--- title: 'Rock Your CRM Integration: Understanding Data Architecture in CRMs' url: 'https://www.staging38.commercient.com/rock-your-crm-integration-understanding-data-architecture-in-crms/' date: '2025-05-13T12:04:04-04:00' modified: '2026-07-02T13:30:42-04:00' author: 'Beth Walls' excerpt: 'Data architecture—how CRM data is organized into standard, custom, and managed objects—should inform CRM buying decisions, since it determines how well ERP data integrates and flows across systems.' categories: - 'AI Integration' - 'CRM ERP Integration' tags: - AI - crm - 'data architecture' - 'data integration' - erp - sales featured_image: 'https://www.staging38.commercient.com/wp-content/uploads/2025/04/Understanding-Data-Architecture-in-CRMs-blog.jpg' language: en-US post_type: post --- Buying a new CRM can feel daunting. There are the obvious differences to consider, like price and core features, but there are also less obvious differences that can aid in your decision. One of those is data architecture. ## **What is Data Architecture?** Let’s start with the basics. What exactly is **data architecture**? Think of it as the **blueprint** for how data is organized, stored, and flows through your systems. Just like a building needs a solid structure to function properly, your data needs a well-organized structure to ensure it’s secure, easily accessible, and connected across systems. Data architecture covers a lot of ground. It includes naming conventions, data relationships, and structure—deciding what data should be connected, which should be kept separate, and how everything communicates. A well-structured data architecture ensures that the right people have access to the right data at the right time. On the flip side, bad data architecture is like a house with no lights, unfinished plumbing, and wires running everywhere—chaotic and inefficient. ## **Why Data Architecture Matters** When you start working with multiple systems—especially when it comes to CRMs and ERPs—data architecture becomes critical. Without a strong architecture, you risk creating **data silos**—isolated pockets of information that can’t communicate with each other. This leads to inefficiencies and hinders innovation. A well-structured data architecture enhances **flexibility** and **adaptability**, which is crucial as your business grows. ## **Data Architecture in CRMs** Now, let’s talk about how data architecture applies to **CRM** systems. CRMs are at the heart of most businesses, and understanding how CRM data is structured is key to maximizing your platform’s value. There are **two broad categories** of CRM data architecture: **personalized** and **customized**. ### **Personalized CRMs** CRMs like **HubSpot** and **PipeDrive** fall into the **personalized** category. These CRMs give you the ability to tweak and personalize templates to match your business needs without needing to start from scratch. They offer flexibility without overwhelming you with complexity. For example, HubSpot offers users the ability to create custom properties. If your needs are simple—like adding a few extra data points—personalized CRMs can be a great choice because they’re straightforward to set up and maintain. You get to tailor your CRM to fit your business without having to dive into deep customization. ### **Customized CRMs** On the other hand, **customized CRMs** like **Salesforce** and **Zoho** allow for more **extensive customization**. With these platforms, you can build data structures from the ground up—creating custom objects, fields, and relationships to fit your specific business needs. You have total freedom to design your CRM just how you like it. However, this freedom comes at a price. The more you customize, the more time and resources you’ll need to invest. Customization can be complex and time-consuming, and it often means sacrificing out-of-the-box workflows and automation. Plus, with extreme customization, ongoing **maintenance** can become costly and difficult to manage. ## **CRM Objects and How They Work** CRMs use **objects** to organize data. Think of an object like a table in a spreadsheet, with **rows** (records, such as “John Smith” or “Ana Johnson”) and **columns** (fields like name, email, phone number, etc.). It’s critical that objects can **communicate with one another**. For instance, you want your **Accounts** object to be linked to your **Contacts** object, or your **Deals** object to be connected to **Products**. It’s not just about storing data; it’s about facilitating the **flow of information** between related data points to create a more comprehensive view of your business. ### **Standard, Custom, and Managed Objects** When you’re working with CRMs, you’ll come across three types of objects: **standard**, **custom**, and **managed**. - **Standard Objects**: These come pre-built with your CRM. Examples include **Accounts**, **Contacts**, and **Deals**. You don’t need to do anything to use them—they’re ready to go. - **Custom Objects**: These are objects you create yourself to capture data that doesn’t fit into the standard objects. For instance, you might create a custom object to track a specific part of your sales process. But, custom objects require more ongoing maintenance and customization, so be careful before you go down this path. - **Managed Objects**: These objects come from third-party apps, like **Commercient**, and provide additional functionality. These objects help integrate your ERP data into your CRM without you having to build everything yourself. Managed objects can make your life easier by simplifying integrations and adding new features without all the hassle of doing it yourself. ## **Commercient’s Role in Data Architecture** At **Commercient**, we specialize in syncing **ERP data** into CRMs. As you can imagine, ERP data doesn’t always fit into the standard CRM structure. So, we work within the data architecture of the CRM to make sure the data fits properly. For instance, **ERP Accounts** sync into **CRM Company/Account**, and **ERP Products** sync into **CRM Products**. But what about other types of data, like **inventory** or **invoices**? These types of data don’t always fit neatly into a standard CRM object. In these cases, we use **custom fields** or **properties** to fit the data into the closest matching object, like associating inventory data with products. If the CRM allows for **customization**, we may create **managed objects** to handle more complex data structures. This ensures the data is organized properly while minimizing the need for excessive customization. ## **CRM Integration Workflow** When integrating your CRM with other systems, especially ERPs, it’s essential to **think about your workflows**. The goal isn’t to make two systems do the same thing—each system should focus on what it does best. For example, when a **lead** comes in, your CRM is the best place to track it. CRMs are designed for managing leads, tracking activities, and handling customer relationships. However, when it comes time to **quote** that prospect, you’ll want to pull product, inventory, and price data from your ERP—because your ERP is the source of truth for that data. Once the deal is closed, the data about that customer and their purchase moves from the CRM into the ERP to handle order fulfillment, invoicing, and payment processing. But the CRM doesn’t stop there—it continues to track the customer long-term, using the ERP data to monitor credit limits, unpaid invoices, and order statuses, all in one place. At **Commercient**, we see this workflow in about **95% of our integrations**. The key is to sync the right data between the CRM and ERP, while making sure the **data integrity** and **consistency** are maintained and aligned with the data architecture of the integrated platforms. ## **What Do You Need to Know About Data Architecture?** To wrap things up, here’s what you should keep in mind when thinking about data architecture for CRM and ERP integration: 1. **Understand your CRM’s capabilities** – Different CRMs are architected differently, and each has strengths. Choose the one that fits your business needs. 2. **Use custom objects sparingly** – Only create custom objects when necessary. Too many custom objects can increase complexity and maintenance costs. 3. **Define your source of truth** – Not all data should sync bidirectionally. It’s important to know where each type of data should live and how it should flow between systems. And remember, with **Commercient**, we’ve built a **pre-configured data architecture** that prioritizes standard objects and uses custom objects only when absolutely necessary. This ensures that data integrity is maintained, while also making your integration process easier and more efficient.