US Retail Innovation Outlook 2020...initiatives such as using AI-driven hyper-personalized targeting...

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Whitepaper | November 2019 US Retail Innovation Outlook 2020 Enabling the future of retail with Artificial Intelligence

Transcript of US Retail Innovation Outlook 2020...initiatives such as using AI-driven hyper-personalized targeting...

Page 1: US Retail Innovation Outlook 2020...initiatives such as using AI-driven hyper-personalized targeting methods and demand forecasting. However, with shrinking margins there are strains

Whitepaper | November 2019

US Retail Innovation Outlook 2020Enabling the future of retail with Artificial Intelligence

Page 2: US Retail Innovation Outlook 2020...initiatives such as using AI-driven hyper-personalized targeting methods and demand forecasting. However, with shrinking margins there are strains

US Retail Innovation Outlook 2020 - Enabling the future of retail with Artificial Intelligence

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Table of Contents

1. 3Introduction to Retail Innovation

3.

2.

5

4

AI Initiatives in US Retail Market

Top Three Drivers of Innovation in Retail

4. 7Initiating AI in US Retail Market Can Take Care of Hurdles

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Introduction to Retail InnovationRetail industry had moved from traditional

business models to virtual and smarter ones. Customer centric approach drives the

market and stakeholders are no longer dependent on trends and paper based model. Retailers and suppliers need real time customer insights to enhance penetration and market acceptance. Current and future retail business survival is intricately tied to understanding and responding to shopper or customer evolution in agile and innovative ways.Traditional and new school retailers are using Artificial Intelligence (AI), machine learning and robotics to automate retail chain, store operations, gather customer buying behaviour and more. Machine learning helps retailers predict patterns that help them understand desires, motivation and actions across both physical and digital channels. It also streamlines creation and fine tunes the revenue contributions of up-sell and cross-sell strategies, predict out of stock incidences, optimize supply chain and ensure ROI.To assess the pulse of the market with respect to retail technology innovation and in particular adoption of AI across business functions, SG Analytics conducted a survey in the US retail market in H1, 2019. The results of the study provides insights for US based retailers, foreign suppliers and distributors in the retail space, re-look and re-structure their strategies for 2020.

A total of 152 retailers participated from the US retail market, across all states. It was observed that 15% of retailers revenue is spend on innovation initiatives (including AI). Not surprisingly the key drivers for innovation spend revolves around enhancing customer satisfaction and creating a better shopping experience. Subscription-based models, integrated loyalty programs and social media shopping are innovative business initiatives. These work in sync with technology initiatives such as using AI-driven hyper-personalized targeting methods and demand forecasting. However, with shrinking margins there are strains on a retailer’s budget to adopt new innovation initiatives. Additionally, maintaining or replacing legacy systems require high investment both in terms of finance and human capital.

Type of retail format - Top 4

General Merchandise

Grocery and Supermarket

Apparel, Fashion and Accessories

Health and personal care

Survey Demographics

30%

20%

22%

10%

Type of job functions

CXO

Director

EVP/VP

Manager

16%

30%

22%

32%

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Readers will agree that globally every retail chain understands that it’s goods and services shall become commoditized as we enter the digitized future using AI. Competition and Leadership will require differentiation through personalized experiences as the next evolutionary step in the Experience retail. SG Analytics has

identified top three drivers that can become game changers in the retail industry, across the globe. Though USA will be the early adopters, Europe and others wont be much behind.

Hyper-personalisation is a term used when real-time behavioural data is combined with unstructured data from textual information found in product descriptions, ratings and reviews by using natural language processing (NLP). This makes the information personalized and adds a total new dimension to the customer data. Hyper-personalization can be applied in creating digital kiosk, clienteling applications, robots and more. Among the early users in retail, California based The North Face uses IBM Watson’s cognitive computing technology to check on customers on their preference for wearing coat – occasion, location, purpose and what they intend to achieve with the purchase and accordingly offers personalized recommendations to help customers find the best match (coat) and reduce the gap between the intent of buying and final purchase with more customer centric approach.

