B2B eCommerce Series 2: Assessing Digital Maturity for B2B eCommerce

Rick O'Neill Rick O'Neill

In article 1 of our 8 part series on conducting B2B eCommerce in China, we looked at digital transformation. In this article, we look at how companies can assess their digital maturity when embarking on B2B eCommerce.

According to a recent survey that TMO Group conducted among eCommerce professionals, most respondents believe that digital transformation plays an important role in the long-term eCommerce strategy of companies. We also list some of the main challenges that companies face, and what type of data companies actively collect or analyze, for your reference.


When it comes to the digital transformation of a company, starting eCommerce can be a launchpad for advancing its digital maturity. On the other hand, the level of digital maturity will ultimately determine how successful a company can be in its eCommerce. The higher the level of digital maturity, the more likely a company is to successfully manage competition risks, convert users and increase online sales. You can evaluate the digital maturity of a company from the following aspects:

  • User Experience
  • System Delivery and Operation
  • Data Analysis Management
  • Digital Talents

1. Initiation Stage

1.1 User Experience

Digital Catalog

  • Products are displayed as SKU, including product ID and basic specifications. 
  • No price or inventory visibility
  • A simple picture of the product, or none at all.

  • Contact form
  • Telephone or email inquiry
  • No price or range displayed
  • No option to purchase products online 
  • Sample ordering (without online transaction)
  • No personalization

Channel Scalability

  • Single channel (most of the time a desktop website, but sometimes a mobile app)
  • Little or no social media presence

1.2 System Establishment, Delivery, and Operation

Tasks in the sales and fulfillment process are almost exclusively done manually by company employees.

Most of the company’s platform systems operate independently from each other, and data cannot be synchronized between them. eCommerce, ERP, Customer Relationship Management (CRM) and warehousing operations are all carried out separately from one another without integration. Labor costs can be high. Whether it is a sales freight or order bill, it requires manual input from employees. When tasks are done manually, it leaves the potential for errors. However, by implementing an ERP, many of these tasks can be automated and included into the system workflow in the future. 

1.3 Data Management and Analysis

The eCommerce data gathered focuses on website traffic and page statistics, as well as basic user browsing behavior. This data is analyzed for ‘what happened?’ 

Data analysis is done by viewing dashboards and reports to analyze and obtain results. In most cases, business decisions are still based on assumptions about some unanalyzed data. 

1.4 Digital Talent

Companies will likely lack widespread IT and digital capabilities, and most of the employees will fundamentally have offline work experience rather than digital. They will focus more on marketing and developing the business rather than digital operations. 

2. Growth Stage

2.1 User Experience

Digital Catalog

  • Additional product information beyond SKU
  • More search options for products
  • Product filtering and comparisons – it goes beyond product categories into more detailed product features
  • Multimedia product information, such as pictures, videos, PDF downloads, etc.
  • Recommendations based on product relevance
  • Online customer service

Pricing, Payment and Degree of Personalization

  • Tiered pricing
  • Customer group pricing
  • Standardized payment methods, fixed price online payment, offline cash on delivery, or B2B company credit payments
  • Standardized online sales processes
  • Customer account dashboards, including order status tracking
  • Personalized functionalities such as loyalty points, business lines of credit

Channel Scalability

  • An expansion from desktop website to an optimized mobile experience, and offline POS terminal
  • A consistent user journey across different channels
  • Omni-channel delivery/process tracking


2.2 System Establishment, Delivery and Operation

For the automation of previously manual tasks to occur, the ERP needs to be the main data source for the integration of eCommerce platforms such as the CRM and WMS systems. Organizational workflows such as related to financial, and logistics can now be simplified and optimized, and their efficiency and time effectiveness be fully evaluated.. All departments of the business should collect feedback and adjust their processes in an integrated manner.

  • Integration of back-end systems such as ERP
  • Real-time inventory visibility
  • Real-time warehouse and third-party logistics tracking
  • Provide return and exchange service for customers
  • E-fapiao processing capability

2.3 Data Management and Analysis

With an increasing number of touchpoints, more data is gathered regarding products, user behaviors, and operational processes. Companies can now turn customer-related data into actionable insights to better segment customers and provide personalized experiences to meet their expectations. 

Data is now analyzed for ‘why did it happen.’ By making the transition to diagnostic analysis, companies can start trying to find different patterns in data. To do this, data can be divided into multiple categories, or they can perform sentiment analysis. To tap into its potential, companies must possess both the personnel and software to generate these insights. As the company becomes more digitally mature in the future, diagnostic tasks will also be able to solved through data mining and machine learning techniques

By making the transition to diagnostic analysis, companies can start trying to find different patterns in data. To do this,  data can be segmented by customer demographics or behavior. Sentiment analysis can also be used to track customer sentiment. However, companies need to invest in the sufficient personnel and software that can generate these insights. As a company becomes more digitally mature in the future, diagnostic tasks will also be able to be solved through data mining and machine learning techniques.  

