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The retail sector in 2020, was supposed to be a 26 trillion $ worldwide market. Greatly affected by the economic slowdown across countries due to the COVID-19 outbreak, the market is now expected to be a $21.6 trillion market in 2020; with post-2020 recovery and growth at a CAGR of 5% to recover back to $25.1 trillion by 2023. COVID19 has led to major shifts in global demand, with a reduction in consumer earnings and purchasing power, shutting down malls and retail establishments, and moving consumer demand online. While some retailers are seeing demand fall away and customers shift channels, others are facing demand spikes, viz grocery and essentials, who are dealing with significant out-of-stock situations on key products, because of consumers stocking of essential supplies; this is causing the ability to predict and manage demand in real-time, to be more important than ever before. As eCommerce sales experience a boost, retail firms also need to evaluate their digital brand perception and benchmark themselves against leading competitors in this space. Retail expectations are consistently growing, requiring quality services, experiences, and customer engagement throughout the purchasing journey.
Adapting to the change
Key factors to remain resilient in COVID19 times, start with maintaining financial resiliency – to achieve this, retailers could create digital models of their retail business, considering major demand influencers and stress test ‘what if’ scenarios, to arrive at the optimal financial strategy built for resiliency. Second is Protecting people – losing key people due to temporary measures will cause irreparable long-term damage, repurposing people, and resources to areas of shifting demand and overworked departments would resolve this. Third is to de-risk supply chains – significant variations in the magnitude and timing of supply chain disruptions across geographies and subsectors will affect suppliers, retail firms need to identify and resolve these. Lastly but most importantly staying connected with consumers and getting real-time consumer insights, will help assess changing demand or channels guide proactive planning better.
Seamless Integration: Need of the hour
Retail technology’s fundamental purpose is to help customers find and experience products faster and better, this can be done through virtual store guides, personalized product recommendations, or even virtual contactless shopping and more. The multitude of retail use cases demands enhanced service levels and experiences. Next-Gen service levels, brand experiences, and capabilities for predictive demand forecasts require a significant transformation of multiple touchpoints both physically and digitally, in addition to enhanced back-office and supply chain operations, enabling retailers to meet people where they are. Digital technologies by themselves only enable siloed experiences, e.g. smart fitting rooms, or self-service checkouts, their true value is realized only when they integrate with other digital technologies in the retail ecosystem, enabling blended next-gen, online and offline experiences, such as style recommendations and automated checkout. It also helps the retailer track what is working, while seamlessly integrating into customer’s lifestyle, helping them notice only outcomes. Identifying priority customer journey problems and spaces where digital technology can truly assist, will help create a true customer-centric approach to digitalization. 5G, Edge AI, Mixed reality, RFID, and NFC technologies show great promise with innovating use cases, in accelerating the transformation needed, to make this possible.
How retail could reposition
Creating consistent brand experiences across channels, attuned to shifting demand, requires a strong digital foundation. To design successful digital strategies and enabling technology roadmaps, retail enterprises need information about their existing consumers, target market, and their purchasing behaviors. Economists have classified the consumerist generation into 4 major categories of generations, Baby boomer, gen x, gen y (aka millennials), and gen z. Each generation has had different growth paradigms, technology dependence, and purchasing behaviors.
To customize and market products to every generation of customers in the best way possible, it is imperative to gain customer interaction data and convert it into insights. For most retailers, much of this information lies in multiple disparate systems of record, as shown in the diagram, and it needs to be unified into a single data source for Big data analytics, this can be done leveraging custom APIs, connectors, cloud data lakes, and big data systems. Such a unification could proactively in near real-time, provide insights into changing demand and provide customized insights to create a retail framework, that enables fast change, fuels growth, and repositions them from a firm selling goods efficiently, to a firm that enables consumers to buy exactly what they want and need, from a retailer they trust. Edge AI, NFC devices combined with other retail technologies are improving the big data gathering and customer insights generating process. These further the use cases for virtual and augmented reality services, smart screens, and mobile-cloud services. Furthermore, AI and machine learning could take optimal advantage of social media’s growing influencer network.
Strategizing to win
One strategy does not fit all, and it is especially apt in terms of ROI for retail strategies. The retail strategy must align to its brand positioning, value propositions, and customer preferences, and even more so in terms of their digital strategy. Retailers have different levels of digital maturity to enable various experiences, and most use cases would give varying ROI based on the retail enterprise’s digital maturity, brand, individual strengths, traditional channels, and financial muscle of the firm.
