Power of Data Analytics in Shaping and Enhancing the Customer Experience Online

The retail industry has always been competitive, and it is important for retailers to thrive in this competition by adapting to new technologies and trends. In the current age of e-commerce, any retailer who does not adapt to the changes will stay behind their peers.

With ever-changing customer behaviors and their requirements for personalized shopping experiences, it has become essential for retailers to invest more in these areas. Studies have shown that 73% of customers expect retailers to understand and provide personalized offers and unique recommendations tailored to their needs.

Advanced analytics enables retailers to achieve this by transforming raw data into valuable insights. Analytics can be applied in diversified areas such as customer behavior, sales, marketing, and operational costs. For performing data analytics, the retailer needs critical data like Transactional data from different online platforms, Online Performance and Behavior data, Customer Data, Customer Feedback, and Product Data. This data can be collected and processed to draw valuable insights that help retailers make essential decisions.

Analytics can influence the whole customer journey. For example, Retailers can

• Display product recommendations online based on historical data, customer segments, and current trends.
• Offer tailor-made products designed based on the customer requirements and interests.
• Send relevant and personalized marketing messages through emails, push notifications, messages, or WhatsApp when there are discounts or promotions based on their interests.
• Use website analytics tools to help retailers observe users’ behaviors, identify pain points in their online purchasing journey, and take appropriate action.
• Achieve dynamic pricing of products based on competitor pricing and other conditions.
• Help the customer to choose the right product using a little data input provided by them.
• Deploy chatbots that access the available data and provide valid inputs to customer queries.
• Identify potential issues through analysis of customer feedback and resolve them to enhance the customer experience

Several approaches are available for data analytics, such as descriptive, diagnostic, predictive, and prescriptive analysis. Technologies such as AI, ML, IoT, and CRM play a vital role in shaping the personalized experience for customers both in-store and online.

Major retailers like Amazon have introduced personalized recommendations to their customers based on their previous shopping behaviors, search criteria, etc., more than a decade ago. They are still finding better ways to provide superior customer experiences.

Many retailers have started adapting to the innovations powered by analytics using AI. For example, personalized recommendations and customer service by Fashion Retailer Sephora, Target predicts customer needs based on their shopping habits and provides them with relevant offers; Nike uses the data from its online platforms to create new products that align with customer interests and personalize the marketing messages thus enhancing customer experience.

Conclusion

The year ahead will be prominent for many retailers who are not ready for analytics due to multiple challenges, such as data quality, lack of initial investments in proper infrastructure, and limited availability of skilled resources. Hence, retailers need to work towards modernizing their infrastructure and upskilling the resources to transition smoothly into the analytics trend.

Cigniti, with its proven expertise in end-to-end Retail Testing across multiple channels, helps retailers undergo business transformations by employing quality-optimized and results-driven strategies. They assist enterprises in their Digital journey using a thoroughly thought-out Quality Engineering strategy and impeccable execution. They leverage our strategic test tool partnerships globally to bring agility to the overall business processes. Their approach includes unbiased quality engineering, tailored retail testing frameworks, and industry-specific domain expertise.

Cigniti’s end-to-end testing processes support individual and large-chain retailers to ensure quality across their enterprise applications. They facilitate initiatives such as re-platforming, upgrading, migrating, and setting up complex integrations between CRM, OMS, WMS, Cloud, Mobile, and Web applications.

Need help? Contact our Data Analytics and Retail experts to learn more about the power of Data Analytics in shaping and enhancing the Customer Experience online.