Leverage eCommerce Analytics to Boost Online Sales
As online retail continues to expand, so do the level of competition and the expectations of consumers. Online retailers are increasingly driven to better understand how to meet the needs and desires of their current customers and how to better engage new ones. Ecommerce analytics enables retailers to gain the insights they need via data from various sources, including websites, apps, social channels, and media partners. Let’s explore how ecommerce analytics can help online retailers increase sales and optimize operations. We’ll wrap up by sharing three best practices for online analytics and show how Snowflake can support your ecommerce analytics efforts.
Ecommerce Analytics for the Buyer’s Journey
Online retailers are generating valuable data as customers interact with advertising, social media, and website content and as they take actions such as placing items in a shopping cart and completing a purchase. All of this data can be captured and analyzed. Here’s how ecommerce analytics can help retailers get a clear picture of the journey that customers take from awareness to brand evangelism.
As consumers discover your brand and become aware of your product offerings, you can gather data that reveals demographics such as age, gender identity, geographic location, and economic status. You can also track how prospective customers interact with your website. Metrics such as reach, impressions, and patterns of use on your site and social media channels help paint a data-driven picture of who your customers are, what’s important to them, and how they typically engage online.
Understanding how visitors end up on your website and how much you paid to get them are also important insights. Marketing data analysis tools help decision-makers better understand the cost per lead (CPL), cost per customer (CPC), and other valuable metrics, making it easier to more strategically allocate ad spend.
Driving traffic to your site is a worthy goal, but increasing conversions is what drives revenue. Gaining visibility into which traffic sources send visitors that convert at high rates versus low ones will help you identify which sources you should focus on. Ecommerce analytics makes it easier to understand what’s driving conversions now and to spot promising new sources.
Analyzing key metrics such as sales conversion rate, average order value, and the rate of cart abandonment helps identify ways to increase customer retention. Retention strategies serve as low-hanging fruit that retailers can take advantage of in addition to investing in new customer acquisition.
Using ecommerce analytics can help you identify which customers are likely to promote your brand to their friends and family and gain insights into how to keep them engaged. Actively tracking data such as content engagement and loyalty rewards program participation can help you better understand how engaged your current customers are with your brand and how to motivate them to share their enthusiasm.
6 Ways Online Retailers Can Use Ecommerce Analytics
Data analytics helps online retailers interpret their ecommerce data sets to better manage inventory, boost sales, allocate marketing resources, and more. Here are six of the most common ways ecommerce retailers are using analytics.
1. Better manage inventory
Ecommerce analytics data makes it easier to detect changing trends in product sales, allowing you to predict spikes in demand for certain SKUs. Proactively tracking changes in shopper preferences makes it easier to know when and where to stock inventory and can lead to an increase in sales volume.
2. Understand customer behavior
Today’s consumers are well informed with plenty of choices when it comes to buying online. Understanding needs, desires, preferences, and shopping habits will help you optimize the buying journey and meet customer expectations. Data can also tell you how to effectively prompt shopping behaviors.
3. Improve the customer experience
Understanding customer behavior also allows you to improve the customer experience. Streamlining the buying process and ensuring that customers can accomplish actions easily will increase the percentage of completed purchases. Ecommerce analytics tools are capable of tracking the individual journey of each visitor on your site. Analyzing this data can help uncover pinch points in the user experience that cause visitors to leave before making a purchase.
4. Cross-sell and upsell relevant products
Analyzing individual customer purchasing patterns will reveal relevant cross-selling and upselling opportunities. Armed with this data, you can personalize offers, retarget ads more effectively, and make product recommendations based on the unique preferences and product purchase history of each customer.
5. Maximize ROAS
With a plethora of advertising opportunities and limited marketing resources, it’s crucial to know which advertising channels are sending traffic that converts. With this data, you can maximize return on ad spend (ROAS). Additionally, you can discover which marketing messages are most effective with each market segment. Insights gathered from ecommerce analytics data can also help marketers recognize and cultivate new sources of customers.
6. Use data to drive product development
Analyzing current consumer preferences provides valuable insights for developing new products and improving existing ones. Staying attuned to consumer wants and needs as they evolve helps direct-to-consumer brands remain relevant.
Best Practices for Ecommerce Analytics
While there are endless possibilities for how ecommerce analytics can be used, your success will depend on the foundation you lay. Here are three best practices for getting the most out of your ecommerce analytics data.
Develop a customer 360
To develop a deep understanding of each customer, you need a complete, 360-degree view, using data gathered from multiple sources. Ecommerce analytics can reveal how customers first become aware of your brand, how they interact with your website, which social media channels they use to engage, and their unique purchasing patterns. A customer 360 provides a full picture of the buyer’s journey that you can use to inform all your marketing activities.
Define metrics and data sources
Analytics tools can help uncover answers to many important business questions. But accurate conclusions depend on identifying what metrics you want to track and the sources of valuable data that will inform your decision-making. Before moving forward with any analytics initiative, first define what you’ll measure and where the data will come from.
Consolidate data into a single source of truth
The ready availability of customer data that online retailers have at their fingertips comes with a catch: It’s almost always siloed across multiple sources. Sales data is stored in an ecommerce platform such as Shopify. Social media engagement data is stored with the individual platforms. Paid advertising data is stored with media partners. This separation makes creating a unified view of each customer nearly impossible. Aggregating your data into a single repository such as Snowflake solves this problem, making it easier to get the complete picture of individual customer behavior and sales history by establishing a single source of truth.
Snowflake for Ecommerce
The Snowflake Data Cloud provides ecommerce retailers with a powerful, cost-effective solution for analyzing relevant data in real time. By seamlessly combining data from omnichannel sources, Snowflake makes it possible to gain a 360-degree view of your customers so you can gain the insights you need for better marketing. Additionally, Snowflake can help you optimize supply chain planning, demand forecasting, and inventory management, with the advantage of virtually unlimited analytical scale and performance.
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