OBJECTIVE
The objective of this white paper is to provide a contemporary perspective on how retailers can effectively utilize Artificial Intelligence (AI) and how the infusion of cognitive customer engagement can positively affect the infamously unpredictable consumer behavior.
The term ‘Retail industry’ can be broadly applied to any business ranging from hyper markets to mom-and-pop stores or a multi-channel entity; it can also be applied to any other industry that predominantly functions in the area of consumer engagement.
INTRODUCTION
A retailer’s world is a disruptive ecosystem. Technological advances have transcended traditional business to sales channels never thought possible hitherto. Couple this with an explosion of data with the added onus of enhancing brand perception, you have what we can safely call the Achilles’ Heel of modern-day retail.
CHALLENGES FACED BY MODERN-DAY RETAILERS
Technology has empowered consumers like never before and firmly placed them in the driver’s seat. From this vantage point, collectively, they have the power to influence a brand by harnessing the power of social media, print media, and other mass communication channels.
Empowered customers have also become technologically savvy, and are using a wide array of tools and platforms to shop as opposed to the traditional in-store retailing. The adage “patience is a virtue” does not hold good for the millennial shopper, who craves instant gratification, and the ability to pause and resume shopping from any of the connected channels seamlessly.
Retailers, to ensure an ever increasing patronage, must be able to devise methods that help them intelligently sift through voluminous and varied data sets for meaningful insights, which can be channeled back to business processes for optimizing operations and providing a seamless consumer experience.
In this digital era, retailers have to look beyond selling, and introspect on their existing business processes. The sole objective here is to adopt contemporary technology to augment or replace existing solutions and provide a real-time, bird’s eye view of the problem at hand.
With the growing need to stay competitive and relevant, the Retail industry is headed towards a future where proactive consumer engagement is the key to drive demand and optimize the pricing and operational management components of the ever-sensitive retail supply chain.
DE-MYSTIFYING BIG DATA—THE WAY FORWARD
Disruption is ever prevalent, and technological advancements have made consumer demands esoteric and challenging to fulfil. Modern-day retailers possess valuable data about their customers; however, the catch is that the data available is not standardized. This makes it difficult for traditional systems to process the information and deliver crucial insights in a timely manner. In a happy coincidence, with the emergence of cloud and big data technologies, and a sharp reduction in computing costs, it is possible to process large and disparate data sets in real time.
Retailers can use AI to create intelligent mining bots that can process the available data and deliver causal models or facets about business consumer engagement hitherto unknown, in a relatively short span of time.
Retailers can efficiently adopt AI by deploying an infusion of deep learning networks that can help architect models, and also progressively learn and update itself, based on market/consumer dynamics. Such is the power of these models that a retailer can go from being disrupted to being a disruptor in a short span of time.
DecisionMinesTM is one such platform that can intelligently create value-added insights across the retail ecosystem, supplemented by a prescriptive course correction strategy that can further fine-tune existing business process and improve the bottom line of retailers.
EMBRACING DIGITAL TRANSFORMATION IN RETAIL
Digital Retail is here to stay and retailers would be well served if they choose a planned approach towards embracing digital transformation. Digital transformation is not a new buzzword, but has been in existence for a while. Retailers need to envision a strategy to unify all their existing points of sale or, in other words, their window for customer engagement. Add to this mix a plan for future expansion, and the retailer has the initial blueprint ready for a foray into the digital realm.
For a matured industry like Retail, the unification of existing systems is easier said than done, because of the complexities of the participating systems, some of them bordering on the legacy type.
Such complexities make today’s retailers hesitant to proceed on the digital transformation journey. It takes a planned approach to create a unified ecosystem, which can create experiences that respond rapidly to the real-world events.
Cybage has helped retailers embark on digital transformation by mapping out consumer journeys, standardizing operational and back office systems, designing automated processes, and leveraging targeted marketing to make this move less risky. Retailers can adapt to this new trend by moving away from solutions that deliver only incremental value, to models that have a direct bearing on consumer retention, loyalty, and operational and financial efficiency.
With digital transformation, retailers can derive meaningful actionable insights, and swiftly adapt to changing market conditions.
BENEFITS OF A CAUSAL MODEL
Timely insights supplemented by prescriptive suggestions can provide an engaging consumer experience. The heavy lifting is easily accomplished by AI. Traditional retailers can use this model to efficiently manage areas such as:
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In-Store Experience:
Re-invent the store of the future by using AI-driven models. Retailers can easily identify star performers, get advanced predictions about the impact of employee attrition, and create targeted consumer experience zones. -
Customer Service:
Enhance brand image by proactively knowing your customer preferences. Easily schedule campaigns and promotions that showcase consumer needs and drive sales. -
Never Go out of Style:
With machine learning and AI, retailers quickly adapt their merchandise to trending events, thereby increasing sales. -
Supply Chain:
Retailers can leverage AI-powered location analysis, demand forecast, price sensitivity, and other factors to develop a data-aware supply chain ecosystem.
AI-RELATED TRENDS IN RETAIL
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Alexa/Google:
With voice-activated searches becoming popular, retailers are experimenting with virtual assistants who can intelligently answer consumer queries, or help them complete their shopping either online or in-store. -
Virtual and Augmented Reality:
Traditional brick-and-mortar models are making way for digital shopping. Using mobile phones, consumers can create digital avatars and try out various outfits anywhere, on the go. Bid goodbye to queues and changing room privacy concerns. -
Natural Language Processing (NLP):
This is an area, which, unlike the previous two, is more mature. Retailers have used AI systems to process and understand natural language and provide intelligent responses. Common uses of this technology are the clichéd chat bots and digital shopping assistants, who are trained to understand human language and keep learning to improve their responses
CONCLUSION
Disruption has become the norm in modern retail. Retailers today have to strive towards a unified ecosystem that comprises:
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Data Science Platform:
A data science platform facilitates the transformative journey of decision makers. It takes them from description of issues in hindsight to objective diagnoses, progressing through enhanced incidence prediction and prescription of preemptive solutions, eventually leading to a state of continual self-learning and real-time actions. -
Unified Commerce:
The customer is king, and it is this king that motivates brands to compete. Creating a holistic view of the customer is crucial and this can be manifested by putting in place a unified commerce ecosystem. -
Internet of Things (IoT):
The latest entrant in the field of Retail, however, has a big impact on the way millennials are engaged. An intuitive solution keeps a consumer engaged for longer durations, thereby increasing the probability of conversions.
FACTS AND FIGURES
By 2020, 85% of customer interactions will be managed without a human. By the end of 2018, “Customer digital assistants” will recognize customers by face and voice across channels and partners.
(Source: Gartner)
Out of the 717 retail and e-commerce decision makers surveyed, 42% of them are presently piloting, implementing or expanding their AI programs.
(Source: Forrester)
Companies with strong cross channel customer engagement see a 9.5% year-over-year increase in annual revenue.
(Source: Aberdeen Group)
AI will drive 95 percent of all customer interactions by 2025, with consumers unable to differentiate bots from human workers via online chats and over the phone.
(Source: Servion)
By 2020, 100 million consumers will shop in augmented reality.
(Source: Gartner)