While many companies and organizations have used Splunk for operational efficiency, in this blog post I will talk about how Domino’s Pizza used Splunk to formulate their business strategies based on consumer behavior insights and cut down their costs to a great extent. This Splunk use case proves how Splunk can be used extensively in any domain. This Splunk case study is also ideal for beginners to understand how Splunk works in real-life use cases.
Splunk Use Case: Domino’s
What you all know is Domino’s Pizza is an e-commerce cum fast food giant, but what you don’t know is how Splunk helped them establish their status as one of the best in the world.
Domino’s Pizza had an omni-channel presence – this meant a huge customer base with several touch points for customer service. Domino’s provided all possible types of possible services allowing customers to order food in-store, order via telephone, via their website and through cross-platform mobile applications. The company also introduced a lot of interesting and innovative tools for customers, some of which include voice ordering through the mobile apps and the popular pizza tracker. All of this resulted in explosion of data which needed to be managed and analyzed.
Up until implementing Splunk, managing the company’s application and platform data was a headache, with much of its log files in a ‘giant mess’ – according to their Site Reliability & Engineering Manager, Russell Turner. He said using Splunk for Operational Intelligence in place of a traditional APM tool helped him not only to lower cost, but also to search data faster, monitor performance and to get better insights into how customers were interacting with Dominos. Implementing Splunk, helped them setup the following:
- Interactive Maps, for showing all orders coming from across US in real time which helped bring employee satisfaction and motivation
- Real time feedback, for employees to constantly see what customers are saying and understand their expectations
- Dashboard, used to keep scores and set targets, compare their performance with previous weeks/ months and against other stores
- Payment Process, for analyzing the speeds of different payment modes and identifying error free payment modes
- Promotional Support, for identifying how various promotional offers are impacting in real-time. Before implementing Splunk, the same task used to take an entire day
- Performance Monitoring, to monitor the performance of Domino’s in-house developed point of sales systems
Splunk proved to be so beneficial that it’s use was not limited just to the IT department. Many other teams wanted to use the tool to get insights out of their.
Splunk For Promotional Data Insights
While the afore mentioned functionalities were setup by Domino’s Pizza with the help of Splunk, I am going to present to you a hypothetical Splunk use case scenario which shows how Domino’s Pizza used Promotional data to get better clarity as to which offers/coupons works best with respect to different regions, order revenue sizes and other variables.
*Note: The example of Promotional data used is representative in nature and data present might not be accurate.
Domino’s had no clear visibility into which offer works best – in terms of:
- Offer type (Whether their customers preferred a 10% discount or a flat $2 discount?)
- Cultural differences at a regional level (Do cultural differences play a role in offer choice?)
- Device used for buying products (Do devices used for ordering play a role in offer choices?)
- Time of Purchase (What is the best time for the order to be live?)
- Order revenue (Will offer response change wrt to order revenue size?)
Domino’s Pizza collected data from several outlets across the world and analyzed the data using Splunk. Each outlet sent the promotional data which was generated in real time. The data contained information on customer response when they were given offers along with the other fields like demographics, timestamp, order revenue size, device used. Customers were divided into two sets for A/B Testing. Each set was given a different offer: 10% discount offer and flat $2 offer. Their response was analyzed to determine which offer was preferred by the customers. The data also contained the time when customers responded and if they would prefer to buy in-store or do they prefer to order online. If they did it online, then the device they used to make the purchase was also included. Most importantly, it contained Order revenue data – to understand if offer response changes with the order revenue size. All this data was used to find useful insights.
Once the raw data was forwarded, Splunk was configured to extract only the relevant information. Relevant information was which group of customers preferred $2 offer and which group of customers preferred a 10% discount, time at which they got immediate response from customers, device used by customers for redeeming the coupons/offers were among the other relevant information which Splunk extracted. Once all the relevant data was extracted, it was stored locally in a Splunk instance. Typically, the below information was stored:
- Order revenue based on customer response
- Time of purchase of products
- Device preferred by customers for placing the order
- Coupons / Offers used
- Sales numbers based on Geography
Based on the data stored in Splunk, the following were the insights that were gained:
- Which offer works best in which geography? Is there any cultural impact on offer usage?
- How does the customer behavior change w.r.t changes in order revenue? Do customer devices have an impact on response to offers?
- What time of the day is most appropriate for the offers? Do they prefer 10% discount compared to $2 off for a higher revenue order?
To analyze and visualize the data, Splunk’s built-in dashboards were used. The below graphs offer a similar representation of the kind of visualization offered by Splunk.
There are several other Splunk use cases where companies have benefitted and grown their business, increased their productivity and security.
Do you plan to grow your business productivity with Splunk? Check out our Splunk certification training here, that comes with instructor-led live training and real-life project experience.
Now, that you have understood how Splunk works with the help of Domino’s use-case, our next blog on Splunk architecture will help you understand it better – Coming Soon!