Source: TheNorthFace website

>80% customers expect retail brands to help them sustain in a more environmental friendly way and the millennial and Gen X are leading the brigade, as more climate changes are happening across. This drive has already started yielding results and expected to grow stronger in 2020. Procter & Gamble, PepsiCo, Nestle and more are joining the zero-waste loop platform to eliminate excess packaging from their carbon footprints, clothing brands Adidas are attempting to make sneakers out of ocean plastic.AI shall play an important role to measure the sentiments of the conscious customers and provide insightful trends to the retailer and manufacturers. The survey conducted by SG Analytics corroborated the same trends as

Top Three Drivers of Innovation in Retail

Hyper-personalization

The Rise of Conscious Customer

1

2

54%retailers felt that customer end satisfaction was imperative for survival and AI and technology can drive this further

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AI Initiatives in US Retail Market

Considering the fast changing trend in 2018/2019, retailer such as Walmart and Amazon (Amazon Go) to Domino’s and Stitch Fix, seasoned retailers to

disruptive start-ups, everyone has initiated the use of AI to streamline logistics and inventory management, to increase demand and prevent shrinkage and deliver personalized shopping experiences both in brick and mortar stores and virtual online stores.

“Today’s smart retailer is engaging in a new era of shopping experience, combining the

human touch and technology to deliver a more tailored consumer experience.”

Guita Blake, SVP, Mindtree

“Artificial Intelligence will be rampant in the digital supply

chain.”Dave Waters

It might shock some of the readers but wearables may replace smartphones in retail very soon. A buyer may depend on his wearable compared to his phone and dynamics of consumption will change accordingly. Experts believe that wearables are far more effective for personalization and user experience than smartphones. AI enables smart consumption among buyers reaching far more targeted and efficient consumption patterns by offering precisely what the customer wants. A recent example of diaper brand Huggies which launched material version of its product based on JD.com’s comprehensive analysis of orders and consumer reviews.

AI enabled Smart Consumption3

45% retailers had initiated or

currently were part of AI initiative

23% retailers were planning to introduce or

adopt AI in 2020/2021

AI can impact the supply chain management in more than one way. Forecasting, stock placement, replenishment, order fulfilment, and product returns or refunds supported by AI and automation, can reduce the gaps in supply chain. AI can play an important role from storage to sending and receiving products and bring down the cost associated with logistics and increase efficiency.

Inventory ManagementReducing inventory costs improves working capital performance; which can be an additional benefit for tier2/3 and start-ups where capital is constrained. Since 2016, two of America’s retail giants have been using robots to manage inventory. One such retailer Lowe’s introduced LoweBot in 11 stores across San Francisco Bay area to create real time data using computer vision and machine learning to scan inventory and develop/track patterns in products or price variations.

Initiatives in Supply Chain Management

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Dynamics in Merchandising has changed today – no two stores are similar, and treating them alike shall require an acceptance of the notion of acceptable financial loss. Retailers consider that AI enabled forecasting shall be in demand for merchandizing planning and pricing management, which would decide the future of merchandizing. AI engines predicting the above will have to process huge amount of data across channels and stores.Retailers based out of USA are eager to adopt AI because they believe that AI engines can predict out of stocks versus over stocks and can help in creation of real time inventory visibility, thereby improving inventory accuracy and indirectly managing customer satisfaction and increasing ease of purchase.

Demand ForecastingAI can be linked with other systems to balance potential demand, supply and capacity changes for products and inventory. It can be used to optimize the throughput of orders, suppliers and help the manufacturers to meet demand, thereby impacting the supply/demand management in to 30% of the participating retailers in USA claimed that they have started focusing on machine learning in demand generation and 33% have allocated budget for its adoption in next 12/24 months and soon shall follow others.

Initiatives in Merchandizing Management

“AI has been powering retail for years, and retailers have only been scratching the surface of what’s possible. A combination of the right solutions and an intelligent

approach to adoption and data management will help all retailers reap the benefits of AI.”Geoff Hueter, CTO, Certona

US retailers have started measuring the results of AI in marketing. For developing a successful marketing

management model, retailers prefer “personalization” as one of the pillars, followed by “interaction”.

Personalisation is a crucial element of the online retail and offline marketing mix that is transforming alongside the

integration of AI.The increasing use of chat-bots have led to enhanced

customer satisfaction, the disrupters in retail are adopting AI initiatives. 50% of the retailers are positive that more

AI and technology adoption would be focussed upon, besides 30% of respondents would focus on personalized marketing through dynamic personalized search engines

and social sentiments analysis.

