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Practitioners of data analytics for Ecommerce businesses often focus on its impact on B2C (business-to-consumer) companies. By collecting customer data, for example, B2C companies can improve the customer experience, increase their conversion rates, launch smarter marketing campaigns, attract and retain new customers, and a variety of other benefits. However, B2B (business-to-business) Ecommerce companies can see just as many advantages from smart use of their Ecommerce data for analytics.

The major difference between B2C and B2B Ecommerce retailers, of course, is the type of customer they sell to whereas B2C companies target individuals, B2B customers tend to be other businesses and organizations. While this distinction has an impact on certain factors such as marketing strategies, B2B companies ultimately have many of the same goals as B2C companies do: understanding customer behavior, acquiring new customers, improving customer retention, and making wiser business decisions.

So how can B2B businesses get the most from their Ecommerce data for better analytics and smarter decision-making? In this article, we’ll discuss everything you need to know, including the benefits of Ecommerce data for B2B analytics and how to get started analyzing your B2B Ecommerce data.

Related Reading: Big Data Analytics in B2B E-Commerce: What It Is and Why You Need It

What is Ecommerce Data for B2B Analytics?

Ecommerce data for B2B analytics consists of any information about a B2B Ecommerce site that can help key decision-makers improve the business and gain a competitive advantage over the company’s rivals.

There is a tremendous amount of data available for B2B Ecommerce analytics—if you only know where to look. The list of potential data sources in your IT ecosystem includes:

  • Ecommerce platform: Your choice of Ecommerce platform itself (such as Shopify, Magento, or BigCommerce) contains tremendously valuable information about your online store. From a user’s first visit to your site to their most recent checkout, your Ecommerce platform can track individual customer journeys to help you understand how to improve the customer experience.

  • CRM (customer relationship management): CRM platforms track the entire omnichannel history of a customer’s interactions with your business. This includes touchpoints such as website visits, purchases, returns and refunds, phone calls, email messaging, social media, and more. CRM data can help your business identify loyal customers or inactive users so that you can launch targeted campaigns for different audience demographics.

  • ERP (enterprise resource planning): ERP systems help companies optimize and streamline their business processes, often through automation, across a wide variety of functions—from human resources and accounting to project management and supply chain management. ERP Ecommerce data can provide crucial information about products, stock levels, pricing, shipping, invoices, taxes, and more.

  • Digital marketing tools: To monitor the success of your B2B marketing initiatives across marketing channels, from social media and email marketing to SEO, you’ll need a variety of digital marketing tools. These applications can produce important metrics to judge the success of your marketing campaigns, from the click rate of an email to the number of impressions for a social media post.

What are the Benefits of B2B Analytics for Ecommerce?

More and more key stakeholders in B2B Ecommerce companies are realizing the power of big data to help improve their Ecommerce sales. Below are just a few benefits and use cases that B2B businesses can realize with Ecommerce analytics:

  • Better customer service: By analyzing your Ecommerce data, you can better understand and cater to the businesses who make a purchase at your online store. For example, B2B companies can use Ecommerce analytics to resolve tickets more quickly by optimizing their customer support workflows (e.g. building a knowledge base that answers many common questions).

  • Higher profitability: B2B analytics can help you achieve higher profits for your Ecommerce site. If you know which items are often placed in a customer’s shopping cart together, for example, then B2B sales reps can find opportunities to cross-sell and upsell other products. You can also display better product recommendations while users are shopping or identify potential ideas for developing new products.

  • More efficient supply chain: Out-of-stock products are one of the most common reasons why customers leave an Ecommerce site for a competitor. The good news is that Ecommerce analytics can provide better visibility into your company’s supply chain so that you can predict when a product will be running low and send a restock order ahead of time. Stock levels are just one example—B2B Ecommerce analytics can help you identify potential risks and disruptions in the supply chain before your competitors know about them so that you’ll always be the first to act.

  • Greater market opportunities: B2B Ecommerce market trends are always on the move, which makes it essential for companies to keep on top of them. With the right Ecommerce analytics setup, B2B companies can discover actionable insights to help them stay ahead of the curve. These might include new revenue streams, shifts in customer sentiment or desire, opportunities for raising brand awareness, and more.

  • More accurate forecasts: Being able to see into the future—and adapt the business for what’s to come—is the ultimate goal for any organization. Using techniques such as predictive analytics and machine learning algorithms, B2B businesses can use historical data to forecast upcoming events and outcomes, such as the chance that your market will slump in the next year. You can then move proactively to anticipate what’s to come (e.g., developing new products or marketing campaigns).

  • Smoother sales campaigns: For maximum success, your B2B sales team needs to know what makes your customers and prospective customers tick: what problems they’re looking to solve, what brought them to your business, and more. B2B Ecommerce analytics can help open a window into the minds of your sales leads, evaluate which sales activities are most likely to be effective, build stronger connections and relationships, and ultimately help you close more deals.

 

How to Use Ecommerce Data for B2B Analytics

It’s indisputable that Ecommerce data can have a major impact on your B2B analytics workloads. So how can you get started with B2B Ecommerce analytics? In this section, we’ll offer a few tips and best practices for using Ecommerce data in B2B analytics.

  • Take the long view: Success with B2B Ecommerce analytics won’t happen overnight, nor will it occur simply by haphazardly adopting a few analytics tools. Instead, you’ll need to design an end-to-end analytics program that spans the entire organization, leveraging your Ecommerce data for maximum effect.

  • Understand your objectives: The first step in creating an analytics program for your B2B Ecommerce site is to understand what you want to accomplish. Do you want to retain more loyal customers, optimize your marketing campaigns, make your supply chain more efficient—or something else entirely? When first starting out, it’s best to select one or two of the goals that are most important to you, as well as the metrics and KPIs (key performance indicators) that you’ll use to judge the success of the initiative.

