As marketing service providers (MSPs), you understand the power of real-time data – for generating better insights, for delivering personalized experiences, and for maintaining an edge in a fast-moving technology landscape.   However, effectively harnessing data in real time is no small feat. Before MSPs can use real-time data to drive powerful marketing action on behalf of their brand clients, they must first overcome numerous complexities, from data processing challenges to regulatory compliance. 

Continue reading to learn how to collect, process, and design a data infrastructure capable of actioning data in real time. 



Challenges of Real-Time Data Processing

There are significant challenges and complexities associated with processing data in real time. MSPs must prepare to manage complex data sets with low latency while maintaining quality and consistency. 

Low Latency  

Low latency is a significant hurdle in real-time data processing. Even milliseconds of delay can mean the difference between a personalized experience and a missed opportunity. Ensuring low latency requires robust infrastructure and optimized data pipelines to minimize lag between data ingestion and insight generation.

Quality and Consistency

Data quality and consistency are equally critical challenges. Inaccurate or incomplete data can lead to flawed customer profiles, undermining your clients’ personalization efforts. Implementing robust data governance processes and real-time data validation mechanisms is essential to maintain data integrity.


Managing the complexity of batch and streaming data simultaneously is another hurdle. While batch data provides historical context, streaming data is necessary for real-time insights. Integrating these data sources seamlessly and deriving meaningful insights is a significant technical challenge.


Balancing Volume and Velocity

Effective applications of real-time data hinge on finding the right balance between data volume and velocity. While data volume is crucial for building comprehensive customer profiles, velocity is the key to acting on insights in real time. Too much emphasis on volume can lead to sluggish response times, while prioritizing velocity alone may result in an incomplete or inaccurate picture.

As a service provider, you must help your clients strike this balance by understanding their specific use cases and requirements. For some clients, velocity may take precedence for time-sensitive actions, while others may prioritize volume for more comprehensive personalization strategies.


Requirements for Successful Real-Time Data Processing

Robust infrastructure is a fundamental requirement for successful real-time data processing. This includes scalable and reliable data ingestion, processing, and storage systems capable of handling high-velocity data streams without compromising performance or data integrity.

Implementing comprehensive data quality and governance practices is equally crucial. These practices should encompass data validation, cleansing, standardization, and deduplication processes to ensure data consistency and accuracy across all touchpoints.

The importance of data privacy and consent is also a key concern with real-time data capture. From state-based privacy laws in the US to regional regulations like GDPR in Europe, the standards for data privacy are ever-evolving. When developing real-time data processing mechanisms, it’s important to build with a privacy-first mindset, especially when dealing with cross-border compliance. 

Investing in the right technologies is also essential. Real-time stream processing engines, in-memory databases, and advanced analytics platforms are necessary to extract insights from data in motion and enable real-time decisioning. Marketing service providers should seek a cost-effective balance between necessary features and elastic demand to maximize their investments without suffering from performance issues. Consider low-latency, high-throughput OLTP infrastructure options such as AWS Dynamo DB, Aerospike, or Azure Cosmos DB, along with Aqfer IO to handle the data layer for your real-time personalization needs.


From Insight to Action

Now to the good (sellable) stuff. Once MSPs understand how to process data in real time, the applications of that capability are endless. From insights generation to powering personalized marketing experiences, MSPs who can act on real-time data will maintain the market advantage with their brand customers.

The importance of perfecting the mechanisms for real-time data processing can’t be understated – that’s where Aqfer comes in. As a leading provider of data solutions, Aqfer understands the intricate challenges of real-time data. Our expertise spans from building robust data infrastructure to implementing advanced analytics and governance practices. We can help you power the data layer and infrastructure required to enable your clients’ most challenging marketing use cases. Click here to learn about our solutions.