This account is pending registration confirmation. Please click on the link within the confirmation email previously sent you to complete registration. Need a new registration confirmation email? Click here
Splunk Inc. (NASDAQ:SPLK), provider of the leading software platform for real-time operational intelligence, today announced that Domino’s Pizza is using Splunk
® Enterprise to help the pizza chain strengthen its online business through new levels of customer interaction and understanding. Domino’s originally selected Splunk Enterprise to resolve IT issues by collecting, indexing and monitoring machine data and reports upfront savings of more than $300,000 by replacing legacy technology. This initial investment in Splunk quickly led Domino’s to expand its use across the organization, leading to revenue insights in both business and marketing through online sales data collected across its entire corporate and franchise network of more than 10,000 stores. To learn more about the transformation, watch the
Domino’s video case study.
“In business and marketing, we have just begun scratching the surface of how we can use Splunk Enterprise to make better decisions. Comparing coupons, for example, already has vastly improved the effectiveness of those campaigns,” said Russell Turner, manager of site reliability engineering, Domino’s. “Splunk software cut our mean time to resolution from hours or days to minutes and seconds, which frees up our IT and engineering teams to spend more time dreaming up new ways to use Splunk. In fact, if we unleashed all the business insights we now have access to with Splunk, we would be inundated with company requests for information. It really is our secret sauce.”
Using Splunk Enterprise, Domino’s IT teams routinely resolve issues including quickly identifying and fixing network bandwidth and latency, Internet connection or payment processing issues across stores. Beyond traditional IT operations, Domino’s uses Splunk Enterprise to visualize business sales trends across geographical locations such as orders per minute, numbers of transactions per store, what types of pizza and other food items customers order and what coupons they may be using to do so.