Every business, across industries, is aiming to make data-driven decisions. In eCommerce, every click, every conversion, and product interaction holds valuable insights.
For eCommerce, this data can be used to fine-tune strategies, optimize performance, and ultimately drive more sales.
However, analyzing product data isn’t always simple. As businesses scale, the complexity of managing and interpreting data grows, leading to various obstacles that can hinder effective decision-making.
In this blog, we’ll dive into the four key challenges eCommerce businesses face when it comes to product analysis. But don’t worry – we’ll also provide practical solutions to help you overcome these hurdles and turn your data into actionable insights.
Let’s dive right into the challenges!
Challenge 1: Scattered data across multiple marketplace platforms
Product analysis hinges on having unified data to make informed decisions. However, eCommerce businesses operate across various marketplaces—Amazon, Shopify, Lazada, and more—each with unique data formats and reporting tools. This leads to scattered data across multiple platforms, making it difficult to track how a product performs across these channels.
Without a consolidated view of product data, businesses face challenges in identifying best-sellers, monitoring stock levels, and detecting emerging trends. This fragmentation leads to missed opportunities and potentially costly mistakes. For example, if a business can't accurately see which products are best-sellers on a platform like Amazon but are underperforming on their own Shopify site, they might overstock on one channel while under-serving demand on another.
Inaccurate data also impacts product-specific decisions such as inventory and marketing. A fragmented view may cause businesses to over-invest in marketing for a low-performing product or under-stock a high-performing SKU. This inefficiency not only affects profit margins but also reduces customer satisfaction when popular items are out of stock.
Solution: Integrate data from all the sales channels
To overcome this challenge, businesses need to invest in an eCommerce analytics tool that consolidates data from multiple channels into a single, unified dashboard.
This tool gathers information from every marketplace, allowing businesses to easily compare product performance across platforms.
Challenge 2: Data Overload from multiple metrics
In eCommerce, every product interaction generates data—from clicks and views to cart abandonment and conversion rates.
While this data holds valuable insights, the sheer volume can be overwhelming. When businesses focus on too many metrics, they risk diluting attention from essential product-focused KPIs, making it harder to pinpoint what’s driving a product's performance.
Data overload can lead to misinformed decisions if critical metrics aren’t prioritized. For instance, a product may appear to have poor sales due to high cart abandonment rates. However, without analyzing deeper product-specific factors—like price competitiveness or customer feedback compared to similar offerings—it’s easy to misinterpret the issue.
The true problem could lie in a higher price than competitors, outdated descriptions, or lack of compelling images, but the flood of other metrics distracts from identifying these core issues.
This overload makes it challenging to focus on actionable metrics, hindering a clear view of what drives product success or failure. For effective product analysis, businesses must filter out noise and focus on key indicators such as price sensitivity, competitive positioning, and customer behavior. This allows for a more accurate understanding of product performance, leading to informed, strategic decisions.
Solution: Automate data collection and processing
To handle this complexity, automate data collection using advanced analytics platforms that gather, process, and categorize key metrics for you.
These tools filter out the noise and prioritize the most relevant information, allowing you to focus on actionable insights that directly impact your product performance.
By simplifying how you track metrics, you can make more informed decisions without getting bogged down by data overload, ultimately improving efficiency and profitability.
Challenge 3: Defining relevant KPIs for product analysis
Effective product analysis depends on selecting the right KPIs, yet many eCommerce businesses default to focusing heavily on sales volume alone.
While sales volume indicates product popularity, relying solely on this metric without understanding profit margins, customer retention, or lifetime value can lead to misguided product assortment decisions.
In some cases, high-sales products might have low profitability, and promoting these without assessing their true impact can drain resources and miss opportunities to scale more valuable products.
When the wrong metrics are prioritized, businesses might push underperforming products while overlooking those with high growth potential.
