Why do you need Product Performance Analytics?
The global e-commerce market today is growing fiercely. And every e-commerce store is looking to capture its share of the pie. To make this possible, businesses are trying to produce unique ideas that entice the customers and make them stick.
But all their efforts would go in vain if businesses do not realize the importance of looking at the nuances of product performance. One of the best ways to capture all those intricacies is through product performance analytics. It provides critical information and valuable insights that businesses can use to continuously improve their product offerings. Also, knowing which product is giving more sales, which one is getting frequently abandoned at the cart stage, etc. makes a significant difference in decision making.
Yet, many businesses neglect this level of analysis because they are not sure why or how they should do it.
To help businesses make the most of their efforts and increase sales, we have listed the use cases (below) of product performance analytics.
Use Cases of Product Performance Analytics:
Understand the Product Funnel:
Product performance analytics helps in understanding how well a product moves through the purchase funnel (first impression to final purchase). Since no two products are the same, it is important to see the likeliness of each product being abandoned before checkout. Armed with this information, businesses can find which products are poor performers.
Optimize Product Detail Pages:
Once the businesses identify the products which need help to make it to check out, they can figure out why. For instance, the problem can be with how the product is displayed on the product detail page. Product images or descriptions might not be robust enough to motivate visitors to take the plunge and make a purchase. Businesses can tweak product detail pages to include in-context images, product demo videos, etc.
Analyze Marketing Efforts:
Tracking product-level performance helps in understanding the impact of marketing efforts on sales. For instance, after promoting a specific product on any marketing platform, businesses could see if that promotion had any immediate effect on sales. They can also look at how long after the promotion period those sales evened out.
Inventory tracking is an important part of product performance analytics. Looking at how many items are being sold at the product level can help businesses forecast stock needs and work more efficiently with suppliers. This helps them in avoiding stock-out situations. Businesses can deep dive by looking into regional-specific sales data to optimize inventory management. They can also look at the effect of seasonality/ sales seasons on individual products.
Identify Opportunities to Increase Sales:
The end goal of running an e-commerce business is to generate revenue. Product performance analytics make it easier to identify opportunities to do that. For instance, businesses can find lower-performing products and couple them with top-performing products and introduce them as a bundle at a better price. This helps in boosting sales of lower-performing products. Businesses can also identify products (groceries, baby food/ diapering) with recurring purchases and introduce subscription models to make the customer stick.
Product Performance Metrics:
Till now, we have seen the use cases of product performance analytics. But to get those insights, businesses should track certain metrics (as below).
Average Order Value (AOV):
When looked at it as standalone, AOV can give businesses insight into the amount users spend on a single visit to the store. But when they couple this metric with product-level detail, they can uncover the impact of products on AOV (increase or decrease). For instance, a mobile phone can increase the AOV as the user purchases the accessories like a case cover, headset, etc.
Conversion Rate Vs Abandonment Rate:
Conversion rates show the percentage of successful movements between various stages. They are crucial in identifying weaknesses in the buyer’s journey and purchasing funnel. For instance, cart-to-buy rates tell businesses what % of products made it from the shopping cart to a successful purchase. They can also look at abandonment rates. If the abandonment rate of a particular product is high, it implies that users added the product to the cart but changed their minds later.
Sales Vs Returns:
Along with tracking sales, tracking which specific products are returned is critical. Analyzing return rate at product level helps businesses understand the underlying issues. It is also important to understand the qualitative reasons behind the returns.
One-Time vs Recurring Purchases:
In the case of products with recurring usage, businesses should see if there are returning buyers. If the returning buyers’ proportion is low, businesses need to figure out the problems and address them.
Revenue is the key metric for business success. There are endless ways to break up and understand revenue streams. But tracking revenue by product enables businesses to quickly look at the incremental contribution by top-performing products, new entrants, and simultaneously see the impact of least performing products and product exits.
Segregating the revenue at the category/ product level helps businesses spot popular product attributes. It will also help them understand if the product introductions are on track and meet customer expectations.
General metrics like revenue, visitors give top-level insights into the performance of an e-commerce store. Whereas product performance analytics provides businesses with deeper insights into the product portfolio. This information not only helps product managers in coming up with better products. It also plays a critical role in inventory management and optimization of sales and marketing efforts.
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