Many companies are unaware of how e-commerce influences B2B analytics.
E-commerce can improve analytics by providing additional context to algorithms and metrics. That can improve sales and inventory management processes.
E-commerce can also strengthen predictive analytics.
Moving e-commerce data to a warehouse and running it through business intelligence software can enhance analytics for B2B companies.
Integrate.io uses a low-code/no-code environment to transfer data between e-commerce sources and a warehouse.
E-commerce is the future of B2C retail, with online retailers expected to generate a total of $5.55 trillion in sales in 2022. The benefits of e-commerce are almost endless: This business model overcomes geographical limitations, allows merchants to sell new products and services 24 hours a day, and eliminates many of the costs associated with managing a brick-and-mortar store. But do you know how e-commerce influences B2B analytics?
In this guide, explore the relationship between B2B e-commerce and analytics and learn the easiest way enterprises can generate insights about their business-to-business activities.
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Table of Contents
- E-commerce Influences B2B Analytics in Your Data-Driven Enterprise
- E-Commerce Improves Inventory Management
- How E-Commerce Influences B2B Analytics: E-commerce Supports Predictive Analytics
- How to Use E-Commerce Data for B2B Analytics
- Different Data Integration Types for B2B Analytics
- How E-commerce Influences B2B Analytics: How Integrate.io Helps
Integrate.io is the data warehousing integration solution built for e-commerce. It moves data between B2B e-commerce sources to a centralized target system, allowing managers to run data through business intelligence (BI) tools. Integrate.io differs from other solutions because it streamlines the entire data integration process. There's no jargon, and managers can build data pipelines in a stress-free no-code/low-code environment. Email Integrate.io for a 7-day demo and discover how e-commerce influences B2B analytics.
E-Commerce Increases B2B Sales Opportunities
One of the ways how e-commerce influences B2B analytics is the abundance of information it provides about clients. E-commerce data such as online transaction numbers, average order values, checkout information, and shopping cart abandonment rates reveal how clients interact with B2B products on your website. You can then use this information to optimize B2B data analytics, meet customer needs, improve decision-making, fine-tune digital marketing campaigns, and increase sales opportunities.
Take sales conversion rates, for example. By feeding this metric into a BI tool and comparing it with other e-commerce platform data, you can learn which sales reps convert the most clients and provide the most value. These insights can help you train other reps and fine-tune your selling strategies for increased revenue. Cost per acquisition (CPA) is a metric that measures the costs associated with clients performing a particular action. Taking a deeper look at CPA by running this metric through BI tools can help you make smarter decisions in your business.
The information you need to perform B2B analytics might exist in several different systems in your organization, making customer data analysis a challenge. You will need to move e-commerce data like sales conversion rates and CPA to a centralized system to generate more valuable B2B insights. (More on that later.)
E-Commerce Improves Inventory Management
This is another way how e-commerce influences B2B analytics. Typically, B2B managers use an enterprise resource planning (ERP) system or similar tool to glean insights into their inventory management and supply chain processes. Adding e-commerce data to the mix, however, allows these managers to generate deeper insights into inventory processes such as warehousing and order fulfillment.
By analyzing data from other platforms used in e-commerce like B2B customer relationship management (CRM) systems and transactional databases, companies can learn more about how clients and sales processes relate to inventory management and use these insights to improve day-to-day operations. For example, data from a CRM that reveals clients' previous purchase orders can determine whether a business should maintain sufficient stock of particular products. Including additional data sources in B2B analytics results in more successful outcomes for ordering, storing, and selling inventory, which can improve the user experience.
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E-Commerce Supports Predictive Analytics
E-commerce now accounts for 16% of all retail purchases, and with those purchases comes a wealth of data for analytics. Every day, B2B managers collect, process, and store data about clients, products, pricing, sales, and inventory from e-commerce sites—valuable information for statistical algorithms and data modeling techniques.
One of the most effective ways how e-commerce influences B2B analytics is predictive analytics, which uses machine learning and artificial intelligence to forecast future outcomes based on historical information. While B2B managers can't predict the future, this analytical approach can certainly help them make smarter decisions in real-time and identify potential pain points in their enterprise.
