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eCommerce Analytics: Use Data to Grow Sales


eCommerce Analytics

Operating an eCommerce store doesn’t revolve around one particular metric or channel. You have to look at how different functions are doing, such as marketing, inventory, sales, etc. At the same time, you also have to look at things as granular as how the ad set of a campaign is performing, which are your top-selling products, which channel brings maximum sales, and so on. 


Guesswork will only take you so far. You need to make decisions based on insights that are driven by data. And this is where eCommerce analytics comes in. 


In this blog, we discuss the role of eCommerce analytics in business growth, what are the types, and also share some best practices that’ll help you grow sales. 


What is eCommerce Analytics? 


eCommerce analytics is the practice of collecting data on your website and customer behavior and then analyzing it to understand what makes your sales tick. By decoding this data, you can derive valuable insights to optimize your store and target the right audience. The result? You can increase your conversion rate, reduce your cart abandonment rate, and hence, generate more revenue. 


The role eCommerce analytics plays in business growth 

eCommerce analytics allows businesses to use their valuable data to gain insights for sustainable growth. By using customer behavior and website activity, businesses can gain a deeper understanding of their operations, optimize their strategies, and ultimately achieve significant sales increases.  


Let's see how eCommerce analytics can help you drive business growth: 


1. Building a robust supply chain


Customer satisfaction depends on convenience and competitive pricing. However, offering attractive prices can backfire if your inventory lacks the necessary stock. 


eCommerce analytics is crucial in striking the right balance between supply and demand. By analyzing past sales data, you can forecast future trends and ensure you have the right amount of products readily available. This approach prevents stockouts and keeps customers happy while also minimizing storage expenses. 


2. Predicting future trends 


Powerful eCommerce analytics tools like Graas can analyze factors such as transaction size, seasonality, and product categories to predict future trends. 


This foresight is invaluable in shaping your business strategy. Knowing what's likely to be popular in the coming months allows you to focus on the right products, adjust inventory levels accordingly, and create marketing campaigns to promote specific items. Moreover, you can plan promotions and discounts to maximize sales for different products throughout the year. 


3. Forecasting inventory for the next season 


Inventory management is a constant challenge for retailers. Determining which products deserve a place on your shelves is crucial. 


With eCommerce analytics, you can analyze sales volume, future sales projections, and customer satisfaction rates. This helps you identify which products consistently perform well and deserve continued investment. Conversely, you can remove underperforming products from your inventory, freeing up space and resources for potentially more profitable items. 


4. Measuring marketing and sales campaign effectiveness 


Marketing campaigns are a significant financial investment for eCommerce businesses. Without proper measurement, it's impossible to determine if your strategy is delivering a return on investment.   


eCommerce analytics bridges this gap by providing detailed insights into campaign performance. Metrics like ad clicks, visitor engagement time, channel data, and promotion effectiveness clearly show how your campaigns are resonating with your target audience. 


By analyzing marketing data, you can assess the return on investment (ROI) and refine your marketing strategy for maximum impact. 


5. Understanding your customers 


Building a loyal customer base requires a deep understanding of your customers. eCommerce analytics gives you insights into customer demographics, behavior patterns, and even instances where customers abandon their carts (churn rate). 


These insights allow you to build your product strategy to meet your target audience's specific needs and preferences. It also allows you to design targeted promotions and marketing campaigns that resonate with your customers, which leads to higher conversion rates. 

6. Optimizing product pricing 


Several factors come into play while deciding the product price, including customer demand, competitor pricing, and market availability. Predictive analytics allows you to analyze pricing trends within your industry and identify the optimal price point to maximize your profit margin. 


Amazon, for example, uses sophisticated algorithms to adjust product pricing in real time based on market conditions — this is a prime example of how data can be used to gain a competitive edge. 


What are the types of eCommerce analytics?


Having explored the role of eCommerce analytics in driving business growth, let's look at the different types of eCommerce analytics


1. Audience analytics 


Audience analytics provide in-depth insights into the demographics of your customer base. Here, you deal with data like age, gender, income level, occupation, location, and even preferred language. 


But it goes beyond demographics. 


Audience data also gives you insights into the devices your customers use to access your store. Do they primarily browse from their smartphones or desktops? Well, we know most customers use mobile devices. But then you need answers like, are they predominantly Android or Apple users? 


You also get insights into what products your audience frequently buys together. Based on which products they buy together, you can curate product bundles. These product bundles will help you sell more to customers who come to your store to buy a single product. 


Having these insights essentially allows you to create your online store for optimal viewing and user experience on different devices. 


Moreover, audience analytics allows you to refine your marketing and shipping strategies. Understanding your audience's location allows you to offer targeted shipping options and create your advertising efforts to resonate with specific regions. 


2. Acquisition analytics 


Acquisition analytics reveals how visitors discover your online store and ultimately land on your website. By analyzing acquisition data, you can measure the effectiveness of different marketing channels in attracting visitors and driving sales. 


Do social media posts generate the most website traffic? Are email campaigns a powerful tool for bringing in new customers? How about blog posts – do they result in conversions? Acquisition analytics answer these questions, allowing you to identify the marketing channels that deliver the highest ROI. 


