Today, ecommerce has become a highly competitive space because brands, be it big or small, need to necessarily build a presence in the online space. Especially in the last three years, customers have turned to online shopping over brick-and-mortar purchases. They prefer purchasing online and having their products door-delivered or picked up from a nearby outlet.
A Statista report shows that the share of online sales in the global retail sale market rose from 17.8% in 2021, to 19.7% in 2022. This number is likely to reach 20.8% this year and go as high as 24% by 2026.
As the demand for online shopping continues and customers demand better shopping experiences from brands, the one key factor that can help ecommerce retailers stand out from competition is getting their merchandising strategy right.
A Merit expert says, “A merchandising strategy is nothing but techniques and tactics that ecommerce players adopt to identify products that are in demand, price them right, and display and promote them in a way that they can deliver higher sales and revenue. Given that practically every business today runs on data, it is imperative for ecommerce brands to base their merchandising strategy on data-driven insights.”
With data, brands can analyse data related to website traffic, customer behaviour, sales, and inventory, to arrive at the right merchandising strategies to drive higher revenue growth and sales.
Businesses typically use a combination of tools like Google Analytics, Adobe Analytics, Tableau and Mixpanel to conduct ecommerce merchandising analytics. They supplement these with advanced machine learning algorithms and predictive analytics tools to identify patterns and make recommendations for optimising online shopping experiences for customers.
How ASOS Increased Online Revenue with Merchandising Analytics
ASOS is a British online fashion and cosmetic retailer primarily aimed at young adults. The brand wanted to optimise online sales and improve its customer experience, and it turned to merchandising analytics to achieve these goals.
ASOS used analytics tools to track customer behaviour, such as which products were being viewed and purchased, as well as how customers were navigating the site. They also used predictive analytics to make recommendations for which products to stock, and to personalise the shopping experience for individual customers.
Using this data, ASOS was able to make strategic changes to its online store, such as improving the search function, optimising product descriptions and images, and tailoring promotions to individual customers. They also introduced a “suggested for you” feature, which recommended products based on a customer’s previous browsing and purchase history.
The result? ASOS reported a 26% increase in revenue, with a 16% increase in average order value.
7 Components of Ecommerce Merchandising Analytics
Ecommerce merchandising involves a variety of elements that work together to create a compelling and effective shopping experience for online customers. Here are some key elements of ecommerce merchandising:
- Product Selection: Choosing the right mix of products to offer on an online store is critical. This involves understanding customer preferences, market trends, and the competitive landscape to select products that will resonate with the target audience and drive sales.
- Product Descriptions: High-quality product descriptions are essential to helping customers make informed purchase decisions. Effective product descriptions should be accurate, detailed, and engaging, and should include information about the product’s features, benefits, and potential use cases.
- Product Imagery: Product imagery is an important element of ecommerce merchandising, as it helps customers visualise the product and understand its features and benefits. High-quality product images that show the product from multiple angles and in different settings can be particularly effective.
- Navigation: Navigation refers to the way products are organised and displayed on an online store. Effective navigation makes it easy for customers to find what they’re looking for and should be intuitive and user-friendly.
- Pricing: Pricing is a critical factor in ecommerce merchandising. Effective pricing strategies involve setting prices that are competitive yet profitable, and may include tactics such as offering discounts, promotions, or bundling products.
- Promotions: Promotions can be an effective way to drive sales and revenue. Effective promotion strategies involve targeting the right audience, creating compelling offers, and using the right channels to reach customers.
- Personalisation: Personalisation involves tailoring the shopping experience to the individual customer based on their preferences, browsing history, and purchase behaviour. Personalisation can be used to recommend products, promotions, or content that are relevant and compelling to the customer.
The Future of Ecommerce Merchandising Analytics
As digital technologies like AI and predictive analytics come into play, new merchandising techniques and strategies are emerging to take the customer one step further in having a great online shopping experience. For example, with AR and VR technologies, brands are now able to encourage customers to “try on” the products before purchasing them. On the other hand, with beacon technology, brands are able to use Bluetooth-enabled devices to detect customers’ location within a store and send personalised messages or offers based on their shopping history or preferences. As online shopping continues to grow in popularity, it has become more and more important for brands to pay attention to their merchandising analytics strategy, as this can hold the key to sustaining their presence in the ecommerce space.
Merit’s Expertise in Ecommerce 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 and retail 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: https://www.meritdata-tech.com/service/data/retail-data/
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