed by a large robotic arm. Orders are entered via kiosks and drinks are picked up by entering a code on the arm’s enclosure. Cafe X’s vision of mechanized accommodations brought in line with the limits of material reality.
iv. BingoBox : Founded in 2016, the Chinese company BingoBox, counts today around 300 automated shops, in almost 30 cities around the country. The process of automation is not as high-tech as the Amazon Go’s one: all the items are labeled with RFID tag, the customers at the exit must scan the products in a standard self-checkout machine, and then pay using WeChat.
v. McDonald : McDonald’s has been the forefront of using kiosks for ordering. This technology gives restaurant workers more opportunity to focus on customers but also lowers the size of the workforce, at least in the long run. Let’s think about the kiosks in McDonalds, where costumers are able to order and pay using a screen and pick up the meal when ready; or the self-checkout cashier at almost every franchise grocery store today.
vi. Walmart : Walmart using Bossa Nova robots to automate inventory monitoring, helping customers, cleaning, or as checkout cashiers.
b. Fashion : How does this trend translate into fashion?
i. Zara : The expectations of someone buying cereals and milk are different from the service a person looking for an expensive dress expects. How can automation affect the customer experience in fashion? Can we still expect to have a level of human interaction ? In 2018 Zara, Mango and other big actors started automating part of the instore experience, creating self-checkout kiosks and/or giving the possibility to pay with the mobile phone via App. The customer only has to walk in, pick up the clothes she/he likes, self-checks out and exits the store. No human interaction needed.
ii. Rebecca Minkoff : Same thing happening in the NYC store of Rebecca Minkoff, where, since December 2016 customers have the possibility to self check out using ipads instore, with the same technology employed by the Chinese BingoBox.
iii. Alibaba : Alibaba wants to close that gap by merging the two experiences. Its newest venture FashionAI takes almost all of the conveniences of online shopping and puts them into an inventory-filled brick-and-mortar store built with RFID racks and AI mirrors.
iv. Nordstrom Local : Retail experts are now talking about different types of store formats and experiences that shoppers want. They are broadly divided into two. The first is that shoppers value convenience over anything. A transaction that is hassle free, low on effort and time and provides ease of access to purchase is an ideal transaction. Nordstrom Local, the big box retailer’s innovative service hub that serves as an ideal “pick up” store for customers that don’t want to spend more than a couple of minutes at a physical store. There are several reasons for customers opting for these types of efficient visits. It ranges from mindset, ability to save time, the overwhelming nature and interaction with support staff at physical stores.
v. Story : The other type of store is an experience store — a space that is designed as an escape for shoppers to feel like they are in a whole new environment. Stores like Story have built retail concepts that transport customers into spaces they never imagined. For instance, Story curated a summer experience store that people couldn’t stop talking about. With pool floats, cold herbal teas, beach drinks, swimwear and accessories, they made shoppers feel like they were on an island. Similarly, newer millennial-minded brands like Kith and Glossier are all about experiences. Kith features an expansive cereal bar for exhausted shoppers who want to feel refreshed and motivated to shop more.