Realtime Data - The Future of Digital Commerce

Discover the power of real-time data in digital commerce! Learn how it can transform your business and drive growth. Read our blog now.

Digital commerce is always evolving.

And the fact today is that a consumer turns to an average of 7 different channels to communicate with brands.

Businesses need to create a seamless journey — complete with hyper-personalised shopping moments.

This is why Real-time data is crucial for e-commerce businesses in India, as it allows them to make informed decisions based on up-to-date information. So today, let us walk you through an extensive guide on Realtime Data - The Future of Digital Commerce.

What are the benefits of using real-time e-commerce analytics?

  1. Streamlining operations to reduce costs 
  2. Improving customer experience to gain loyalty.

Which requires the right tools & strategies, where Real-time Data Reigns Supreme

What are the real-time features?

  1. Understand Customer Behaviour: Real-time data can help e-commerce businesses track customer behaviour and understand what customers are looking for, what products they are buying, and how they are interacting with the website. This information can be used to make data-driven decisions, such as optimising the website layout or product offerings to better suit customer needs.

    A study by Google India and Forrester Consulting found that real-time data is critical for e-commerce businesses to understand customer behaviour and make data-driven decisions. The study found that 70% of e-commerce businesses in India believe that real-time data is important for their success.
  2. Monitor Inventory Levels: Real-time data can help e-commerce businesses keep track of inventory levels, ensuring that popular products are always in stock and ready to be shipped to customers. This can help reduce the risk of stockouts and lost sales.
  3. Identify Trends and Opportunities: Real-time data can be used to identify trends and opportunities in the market, such as new product categories that are gaining popularity or shifts in customer preferences. This information can be used to adjust business strategies and capitalise on emerging trends.
  4. Improve Order Management: Brands can efficiently track and manage all operations
  5. Improve Customer Service: Instantly update across preferred channels. Differentiate users based on their needs across channels and target right (Conversion Funnel).
  6. Enhance Marketing Efforts: Real-time data can be used to optimise marketing efforts, such as targeted advertising and personalised promotions. This can help e-commerce businesses reach the right customers at the right time with the right message, leading to increased sales and customer engagement.
  7. Scale Hyper Personalisation: Predict user behaviour to provide personalised brand experience
  8. Automate processes: Respond to customer needs as they arise by automating Return Management, Support via Chatbots etc.

How do you integrate Real-time Data? 

  1. Connect all your analytics

    Bring together all your customer data across platforms, devices, locations and more

  2. Harmonise the information

    Analyse that data to get customer graphs, and to optimise overall marketing strategy

  3. Engage deeply

    Empower every department and stage of your brand experience with unified consumer profiles and adapt to their activity in real time.

  4. Implement end-to-end personalised experience

    Create magical experiences at the right time with your customers - for milliseconds could make a lot of difference

    Example: 1Checkout sets the preferred address and payment mode based on past history (across 450+ brands) to enable a purchase under 5 seconds, and to personalise upselling & cross-selling post purchase.

Targeting the various platforms based on the real-time data. That’s the goal!

  • Advertising products on Facebook
  • Using Instagram posts & ads
  • Improving your SEO for holiday traffic
  • Sky-rocketing open rates for WhatsApp and Email

What E-Commerce Metrics Should I Monitor in Real-Time?

Real-time Data for Consumer Behaviour

  1. Clickstream data: This type of data tracks the sequence of web pages that a user visits on an e-commerce website. Clickstream data can be used to understand user behaviour, such as which pages are most popular, how long users spend on each page, and which products they view.

    96% of users who start a purchase on an e-commerce website do not complete it, but with the real-time data, you can monitor the region of drop-off.

    And eventually analyse the reason behind it.
  2. Search queries: This data shows the keywords that users are using to search for products on your website. It can help you optimise your website for search engines and improve the user experience.
  3. Time spent on site: This metric measures the amount of time a user spends on your website. It can help you determine the effectiveness of your website in engaging users.

    The average time spent on e-commerce websites in India is 3-5 minutes, and brands should understand consumer behaviour through tactics like heat mapping; and learn their interests.
  4. Bounce rate: This measures the percentage of users who leave your website after visiting only one page. A high bounce rate can indicate that your website is not meeting user expectations.