For example, if a business focuses exclusively on total units sold, it might fail to notice that a particular product has a high customer retention rate, indicating long-term profitability. As a result, they may overstock or aggressively market items with low margins, while failing to invest in high-retention, high-margin products that can foster customer loyalty and drive sustained revenue.
This skewed analysis not only hampers effective product management but also limits the ability to create a profitable product assortment that aligns with customer demand.
By identifying relevant KPIs—such as profit margin, retention rate, and competitive positioning—businesses can make more strategic, data-driven decisions, avoiding the costly mistakes of irrelevant metrics.
Solution: Customize KPIs based on your unique business needs
The solution is to use an eCommerce analytics tool that allows you to customize KPIs according to your business’s specific objectives.
By tailoring KPIs, you ensure that you’re focusing on the metrics that truly matter to your growth, such as profit margins, product returns, or customer retention rates.
This approach helps you measure performance more accurately and make decisions that align with your long-term strategy.
Challenge 4: Delay in decision-making process
Timing is everything in eCommerce. And delays in analyzing and acting on product performance data can lead to missed opportunities.
When there are lags in making pricing adjustments or stock decisions, businesses risk losing market share, disappointing customers, and incurring excess costs.
For example, if a business notices a sudden spike in demand for a specific product but takes too long to increase stock or reallocate marketing budget, they could miss out on potential revenue.
Similarly, without real-time data, it’s challenging to quickly adjust pricing in response to competitors, resulting in either losing customers to lower-priced alternatives or eroding margins by not increasing potential sales.
Real-time product analysis allows businesses to quickly identify top-performing products and reallocate budgets towards marketing those items. It also enables proactive inventory management, ensuring popular items are well-stocked and minimizing overstock for slower-moving products.
By accessing and acting on data in real-time, businesses can refine their product strategies, manage inventory effectively, and make agile marketing decisions to stay competitive and responsive to changing customer demands.
Solution: Use real-time eCommerce analytics tools
To avoid this, invest in a robust eCommerce analytics tool that provides real-time data and automated reporting.
These tools ensure that you can access up-to-date metrics and insights at any moment, enabling you to act quickly.
With easy-to-understand visualizations, you can immediately interpret data and implement changes faster, gaining a competitive edge by making decisions when they matter most.
Do your product / SKU analysis right with Graas’ advanced eCommerce analytics tool!
Product analysis is crucial for any eCommerce business looking to stay competitive and prioritize the right products.
By understanding which products perform well and which need improvement, you can make data-driven decisions that enhance your strategy and boost sales.
However, challenges like scattered data, overwhelming metrics, unclear KPIs, and delayed insights can make product analysis difficult.
Fortunately, all these challenges can be easily solved with the right eCommerce analytics tool. That’s where Graas comes in – a tool that takes your eCommerce product analysis to the next level.
Here’s how Graas solves these issues:
Consolidated View: Graas offers a unified dashboard to track product performance across multiple platforms, saving time and improving accuracy.
Data Prioritization: It filters and prioritizes the most important metrics, allowing you to focus on actionable insights.
Customizable KPIs: You can set and track KPIs that are aligned with your specific business goals.
Real-Time Insights: Get real-time data analysis, so you can make decisions faster and more effectively.
Graas also provides a Product / SKU Analytics feature, offering a detailed view of product performance by categorizing items into four quadrants to refine your strategy further:
High Visibility (Low Traffic, High GMV): These products generate substantial revenue despite lower visits.
Low Visibility (Low Traffic, Low GMV): Products in this quadrant may need a reassessment.
Hero Products (High Traffic, High GMV): These are top performers bringing in both high traffic and revenue.
Non-Performers (High Traffic, Low GMV): These products attract visits but fail to convert them into sales.
When you know which product to put your focus on — the workflows will be more streamlined and you won’t be wasting your resources.
With Graas, you no longer have to worry about eCommerce product analysis challenges. Don’t miss out – Signup for a 30-day free trial today!
Opmerkingen