The more e-commerce data available, the more effective predictive analytics will be. When running data from several e-commerce systems through the appropriate BI tools, you can identify revenue opportunities, increase profitability, improve client retention, improve product recommendations, enhance B2B marketing, and reduce any potential risks that might jeopardize your enterprise.
Integrate.io helps you move data to a warehouse, which allows you to run that data through BI tools that perform predictive analytics. Unlike some other data warehousing integration platforms, Integrate.io specifically targets e-commerce and doesn't require any data engineering experience. The platform warehouses data via ETL, ELT, and ReverseETL, providing more data integration methods than other tools. It also offers super-fast CDC capabilities. Email Integrate.io now for a 7-day demo and learn more about how e-commerce influences B2B analytics.
How To Use E-Commerce Data for B2B Analytics
Often, e-commerce data exists in several siloed systems that can't communicate with each other, making successful analytics an uphill struggle for B2B managers. Data integration—a broad term that refers to the combining of data from multiple sources—is the only way to achieve a single source of truth for all the e-commerce data that flows in and out of your enterprise.
Data integration takes many forms, but the easiest way to achieve this objective is to transfer e-commerce data from a source to a data warehouse—a data management system that enables analytics to take place. From here, you can run data through BI tools and identify patterns and trends in that data that help solve business-related problems. Ultimately, data integration results in more productive B2B analytics and improves your marketing strategies.
Different Data Integration Types for B2B Analytics
There are various data integration methods that help you understand how e-commerce influences B2B analytics:
Extract, Transform, Load (ETL) is a method that involves extracting data from a system used in e-commerce, cleansing and transforming the data so it's suitable for analytics, and loading the data into a warehouse-like Amazon Redshift or Microsoft Azure. Then you can run the data through BI tools like Looker or Tableau and generate better B2B analytics.
Extract, Load, and Transform (ELT) is similar to ETL, but it reverses the "load" and "transfer" parts of the process. Better suited for unstructured data and larger data loads than ETL, ELT extracts data, loads it to a warehouse, and then transforms the data to the appropriate format for analytics.
ReverseETL involves moving data from a warehouse back to an operational system like a SaaS tool. It allows you to push data from a warehouse into your B2B team's favorite tools.
Change data capture (CDC) is a data integration technique that syncs two or more databases. It lets you view any changes made to those databases (such as updated tables or deleted entries), allowing you to take quick action and protect your data assets.
All of the above data integration techniques require, at the least, intermediate knowledge of programming and data engineering. For smaller B2B companies that want to use e-commerce data to improve analytics, it might not be possible to create the complex data pipelines required for successful data integration. Using a data warehousing integration tool, however, streamlines the process. The best platforms require little or no code and come with out-of-the-box connectors that non-engineers can use to integrate data.
Integrate.io Helps How E-Commerce Influences B2B Analytics
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Integrate.io is a data warehousing integration tool for managers in the B2B space. It can transfer data to and from a warehouse via ELT, ETL, and ReverseETL and offers fast CDC capabilities, providing you with multiple data integration options. Integrate.io has a simple philosophy of removing the jargon associated with integrating data between sources and destinations, helping you generate the latest data insights about your enterprise without the hard work.
Integrate.io has a simple drag-and-drop interface, enabling e-commerce businesses to create data pipelines in minutes with its out-of-the-box connectors for transactional databases, relational databases, SaaS tools, apps, sales channels, email marketing automation tools, messaging platforms, social media, CRMs, ERPs, and more. With its low-code/no-code environment, you can warehouse data and run it through BI platforms without worrying about constant pipeline maintenance or configuration. The result? More powerful B2B analytics that solves problems, improve the customer experience, target existing and new customers, forecast future outcomes and help you make smarter decisions.
Integrate.io abides by all major data governance initiatives, meaning you can move data between sources and destinations without breaking the law. It also offers enhanced security by hosting and storing data in Amazon's renowned data centers. Other Integrate.io features include superior customer service and simple pricing.
Integrate.io knows how e-commerce influences B2B analytics and can help you warehouse e-commerce data for better insights into your business. Schedule a demo now!