- Multidimensional health
- Account health
Regardless of health model used, choose your preferred enterprise calculation if you leverage account hierarchies.
Suggested uses for the multidimensional health model
Multidimensional health models are more sophisticated and are typically best for the following scenarios:
- You need to understand issues at a dimensional level, not just a single metric
- Not all health indicators are equal; fine-tune your calculations using weights for individual metrics and for each dimension
- You want a numerical score with the option to customize the scale for good, average, and poor
- You want to choose how to process metrics without a value
Calculation for multidimensional health
Multidimensional health is defined based on a color indicator and numbered score. Score values are calculated based on pre-defined weights for each dimension in the health profile.
Scoring uses a weighted average:
- Good = 100 points if the good criteria is met
- Average = 60 points if average criteria is met
- Red = 0 points if the poor criteria is met
- Dimensions score: Each dimensions is calculated and weighted to provide a total score for that category (a number between 0 and 100). The calculation is: MetricScore1 X Weight1 + MetricScore2 X Weight2 + ...MetricScoreN X WeightN, rounded to the nearest integer.
- Overall score: The score(s) from each dimension are calculated and weighted to provide a total score (a number between 0 and 100). The calculation is: DimensionScore1 X Weight1 + DimensionScore2 X Weight2 + ...DimensionScoreN X WeightN, rounded to the closest integer number.
You can set ranges for how all scores in the profile are classified, and optionally exclude metrics with no values from the calculation.
See a calculation example:
Configure a profile (multidimensional health model)
Totango includes the following starter profiles under the multidimensional health model:
- High touch onboarding
You may add other profiles as needed.
Before you update your health profile, we recommend that you do the following:
- Map your customer journey stages first. If your profiles rely on the onboarding stage of the journey, we also suggest that you map your onboarding stages prior to configuring health.
- Confirm your dimensions and attributes/metrics in Data Modeler. For example, drill into the dimension (e.g. “Usage”) to see the metrics available. If something is missing from this list, search for it in and move it to the dimension you want to use.
- From the left nav, click Settings.
- Within Settings, expand Data Management > Health Designer.
- Click on the Multidimensional Health tab.
- Click on a starter profile to edit properties, duplicate from another profile, or click +New Profile.
- If creating a new profile, choose the position in which to create the new profile. You can re-order the position later.
- Configure properties for the profile:
- Name: Add a name to identify the profile. This name is visible in the health widget on the account profile.
Account type: Define which level of the hierarchy this profile will be used. If you have a flat hierarchy, leave set to Company. If you have a two-level hierarchy, you may choose both levels if it is appropriate to use the same profile for both the parent and the child accounts (see calculated health considerations).
Products: If you have more than one product you will see an additional option. If your onboarding process applies to a single product, then choose the product you want to apply this health profile to.
Segment criteria: Click in the grey box to add filter criteria to determine the segment of accounts that apply to this profile, such as customer journey stage changed from onboarding in the last 90 days.
- Click Add Metric to search for a metric to add. If you use "Is in Segment" as criteria, the segment cannot include any user attributes or touchpoint criteria.
In our example, we're setting up a separate profile to apply to newly onboarded accounts within their first 90 days of going live. We want to add metrics that are particular enough to this period of time to warrant having a separate profile. Perhaps we expect an aggressive usage metric or want to measure training activity during this critical period.
- For each metric added, the dimension automatically is displayed.
- Set the dimension weight. Must be an integer. All dimensions must add up to 100%.
- Set the metric weight. Must be an integer. All metrics within a dimension must add up to 100%.
- Set the metric properties. Click Add Attribute Value within the Good and Poor columns.
In order for an account to qualify for good health within a dimension, it must meet all criteria in that column (AND statements). On the other hand, an account can qualify for poor health within a dimension if it meets any criteria in that column (OR statements). Accounts that meet some criteria in the Good column and none of the criteria in the Poor column in the dimension are considered in average health.
- Click Preview.
