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5 Tips to Harness Big Data E-commerce Analytics to Increase Sales and Engage Customers

Today, the Business Intelligence landscape is dominated by Big Data and online retailers are rapidly adopting Big Data analytics solutions to better understand the data that is being generated by every transaction, and engagement on their stores.

The rise in popularity of Big Data e-Commerce analytics has made e-Commerce store owners modify their advertising strategies to target specific segments, in a concentrated bid to increase sales and boost revenues.

This has enabled e-Commerce businesses to tailor their marketing strategies to capture those customers who are actually interested in their products. Many e-Commerce businesses can effectively work with zero inventory, ordering products directly from manufacturers or producers as and when required. They also are making efforts to fully automate customer support, with a view to increasing profits and reducing use of excess resources.

The immense variety of data available to e-Commerce businesses has positively impacted business efficiency.

Let us understand how Big Data e-Commerce analytics is making an impact on the retail landscape and how online businesses can use e-Commerce data analytics more effectively.

Intelligent Marketing and Advertising Strategies

In the last five years, drop shipping has changed the e-Commerce landscape with smart advertisement strategies for targeting users.

In the drop shipping model, e-Commerce marketers market products of manufacturers at prices of their choice and earn a commission on the upscale price. Shopify is one of the online e-Commerce platforms that primarily rely on the drop shipping model.

Let’s give you a quick introduction to what drop shipping is.

Intelligent and strategic marketing efforts do certainly make an impact on sales and conversions. This is evident from the advances made by digital advertising platforms like Facebook, Google and Pinterest, which offer 99.9% accuracy in targeted advertising. They effectively optimize their advertising algorithms to reduce costs and boost sales.

Benefits: Retargeted advertising is one of the most successful e-Commerce advertising strategies

E-commerce businesses must hire paid marketing experts to target customers through relevant platforms. They can spearhead unique re-targeting ad campaigns.

Optimize Sales Funnels

Big Data e-Commerce strategies can help online businesses create optimized web pages to showcase their products. Many Big Data-based strategies provide e-Commerce stores with valuable, in-depth analysis of each product page on their website. In this way, e-Commerce stores can gain actionable insights on clickstream data received from users, as well as find out which products and categories are popular etc. Strategic implementation of real-time clickstream data can enable businesses to act on recommendations and increase conversions.

Benefits: Harness powerful user tracking tools offered with Big Data analytics solutions

Big Data analytics solutions have built-in user tracking tools that effectively track various actions of users. This allows e-Commerce business owners to identify the pain points in the existing conversion process and take actions to rectify errors. This data can also be utilized to enhance the functionality of the e-Commerce sales funnel and encourage visitor engagement.

Optimize Product Listings

Optimizing product listing on e-Commerce websites will help to identify areas for improvement to increase the ranking of stores in search engine listings. Optimizing product listings on e-Commerce websites has rapidly become a widely adopted practice in the industry to enhance landing pages and overall store performance.

Big Data analytics has played a pivotal role in this optimization process by introducing various automated tools to optimize product listings on several pages. These tools provide reports and insights on how to further improve product pages for e-Commerce stores.

Benefits: Reduce workload and automate optimization with Big Data analytics

Using automated optimization tools and solutions to gain a deeper understanding of their product listings can help e-Commerce businesses boost conversions.

Inventory Management

Several e-Commerce stores find that keeping track of inventory is a big challenge as there is no unified process that allows them to track their inventory.

Several inventory management tools and solutions enable businesses to maintain extensive inventory records and provide real-time data analytics for e-commerce stores with the aim to improve efficiency.

These tools can also help e-Commerce businesses greatly improve their order fulfilment processes through automating their inventory management.

Benefits: Use predictive Big Data analytics to identify inventory trends

Big Data analytics for e-Commerce businesses allows store owners to accurately predict inventory trends in order to optimize store listings and see an improvement in revenues.

Futuristic Customer Support

The introduction of chatbots in the e-Commerce industry is rapidly making it possible for e-Commerce stores to automate customer support. One of the key tenets of a successful e-Commerce business is to keep customers happy. Now, in this age of instant communication, customers are increasingly expecting real-time responses to purchase related queries.

Chatbots created with built-in Artificial Intelligence and Natural Language Processing capabilities can respond to trigger words or transfer the queries to human customer representatives.

Benefits: Tap the potential of Machine Learning and Artificial Intelligence to enhance the customer support experience

E-commerce businesses looking to succeed in customer support must consider implementing chatbots powered by Machine Learning capabilities to provide customers with a fulfilling online shopping experience.

The Last Word

Big Data analytics is strategically poised to revolutionize the e-Commerce industry in the coming years. Big Data analytics has quickly become a necessary ingredient of a successful e-Commerce business strategy.

 

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