Top 7 Tools for Digital Commerce Analytics Mastery

Digital commerce analytics is the process of collecting, analysing and interpreting data from digital commerce activities to gain insights and inform decisions. It enables companies to identify meaningful trends and other behaviour of their customers.

Analytics is a crucial digital commerce analytics tool for firms to know their customers and make wise choices. It helps businesses to identify trends, measure performance, and optimise their online presence. Businesses can gain insights into customer behaviour, identify opportunities for growth, and improve their overall customer experience with these tools.

This article will explore the importance of analytics in digital commerce, the types of data that can be collected, and the tools and techniques used to analyse digital commerce data.
 

What Is Digital Commerce Analytics?

Digital commerce analytics allows companies to make more informed decisions with regards to marketing, operations, and customer behaviour. The use of analytics in digital commerce is essential for both small and large businesses. Analysing customer and business data using analytics, statistics, and technology allows for the discovery of insights not possible with more conventional approaches. Analytics for digital commerce enables businesses to make better decisions on operations, marketing, and consumer behaviour.

The first step of using these analytics is gathering the data. This means tracking customer purchases, website visits, marketing campaigns, and other activities that provide insight into customer behaviour. Companies must ensure they are collecting the right data and use the right tools to do so. The next stage is to analyse the data after it has been collected. Client data, including purchase history and customer segmentation, must be sorted, filtered, and examined in order to do this. To improve marketing and product strategies, significant customer insights can be discovered using sophisticated data analysis technologies.

Analytics for digital commerce are, in general, a very useful tool for companies of all sizes.It allows companies to gain valuable insights into customer behaviours, track the performance of their campaigns, and understand customer lifetime value. By taking advantage of advanced data analysis and digital commerce analytics tools, businesses can improve marketing strategies and product offerings, and gain a competitive advantage.

Digital commerce analytics 2023 is poised to revolutionise the way businesses make decisions about their online sales strategies.

 

Importance of Digital Commerce Analytics

The importance of these analytics stems from the fact that digital commerce has become an integral part of how businesses do business today. Businesses must use digital channels to connect with both current and new customers, as well as to broaden their reach internationally. To make an informed decision on how to best use digital platforms, businesses must have accurate analytics on what strategies and content are resonating with customers.
 

For example, when crafting marketing campaigns, businesses can leverage them to determine which channels should be used, what content should be targeted, and when it should be sent. These analytics can also provide valuable insight into the effectiveness of various tactics and campaigns. By examining website traffic, user engagement, and conversions, businesses can determine whether their current tactics are successful or need improvement.
 

In addition, they can also provide businesses with insights into customer buying behaviour. By looking at customer demographics, website visits, searches, products viewed, and purchases, businesses can gain valuable insight into what customers are interested in buying, how often they make purchases, and where they are getting their information from. With this information, businesses can tailor their digital campaign to ensure that the right message is reaching the right audience.

Companies that invest in advanced digital commerce analytics 2023 will have a distinct advantage over their competitors in understanding customer behaviour and optimising their online sales channels.

 

Key Features of Digital Commerce Analytics 

The key features are : data-driven insights, comprehensive analysis, comprehensive reporting, and ease of use. It helps businesses to collect, monitor and analyse data from their digital commerce platforms, such as shopping carts, web shops, and mobile applications. This allows businesses to gain insights from the data and make more informed decisions.

 

1. Valuable Data Sources Insights

Data-driven insights are at the core of digital commerce analytics. It takes data from sources like customer orders, purchases, checkouts and page views to give businesses valuable insights. These insights can help businesses understand their customers’ shopping behaviours and better identify opportunities for improvement. For example, these analytics can provide data points such as customer gender or age, country or region where the customer is located, or the products they purchased.

2. Comprehensive Analysis
 

Another feature of digital commerce analytics is comprehensive analysis. It enables businesses to track customers’ buying habits over time, analyse how their campaigns are performing, or measure their ROI on marketing spend. This can help them optimise their e-commerce strategies and prioritise areas that need improvement. It can also help them identify new customer segments they could target in the future.

3. Automated Reports
 

Reporting is another important feature of digital commerce analytics. Businesses can generate reports based on their analysis of the data. This gives them a clearer picture of the success of their marketing campaigns, customers’ engagement and purchasing, and any other KPIs (key performance indicators) they have set. These reports can be used for decision-making, as well as for communication with stakeholders.

4. User-Friendly Dashboards

Finally, ease of use is an important feature of digital commerce analytics. Businesses can use analytics dashboards to easily visualise and analyse their data. Dashboards and other analytics tools should be user-friendly, easy to navigate, and mobile-friendly. This helps businesses track their data from any device.

5. Growth Oriented Approach

Digital commerce analytics is a powerful tool that helps businesses gain insights and make better decisions. By leveraging its key features of data-driven insights, comprehensive analysis, comprehensive reporting, and ease of use, businesses can maximise their digital marketing and online sales strategies.
 