- Review the preview of accounts that would qualify for this profile segmentation in the current order of precedence. View current health against this new profile for each dimension added. Search for a specific account if you want to add it to the preview.
- Done Editing.
- If you want to continue refining before launching, click the Ellipses (...) and choose Disable Profile prior to saving. Otherwise, the profile will be applied immediately if the model is active.
- Click Save Changes.
When enabled in the active model, you can click into the profile to view the number of accounts included, the average score, and a score preview for each dimension.
Set health score ranges and preferences for unused attributes
Multidimensional health provides a numerical score with the health classification. Set the range to apply to good, average, and poor scores.
Additionally, you can decide how you want Totango to process metrics that don't have values (e.g., unused attributes).
- Attributes/metrics with no value for a specific dimension are ignored and are not used in the health calculation of the dimension of that account
- Dimensions where all their attributes are missing for an account are ignored and are not part of the overall health calculation of the account
- When an attribute is ignored, its weight is distributed between all the other attributes of the that dimension proportionally to their weights
- An ignored dimension weight is distributed between all the other dimensions proportionally to their weights.
- From the health designer, ensure you're on the Multidimensional Health tab.
- Click Health Settings.
- Drag the slider bars to set your preferred health score ranges. Poor can be up to a maximum of 50; good can start from a minimum of 55.
- From the Health Calculation toggle, choose to exclude or include unused attributes.
- Click Save Settings.
Ignored values and dimensions are denoted as such in the health widget on an account profile.
Calculation distribution for ignored metrics
When an attribute is ignored, its weight is distributed between all the other attributes on the same dimension proportionally to the attribute weights. Let's say we have a dimension with 3 metrics with the following weights:
- Metric1 - 60%
- Metric2 - 20%
- Metric3 - 20%
If Metric3 does not have a value and it is ignored, the 20% weight of Metric3 will be distributed between Metric1 and Metric2 proportionally, meaning Metric2 will get 20/80= 25%, and Metric3 will get 60/80=75%. As you can see, before the change, Metric1 weight was 3 times than Metric2 (60% vs. 20%), and this proportion is kept after the change as well (75% vs. 25%). After the weight distribution, weights that are not integers are rounded to the nearest integer. Ignored dimension weights are represented as 0%, and other dimensions weights are adjusted accordingly.
If you define "No Value" as one of the filter conditions of a metric *within the health profile,* the metric will not be ignored and will get the value of "good" or "poor," depending on where "No value" is defined in the health profile.
Re-order and enable the health profile
Totango uses the active profile with the lowest order (top) first before using other profiles. In other words, best practice is to position the profile(s) with the most restrictive criteria first. If an account doesn't match the criteria, Totango will continue to move down the list of profiles toward the most general profile at the bottom.
Anytime you edit, reorder, or create new profiles, Totango will recalculate the health automatically if the profile is set to enabled.
- From the health designer, ensure you're on the Account Health tab.
- From the Ellipses (...) next to the profile you want, click Enable.
- Drag-and-drop the profile to the top of the list.
- Click Save Changes.
If the health model is active, Totango starts calculating health from this point forward immediately using the new settings (may take a few hours to reflect on account profiles). Going forward, Totango evaluates health on a daily basis. You can optionally tell Totango to recalculate health historically.
Activate multidimensional health
You can enable multiple profiles under any model, but you can only have one overall model activated at a time.
Before switching from an account health model to a multidimensional health model, we recommend creating a segment to compare health scores under each model. You can use any of the following attributes as segment filters or columns for comparison:
- Health rank: Account health rank
- Multidimensional health account score: Account level score (0-100)
- Multidimensional health score: Account level rank (red/yellow/green)
- Multidimensional Health Rank: Select a dimension to view dimension score (0-100)
- Multidimensional health score: Select a dimension to view dimension (red/yellow/green)
- From the health designer, ensure you're on the Multidimensional Health tab.
- Click Activate Multidimensional Health.
- Read the confirmation, and click to confirm.
Totango starts calculating health from this point forward using the new settings immediately (may take a few hours to reflect on account profiles).