With every use case requiring a unique blend of technologies, processes, and frameworks, and in-depth context to be assessed; partnering with technology consultants and retail experts can be a good start to identifying aligned business use cases and devising a winning retail strategy that defines clear and quantifiable metrics for measuring success. Use Cases can be classified under three categories shown in the following diagram based on complexity, technology assessment, and strategic alignment.
While each use case would have to be contextualized to the retail enterprise, few of the low hanging use cases are as below: –
Digitally Mature (Digital NHI and Contactless experiences)
Leverage deep neural networks to train video analysis systems to mimic human behavior and engage in real-time interactions as well as provide insights
Track in the shop, outdoor environment sensors, and external partner data sources for mass-customized real-time shelf displays and predictive inventory management
Contactless shopping where the customers can walk out of a store with payments and deliveries taken care of, like Freshippo
VR based shopping assistance to “guide” consumers through physical stores via an augmented or mixed reality overlay on their smartphone
Digitally Growing (Maturing Targeted Retail and optimize supply chains)
Enhancing retail search capabilities from a keyword or NLP based communication to a Contextual NHI level (can be done by integrating cloud NLP, ML, and AI search tools)
Tracking store visitor traffic, direction of gaze, and dwell times to understand patterns and use NFC to provide real-time product info and guide to the fine exact aisle
Reduce Inventory distortion and improve supply chain transparency through 5G massive machine type communication features IOT sensors, tracking assets such as perishable goods in real-time
Maximize the effectiveness of retail floor plans through buying behavior insights
Vcommerce to enable consumers to buy products through Voice and Virtual channels in an automated fashion
Digitally Emerging (Gain consumer Insights and Automate functions)
Monitor COVID19 compliant safety behavior in stores and with employees
Generate traffic heat maps and end cap analyses to spot trends in merchandising and display performance
Chatbots to manage and automate the item return process
Auto tracking Security using thermal imaging and advanced motion recognition algorithms and track movement into unwanted or restricted areas
Consumer – brand interactions enabled by 5G enhanced mobile broadband, mixed reality, and video analytics will enhance virtual and remote sales support and provide better product information pre- and post-sale. Moreover, 5G will enable massive machine-type communications to connect many devices further easing the enablement of several new use cases.
Omni channel congruence
A solution to combat shifting purchasing channels without compromising brand experience is a robust omnichannel retailing strategy. Omnichannel is largely enabled by unified systems and platforms. It is an evolution of multichannel retailing, allowing customers & multiple distinct channels to interact, get information, evaluate, and make a purchase while interfacing with combinations of multiple channels yet getting a single unified experience from all of them simultaneously.
A customer could buy a product online and come pick up in-store or use a mobile interface to research or use virtual/extended reality to experience a product before purchase, or they can buy in-store but initiate a return online. The focus for retailers would be, to implement customer insights from unified integrated systems to fine-tune perfect omnichannel strategies that ensure strong competitive positioning with digital and other channels. With a 360-degree view of customer purchases and interactions across all channels, retailers would be able to provide a seamless experience and communicate consistent brand positioning.
Bringing it together
Enabling complex use cases requires a convergence of vertical expertise around – eCommerce and digital models, physical and digital payment solutions, retail core business, customer experience needs, supply chain metrics, mobile experience metrics, Omnichannel retail metrics, and Core Technology expertise around – tech benchmarks, machine learning models, video analytics essentials, edge analytics, mixed reality products, custom chatbots, conversational computing platforms, Internet of Things (IoT), personalization and more. Partnering with technology or digital vendors to implement these use cases, with predefined outcomes, could help retail firms bridge gaps and catalyze the achievement of a sizeable market share.
Implementing custom digital strategies are needed to improve efficiency, safety, experience, and revenue. Insights combined with design thinking will create new business models and marketplaces allowing retailers, to predict human desires and adapt the brand experience to move beyond revenue growth to meeting customers’ wants in new ways. The fast-changing economy is forcing retailers and digital firms to continuously innovate to stay ahead, but it isn’t without reward, as retailers who can synergize with Technology and Digital firms, to design memorable brand experiences across channels will provide indispensable value, significant ROI, and attract demand fast.
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Content:
Introduction
Convergence of RPA with AI
Real-life use cases
Diverse Applications of RPA in Marketing for NBFIs
Benefits of RPA in Marketing for NBFIs
Best Practices for Implementing RPA in Marketing
Challenges and Considerations…
Introduction
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