Digital Commerce Analytics: Tools

Digital commerce analytics is the study of how people interact and shop on the internet. It is used to understand how customers interact with digital channels, such as web stores and apps, so that companies can tailor their products and services to meet the needs of their customers and enhance the customer experience. As digital commerce becomes more ubiquitous, businesses need to use the insights and analytics from digital channels to increase sales and optimise their customer experiences. There are several types of analytics that are used to better understand and serve customers.

Digital commerce analytics tool is a powerful technology that helps businesses to analyse and understand customer behaviour, measure their marketing performance, and optimise their online presence. This tool is essential for any business that is looking to succeed in the highly competitive world of digital commerce. It enables businesses to gain valuable insights into customer behaviour and make data-driven decisions that can improve the customer experience and drive growth.

With artificial intelligence and machine learning technologies continuing to evolve, digital commerce analytics 2023 platforms will be able to provide even deeper insights into customer preferences and behaviour, enabling businesses to tailor their marketing and sales efforts more effectively.

Sekel Tech offers a wide range of digital commerce analytics to help businesses gain valuable insights into their online performance. These analytics include search analytics to track the effectiveness of search terms and keywords, location analytics to see where website traffic is coming from, campaign analytics to measure the success of marketing campaigns, product analytics to understand how individual products are performing, review analytics to track customer feedback, blog analytics to monitor the engagement of blog readers, and engagement analytics to gauge overall customer engagement on the website. By providing access to all these analytics, Sekel Tech enables businesses to make data-driven decisions and optimise their online presence for maximum success.

 

1. Search Analytics

Search analytics is the process of analysing data from search engines to understand user interactions with a website. The aim is to gain insights on user searches and engagement to optimise websites for better search engine visibility and user engagement. This includes analysing keywords, click-through rates, user engagement, and making changes to website content, structure and meta tags to improve search engine ranking.

2. Location Analytics

Location analytics is the process of analysing data to understand the geographical location of website visitors. The goal is to gain insights on how users from different regions engage with the website and use that information to improve website performance in those regions. This can include making changes to website content and design to appeal to specific locations, identifying areas for improvement, and measuring the effectiveness of marketing campaigns targeting specific regions and understanding the impact of cultural differences on user engagement.

3. Campaign Analytics

Campaign analytics is the process of analysing data to measure the performance of marketing campaigns. It aims to understand how users interact with a website as a result of campaigns and optimise them for better performance. This includes analysing metrics such as click-through rate, conversion rate and ROI of different campaigns to identify the most effective ones and tracking individual user’s journey through the campaigns to understand engagement and identify areas for improvement. By providing insights on campaign performance, it helps businesses make data-driven decisions on allocating marketing budget and resources.

4. Product Analytics

Product analytics is the process of analysing data to understand the performance of individual products or product categories on a website. This includes data on sales, revenue, and profit margins, as well as data on user interaction with product pages. The goal is to gain insights into popular products, revenue-driving products, and products that may need improvement. This information can be used to make data-driven decisions on product promotion, pricing, and product page improvement. Additionally, it can also be used to understand the impact of marketing campaigns on product sales and identify trends in customer buying behaviour. By providing insights into product performance, product analytics helps businesses to optimise their product offerings for success.

5. Review Analytics

Review analytics is the process of analysing customer feedback and reviews on a website or platform. This includes data on the number of reviews, average rating and sentiment of the reviews. The goal is to gain insights into customer satisfaction and use that information to improve products and services. This can include identifying common themes and issues in customer feedback, tracking changes in customer sentiment over time, and comparing the performance of products or services across different regions or time periods. Additionally, it can also be used to identify patterns in customer behaviour and understand how product attributes or pricing strategies affect customer reviews. By providing insights into customer feedback, review analytics helps businesses make data-driven decisions to improve products and services to meet customer needs.

6. Blog Analytics

Blog analytics is the process of analysing data to understand the performance of a blog and its readers’ engagement. This includes data on traffic, readership, and engagement metrics such as page views, bounce rate, time on page, and click-through rates. The goal is to gain insights into how users interact with a blog and use that information to improve its performance. This can include identifying popular blog posts, topics driving engagement, and types of content resonating with readers. Additionally, it can also be used to understand the impact of marketing campaigns on blog traffic, identify patterns in reader behaviour, and track changes in reader engagement over time. By providing insights into blog performance, it helps businesses make data-driven decisions on how to improve their blog and better understand their readers.

7. Engagement Analytics

Engagement analytics is the process of analysing data to understand how users interact with a website or application. This includes data on user behaviour such as page views, clicks and conversions, as well as data on user engagement such as time spent on the site and number of returning visitors. The goal is to gain insights into user interactions and use that information to improve the user experience. This can include identifying popular pages or features, areas driving engagement, and types of content resonating with users. Additionally, it can also be used to understand the impact of marketing campaigns on user engagement, identify patterns in user behaviour, and track changes in user engagement over time. By providing insights into user engagement, it helps businesses make data-driven decisions to improve websites or applications to meet user needs and increase engagement.

