Metrics
Why do we need the feature METRIC?
What is a Metric?
A quantitative measurement of your data. Metrics in Analytics can be sums, ratios etc.
Metrics are individual elements of a dimension that can be measured as a sum or a ratio. For example, the dimension Total Population can be associated with a metric like Population, which would have a sum value of all the residents of the specific city.
Metrics comprise the logic of your incentive campaigns - on Compass, it’s a GUI based rule builder palette with standard and advanced mathematical and logical functions that enable you to break down, design and customize your most complex structures and campaigns.
Linear Metric - A metric which takes a single input value and then transforms it on the basis of a linear function and stores it.
Aggregate Metric - The process of taking multiple input values and then using them to produce a single output via the rules defined by the aggregation type. For example, taking an average of multiple values.
On compass, we have AVERAGE, SUM, and COUNT functions as aggregate functions.
Why do we need the feature METRIC?
Every report in Analytics is made up of dimensions and metrics. Metric is the building block for any Program that we configure on Compass.
Let us consider a simple example to understand the relevance of metrics and how and where they need to be used:
Incentive Structure | |
Slab | Flat Incentive |
Ach % < 50% | $1,000 |
Ach % < 75% | $2,000 |
Ach % < 100% | $3,000 |
Ach % >= 100% | $5,000 |
Dimensions (Name of Metric) are attributes of your data. For example, the dimension City indicates the city, for example, "Paris" or "New York", from which a session originates.
Metrics are quantitative measurements. The metric Sessions is the total number of sessions. The metric Pages/Session is the average number of pages viewed per session.
The tables in most Analytics reports organize dimension values into rows, and metrics into columns. For example, this table shows one dimension (City) and two metrics (Sessions and Pages/Session).
DIMENSION | METRIC | METRIC |
City | Sessions | Pages/Session |
San Francisco | 5,000 | 3.74 |
Berlin | 4,000 | 4.55 |
In our system below is the way of representation.
Using the Feature
Metrics are parameters, based on which participants are evaluated and are rewarded incentives.
To access this feature, click on the ‘Metric’ in the admin main menu on the left side of the home page.
New metrics can be created using the option "Create a Metric" present on the top right corner of the screen.
Details such as name of the metric, connection of the metric (to any program) and condition has to be entered.
Select a connection (any program/Table/Metric) to add conditions.
Under conditions, admin has to enter field, function, metric and static data to create a condition for the particular metric.
Like under Field, we can select the output of connection (Milestone-Reward/Score) or Headers of a Table which comes from the connection we select.
Also, we can include functions to define the criteria. Under function, we have Logical functions, Mathematical functions and Operators.
Further, an aggregate function performs a calculation on multiple values and returns a single value. Compass provides many aggregate functions that include avg, count, sum, min, max, etc. An aggregate function ignores NULL values when it performs the calculation, except for the count function
The GROUP BY function in Compass is used to group rows that have the same values. Optionally it is used in conjunction with aggregate functions to produce summary reports from the data. WHERE is used to extract only those records that fulfill a specified condition.
The AND operator displays a record if all the conditions separated by AND are TRUE.The OR operator displays a record if any of the conditions separated by OR is TRUE.
Under metric dropdown, we can see and use all the other relevant metrics that are already created using the same connection.
If there is a requirement to include any numerical value in calculation, for that we can use STATIC where the required numerical value is added and submitted.
Once completed, click on "Save" to complete the creation of the metric.
Later if we need to make changes in metric that is also possible.
On clicking the 3 dots, we get Edit, Clone, Disable & Delete options. The metric already in use in any Program must not be Edited, Disabled or Delete, as it can affect program outcome.
Example Use Case
Here is an example on how to create a metric. After clicking CREATE A METRIC tab, enter the name of metric (say) Test 2.
Now we can select a Connection (say) User Disb Target. This is a table we have created using User table, Disbursement Table and Target Table.
As a result, under field dropdown we can use the data present across all 3 tables. As per the requirement, we can use aggregate function, Logical function or Operator.
Under metric dropdown, we can see the Sum Processing Charge metric that will be used in the final expression and is written using the same connection User Disb Target. Below is an example for better understanding.
All the metrics that are created using User Disb Target Table as connection, are present under Metric Dropdown.
For the above expression we also need to include 100 as numerical value in calculation, for that we can use STATIC where the required numerical value is added and submitted.
UI Elements
Below screenshot shows the landing page of Metric.
The main UI elements are as follows:
Name - name of the metric created
Expression- Logic/formulae used for that metric.
Other UI elements include:
Rows per page - Dropdown to select number of metrics to be displayed from the option 10, 25, 50, 100 for pagination at the bottom right, element 1
Arrows - To navigate to next or previous page, grayed out based on the current page the user in on (first/last) at the bottom right, element 2
Search - Magnifying glass icon where user/admin who made the metric can be searched for, returning all corresponding metric made by the user at the top right, element 1
METRIC DETAILS
On clicking on any of the metrics you can find all the details of the Metric. It includes Metric name, Connection, Expression and its status (active/inactive)
Under metric details, we have the option to cancel (exit) and update the metric.
Feature Details
Name | Metric |
Description | This feature helps admin to create expressions/logics that are used in program creation on Compass |
Vision | Used to set up Logics for Compass Programs |
Goals | Enable end users to be able to create a valid Logic/Formula |
Personas | Admin |
Not doing | NA |
Acceptance criteria | 1. The expression logic should be valid, like using SUM function for a numeric value etc. 2. Number of characters in metric name should lie between 5 to 30 |
Analytics
How long it takes for people to interact with the feature for the first time, measure of ease of use and adaptability
Fairly simple to understand, complexity depends on the expression the user is trying to create.
How often feature is being used
Critical feature, hence used frequently
How long users spend interacting with the feature
Depends on the requirement of different Logics/ formulas we want to include in program creation.
Abandonment rate
Should be 0 as long as you have the required data.
Future work
Update the "Not equal to" function to take blanks into account
Inclusion of dynamic date functions like TODAY() to calculate KPI achievement in last x days/months, etc.
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