A match score is a number from 1 to100 that indicates the likelihood that a match obtained by InsideView Enrich™ is accurate. Match scores provide insight into the quality of a matched record.
The match score is also by used InsideView Refresh™ and InsideView Diagnose™ products to return a quality matched record based on your input values.
Note: Match scores do not exactly correspond with raw probability; that is, a match score of 60 does not mean that a match is 60% likely to be accurate. In fact, a score of 60 corresponds with accuracy rates of about 90%.
How are Match Scores calculated?
Match scores are composed of additive and subtractive components. These additive (adding to the score) components affect the match score thresholds based on:
- Number of data fields provided as input by you—lesser the data fields lesser the match score is because the accuracy of data depends on number of fields for which InsideView has the information that can be matched.
- Number of potential matches in the pipeline—higher the number of potential matches in the pipeline lower the match score is because if the number of alternatives are many, then matching and choosing from multiple alternatives is a difficult choice.
Any company with a lot of potential matches in the database would be subtracted from the score proportionately to the number of companies that could potentially dilute the match results.
Why you should use Match Thresholds?
When configuring InsideView Enrich, account administrators may set a match score threshold—i.e. a minimum match score below which enriched leads will not be sent into the marketing automation system. The appropriate match threshold for your use case will depend on your business requirements.
Because match scores are correlated to levels of data accuracy, the choice of where to set the match score threshold is, in essence, a question of how many false positives can be tolerated in the lead supply.
Generally speaking, a lower threshold will conduce to a greater number of leads with a higher proportion of false positives, whereas a higher threshold will yield better accuracy but at lower volume.
Use Case Example
An InsideView customer from the tech industry wanted to fine-tune InsideView Enrich with a match score, which would enable them to have right balance of accuracy versus enrichment.
InsideView’s approach was to provide this customer with three options. The following table illustrates these options, showing levels of accuracy, false positives, and enrichment for match score thresholds of 70, 60, and 50 respectively:
|Accuracy versus Enrichment Balance||Match Score Threshold||Percentage of Actual Match Accuracy||Percentage of False Positives||Percentage of Lead Enrichment Rate|
|High Accuracy & Low Enrichment||70||95%||5%||30%|
|Medium Accuracy & Medium Enrichment||60||90%||10%||35%|
|Low Accuracy & High Enrichment||50||85%||15%||40%|
In the case of the technology company, our customer chose the middle option, since it was the most accurate option that would enable them to meet their lead volume requirements. Your needs may differ, and we can help you decide the threshold that is best for you.
InsideView's Technical Support team can work with you to decide options based on your requirements for overall lead enrichment. For any technical issues, submit a request for technical support . InsideView’s support team will contact you to address your problem.