Operationalizing AI / Advanced Analytics to Improve Online Retail businesses

Blog: NASSCOM Official Blog

Savitha Chinnappareddy – Technical Lead, Emerging Technologies & Solutions

A recent report titled COVID-19 Impact on Global E-Commerce & Online Payments – 2020 revealed that a double-digit share of online shoppers was buying more digitally due to COVID-19, and some of them adopted the practice for the first time during the outbreak. The share of global retail sales generated via E-Commerce was rising and projected to reach one-third by 2024. There has been a sudden change in how people are approaching this period of isolation, and it has changed their shopping behavior. From bulk-buying to online shopping, people are changing what they’re buying, when, and how. This has also pushed a lot of rather traditional brick and mortar operations, finding ways to sell online. New data from eCommerce platform provider, Shopify Inc., suggests the number of new online stores across the globe on its platform increased 20% week over week for each of the last two weeks of March 2020. As we move into a new normal in the coming days, it is safe to say that people would be looking forward to shopping online rather than visit crowded markets which will act as a catalyst to the growth of online retail.

The changing technological landscape in retail

In an ever-changing retail landscape, retailers who have successfully embraced digital transformation are gaining a significant competitive advantage in an atmosphere where customer experience rules. While traditional retailers are adopting digital technologies such as the Internet of Things (IoT), mobile, Augmented Reality (AR) and Virtual Reality (VR), Artificial Intelligence (AI) and Machine Learning (ML) to connect with customers, digital players have recognized the advantages of establishing brick-and-mortar locations to round out the experience they can offer their customers. Here are a few of the most disruptive developments in retail today:

VR and AR – Simulation technology allow customers to arrange furniture in a virtual rendition of their home, check the fit of clothes without trying anything on, and even test drive a car.
Customer adoption of emerging platforms – Shoppers increasingly use technology to research products and services, making it essential for retailers to address customer concerns in real-time.
New class of retailers – Retailers are inventing new business models such as brick-and-click that integrate online and offline sales portals.
New metrics to measure success – Customer experience per square foot is supplanting sales per square foot as the primary measure of retail performance.
Rising digital adoption – Retailers are engaging in AI technology to supplement human customer support. Chat-based shopping and voice commerce increasingly being adopted.

Data Analytics and AI changing Online Retail Operations

We live in a world where consumers expect and demand instant gratification when shopping online. It is becoming increasingly difficult to satisfy consumers at the pace they expect without compromising on the quality they demand. To add to that, competition across markets are at an all-time high. Even during these times, two solutions stand out and show long-term promise – Data Analytics & Artificial Intelligence (AI).

Let’s delve deeper into a few sectors which are being disrupted with the introduction of data analytics and AI into online retail –

Customer Segmentation and Interaction

While traditionally, segmentation is generally done based on mass and demography based data sets, with AI capabilities in place, online retailers can now adopt micro-segmentation by building a strong opinion based individual customer persona. This leads to more personalized offers being generated for prospective customers. On the other hand, customer interaction has moved from being one-sided to interactive, where responding to customer questions are done through voice and chatbox based AI bots. Through AI, online retailers can also predict customer attrition based on the customer’s persona, buying behavior, and other external factors.

Another area where AI is revolutionizing the retail sector is through wait time prediction. Rather than merely providing a pre-determined estimate to a customer for any tech support or servicing stores, looking at previous data and using ML, online retailers can set better wait time expectations leading to better customer satisfaction.

Intelligent Product Recommendation and Pricing

The implementation of data analytics and AI has enabled online retailers to recommend a product by understanding the what, how, and why of customer requirements rather than just product compatibility and sales history. Pricing strategies have also changed with the introduction of AI. While traditionally pricing would be based on pre-defined factors like sales history, promotion and holiday calendar etc., AI can now monitor competitor price changes and market fluctuations in real-time and recommend pricing at product and store level. In case the system requires to provide estimated pricing, with data analytics and ML, it can offer such approximate estimations more accurately. Additionally, based on feedback regarding the performance of the products and upgradation journey, online retailers can predict or decide the warranty of the products in a much better way.

Forecasting, Inventory Management and Logistics

With traditional tools, it was difficult to predict demand and manage inventory based on internal and external events. At the same time, tracking orders and predicting delays was also a cumbersome task leading to dissatisfied customers. However, with newer AI tools being introduced, online retailers are now able to predict demand better by monitoring events, manage inventory by monitoring real-time stock situations and predict out of stock or stock at-risk situations by analyzing customer behavior, fashion trends, weather patterns. Based on the analysis of delay in delivery or delay in response in case of the online segment, decisions can be taken for locating the new inventory or stores accordingly. The logistics team can enable real-time data sharing, order tracking, and delay prediction through the supply chain critical path with AI tools. With AI, it is also possible to predict the areas where demand will come from and assign delivery resources accordingly.

To achieve a successful digital transformation, retailers need to do more than merely acquiring huge data sets. AI capabilities can equip retailers with the ability to ingest large volumes of data in various formats across locations, learn from patterns, and respond in real-time. Creating a 360˚ customer profile also helps generate relevant, personalized offers to customers. In addition to helping retailers customize their offers, AI and ML enable predictive analytics, allowing retailers to project the details of a customer’s history into the future, and calculate outcomes for events such as product sales or store renovations. Understanding these outcomes vastly increases retailers’ ability to prepare for events and respond to customers proactively. Thus, AI and ML offer enormous potential for retailers to deliver compelling customer experience, drive cost efficiencies, and even improve employee motivation. Data analytics, AI, and, ML have already begun to disrupt the way retailers do business. Retailers that successfully adopt digital technologies will reap competitive advantages in days to come.

The post Operationalizing AI / Advanced Analytics to Improve Online Retail businesses appeared first on NASSCOM Community |The Official Community of Indian IT Industry.