Optimizing Data Architecture for Competitive Advantage in B2B

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Currently, there are five billion active internet users, accounting for 63% of the entire global population. Each user has different preferences and consumes specific content. 

Modern business leaders are gradually understanding the relationship between user data and their business objectives. With all the data available on the internet, businesses are improving how they connect with clients. 

Knowing how to meet all the needs of your clients is a vital skill for any business owner, particularly for B2B. The nature of B2B explicitly revolves around companies, and by analyzing data from a specific company, you get a clear picture of the solution they are looking for.  

B2B leaders need to have a structured data structure if they are looking to gain (and maintain) a competitive edge over their competitors. 

What is Business Data Architecture?

For some time, data architecture was mostly associated with databases or system design. But as more user data becomes available, business owners are implementing the same concept to deliver personalized services or products. 

Data architecture in business is simply a framework for managing data to align with organizational goals. It is made of rules, models, standards, and policies that oversee collection, storage, integration, classification, and use of data in your company. 

The main goal of a data architecture is to translate your business's objectives into data and system requirements. Data architecture also streamlines the management and flow of information within the company. 

Currently, more B2B business owners are adopting artificial intelligence (AI) technology to fully optimize and modernize their data architecture models. Despite the adoption of new technologies, you have to follow a particular set of principles when developing your business data architecture. 

  • Data is a shared asset – All stakeholders at the company should have access to data, which gives them a clear view of the business.  
  • Users require sufficient access to data – The stakeholders need to be able to consume and interpret the information easily using  familiar tools.  
  • Security is vital – Threats to data are a constant concern for every business, meaning access control and support data policies on raw data have to have high priority. 
  • Curate data – Adopt modern technologies such as AI that perform data curation (cleansing raw data, modeling vital relationships, and curating key dimensions).
  • Optimize data flow for agility – To save costs, reduce the number of times you move data while increasing data freshness and enterprise agility. 

Getting Started with Data Architecture for B2B Businesses

With 23.6% of businesses in the US being involved in the B2B market, the industry is highly competitive. As a business owner, it's your job to ensure you remain ahead of the competition through successful strategies.  

The strategy should not solely rely on massive amounts of information. It should also focus on collecting relevant real-time product-in-use data to optimize possible advantages. By observing how users interact with your product, you accumulate richer data which helps evolve your customer experience.

Here are some steps you can follow to get started with data architecture for your B2B business. 

Develop the Perfect Strategy

The first step of developing your data architecture starts by bringing together your company's stakeholders and data scientists. The stakeholders outline the company's objectives, while the data scientist translates these objectives into actionable data. 

Remember, the work of the data scientist is to conceptualize your B2B business objectives into data. B2B business owners together with other stakeholders have to consider how the data gives them an advantage. You should also consider how speed, scale, and scope through acquisitions can help you achieve an effective data architecture strategy.    

Proprietary Algorithms

As the amount of user data continues accumulating, it is becoming increasingly challenging for companies to perform various forms of analysis independently. B2B business leaders now prefer to use third-party algorithms to perform diagnostic analysis, descriptive analysis, prescriptive analysis, and predictive analysis.  

An easy way to develop your data architecture is by using existing architecture to evolve your model. Proprietary algorithms can analyze data at rest as well as real-time data in motion. You should regularly benchmark the algorithms against what competitors are using and others in the same class. 

Generate Trust

Managing the data of users within your company is always a massive responsibility. Most users are wary of technology, with some believing their data is used to make some companies powerful and profitable. 

When developing a data architecture, you must develop it to engender trust. Your business has to earn the right to collect, analyze, and deliver custom ads through data. New EU internet laws require every website to outline how you tend to utilize user data. Additionally, the user has to agree to your data privacy terms for your company to use their data. 

Update Company Infrastructure

As a B2B business owner, you have to be ready to allocate sufficient resources to upgrade the technology infrastructure behind the data architecture project. This includes recruiting talent with the breadth and depth to deliver your data and business goals. 

In this modern age, data organization needs to be the backbone that holds your entire company together. Despite the significant benefits of data to business, some don't appreciate the concept and, you have to find the perfect balance. These conflicts form the foundation of how your company will interact with user data. 

Monetize Data Graphs

Data architecture offers you insights on how to address specific issues facing your B2B clients and general market. Information from data graphs helps you select the perfect monetization model and defines the connection between the data and business results.

You can retain your current monetization mechanisms based on recommendations from real-time data network effects. You can also use the same recommendations to counter what competitors are doing in the market. 

Need Some Help Getting an Edge Over Competitors?

Implementing a data architecture model will surely give you the edge you are looking for over your competitors. But as a leader, it can be challenging to implement the entire process on your own, especially with regard to time. 

FitzMartin is a sales and marketing consultancy company that borrows from the science of behavioral change. Our primary focus is to help clients like B2B leaders to drive new profitability and growth. We'd love to share some ideas to help you get started -- no string attached:

 

 

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