  • Evaluate your existing analytics setup: Most B2B Ecommerce companies are already using analytics in some form or fashion—but their existing setup may not be optimal in terms of speed, efficiency, or automation. Whether you’re searching through Excel spreadsheets for insights or you’re already using a few analytics tools, take the time to survey what’s in place.

  • Identify the right processes to optimize: Once you’ve defined your goals and understood your current situation, the next step is to target a process or processes for optimization. If you want to convert more leads into paying customers, for example, you’ll likely want to start by reforming the processes that your sales team uses to move from the top to the bottom of the funnel.

  • Find the right tools and technologies: Each B2B Ecommerce company will have its own analytics strategy—and the good news is there’s no shortage of analytics tools on the market to meet these needs. In addition to a full-fledged analytics platform to crunch the numbers, you’ll likely also need a solution for data integration to get all this information in the same place (as we’ll discuss in the next section).

  • Measure, analyze, and refine: After putting your Ecommerce analytics plan into action, the final (and never-ending) step is to monitor your metrics and KPIs. If you notice that your sales team’s performance is lagging compared with the previous quarter or year, for example, then you can dive deeper into the data to understand why this is occurring and how you can correct your course.

Data Integration for B2B Ecommerce Analytics

We’ve discussed how to use Ecommerce data for B2B analytics in the general sense—but what does this look like in practice?

The fastest, most efficient, and most effective way to analyze your B2B Ecommerce data is by collecting it all in the same place. This centralized repository will typically be a data warehouse or other database optimized for online analytical processing (OLAP). From here, you can connect the dots between disparate data sources, identify crucial hidden insights, and generate reports, dashboards, charts, graphs, and other visualizations.

Data Integration and ETL

There’s just one question: how do you actually perform big data analytics in B2B Ecommerce? The right answer here will likely be some form of data integration platform. These tools can automatically take in massive quantities of information and combine them in a central location, establishing what’s known as a “single source of truth.”

In the field of data integration, the most common technique is known as ETL (extract, transform, load). This name describes the three steps of an ETL workflow: data is first extracted from one or more sources, transformed to improve its quality and fit the target schema, and finally loaded into a destination such as a data warehouse. ELT (extract, load, transform) is a variant of ETL in which the data is first loaded into the target location before being transformed, making it more suitable for high-volume or real-time use cases.

Related Reading: What is Ecommerce Integration & Is It Important?

Data Warehouse vs. Data Lake

The target location for an ETL job is typically a data warehouse, which is a system that efficiently stores large amounts of data and makes it available to business intelligence and analytics software. Public cloud providers such as Amazon Web Services, Microsoft Azure, and Google Cloud Platform all offer their own version of a cloud data warehouse. Some of the most popular cloud data warehousing solutions include Amazon Redshift, Google BigQuery, and Snowflake.

A data lake is a variant of a data warehouse that is designed for storing unstructured data. Unlike structured data, which can be organized into rows and columns (like an Excel spreadsheet), unstructured data can’t be neatly categorized along these lines. Examples of unstructured data include text, images, and videos. Data lakes are intended to contain large quantities of unstructured data without needing to transform this information first; instead, the transformations occur within the data lake on an ad-hoc, as-needed basis.

ETL Tools for B2B Ecommerce Analytics

Regardless of whether you choose a data warehouse or data lake as the final destination, you need the right ETL and data integration tool for the job. Building your own data integration scripts or pipelines is highly inadvisable: it’s time-consuming, requires a high level of technical knowledge, and may need to be regularly maintained if the components of your workflow suddenly change.

When selecting the best ETL tool for B2B Ecommerce, consider the topics below:

  • Ease of use: Most B2B Ecommerce businesses don’t have a full in-house team of data experts, which means that any ETL tool will need to be user-friendly. Prioritizing ease of use also means that non-technical business users can be empowered to build their own data pipelines.

  • Integrations: One important factor in an ETL tool’s ease of use is the number of pre-built connectors and integrations it has. Make sure that your choice of ETL platform can easily link your data sources with your choice of data repository. The list of integrations to look for might include Ecommerce platforms such as Shopify, Magento, and BigCommerce; CRM and ERP systems; marketing and analytics tools; and more.

  • Security and privacy: Ecommerce retailers are subject to strict laws and regulations governing how they use customer data. The applicable statutes here may include PCI-DSS for payment card information, as well as privacy regulations such as GDPR and CCPA. Your choice of ETL tool should be compliant with these laws and regulations.

How Integrate.io Can Help with B2B Ecommerce Data Analytics

To get the most out of your Ecommerce data for B2B analytics, you need a top-notch ETL tool. That’s exactly where the Integrate.io data integration platform comes in.

Integrate.io is a powerful, feature-rich, user-friendly solution for building real-time ETL, ELT, and data integration workflows. The Integrate.io platform has been built from the ground up for the needs of Ecommerce businesses.

With a simple, no-code, drag-and-drop interface, it’s never been easier for users to get started creating their own pipelines from their data sources to a centralized data warehouse or data lake. Integrate.io also comes with more than 140 pre-built “plug-and-play” connectors for the most popular data sources, from files and databases to CRM, ERP, and analytics tools.

Integrate.io also comes with advanced data integration features that make your ETL processes more efficient. For example, Integrate.io’s FlyData CDC (change data capture) functionality alerts you when changes are made to a source table or database so that your next data integration job only includes those records that have actually changed. Integrate.io also supports reverse ETL for moving data out of a centralized repository (like a data warehouse) into third-party systems for easier access and analysis.

Ready to learn how Integrate.io can help B2B companies get more from their Ecommerce data? Get in touch with our team of Ecommerce data experts today to discuss your business goals and requirements.