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Technology Shots That Retailers Need To Level Up Customer Experience
An immediate shift from the traditional model to a phygital (digital and physical) model along with contactless buying experience is needed to maintain consistent sales.
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As work-from-home and learn-from-home became the new normal during the pandemic, OEM brands witnessed increased demand for smartphones, laptops, and tablets. Corporates procured laptops and smartphones in thousands for their employees. However, with dwindling customer confidence and expense cuts, the demand for computer and mobile products contracted gradually. Reaching self-isolating customers, understanding their needs, and regaining their trust is a challenge in the current market situation.
An immediate shift from the traditional model to a phygital (digital and physical) model along with contactless buying experience is needed to maintain consistent sales. While terms like ‘omnichannel retailing’ is discussed widely, the number of retailers that possess the infrastructure to build a seamless shopping experience from online to in-store is very minuscule. Workforce quality and productivity are also a huge concern in the wobbly marketplace.
Let’s look at some of the technology shots required to boost retail effectiveness and optimize the in-store experience in the modern marketplace.
Technology shots for retail recovery
Customer behavior and expectations have changed considerably since the pandemic. They are now looking for a seamless buying experience at their fingertips. ‘Touchless’ is the new buzzword, and retailers must adopt measures that make customers feel safe and secure. The impact of digitalization and data-oriented practices are apparent as big brands build their business models around data-driven digital transformations.
#1 Data-led tools and practices
Retailers need to leverage data-oriented platforms to optimize the in-store experience and improve the bottom line. Data-led salesforce management tools deliver actionable insights for the stakeholders to assess and reconfigure their operations. Insights such as sales/retail KPIs, operational hygiene, competitor data, customer touchpoints, and merchandising data optimize everyday retail operations. Furthermore, tracking consumer behaviour to create customer recommendations is essential for personalized in-store experiences.
The traditional retail environment is siloed with marketing, sales, and other departments working disjointedly. The old model had a linear flow of operations where products were prioritized through one channel. New business models supported by a combination of data-backed operations and techno-enablement helps connect processes, people, and channels to enhance the store visibility.
Big OEM brands struggle with low stock visibility and sales loss due to channel inefficiencies. Additionally, they face bottlenecks with real-time issue management hurting stores’ productivity. Leverage real-time automated software to update real-time stock information across all channels allows minimizing out-of-stock instances. A unified retail management engine built-in BI analytics streamlines data collection and reporting to optimize store hygiene, POSM deployment, and retail audits.
#2 Optimizing customer experience using visual merchandising solutions
Retailers must continuously optimize their physical stores with evolving consumer expectations. Some retailers have to evolve their merchandising quicker than others, for instance, electronics and OEM retailers.
Strategies like building strong relationships with key accounts, advocating premium shelf space, blocking visual and display items, and stocking up focused products, are crucial to maximizing sales. Intelligent merchandising strategy deploys next-gen capabilities to orchestrate the merchandising and shelf strategy based on market requirements. Business intelligence regarding purchasing history, demographics, engagement pattern, etc., helps augment the display elements of exclusive stores.
Capable data-driven software automates retail planogram software, optimizes shelf-space, increases products’ visibility, and creates a consistent in-store branding strategy. Brands have implemented an appointment system with staggered timings to comply with social distancing guidelines. Limited customers in the store allow for more cross-merchandising and off-shelf visual merchandising. Visual elements bridge the gap between in-store and digital shopping for a wholesome omnichannel experience.
#3 Retail analytics powered by AI and ML capabilities
Retail analytics, today, is mandatory to augment pricing, supply chain, operational hygiene, and customer loyalty. It entails analyzing customer shopping habits to derive business intelligence and using it to attract and engage customers across different channels.
Data analytics for retail is a comprehensive use case to capture and process a heap of data, including firmographic, technographic, and demographic data. Leading OEM brands are already embracing data-based retail solutions to streamline hygiene parameters, workforce upskilling, end-to-end program management, and more. AI-powered retail planogram software can track shoppers as they buy products off the shelf and analyze historical data to determine product placements. Retail analytics helps automate retail space planning and capture useful insights into cluster products, categories, and brands for increased buy-ins.
AI and ML-led retail analytics can boost retail effectiveness by collecting and analyzing field data to customize product roll-out, visual merchandising in relevant markets, customer support communication, etc.
Markets have opened up, and vaccine rollout has allowed customers to venture out. However, the retail experience has already undergone a seismic shift on the back of digital expansion, evolved customer preferences, and buying behavior.
Retailers must adopt data-oriented tools, software, and strategies to achieve uninterrupted sustainable growth. Proprietary retail management solutions are mandatory to achieve business growth through planogram automation, marketing automation, promoter training, retail audit, and more. Data analytics will also help retailers make informed decisions and optimize in-store operations for maximum customer engagement.
Disclaimer: The views expressed in the article above are those of the authors' and do not necessarily represent or reflect the views of this publishing house. Unless otherwise noted, the author is writing in his/her personal capacity. They are not intended and should not be thought to represent official ideas, attitudes, or policies of any agency or institution.