Kibana - Ask the Questions and Get Your Index

While diving right in and clicking and dragging fields around can get some quick results, we find the best practice is to stop and get a few answers before even starting the report. These answers will be consistent across all reports and having these answers before starting will save you a number of 'false starts'. In fact, if you contact our support team and ask for help with a report, these are the same questions we will ask you before jumping in to assist. 

Note: Yes, our support team is trained on how to write Kibana Reports so they can be a great resource for getting a report out that matches your needs - or if you just have a question, toss the question up on our Kibana User Community board.

So back to those questions. 

1. Data - What data elements are you wanting to see? (ex: order details, memberships, ticket sales, etc)
2. Timing - What will the date filters I use impact?  (ex: do I want to see tickets sold this week, or do I want to see tickets sold FOR events this week?)
3. Visualize - How do you want to visualize the data? (ex: is my data best presented in a chart? a single metric number, or standard cross tab view?)

Having the answers to these questions will ensure that you select the proper visualization to start, as well as the proper index from which to pull your data.

Know Your Index

Data within Kibana is organized into various indexes, which can be thought of as a collection of related fields that are aggregated together for improved performance. One of these indexes will serve as the foundation for each visualization that you build so it is important to understand the data that is stored in each and how they are arranged. Let's have a quick look at the available indexes and when you may use them - with the most commonly used indexes at the top.

Transaction-by Indexes

The Transaction by Occurrence and Transaction by Session Indexes are probably the 2 most popular indexes leveraged. These indexes are where you can report on ANY action, not just sales within the system. Whether it be looking for the total sales for a period of time or the number of people who redeemed their tickets for a particular session, we would have to estimate that ~90% of reports we create for customers come from these 2 indexes.

The fields within each of the indexes are basically the same, so the differences in the indexes come down to the date range that the report will be filtered by. 

• Transaction By Session - You want to know what happened for a particular session. Ex: Show me the sales for events/sessions this week. 
• Transaction By Occurrence - You want to know what happened for a particular time period. Ex: Show me my sales for this week - regardless of when the event/session is.

Membership by Indexes

The Membership By Purchased and Membership By Expiry are similar to the Transaction By indexes, but the data contained within the Indexes is geared more towards reporting on Members and Memberships. Just like the Transaction By indexes, these indexes will store everything about a Membership, from purchases to renewals, and provide a full timeline of the member's actions.

• Membership by Expiry - You will want to know what happened with memberships based on their expiry/expiration date. Ex: give me a list of all members who are expiring in the next 3 months but are not enrolled in Auto-Renew.
• Membership by Purchase - You want to know what happened with memberships over a given time period. Ex: Show me all the memberships purchased/renewed during Black Friday.

Inventory

The inventory index is great for analyzing the overall inventory of your sessions/time slots. You are worried less about the details of who is coming and when did they buy their tickets and more about what is available to be purchased, how many people have scanned in, etc. 

Cart

The center of any transaction in Ticketure. is the Cart. This index allows you to view the cart and determine things like 'unbalanced' carts - or carts that have more/less inventory in them than payments. From this index, we have provided reports like the Aging Reports or Overpaid and Underpaid by Visit Date reports. The cart index (as well as Transaction By indexes) contains the Campaign details that are being tracked for conversions.

Discount

The Discount Index is a very useful index for performing analysis of coupon redemption, usage, original amounts, and amount of discounts given, etc. Grouping discounts by code group and even down to the exact code used allows for detailed data segmentation for discounts.

Ticket

This Index is similar to Transaction by Session in that the date filters are related to the Session date of the event. This index isn't used as often as one would think given the capabilities/similarities to the Transaction by Session index but can be useful for looking for a ticket's status or for pulling a list of scan codes (barcodes) for a particular list/run of tickets.

Identity

Not used often is the Identity Index. The basis of this index is mostly for audit reasons but contains only the name, email address, membership code, and role of the identity/Customer within Ticketure. In addition to customers, this index also stores basic information about Organizations. This index would only be useful if you are pulling a list of Customers and wanted to include those Customers who had NOT completed a transaction. Otherwise, we would suggest using the Transaction_By indexes as they will provide the additional data requested.

Trail

The Trail Index is short for the 'audit trail' index. This index tracks every API call within the system allowing our development team to analyze a series of API calls to help determine the cause of an issue, or provide an answer to the age old question of 'Who made this change and when did they make it?'. As with the Identity index, this one isn't typically used by Customers.

Next Step

Now that you have context into Indexes and how data is structured/stored, the next step in your Kibana journey is to put these indexes into Visualizations and start seeing some of the data come together.

Let's build a Visualization!