More and more businesses are looking to better leverage their outsourced call center data to make more data-driven decisions. To do this on your own, you would need to create a data warehouse, optimize the reporting performance, and very clearly visualize the data.
Or, all of this could be done – in a more simple and efficient manner – with the help of the Snowflake Data Cloud.
In this blog, we’ll cover why Snowflake is the best option for optimizing the usage of outsourced call center data, go over a few of Snowflake’s most powerful features for call centers, and share a few best practices.
How Does Snowflake Help with Call Centers?
Many organizations in the call center industry work with massive loads of data. Historically, they rely on heavyweight enterprise data warehouse platforms with limited ability to capitalize on their data. In a sense, they’re using old technology to solve today’s business challenges.
Snowflake is a cloud-based data warehousing platform that can help call centers in several ways.
First, Snowflake allows call center managers to easily store and analyze large amounts of data, such as call logs and customer information, in a centralized location. This can help them identify trends and patterns in customer behavior, and make more informed decisions about how to improve their operations.
Second, Snowflake’s flexible architecture makes it easy to integrate with other tools and systems, such as customer relationship management (CRM) software, allowing call center agents to access the information they need quickly and easily.
Third, Snowflake is not only a place to store data but also a computational powerhouse that can help recognize repeat callers and their historical activity. It also processes and gives you additional information to store in real time without compromising any performance.
Finally, Snowflake’s scalable infrastructure can support high levels of concurrency, ensuring that call centers can handle large volumes of data and users without performance degradation.
Overall, Snowflake can help call centers improve their efficiency and effectiveness, and better serve their customers.
Why is Snowflake the Best Data Platform for Call Centers?
With Snowflake, call center managers can easily access, store, and analyze customer data in real time, which can help improve the efficiency and effectiveness of their operations.
Additionally, Snowflake’s scalable architecture means that it can easily grow with a call center as its data needs increase, which can save time and resources in the long run. Overall, Snowflake’s combination of powerful features and ease of use make it an excellent choice for call centers looking to improve their data management and analysis capabilities.
Speaking of powerful features, let’s investigate two of Snowflake’s most powerful features for call center operations; Snowpipe & Data Sharing.
Snowpipe for Data Ingestion
Snowpipe is a feature of Snowflake that helps with continuously ingesting data. Snowpipe usually loads the desired data in a matter of minutes after the files are added to the stage and submitted to ingest.
Snowpipe’s new compute model is serverless and can manage a larger load capacity. This provides an adequate “pipeline” to load a lot of fresh data in the form of micro-batches.
With Snowpipe’s feature of automated data loading, it also leverages event notification for the purpose of cloud storage. This functionality also informs Snowpipe of the arrival of the new data for loading. Snowpipe enables copying these files into a long queue. From there, the data are loaded to the target table in a serverless and continuous fashion based on certain pre-set parameters.
Automated Snowpipe utilizes the event notifications for determining the time of arrival of the new files in the cloud storage that is being monitored. The notifications help identify the event in the cloud storage and usually include a list of file names. These do not contain the actual data that are in those files.
When the Snowpipe is paused, those event messages received for the pipe usually enter a retention period of a limited time. This limited time period is fourteen days and is set as default if a pipe is paused for an interval longer than 14 days, which is considered stale.
Secure Data Sharing for Reverse ETL
Reverse ETL/data sharing is one of the emerging pieces of the modern data stack that enable users to use analytics effectively and make it more productive. With the help of Reverse ETL, every data warehouse becomes a major source of information instead of just a destination.
The data is extracted from the warehouse, then transformed optimally to match the data formatting needs of the destination, and finally loaded into the desired visualization application. This feature helps to send concise and accurate data to the stakeholders in simplistic terms and figures. Another way to think of it is as Data Activation.
Reverse ETL helps operationalize data in an organization by putting the data back into the business applications. A Reverse ETL is useful in replacing the ELT or ETL data pipelines. This is instead being used in conjunction with the data stack and Snowflake makes it very easy to store data and then send it out via its various connectors and features to the visualization applications.
Taking data out of Snowflake is as easy as bringing data into it and this is where Snowflake is years ahead of its competitors. It will not just solve your current problems but will also be a step ahead ready to solve future issues through updates intended to address current trends.
To summarize, Snowflake might just be the solution you have been looking for. At phData, we’ve helped a number of clients achieve analytics excellence with the power of Snowflake. Recently, we helped a major bank save $425,000 annually by automating call center insights.
If you’re interested in harnessing data (and Snowflake) to do more with less in your call center, explore phData’s call center analytics services today!