ecommerce data

In our earlier blogs on best marketing practices, we talked about the importance of collecting and collating structured and unstructured data. Ecommerce companies, or any business for that matter, collect a ton of data that can include information from registration forms, transaction details at point-of-sale, loyalty members, customer complaints, information on abandoned carts, photos, videos, customer reviews and so on. 

In fact, we are reaching an information age where businesses are left with terabytes of data which continues to grow every day, and they don’t know how to use it. While we talked about removing data silos and centralising data, we have already gone one step further to talk about what data to extract and analyse, once the data has been centralised – a topic we will be covering in this blog. 

Ecommerce businesses are left with a ton of pre-existing and real-time customer data. How can they determine what data is useful, and how can they effectively use dashboards to analyse the ‘useful data’? Let’s find out. 

Identify Core Business Objectives 

Before you go looking through your data, identify what your larger business objectives are. For example, a business objective can be to increase the number of daily website visitors to 10K in 5 months. Or, it can be to increase repeat purchase from customers to 4 annually.  

If you are working towards meeting the first objective, you need to gather data related to the current number of website visitors, where these visitors are coming from (Internet search, social media campaigns, SEO etc.), how much time the visitors are spending on your site, which pages they are browsing and so on.  

If it’s the latter objective, you need to look at what your existing customers have bought, what items they have shown interest in the past, whether they have any items in the cart, if they have taken an item to cart and not purchased and why, and so on. 

When you set specific objectives, scouting for data related to that objective can ensure that any steps you take to achieve that outcome can be measured with measurable metrics and that adequate data is available to analyse and take actionable steps to meet those objectives. 

Design Relevant Dashboards 

A Merit expert says, “One doesn’t need to be an expert at dashboards to put one together. The idea here is to create a simple dashboard that can bring out all necessary data related to the objective in a single view. Keeping the dashboard simple yet complete is easier said than done!” 

For example, below is an example of a simple dashboard (Source: that shows which sources the website visitors are from.  

Inventory Management

The second example (image source) shows an inventory dashboard that clearly reflects the data necessary to make inventory-related decisions. It shows the number of orders placed in a day, the average inventory costs, the inventory turnaround, and so on.

Important dashboards that ecommerce businesses typically use are; inventory dashboards, marketing dashboards, sales dashboards, customer dashboards, shipping dashboards, and revenue dashboards. 

Bring Visualisation into Dashboards 

Here’s a question; would you rather look at elaborate excel sheets with numerous data points, or visual charts which immediately show you the key metrics you need to be paying attention to? Our guess is, the latter.  

Creating visually appealing and clear dashboards with bar graphs, pie charts, line graphs and heat maps can be useful in many ways; it can help the individual identify the data they are looking for immediately, it can save time, and enable quicker decision-making based on charts. Also, visuals just appeal better than blocks of numbers, don’t you think? 

Ensure Data Is Relevant 

There’s no shortage of data for ecommerce businesses. In fact, today businesses are grappling with more data than they can handle. So, while one aspect of data-driven decision making is to identify what data you need based on business objectives, the other aspect is to ensure that your data is current and relevant. For example, if you’re looking to increase repeat purchases from customers to four times a year, you need to look at who your current customers are, for a start. Those who bought from you last year may not still be purchasing from your site. So, the key here is to use relevant and ‘current’ data. 

Now that we’ve looked at what you need to do when gathering data to meet specific business objectives and how to do it, let’s look at common mistakes you need to avoid when making data-driven decisions. 

Common Mistakes to Avoid When Analysing Ecommerce Data 

One of the first things that happens when a business is left with significant data is, it doesn’t know where to start, and to understand how much data is too much data. Let’s look at common mistakes businesses make and why they need to avoid it; 

  • Metrics that work for other businesses may not work for you. The business objectives you set and the metrics you choose to follow depend on a number of factors like the size of your business, your geographic presence, your customer demographics and more. So, the first step is to understand what works for you, and what is relevant for your business.  
  • It’s easy to get data-high and design complex dashboards with numerous data sets. Avoid this as much as possible. Keep your measurable metrics to a minimum and keep it on-point and relevant.  
  • Ensure that your dashboard is updated from time-to-time so that the data is current and useful for teams referring to it. 
  • When analysing data, don’t just view it from your business’ perspective. Combine it with competition and industry insights, to draw more accurate conclusions. 

Merit’s Expertise in e-Commerce Data and Intelligence  

Our state-of-the-art eCommerce data harvesting engine collects raw data and provides actionable insights  

  • Three to four times faster than standard scrapers  
  • At lower cost  
  • With Increased accuracy (up to 30% compared to standard scrapers)  

Our powerful, new scraper engine can gather massive data sets from multiple sites and geographies in real-time so you can stay informed on customer behaviours and market trends.  

Merit’s eCommerce data engine provides a high degree of confidence in insights generated from analytics – thanks to confidence in the data quality and access to enriched data.  

To know more, visit:

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