Ad
More Related Content
What's hot (20)
Similar to E commerce with data analytics (20)
Ad
Recently uploaded (20)
![PRE-NATAL GRnnnmnnnnmmOWTH seminar[1].pptx](https://cdn.slidesharecdn.com/ss_thumbnails/pre-natalgrowthseminar1-250427093235-de04befc-thumbnail.jpg?width=560&fit=bounds)
Ad
E commerce with data analytics
- 1. Empowering E-commerce with Data Analytics www.positivenaick.com How to stand out and keep customers on your website.
- 2. The Need for Analytics One of the fastest growing industries in the modern age is that of the e-commerce industry. At first glance, this industry is where giants like Amazon and Walmart reign, with others looking to grab a piece of the lucrative pie. Competition in this landscape is reaching a fever pitch, and without a clear edge against competitors, many companies can easily find themselves shutting down their websites. Most companies already have the raw material they need to find that edge, the data they generate on a daily basis. But this data has to be transformed and compiled into meaningful insights. Data analytics does just that, finding meaningful patterns using the mountains of raw data companies often have on their hands. With data analytics, e-commerce companies can find out what specific products are likely to be bought together, find out the reasons behind their customers leaving for competitors, and even anticipate demand for future sales and holiday seasons. 1 Scope of Data Analytics In E-commerce Industry Customer Lifetime Value Marketing Customer Acquisition Customer Experience Enhance Business Intelligence Better Price Management Personalized Product Suggestion Customer Churn Prediction
- 3. 2 Enhanced Shopping Pattern Analysis Finding the purchase habits of different types of customers to provide information for more targeted marketing and discounts for particular customers, or use the information to create new product combinations altogether. Business Need Using Enhanced shopping pattern analysis, e-commerce companies can understand the conscious and subconscious shopping patterns of their customers, and use these insights to offer clearance discounts on specific products, display related items through product recommendations, and even offer loyalty rewards for continued customers. OutcomeApproach Using segmentation analysis, we can discern various details such as customer search history, purchase history, customer service history, etc and other forms of data, we can use data analytics to find the different patterns that may arise with customer browsing through. There are definite patterns to how customers shop, and those patterns overlap depending on a variety of factors. These shopping patterns vary for different groups of people. But this kind of information can be fine-tuned, turned into information giving insight into how customers are more likely to buy certain items over others. Coupon drivenPurchase through mobile Card payment Write a review about purchase Brand conscious purchases Often makes electronic purchases 25% 20% 33% 38% 20% 35% 40% 34% 35% 34% 43% 37%
- 4. 3 Effective Customer Service A large customer base needs appropriate customer service, and the quality of customer service has to scale proportionately. The issue with scaling customer service with size, is that the scaling doesn’t always equate to higher quality customer service. Customer service needs to cater to a growing customer base as well as maintain or improve in quality. Business Need The outcome here would be to understand what customers expect from customer service, and in turn, use affordable scaling options to expand and improve the quality of customer service. OutcomeApproach Using segmentation analysis, we can separate customers into different buckets for what common issues prop up. We can also go through customer service calls to find out how calls are being handled on an individual scale. With this, we can use data analysis to glean insights. Customer service has recently become one of the cornerstones of business success. In this age of hyperconnectivity, a dissatisfied customer can often mean more than just one lost sale. This is the reason why companies are going above and beyond to give their customers the service they expect. Customers have more reason than ever before to find new businesses to purchase from, so businesses are constantly on the lookout to see what they can do to retain their customers to prevent them from going back. Eliminate data silos CRM and other database Create a single customer view Map the customer journey Increase customer lifetime value Higher Customer Retention Rate Empower cutomer support User details customer account Web Mobile App
- 5. 4 Future sales operations need to have their results predicted to ensure that e-commerce providers have proper stock of all items in time for a future event. This is to ensure that all customers visiting the site can purchase the products they want, without the e-commerce site overstocking items and losing revenue in warehousing costs. Business Need Here, it is expected to give information into how many products should be stocked, and in what quantity. Additionally, it can also show information on slow-moving products, which can give e-commerce retailers an option to provide discounts or combo offers. OutcomeApproach By calculating past and current sales trends with sales reports, we can find out what products are typically sold during a specific period in time. Additionally, we can also look into upcoming products and the hype for them using social media analysis. These methods will provide the insights needed to make predictions. Predict Future Operation Sales Sales predictions are a vital part of any e-commerce provider, since they need to know how much stock to keep of specific products so they aren’t over or understocked. Without proper sales predictions, they can end up wasting valuable warehouse space, as well as risking customer dissatisfaction