2.4 Digital Talent

Companies will by now have teams with IT expertise and digital thinking capabilities. All departments of the company will need to appoint personnel who can coordinate digital transformation.

3. Advanced Stage

3.1 User Experience

Digital Catalog

  • Data-driven product marketing
  • A wide array of product categories, meaning customers can look very specifically for what they want, and enhancing the shopping experience
  • Automated, unique product recommendation and personalization for individual customers based on the AI engine
  • Advanced search options, such as by product specifications, making the purchasing process more accurate and efficient for users
  • Support multi-market, multi-currency, multi-language and localized catalogs
  • Being able to manage products efficiently using a Product Information Management (PIM) system

Pricing, Payment and Degree of Personalization

  • Customized price lists
  • Personalized, exclusive offers for customers
  • Price negotiation
  • Multiple payment methods:
  • Online payment
  • Offline payment (bank transfer, purchase order, credit limit)
  • More personalized B2B order models, such as subscriptions or recurring orders 
  • Quick orders, re-order and requisition orders
  • Intelligent online customer service 
  • Customized company account registration

Figure 2.5: User experience in the advanced stage of digital maturity

Channel Scalability

  • Multichannel social media is supported, for example with WeChat, Weibo, Baidu, in China.
  • Multimarket expansion, including multi-languages, currencies and market localization.
  • A complete virtual inventory of products online.

3.2 System Establishment, Delivery, and Operation

  • API orchestration allows for more integration from the external supply chain and partners. This helps to automate workflows and reduce manual input, thus allowing for higher accuracy and efficiency 
  • AI and big data is used for the scheduling and optimization of freight management and delivery, (which allows for the optimization of freight rates), as well as to integrate company data and processes. 
  • The usage of a PIM system provides companies with a single place to collect, manage and enrich complex product catalog information to distribute to your online & offline channels. This ensures company-wide consistency on product information, complementing the more basic information that can be acquired from SKU/SPU based systems such as the company’s ERP or Order Management System (OMS)
  • The sales team will follow up with their customers through mobile CRM systems. Clienteling can solidify long-term relationships between the company and customer. Furthermore, customer service & after-sales is primarily supported by AI-powered chatbots, which thanks to their 24/7 support and ability to give immediate answers to customer queries, can optimize the sales funnel. 
  • Through quantitative supply chain optimization, the company’s digital resources are leveraged to optimize supply chain operations
  • Companies can partner with distributors to offer offline services such as after-sales and installations
  • The partner ecosystem (incorporating for example –  marketing, consulting and financing) are integrated to provide more efficient and transparent services 
  • All departments of the company use a single sign-on (SSO), which improves data security and lowers IT costs

3.3 Data Management and Analysis

Two forms of AI and big data-driven analysis become increasingly important in the advanced period of digital maturity:

  • Predictive analysis – ‘what will happen’

By capturing patterns from data and movable assets, companies can predict what will happen based on historical data – for example, will this user churn? How should this product be priced? How long does it take for the machine to be served under the current workload? Predictive analysis is usually achieved through machine learning. 

  • Normative analysis – ‘what should be done’ 

When solving problems, normative analysis can provide recommendations or views on which actions can be taken. For example, the platform can gather external data on the credibility and risk scores of new users and provide recommendations to decline or prepay orders for the accounts of certain customers.

3.4 Digital Talent

Digital is at the core of the company’s work culture. eCommerce is now fundamentally decentralized, with every team possessing certain digital skills for autonomous assessment and for devising key strategies.

Data Management Maturity Model

As a data-driven eCommerce technology service provider, TMO Group focuses on helping companies build data assets toward data management.. The model for the evolving process of data management is attached for your reference.9 It will be explored in more detail in our next eCommerce guide.


B2B eCommerce Implementation Roadmap

How can your company go about implementing B2B eCommerce? Here is a four step roadmap: 


Step 1: Create a complete digital product catalog, and focus on building a complete user experience in product navigation, filtering and search. Provide users with comprehensive product and brand information, and provide inquiry requests to understand the user’s interests and needs. 


Step 2: Provide new sales channels to contact new and maintain existing customers, and achieve sales automation with standardized and Taobao-like online purchasing workflows. 


Step 3: Optimize eCommerce operations and sales through in-depth localization and B2B features. Reduce service response times, implement a personalized product price and delivery process, and establish an account-level sales structure to serve B2B customers.


Step 4: Replicate the success of one market to another and adopt new digital business models to meet new and changing market demands. 

If you would like to know what stage your company is currently in:

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