Zia's Similarity Recommender makes pattern recognition systematic and available to every rep on the team. It analyses CRM records and surfaces the most similar matches based on shared characteristics across multiple dimensions. When a rep opens a contact, lead, or account record, they can see which other records in the CRM closely resemble it and use that context to inform how they approach the relationship.
Zia evaluates similarity across four distinct analytical dimensions, which can be applied individually or in combination when configuring a similarity rule:
| Dimension | What It Analyses |
|---|---|
| Interest | Shared product interests, service categories, or engagement patterns — useful for identifying leads who closely resemble existing customers who converted on a specific offering. |
| Demographic | Attributes such as company size, job title, seniority, or industry classification — helping reps identify leads who fit a known buyer profile. |
| Geography | Location data including region, country, or city — enabling geographic pattern recognition such as identifying a cluster of high-value accounts in a specific area. |
| Industry | Sector or vertical classification — enabling reps to see how a current record compares with similar customers in the same industry, including deal values and conversion timelines typical for that vertical. |
Zia surfaces up to five of the closest matching records. For each match, the view shows the specific factors that contributed to the similarity score — making the comparison transparent and actionable. Representatives can use this to:
| Requirement | Detail |
|---|---|
| Zoho CRM Edition | Professional and above |
| Minimum Licences | 20 user licences |
| Data Centres | US, EU, IN |
| Similar Records Displayed | Up to 5 per record |