How Data Analytics Fuels Shiprocket
Shiprocket, one of the biggest e-commerce companies in India, is using its tech stack for building and they claim to grow businesses by providing a seamless data platform that connects retailers, carriers, and consumers across national and international locations. To know more about how Shiprocket uses Data Analytics, Analytics India Magazine reached out to Praful Poddar, Senior VP, Shiprocket. AIM: How does Shiprocket use data analytics to improve its operations and drive business growth? Praful: We think of data analytics as two objectives at Shiprocket; the first is using data insights to track, measure and improve business performance for Shiprocket as an organisation. For example, we use data to optimise new customer acquisition. Data is generated across our entire funnel from campaigns -> leads generations _ acquisition -> activation -> daily transactions -> churn. Looking at funnel conversions and channel/campaign-level performance helps us deploy the right budgets for customer acquisition. Additionally, Cross-sell/up-sell-data helps us understand our customer needs and affinity towards the different products in our suite, which help us target customer more effectively for higher ARPU generation Second is building products that extract data insights and are actionable for our customers (merchants/D2C brands) to help them optimise their business. For instance, we use historical courier performance across the platform for all shipments. Shiprocket helps recommend the best couriers to sellers when they ship their orders which helps reduce costs and better delivery performance. We provide this through our AI-led platform, CORE (Courier Recommendation Engine). CORE offers recommendations to sellers on how to deliver the best logistics experience at reduced costs by selecting the best delivery partners and creating a customised brand experience. Additionally, by creating visual and actionable dashboards for sellers using their orders, customers, catalogue, shipments, and returns data, we help sellers understand key trends in their business and where to focus on. These analytics are handy for brands while assigning marketing budgets, augmenting shipping costs, and more. AIM: What kind of data does Shiprocket collect, and how is it used to inform business decisions? Praful: At Shiprocket, we leverage numerous data points to tailor the products to the market’s needs. Shiprocket data primarily includes ecommerce order data, shipment data, returns/cancellations, catalogues, communication, and more. With the help of courier-level performance analytics and ratings, Shiprocket is enabling sellers to make informed business decisions about the best-performing courier partners. Shiprocket uses customer data to provide signals to sellers in case of fraud buyers to minimise. The company provides sales trends and benchmarks across the industry to help sellers target the right segments. Shiprocket sends back order delivery information to marketing channels to optimise campaigns for better performance. AIM: Can you provide examples of how data analytics has been used to solve specific business challenges or opportunities at Shiprocket? Praful: At Shiprocket, we aim to empower businesses with the right technology to analyse and leverage the data points in a way that provides them an edge over the competition. We are utilising Industry 4.0 technologies to become an efficient logistics platform. We are also leveraging Machine learning to solve for selecting the right courier partners, enrich customer addresses, and predict potential fraud. Through our CORE technology, we have improved the delivery percentage by up to 10% and reduced costs by up to 8%. By enabling an RTO score of up to 5%, Shiprocket has helped reduce failed deliveries by up to 30%. We have also increased deliverability (Non-delivery report/NDR) by creating different tech touchpoints with the user to capture their intent. This resulted in 10% better delivery performance. AIM: How does Shiprocket measure the success of its data analytics efforts, and what metrics are used to track progress and performance? Praful: There are some clear ways to measure impact by knowing what business results in a data insight/actionable/optimization end up creating either for customer acquisition, cost reduction, or higher revenue generation. There will also be indirect ways to measure the success of data analytics, enabling internal teams to do their job more efficiently. The quality and timeliness of such deliverables are good metrics. AIM: How can we use data and analytics to identify trends and patterns in our operations, and what insights can we gain from this analysis? Praful: In today’s data-driven world, when all the big brands are exploring different ways to analyse their bank of data, it becomes imperative to unlock this data in a way that creates a direct business impact. For example, the customer data analysis helped us anticipate the rising need for faster deliveries for our customers right before the festive season in October. Basing this analysis as our guiding principle, we expanded our warehouse network aggressively across the country to enable same/next-day deliveries. The analysis enabled us to cater to the needs of the real Bharat; hence, we clocked a 40% increase in demand during the festive season. AIM: What are the key metrics we need to track to understand the health and performance of our business? Praful: The different CX metrics are the ultimate measure of the success of a brand’s CX strategy. It’s simple, if you have the right tech to analyse and leverage the customer data, you will always have the competitive edge. And this is exactly what these metrics are solving for. CX analytics are helping businesses in making data-backed decisions for enhancing the customer journey. There are a plethora of metrics to analyse the CX experience but, to get actionable insight into the customer journey, we focus on a few key metrics like NPS (Net Promoter Score), customer churn rate clubbed with customer retention rate, and customer satisfaction score. Growth metrics and share of business Shiprocket is serving for our sellers is an important metric for us to know if we are maximising value delivered and business generated from our sellers Cross-sell and up-sell metrics of how many of our products a seller is using is another key metric to know if we are solving more and more use cases for the sellers across their post-order journey.
The customer data analysis helped us anticipate the rising need for faster deliveries right before the October festive season: Shiprocket
To know more about how Shiprocket uses Data Analytics, Analytics India Magazine reached out to Praful Poddar, Senior VP, Shiprocket. 
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Tech-savvy storyteller with a knack for uncovering AI's hidden gems and dodging its potential pitfalls. 'Navigating the world of tech', one story at a time.
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