Boosting productivity and revenues with e-commerce data analytics
Data makes everything better. From travel to retail, from enterprise software solutions to marketing, the implementation of data analytics is increasing every day. E-commerce is no different. It is possible to boost operational efficiency and increase revenues for your online retail brand using e-commerce data analytics.
As an e-commerce brand, the main disadvantage is that you don’t really get to interact with your customers. If you had a retail outlet, you could speak to anyone who walked through the doors. You could get a first-hand understanding of how your products are being perceived by customers.
You could also form an idea of what customers are demanding. This is very important. Brands have control over the supply. If you get an understanding of what your potential customers want, half the problem is already solved.
But an e-commerce brand has few avenues to understand customer needs at that level as compared to offline or omni-channel brands that directly interface with customers through physical stores or touchpoints. Leveraging analytics in the e-commerce management process is one of the most effective ways to gauge customer needs and deliver the products and experiences they want.
What is e-commerce data analytics?
Every individual who comes to your website is a potential customer. They may not always buy, but you can still track their journey through your website. You can see which products are being viewed the most. You can even see how long people are pausing on different sections of the web page.
All the information that you require to understand customer behaviour is already present in the form of raw data. E-commerce data analytics simply runs that data through a framework and displays it in a form that is easy to understand. For instance, a bar graph that shows you which products are the most popular is far easier to comprehend than a huge excel sheet.
Most e-commerce data management systems can perform the required analytics. All brands need to do is select the metrics that they want to consider. For example, you can use the customer retention rate as a metric to judge how well your products are being received. On the other hand, if you want to judge which marketing campaign is better for your brand, you can consider the conversion rate.
What are the advantages of e-commerce data analytics?
Most modern e-commerce management platforms such as Ordazzle offer analytics, reporting, and dashboard capabilities to track key e-commerce metrics and use the data to optimise their processes. This is especially useful for enterprise e-commerce players with large-scale, multi-geography operations who can leverage e-commerce data analytics to boost different areas of your e-commerce operations. Let’s take a look at how you can do that.
Data analytics can be instrumental in the outreach and discovery of your potential customers. It can start right from competitive analysis and extend into the identification of new market segments that you can tap into.
If you look at the business models of most FMCG giants, they have a dedicated team for analytics. This strategy is also very important for the success of B2C and D2C e-commerce brands.
The attention span of potential customers is reducing every day. Hundreds of different brands are creating new content all the time. E-commerce brands will therefore have a few scant seconds to hook a customer and attract their attention.
The only sure strategy for success is to tailor the products to fit exactly what customers are looking for. E-commerce data analytics plays an instrumental role in this process.
This is the process of acquiring leads from social media and digital advertisements and bringing them to the e-commerce website. There can be various strategies for customer acquisition. You can opt for paid social media ads or Google ads. You can enlist the services of influencers for marketing purposes, or you can run targeted campaigns.
New brands generally experiment with various strategies before they can narrow down on the ones that work best for them. Data analytics can help make an informed decision.
For example, there are certain key metrics that you can consider to judge how effective a particular strategy is. The Customer Acquisition Cost (CAC) is a popularly accepted metric. You can also refer to your Cost Per Lead (CPL) to see whether the cost of a strategy is justified by the results.
Once the potential customers have landed on your website, the next step is to convert them into customers.
Here, you can use e-commerce data analytics to understand which products are being preferred by people, and where you can optimise your process.
For instance, if you see that a lot of people are abandoning their carts, it sends up a red flag. There must be something wrong with your checkout process. You can consider giving discounts to first-time customers, introducing cash-on-delivery services and simplifying your web page to solve this problem.
Some commonly used metrics to judge customer conversion is the Conversion Rate and Cart Abandonment Rate.
Data analytics used in the conversion process can also help optimise your customer experience. For instance, if you see that people are pausing at different sections and then leaving the website, you can set up a chatbot and a virtual assistant. It’s all about targeted reminders and nudges to offer assistance whenever required.
All e-commerce brands can acquire customers. But only the best e-commerce brands can retain customers.
If you want to build a sustainable e-commerce business, customer retention is the main problem that you have to solve. Once you crack this secret, everything else will fall into place. When you get repeat customers, that’s when you know you’re actually adding value to people’s lives and your e-commerce productivity will blow through the roof.
Popular data-based metrics that are used to judge retention are the Retention Rate (RR) and Customer Lifetime Value (CLV). The aim is to increase the retention rate and extend the customer lifespan as long as possible.
There are numerous strategies to increase customer retention. Personalised recommendations, email marketing, social media engagement — all these have worked for various brands in the past.
The use of big data analytics in e-commerce can help you judge which method works best for your brand. Thus, you can streamline your operations and boost productivity and revenue.
Ordazzle is an all-in-one solution that streamlines the entire e-commerce management lifecycle, making it easy for enterprise e-commerce brands, sellers, and marketplaces to manage orders, track inventory, and monitor shipments, all in one place. With real-time updates and automated processes, you’ll never have to worry about manually inputting data or missing an important shipment deadline again. The platform also provides detailed insights into your business performance, including sales trends, inventory levels, shipping data, and more, through interactive dashboards. This helps you to make informed decisions that drive your business forward and improve your bottom line.
Take your e-commerce efficiency to the next level with Ordazzle!