When it comes to CRM systems, companies can choose to process customer data in real time or batches. As a marketer, it’s important to understand the differences between real-time and batch CRM data and how each can be used effectively.
This article tackles what real-time and batch CRM processing looks like, along with key benefits and strategies for leveraging each approach in your marketing campaigns.
Real-time vs. batch-based CRM data processing: How do they differ?
Your involvement in choosing the CRM system’s data processing approach may be limited, but it significantly affects your work.
Real-time means the martech stack, including the CRM platform being used, can collect customer data in real-time and you can use such data in real-time for customer messaging and activations.
On the other hand, batch processes collect customer data over time (i.e., over one day, one week, one year), ingest data points and unify them under customer profiles. Afterward, you can leverage them in your campaigns.
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How CRM data processing influences marketing campaigns
Real-time CRM data activations
This approach involves using the latest customer information and promptly responding to it, especially in terms of customer behavior. It’s ideal for companies that need to swiftly address actions like abandoned shopping carts or customize website content based on recent customer navigation. It is also beneficial for online customer care teams.
To support real-time CRM use cases, you should have an ongoing, relevant stream of behavior data through your digital properties (i.e., websites, apps, ecommerce purchases, email communication, etc.) that can also be leveraged to communicate with customers in real-time.
You also need content that aligns with the current customer behavior you’re monitoring. It’s crucial toto avoid having real-time customer data but stale content.
For instance, in ecommerce, you can create (and test) the cart abandonment messages and work closely with the customer care team to prepare messages and understand questions customers may have about products or services.
Batch-based CRM data
When it comes to batch-based CRM data, you can leverage both the latest behavior and customer self-reported attributes (i.e., name, address, preferences, occupation, company name, and interests) instead of focusing and reacting mostly on the latest customer behavior.
Depending on your martech stack and data operations practices, you may even be able to use historical data for CRM activities. Think of B2B companies with long buying cycles and complex sales processes that can take months and involve multiple people.
For these companies, having a more detailed picture of these customers (or prospects) may be more relevant than just having the last customer behavior.
Consider which customer data points will be used for CRM and activation purposes and which channel. Will it use self-reported customer data such as name, occupation, and the latest email marketing? Maybe some CRM channels will use some customer self-reported data (name and interests), while others may use past customer behavior or a mix of both (name and website pages visited in the last week).
Combining real-time and batch-based processing of customer data
Many companies use a combination of real-time and batch processes for handling customer data in their CRM systems. This approach helps them prioritize recent customer behavior for tasks like online customer support. Simultaneously, they can utilize a more comprehensive view of the customer for other CRM activities requiring a detailed understanding of their profile.
Unlocking the potential of real-time and batch-based CRM data
If you are unsure how customer data is being collected and prepared to be used throughout activations and campaigns, reach out to your technical / data teams to get a better picture. When/if you are already familiar with this, the next step is to determine how each type of customer data (and how this data can be used) fits into the CRM / customer activation strategy.
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Customer Relationship Management (CRM) systems are essential tools for businesses to manage their interactions with customers and potential customers. These systems help businesses to track customer data, sales, and marketing efforts, and provide insights into customer behavior. CRM systems can process data in two ways: real-time and batch-based. Both methods have their advantages and disadvantages, and it is important for businesses to understand the differences between the two to make an informed decision on which method to use.
Real-time CRM data processing involves processing data as soon as it is received. This means that as soon as a customer interacts with a business, whether it be through a purchase, a website visit, or a phone call, the data is immediately processed and updated in the CRM system. This allows businesses to have up-to-date information on their customers at all times, which can be useful for making quick decisions and providing immediate customer service.
One of the main advantages of real-time CRM data processing is that it allows businesses to respond quickly to customer needs and inquiries. For example, if a customer makes a purchase on a website, the business can immediately send a confirmation email and update the customer’s purchase history in the CRM system. This can lead to increased customer satisfaction and loyalty.
However, real-time CRM data processing can also be more expensive and resource-intensive than batch-based processing. It requires more powerful hardware and software to handle the constant flow of data, and it can also require more staff to manage the system.
Batch-based CRM data processing, on the other hand, involves processing data in batches at set intervals. This means that data is collected over a period of time and then processed all at once. This method can be less expensive and require fewer resources than real-time processing, as it does not require constant monitoring and updating.
One of the main advantages of batch-based CRM data processing is that it allows businesses to process large amounts of data at once, which can be useful for analyzing trends and patterns in customer behavior. It can also be more efficient for businesses that do not require immediate updates on customer data.
However, batch-based CRM data processing can also lead to delays in updating customer information, which can be a disadvantage for businesses that need up-to-date information for decision-making or customer service. It can also lead to missed opportunities for immediate engagement with customers.
In conclusion, both real-time and batch-based CRM data processing have their advantages and disadvantages. Businesses need to consider factors such as cost, resource availability, and the need for immediate updates when deciding which method to use. It is important for businesses to carefully evaluate their needs and choose the method that best suits their operations and goals.
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