 

How to Use Digital Commerce Analytics Efficiently to Grow Your Business

There are several ways to use digital analytics to grow your business:
 

a. Track key metrics such as website traffic, conversion rates, and revenue to understand how well your online store is performing and identify areas for improvement.

b. Use customer segmentation to understand your different customer groups and their buying behaviours, and tailor your marketing and sales efforts to better target these groups.

c. A/B testing should be done to enhance user experience and conversion rates on websites.

d. Use session recordings and heat maps to analyse user behaviour on your website and spot areas of friction or confusion.

e. Use advanced analytics tools such as multi-channel attribution and lifetime value (LTV) modelling to gain insights on the customer journey and make data-driven decisions on customer acquisition and retention strategies.

f. Keep track of your competitors and industry trends by monitoring their website traffic, search rankings and other metrics regularly to be aware of their strategies and adapt your own.

g. Use automation and tagging to track ecommerce-specific metrics such as cart abandonment, checkout completion and customer lifetime value.

h. Use predictive analytics to make informed decisions about inventory and pricing.

 

It is important to have a solid data tracking and analytical infrastructure in place to be able to have access to the data needed and make sense of it, then use it to create actionable insights.

 

Harnessing the Power of Enhanced Digital Commerce Analytics

a. Use machine learning algorithms to analyse customer data and predict buying behaviours, allowing you to personalise your marketing and sales efforts for each individual customer.

b. Implement natural language processing (NLP) to analyse customer reviews, feedback, and customer service interactions, to understand customer sentiment and identify areas for improvement.

c. Use predictive analytics to forecast future sales and demand, allowing you to optimise your inventory and pricing strategies.

d. Utilise advanced analytics tools such as multi-touch attribution and user journey analysis, to gain a deeper understanding of the customer journey and identify the most effective marketing channels.

e. Use data visualisation tools such as dashboards and heat maps to make it easy for your team to understand and act on the data.

f. Implement tracking and tagging to track customer behaviour across multiple touchpoints and digital platforms.

g. Use real-time analytics to monitor your digital commerce platform and quickly respond to any issues that arise.

h. Implementing a Customer Data Platform (CDP) which can create a unified view of the customer and enable more accurate, timely and personalised experiences.

i. Use data Governance and management to ensure that your data is accurate and reliable, and that your team has the necessary resources and permissions to access the data they need.


Overall, businesses can gain a deeper understanding of their customers and make data-driven decisions that lead to increased revenue and growth.
 

Frequently Asked Questions (FAQs)

1. What should be the main function of digital analytics in an E-commerce?

The main function of digital analytics in an E-commerce is to gather, analyse, and interpret data to gain insights into customer behaviour, purchasing patterns, and sales performance. These insights can help businesses optimise their E-commerce operations, improve customer experience, increase revenue, and drive growth.

2. What are the different elements of E-commerce analytics?

E-commerce analytics is a multifaceted process that involves analysing data related to various aspects of online business operations. The different elements of E-commerce analytics include web analytics, which tracks website traffic, user behaviour, and other metrics such as page views and session duration.

3. What does an E-commerce data analyst do?

An E-commerce data analyst is responsible for collecting and analysing data related to E-commerce operations, identifying trends and patterns, and communicating insights to the business. They work with a variety of tools and technologies to extract and manipulate data, including SQL, Excel, and data visualisation tools such as Tableau.

4. What is an example of digital analytics?

An example of digital analytics is analysing the traffic data of a website. By using tools such as Google Analytics, a business can gather data on the number of visitors, their demographics, their behaviour on the website, and the sources of traffic (such as search engines, social media, or advertising campaigns).
 

Conclusion
 

In conclusion, digital commerce analytics is a powerful tool that can help businesses grow their online presence and increase revenue. By tracking key metrics such as website traffic, conversion rates, and revenue, businesses can gain a deeper understanding of their online store’s performance and identify areas for improvement. You now know everything there is to know about e-commerce analytics and why it’s so crucial for your company.You may use data to help you make more informed decisions that will advance your business and enhance your bottom line. You can only do this if you want to know which parts of your company are doing well and which ones need to be changed and improved. You cannot enhance something if you don’t measure it. By utilising the right tools and strategies, businesses can harness the power of these analytics to drive their growth and success.

 

Take Advantage of Sekel Tech’s Digital Commerce Analytics
 

You’ve made it through the discovery phase and are eager to get your data in one place. Sekel Tech offers a suite of ecommerce analytics solutions for all stages of a digital business. Use our tools to gather insights across your marketing channels, gain intelligence on why customers behave the way they do and take action to improve your risk management practice. We take care of the complex technical architecture and configure a solution that’s integrated with all your services and softwares.