An account will receive 3 scores when scored by Keyplay: the signal score, the similarity score, and the overall score. This article will explain how each score is assigned.
Signal Score
This is the score an account receives based on the number of signals an account matches in your custom scoring model. Then, those signals are weighted per the individual weightings you assign them in the app. Based on the signals matched + their weightings, an account is assigned a total signal score.
You can see this signal score for individual accounts in the preview functionality in the app:
As you can see in this example, Pied Piper is receiving a 100 on it's signal score due to matching the different signals in the custom scoring model.
You can see how many points each signal earned based on the weightings. For example, Hiring Dev Ops is weighted higher than Funding $100k to $1M in this model, so receives more points.
Similarity Score
Accounts that match one of your lookalike accounts will also receive a similarity score based on how close it's business model is to that of one of your lookalikes. To learn more about lookalikes, see our help article here.
You can also see the lookalike score in the preview. In this example, Pied Piper received a similarity score of 80 because of how closely it's business model resembles that of Pied Piper.
Overall Fit/Keyplay Fit Score
This is the overall score an account receives that also translates to the tier assignment.
The overall fit is assigned a few different ways based on the score mode you choose. You can adjust your score mode by clicking "Customize Signal Weights" and chosing from 5 options for score mode:
Here is an overview of the different score modes and some example use cases to help you decide what makes the most sense for your overall scoring.
Take the Highest Score.
Definition: Overall score will be which score is highest between similarity score and signal scores.
Example Use Case: You know that accounts of any employee size which match the signals in your model are a good ICP fit, but you also know that accounts which look like your enterprise customers are always a good fit, even if they don't match all the signals in your model. Using the "take the highest score" mode with your enterprise customer list as lookalikes will ensure that both accounts that match the signals in your model and match your enterprise list will get high scores.
Similarity score + bonus points for signals.
Definition: This mode is mostly based on similarity, but a strong signal score (65+) will add 20 bonus points to the overall score.
Example Use Case: You have a few key signals that are somewhat strong indicators of an ICP fit, but the core of your ICP model strongly resembles your best fit accounts. Using the "similarity score + bonus points for signals" mode will make similarity scores the basis for your overall scoring, but give accounts that match your select signals a bump in overall scoring.
Signal score + bonus points for similarity.
Definition: This mode is mostly based on signals, but a strong similarity score (65+) will add 20 bonus points to the overall score.
Example Use Case: You have spent a lot of time refining, back-testing, and analyzing your signal scoring model and weightings, and feel like it's highly representative of your ICP. However, you still want accounts that match your best fit accounts to receive a bump in scoring. Using the "signal score + bonus points for similarity" mode will make the signal score the basis for your overall scoring, but give accounts that match your lookalike list a bump in the scores they receive.
Similarity score only.
Definition: You'll still see the signal score in the app and CRM sync, but it won't count toward overall score or tier.
Example Use Case: The most important element of your scoring is that you can replicate your best fit account list, and you want focus your time on those accounts only. You would rather have signals be a supporting data point rather than impact overall scoring.
Signal score only.
Definition: You'll still see the similarity score in the app and CRM sync, but it won't count toward overall score or tier.
Example Use Case: You know exactly what signals make up your ICP, and you don't want to cloud that information with another score. You would rather have similarity scores and lookalikes be a supporting data point rather than impact overall scoring.