    After waiting for a mere 3 second period, 57% of online consumers abandon an ecommerce site. And another tough truth is that 80% of visitors do not return again.

    Making it crucial to understand the on-site behaviour.
  5. Conversion rate: This measures the percentage of users who complete a desired action on your website, such as making a purchase. It can help you understand the effectiveness of your marketing campaigns.

    The average conversion rate for e-commerce websites in India is 1.5% - wouldn’t it be smart to capitalise on every small percentage to maximise purchases?
  6. Referral sources: This data shows where users are coming from, such as search engines or social media platforms. It can help you determine which marketing channels are driving the most traffic to your website.
  7. Device type: This measures the type of device users are using to access your website, such as desktop or mobile. It can help you optimise your website design for different devices.

    Mobile devices accounted for 62% of e-commerce website traffic in India in 2020 - and based on such data, your brand can be optimised to service the consumers’ device type
  8. Shopping cart abandonment data: This type of data tracks when users add products to their shopping cart but do not complete the purchase. Shopping cart abandonment data can be used to understand why users abandon their carts and to optimise the checkout process to reduce abandonment rates.

    The average cart abandonment rate in e-commerce in India was 72.9% in 2020 - it wouldn’t be a bad idea to improve cart recovery, and thereby increase revenue.
  9. Site search data: This type of data tracks the keywords that users enter into the search bar on an e-commerce website. Site search data can be used to understand what products users are looking for and to optimise the search function to provide better results.
  10. Purchase history data: This type of data tracks the products that users have purchased in the past. Purchase history data can be used to recommend related products to users and to personalise the user experience.
  11. Geographic location: This data shows where users are located, which can help you target specific regions with your marketing campaigns.

    Top 10 cities in India accounted for 70% of e-commerce sales in the country, and brands need the data for hyper targeting - to target the minor areas as well with least revenue lost
  12. Social media data: This type of data tracks how users interact with an e-commerce business on social media platforms. Social media data can be used to understand how users perceive the brand and to identify opportunities for engagement and customer service.

By leveraging real-time data for user behaviour, e-commerce businesses in India can gain valuable insights into their customers and make data-driven decisions to improve the user experience and drive sales.


Real-time data for Order Monitoring

Ecommerce platform: 

All ecommerce platforms like Shopify, Magento, or WooCommerce, need real-time data on orders, inventory, and customer information.

Order volume: This data point tracks the number of orders received in real-time. It is crucial to track order volume to ensure that your website can handle the incoming orders and to plan for staffing & inventory management.

Inventory levels: This data point tracks the inventory levels of each product in real-time. It can help you plan for restocking and avoid stockouts.

Customer information: Real-time customer data, such as order history, preferences, and behaviour, can help ecommerce businesses personalise their offerings and improve customer retention. As per a report by EY, personalised customer experiences can increase revenue by up to 15%.

Payment gateway: 

Payment gateways like PayPal, Razorpay, or Paytm also provide real-time data on transactions and orders.

Coupled with past purchase data, brands can optimise internal functions and operations to improve online consumer experience during purchase journey.

Payment processing: Real-time payment processing data helps ecommerce businesses ensure timely and accurate order processing and avoid fraud.

Payment status: This data point tracks the status of each payment in real-time. This includes whether the payment has been processed, authorised, or declined.

Order value: This data point tracks the total value of all orders in real-time. It can help you understand your sales performance and revenue generation.

Tracking the average order value (AOV) and total revenue generated in real-time can help ecommerce businesses optimise pricing and promotions.

Logistics and shipping partners: 

Logistics and shipping partners like Delhivery, Blue Dart, or FedEx provide real-time data on order fulfilment, shipping status, and delivery updates.

Order status: This data point tracks the status of each order in real-time. This includes whether the order has been processed, shipped, or delivered.

Shipping status: This data point tracks the status of each shipment in real-time. This includes whether the shipment is in transit, delivered, or delayed.

CRM and order management software: 

There are several CRM and order management software which provide real-time data on orders, inventory, shipping, and customer information.

Return rate: This data point tracks the percentage of orders that are returned by customers. It can help you identify issues with product quality or customer satisfaction.

Fulfilment time: This data point tracks the time it takes to fulfil an order, from receipt to delivery. It can help you identify bottlenecks in the order fulfilment process.

