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# Health Score Calculations

## Composition of the Health score

There are 2 factors that contribute to the overall score for an account.
Normalised score - This is a score that is calculated from the normalised metrics multiplied by the weightage assigned to each metric. Intuitively, this score calculates the magnitude of the usage based on the size of the company. (70% contribution to the overall score)
Consistency score - This measures the increase or the decrease (over a duration of 3 months) of each metric that contributes to the score for that account multiplied by the weightage of that metric. (30% contribution to the overall score)

## Normalised Score

In order to measure if the usage by an account is good or bad we would need to benchmark it against the usage of all other accounts. For example, if there’s an account that creates 20 contracts in a month, is that account doing well?
The way we gauge this is whether the account is getting the value or ROI for the amount they are paying. ARR, licenses purchased or contracts (documents) purchased are all possible normalisation factors. Thus for different pricing packages, we consider the following different normalisation factors
#
Templates + Users
Users
Volume based
1
Normalisation factor
Contracts purchased
There are no rows in this table
Based on the the normalisation factor of an account, the usage metrics for that account will be divided by that normalisation factor and then compared with the median normalised value of that metric across accounts with the same normalization factor.
For example, for an account lies in the “Templates + Users” category, the following are the stats:
Monthly active users (MAU) in the current month is 30
The normalised score for this account is 30/100 =0.3
Say the median of MAU/licenses of all accounts that are in the “Templates + Users” category =0.5
Then we will say that the usage in terms of MAU is below par by 40% since the expected MAU for an account with 100 purchased licenses is 50 while the current MAU is 30.

## Consistency Score

The consistency score only contributes to 30% of the overall score since there are certain flaws with this score. This considers only the increase or decrease in the usage metrics of an account which means:
If an account has never really onboarded to the full potential, then even a slight increase in usage will point the account out as a green account. For example, let’s say an account has purchased 200 licenses and for the past 6 months has always had an MAU of around 5 only. Suddenly in a month if the MAU increases to 10 then the account will show as an excellent account while 10 users out of 200 licenses is possibly not good usage at all.
Conversely if the usage of a highly active account decreases by 10% the score will reflect poorly without considering that the current usage may still be above par.
Notwithstanding, the calculation of the score is done in the following manner:
For any given metric X, a company’s relative change in usage volume will be determined by the given formula.
Eg, if we’re evaluating Contracts created on 26th March’24,
X current month = Number of contracts created between 25th Feb’24 and 26th March’24 (Last 30 days)
X 3 month average =Monthly average of contracts created in the months of December’23, Jan’24 and Feb’24.

## Contributing Metrics and Weightage

There are different contributing metrics based on the pricing of each account and the weightage of each of these metrics are highlighted in the table below. Note that the weightage of each metric is on a scale of 0-10, however the absolute number matters less than the percentage contribution of each metric.
1
Template+users
Template+users
Volume based contracts
Volume based contracts
Users
Users
2
Metrics
Importance (0-10)
% weight
Importance (0-10)
% weight
Importance (0-10)
% weight
3
Active Teams
1
3%
1
3%
1
3%
4
Active Templates
2
6%
1
3%
1
3%
5
Contracts Created
6
17%
6
15%
6
17%
6
Third Party Contracts Created
0
0%
4
10%
0
0%
7
Contracts Created via Template
4
11%
4
10%
4
11%
8
Time Spent By Legal
5
14%
5
13%
5
14%
9
Total Sessions
4
11%
4
10%
4
11%
10
Active Users
4
11%
4
10%
4
11%
11
Active Legal Users
4
11%
4
10%
4
11%
12