When you know which channels are attracting the most customers, you can allocate resources and focus your efforts on them for customer acquisition. 


3. Behavior analytics 


Once customers arrive at your online store, how do they interact with your website? This is where behavior analytics comes in. These insights reveal valuable details about customer behavior, from the products they browse to the pages they visit. 


Behavior analytics answer questions like: 

  • Which products generate significant interest but low sales figures? 

  • How long do visitors typically spend on your website? 

  • Do most visitors abandon their carts without completing the purchase? 

  • What pages do visitors click on first, and which marketing content grabs their attention? 


Understanding these details gives you a clear picture of how customers navigate your website. If a high percentage of visitors leave your page quickly, it might indicate slow loading times or confusing content that doesn't meet their expectations. Behavior analytics allows you to identify areas for improvement and optimize your website for maximum conversions. 


4. Conversion analytics 


Conversion analytics looks into the process of converting website visitors into paying customers. Understanding how and when online users convert allows you to tweak your marketing strategy and messaging to engage with potential customers effectively. 


With conversion analytics, you can get answers to questions like: 

  • How long does it typically take for a visitor to convert into a paying customer? 

  • Do customers tend to make repeat purchases, or are they one-time buyers? 


This data allows you to create marketing messages for different customer journey stages. It also provides insights into factors like average order value and the typical number of items purchased per transaction. You can develop targeted promotions and discounts that align with your existing customer base and encourage repeat business. 


5. Paid marketing analytics


Many eCommerce businesses run paid marketing campaigns to reach a wider audience. Paid marketing analytics are crucial for measuring the return on investment (ROI) of these campaigns. 


By analyzing data on revenue generated from social media ads, pay-per-click campaigns, and email marketing initiatives, you understand which tactics are delivering the most for every penny spent. 


Are your social media advertisements generating sufficient revenue to justify the investment? Are emails a profitable channel for customer acquisition? Paid marketing analytics answer these questions, allowing you to optimize your spending and focus resources on the right campaigns. 


eCommerce Analytics Best Practices 


Let's look at some best practices to ensure you're using eCommerce analytics to its full potential: 


1. Break data silos to get a unified view 


Data from various sources – website traffic, customer behavior, marketing campaigns – resides in isolated silos. This siloed data hampers effective eCommerce analysis and can lead to inaccurate interpretations. 


For example, customer segmentation might be flawed if Facebook Ads data isn't considered alongside Google Ads data or if attribution models aren't properly configured. 


Here's where the concept of a "single view" of data comes into play.  This approach merges information from all your data sources into a unified platform, providing a complete view of your eCommerce operation. 


Here are some benefits of bringing data together from every channel: 

  • Reduced effort: No more logging into multiple platforms to collect data. 

  • Eliminating duplication and overlap: Consistent data eliminates inconsistencies and conflicting information. 

  • Cross-channel insights: Analyze data points across all sources to gain a more comprehensive understanding. 

  • Holistic overview: Gain a complete picture of your eCommerce brand, from customer acquisition to fulfillment. 

2. Maintain data integrity 


In eCommerce, data comes from various sources and can be heterogeneous, meaning it exists in different formats. Structured data, like CSV files or tables, is relatively easy to work with. However, other sources might provide information in PDFs or other formats. 


Manually converting this data into a consistent format is time-consuming and prone to errors. By the time you have everything ready for analysis, the data might be outdated, leading to inaccurate insights and missed opportunities. 


The solution is using eCommerce analytics tools that automatically fetch data from all your channels in real-time. This ensures data integrity and eliminates the risk of errors caused by manual manipulation. With clean, consistent data, you can be confident that your analytics is producing accurate insights. 


3. Account for seasonality and trends 


Many online stores make the mistake of analyzing data in a vacuum without considering external factors. Major industry events, seasonal trends, and competitor activity can all significantly impact your data. 


For example, a surge in sales around the holidays might not be a long-term trend but rather a reflection of seasonal buying patterns. 


Focusing solely on momentary data fluctuations can lead to misleading interpretations. Effective analytics involve understanding the context behind the numbers. Consider seasonality, industry trends, and competitor actions to gain a more comprehensive view of your performance. 


4. Run product category and individual product analysis 


Zooming in on granular product data allows you to optimize both your marketing and sales efforts. Tracking the performance of individual products and product categories over time reveals valuable insights into your revenue drivers. This analysis helps you identify top performers and products that might be underperforming. 


Get reliable eCommerce analytics insights with Graas 


eCommerce analytics can help your business stay on track with success, but fragmented data from various channels can leave you feeling lost. What if you have a central hub that gathers all your marketing, sales, and inventory data in real time – Graas is where your quest ends. 


Graas is an AI-powered growth engine designed to streamline your eCommerce analytics. Here's how it helps: 

  • Unified data dashboard: No more data silos! Graas seamlessly integrates with your existing tools, presenting all your crucial information in one place. 

  • Real-time insights: Make data-driven decisions faster with access to up-to-the-minute information. 

  • Granular visibility: Ditch the surface-level view. Graas lets you go deep. For example, analyzing the performance of specific marketing campaigns, ad sets, or even individual ad creatives. 


Stop wasting time gathering and piecing together data. Graas allows you to focus on what matters most—growing your online store. Sign up for free today! 


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