- 6. 5 The need here is to reduce the number of customers leaving the site due to difficult or unavailable methods of payments. This reduces cart abandonment, and ensures that customers can pay through their preferred method. Business Need By analyzing modes of payment already available, and what issues customers are facing with existing modes of payment, e-commerce retailers can introduce new modes of payment, as well as fix existing modes of payment. OutcomeApproach By analyzing what modes of payment are commonly used on the site, customer feedback on these modes, cart abandonment details, and payment related issues or failures, we can understand the friction experienced by customers. Ease of Online Payments Today, there are a multitude of methods to pay for goods online. E-commerce providers have realized that giving customers more methods to pay have resulted in fewer customers leaving their shopping cards just because their preferred method of payment isn’t available with that particular site. Web UI Shopping Cart ShoppingCart Abandonment EASY TO ACCESS AND COMPLETE DIFFICULTY IN COMPLETING Checkout Abandonment Checkout Payments
- 7. 6 The need here is to find out why shoppers leave their shopping carts with items and not proceed to checkout. Business Need With Cart Abandonment Analysis, we can realize why customers are abandoning carts, and using methods like optimized and personalized recommendations, discounts, and loyalty bonuses, we can reduce cart abandonment rate. OutcomeApproach Using shopping cart data from the e-commerce sites, we can see what items are frequently abandoned, what the total bill was, what they bought together, and other data to find out the patterns behind cart abandonment. Cart Abandonment Analysis Customers on e-commerce sites frequently have a habit of abandoning their carts and removing items from their carts once they get to the checkout page. This can be due to a number of reasons, sometimes they were never really interested in buying the item, sometimes the overall price is too high, or they might want to buy it at a later time. Cancel Continue Shopping Cart Abandonment
- 8. 7 By providing more focus on micro-moments with targeted marketing efforts, e-commerce retailers can understand how to target specific products to specific customers, thereby improving the likelihood of a sale. Business Need By improving micro-moment marketing efforts, the overall sales value for each customer can be improved, as well as improving customer satisfaction and loyalty. OutcomeApproach By understanding what their customers regularly shop through, individual profiles can be built, and using that data, e-commerce sites can launch small marketing efforts personalized to each customer Increased Focus on Micro-Moments Micro-moments are small instances between the time when a user scrolls through the product listings to the time they enter the checkout page. These are time spaces, or spaces in your website, where e-commerce providers can connect with their customers and increase the probability of a sale for a specific product related to the customer. I-want-to-know moments I-want-to-try moments I-want-to-test moments I-want-to-buy moments When consumers are exploring or researching, but they are not necessarily in purchase mode When consumers are showing interest by choosing their preference brand, color, designs, size etc. When customers are convinced to make a purchase but they are evaluting it through reviews and feedbacks When consumers are ready to make a purchase and may need help in deciding what to buy and how to find the right one In moments like these, consumers want what they want, when they want it-and they are drawn to brands that deliver on their needs
- 9. 8 The Process of Analytics Adoption Adopting analytics requires a stage of forethought and planning. Sometimes, lack of implementation doesn’t mean e-commerce companies don’t want to do it, but they have a few obstacles in the way before adopting analytics. • Identifying internal use cases • Measuring analytics • Finding required talent • Technical requirements Finding Required Talent Technical Requirements Identifying Internal Use Cases Measuring Analytics Data analytics needs people with specialized skills to implement and monitor properly. Different retailers will have differing requirements in finding this talent. That’s when the e-commerce provider needs to ask some questions. Can they afford to have an in-house team working on analytics? Do they need a permanent analytics team in-house all the time? Can they use an analytics firm to fulfil their needs? By asking these questions, a company can understand what kind of analytics requirement they can employ. In e-commerce, this means understanding that certain departments will benefit a lot more with data analytics than other departments. Different areas will have different impacts, providing a better ROI than compared to in-store marketing efforts. But it also doesn’t mean certain departments should be ignored altogether. The list should be topped with areas that have the most value, and end with areas that don’t have a high ROI on the analytics investment. The next step is to measure the impact. This means asking a few key questions. -What are the performance goals after deploying the solution? -How are these goals going to be measured? -Does our organization have the tools necessary to measure them? This will provide valuable insight into finding out whether or not the deployed solution is actually performing as intended, or if it’s having any unintended consequences. These kinds of measurements help the e-commerce provider understand how their process changes have actually made an impact. The final thing to consider when looking into analytics is learning what are the technical requirements for the analytics results you’re looking for different technical requirements, and it’s imperative that companies looking to employ analytics solutions have a clear idea of what they need, what they already have on hand, and what they need to acquire.
- 10. We hope this gave you better insight into how Data Analytics can help your company accomplish new business goals. If you have any questions, please contact us using the details below. Thank You PositiveNaick Analytics Ltd. No177,1st floor, LM Tech Park, 1st Main Rd, Nehru Nagar, Kottivakkam, Chennai, Tamil Nadu 600041. Email: [email protected] Website: www.positivenaick.com Phone: +91-44 4857 6162