Shipping cost: This data point tracks the cost of shipping for each order in real-time. It can help you optimise shipping costs and improve profit margins.

Analytics and reporting tools: 

Analytics and reporting tools like Google Analytics, Kissmetrics, or Mixpanel, provide real-time data on website traffic, customer behaviour, and order metrics.

Customer feedback: This data point tracks customer feedback in real-time. It can help you identify issues with your products or services and improve customer satisfaction.

Fulfilment efficiency: Real-time tracking of fulfilment efficiency, such as pick and pack times, can help ecommerce businesses optimise their operations and reduce costs. As per a report by Deloitte India, supply chain and logistics costs can account for up to 30% of an ecommerce business's total costs.

Traffic sources: Real-time data on traffic sources can help ecommerce businesses optimise their marketing and advertising strategies and attract more high-quality traffic. 


What types of issues impact eCommerce the most?

Technical Glitches and Website Downtime: Technical issues such as website crashes, slow loading times, or payment processing errors can frustrate customers and lead to lost sales opportunities.

Poor User Experience: Complicated navigation, confusing checkout processes, or lack of mobile optimization can result in a poor user experience, leading to abandoned carts and decreased conversion rates.

Security Concerns: Data breaches, fraudulent activities, or inadequate security measures can erode consumer trust and deter shoppers from making purchases online.

Logistics and Fulfillment Challenges: Issues with order fulfillment, including delays in shipping, inaccurate tracking information, or damaged goods upon delivery, can negatively impact customer satisfaction and retention.

Inventory Management: Overstocking or understocking products, inventory discrepancies, or difficulties in managing inventory across multiple channels can lead to lost sales opportunities or excess inventory costs.

Customer Service Failures: Inadequate customer support, delayed responses to inquiries or complaints, or unsatisfactory resolution of issues can result in negative reviews, decreased customer loyalty, and damage to brand reputation.

Competition and Market Saturation: Intense competition, price wars, or market saturation in certain product categories can make it challenging for eCommerce businesses to differentiate themselves and attract and retain customers.

Regulatory Compliance: Compliance with evolving regulations related to data privacy, consumer protection, or taxation can pose challenges for eCommerce businesses, especially those operating across multiple jurisdictions.

FAQs

  1. What is real time ecommerce, and how does it differ from traditional e-commerce?

Real-time e-commerce refers to the use of instantaneous data processing and analytics to drive business decisions and customer interactions in the online retail space. Unlike traditional e-commerce, which relies on batch processing and delayed insights, real-time e-commerce enables businesses to respond to customer behavior and market trends as they happen, leading to more personalized and dynamic shopping experiences.

  1. How can real time ecommerce analytics benefit online retailers?

Real-time e-commerce analytics empower online retailers with instant insights into customer behavior, sales trends, inventory levels, and website performance. By leveraging this data in real time, retailers can make informed decisions about product recommendations, pricing strategies, marketing campaigns, and website optimizations, leading to improved customer satisfaction, increased sales, and enhanced competitiveness in the digital marketplace.

  1. What are some key features of real time ecommerce analytics platforms?

Real-time e-commerce analytics platforms typically offer features such as live dashboards, predictive analytics, customer segmentation, A/B testing, and real-time notifications. These features enable retailers to monitor key metrics, identify patterns and trends, segment their audience for targeted marketing campaigns, experiment with different strategies, and receive alerts about important events or anomalies in real time.

  1. How does real-time data contribute to the future of digital commerce?

Real-time data is poised to play a crucial role in shaping the future of digital commerce by enabling hyper-personalized shopping experiences, real-time inventory management, predictive pricing algorithms, dynamic pricing strategies, automated marketing campaigns, and seamless omnichannel integration. As consumers increasingly expect instant gratification and personalized interactions, real-time data will become essential for businesses to stay competitive and meet evolving customer demands.

  1. What are some examples of successful implementations of real time ecommerce analytics in the industry?

Several leading e-commerce companies have successfully implemented real-time analytics to drive business growth and customer engagement. For example, Amazon uses real-time data to personalize product recommendations and optimize pricing dynamically. Similarly, Netflix leverages real-time analytics to recommend personalized content to users based on their viewing history and preferences, leading to higher user engagement and retention.

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