Initiatives in Marketing Management

30% retailers had initiated or

currently were part of AI initiative

More than 40% retailers

consider AI enabled forecasting for merchandizing

planning

33% retailers were planning to introduce or

adopt AI in 2020/2021

5 out of 10 retailers are positive on AI initiatives in marketing management

30% of the retailers are planning to adopt AI driven personalized marketingin 2020/2021

One third of the retailers consider AI

enabled forecasting for pricing management

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Reinventing retail experience needs digitized approach especially for the hyper connected personalized shoppers. The customers of the converged world expect a smooth buying experience with prompt results that can be intimidating to an in-store employee

Initiating AI in retail does not mean laying off in-store employees. AI can actually change the current dynamics of the retail experience, by changing the way customers are served, currently. For that the retailers must gear up to introduce AI and support the employees in selling their products in a different but AI enabled way.In the retail world, CX is considered as the sum of all interactions a customer usually has with a company while EX (employee experience) is the sum total of everything an employee experiences while his or her connection to the organization. While the organizational focus is deeply rooted in CX, then next hurdle is to manage the EX. Manufacturers thinks that comprehensive EX can create engaged and effective in-store employees, empowered with the knowledge and tools necessary to interact with the current pool of informed customers. This transition shall require adoption of more AI to automatically detect and remediate the technical issues that is currently hampering the sales and connectivity between employees and customers. Though training can help employees do all of this, introduction of AI can add wonders.For example: In store employees can only manage the products on the shelved to sell. AI and machine learning can create efficiencies in the complex supply chain that usually involves multiple and compartmentalizied processes such as forecasting stock situation (when will the product be made available to the customer, if it is currently out of stock), order fulfilment and returns (when can the customer expect his returns – the exact day and date). Automation and AI can help in-store employees get customers the products or services they want (What?), When they want and How they want it to be delivered? This will change the current dynamics of customer service in retail using AI.

Managing the Customer Experience Optimizing In-Store Employees

AI expected to minimize the hurdles between online and offline retail and enhance in-store satisfaction

Initiating AI in US Retail Market Can Take Care of Hurdles

Brick and Mortar model is not going anywhere and neither are cloud based models. Future of retail will adopt be omni-channel approach i.e. a cross-channel approach that would ultimately converge the physical and digital shopping experience.The US retail market has market leaders in retail who have already made an effort to minimize this gap. E.g. Alibaba, Amazon and Walmart have taken the lead already, others expected to follow in 2020.Macy’s used IBM Watson (cloud based) in combination with intelligent engagement software from Satisfi (location bases) to enhance in-store environment. Other retailers are expected to follow.

“Let your store associates be active on social. “Friendorsers” are more important than paid models in showing our clothes – social influencers, but also our store associates, who are 100% our customers too. ”Emily Watkins, SVP, Real Estate & Construction, Charlotte Russe

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In 2018, Europe based Ocado entered the North American retail market with its second warehouse automation partnership (after Europe) and collaborated with Canadian food retailer Sobeys, besides, formed a partnership with Kroger to build 20 customer fulfillment centers for the North American supermarket giant from 2018-2021, with warehouses planned for Ohio, central Florida, and the mid-Atlantic region. This model is new in the US retail, however these facilities are fully automated and uses AI to track supply chain real time, bringing down manpower cost, operational cost and reducing the time gap between warehouse to store.

AI enabled to promote Infrastructure as a service model in future?

“With 30% fewer steps and up to 50% less labor, we can produce

a complete pair of uppers in just 30 seconds at scale with less waste.” Eric Sprunk, COO at Nike

(on adoption of AI in Nike)

The Way ForwardAs we enter 2020, partnerships between companies to strengthen data analytics or crucial step delivery must be considered as a captivating model in retail compared to vertical integration models which were followed in the past. AI enabled smart consumption through enhanced personalization that optimizes the risk of failing to offer the shoppers – services and products that they would like to purchase; which in turn minimizes unsold inventory that needs to be cleared and also reduce the likelihood of refunds, making the 2020 retail market more sustainable in USA

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With the emergence of e-commerce in retail industry, consumers now enjoy unprecedented access to markets. As a result, retail sector companies need to work harder to stand out in the crowded marketplace. SG Analytics partners with retail companies globally to deliver a range of retail market research and retail analytics solutions that help clients enhance their understanding of consumers and competitors.

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Dr. Siddharth DuttaSr. Industry Advisor

Dr Siddharth Dutta is a seasoned market researcher and passionate blogger and business writer for 20 years. His articles and surveys have been well quoted in famous business magazines such as Forbes (USA), Bio Spectrum Asia (Singapore), Consultant Reviews (India), Pittsburg Times (USA) and have been quoted in other business magazines in Australia, Japan, Hong Kong, Malaysia, Singapore and India.

Nayanjyoti DasAssociate Vice President

A market intelligence professional with 14+ years of experience in Research & Insights. He has significant exposure in conducting both quantitative and qualitative programs for several global firms across Retail, CPG, Technology and BFSI. He has seamlessly executed several market & competitive intelligence, benchmarking, consumer insights assignments, developed business strategies (GTM, expansion and digital), and launched ROI tools & Innovative indexes.

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