Clicking the Enrich button above the list table opens a modal with tools specific to the entity type you are viewing.
Enrichment for Contacts
The enrichment modal for contacts is divided into five categories:
1. Data Enrichment
Tool | Description |
Enrich Email Address | Searches for the contact's professional email. Includes Advanced Configuration: choose Fast (uses only the quickest sub-providers) or Deep (uses all available suppliers — slower but more thorough). Cost: 5 credits / result. |
Enrich Phone Number | Searches for the contact's phone number. Also supports Fast and Deep modes. Cost: 40 credits / result. |
Find Data by Email Address | Reverse email lookup that enriches a contact using only an email address. It can return professional profile data such as name, job title, company, and LinkedIn URL (when available). If a LinkedIn URL is found, Enginy automatically triggers the standard LinkedIn scraping to complete the contact profile — so you don't need to run a separate LinkedIn enrichment afterwards. Cost: 6 credits / result. |
Find Data by LinkedIn URL | Scrapes LinkedIn profile data using the contact's LinkedIn URL. Cost: 1 credit / result. |
Find Data by Name | Looks up the contact on LinkedIn by name and scrapes data to pull. It follows exactly this waterfall: First: Search by first name, last name, and company / Second: Search by first name, last name, company in keywords / Third: Search by first name, last name, and domain / Fourth: Search by first name and company / Fifth: Search by first name and domain / Sixth: Search by first name and alternative domain / Seventh: Search by first name and last name. Cost: 1 credit / result. |
Enrich contact with Crunchbase | Pulls scraped data from Crunchbase. Cost: 7 credits / result. |
Note: Results depend on whether our enrichment provider (FullEnrich) has data linked to the submitted email. It can work with personal or work emails, but if there's no match in the provider's database, Enginy won't be able to return reverse-lookup data (and therefore won't auto-run LinkedIn scraping). Common use cases include Inbound leads, event attendee lists, and CSV imports missing LinkedIn URLs.
Enriching with Email or Phone
To enrich contacts with email or phone data:
Go to the list of contacts you want to enrich.
Select the records to enrich. To enrich all contacts, select Enrich all (above the first column). To enrich specific contacts, select them using their checkboxes first.
Click Enrich and choose:
Enrich phone and email address — Searches for both phone and email.
Enrich email address — Searches for email only.
Note: "No data found" results are not billed in any of the enrichments.
Fields populated by phone/email enrichment:
Field | Description |
Phone number | Primary phone number |
Professional Email | Primary email address |
Note: Other phones, Other emails, and Company email are not enrichable fields. You can only populate them by importing a CSV, entering the data manually, or moving values from another field into these fields.
2. Data Cleanup
Tool | Description |
Verify Email Address | Checks whether the professional email is Verified, Invalid, or Unsure (risky/unknown). The system sends a test message (not through your email address); if it bounces, the email is marked Invalid. Cost: 1 credit / result. |
Verify Phone Number | Validates the phone number as Valid, Unsure, or Invalid. Cost: 1 credit / result. |
Extract Domain | Extracts the website domain from the professional email address (the part after the @ symbol). Cost: Free |
Combine Name and Last Name | Generates a Full Name column by merging the First Name and Last Name fields. Cost: Free |
3. Enrich with AI
Displays all available contact-type AI variables. Select one or more variables and run them on the selected contacts. You can also click Create New AI Variable from this panel.
To run AI enrichment:
Select the contacts you want to enrich.
Click Enrich > Enrich with AI.
Select the AI variables you want to fill in.
Click Run.
Tips:
To check or edit an AI variable's prompt, click on its column header and select Edit column.
For credit optimization, filter beforehand to enrich only records where the variable is currently empty.
Important: The cost of running an AI Variable depends on the model used, and it also includes the cost of any implicit AI Variables referenced in the prompt that need to be generated (if they haven't been generated yet).
4. CRM Sync
Sync with your CRM — During the CRM sync, Enginy compares the mapped fields between Enginy and your CRM. This comparison only runs when the sync mapping finds a match — when Enginy can link a Contact or Company to its CRM record based on the matching fields defined in the sync mapping.
You can click in Create new CRM field to create in Enginy a new CRM field, which later you will need to map it the integration settings. And you can even sync this new field with an existing field.
You can also switch on the option Full resync, which reset all contact data and sync from scratch.
Note: Free cost.
5. Enrich with Formula
Displays all existing formulas. Select one or more to run, or click Create New Formula to define a new one.
Note: Free cost.
Enrichment for Companies
The enrichment modal for companies has four categories (Data Cleanup is not available for companies):
1. Data Enrichment
Tool | Description |
Get company open jobs from LinkedIn | Retrieves active job postings from the company's LinkedIn page. Cost: 1 credit / result. |
Get company open jobs from TheirStack | Retrieves job postings via TheirStack data. Cost: 1 credit / result. |
Get headcount by department | Gets a breakdown of employee count per department. Cost: 1 credit / result. |
Get company IQ insights | Retrieves company engagement and qualification insights. Cost: 2 credits / result. |
Get company posts from LinkedIn | Fetches the company's recent LinkedIn posts. Cost: 1 credit / result. |
Enrich technology stack | Identifies technologies used by the company. Cost: 1 credit / result. |
Enrich company with Crunchbase | Pull scraped data from Crunchbase. Cost: 7 credits / result. |
Find data by LinkedIn URL | Scrapes data using the company's LinkedIn URL. Cost: 1 credit / result. |
Find data by name or domain | Looks up the company on LinkedIn by name and scrapes data to pull; falls back to domain search if name is not found. Cost: 1 credit / result. |
Get contacts from company | Retrieves contacts associated with the company. Cost: 1 credit / result. |
When using "Get contacts from company" (Add contacts to company):
Select the companies in a company list.
Click Enrich > Get contacts from company.
Configure filters (Function, Current Job Title, Region, etc.).
Click Fetch Preview to see matching contacts.
Assign or create a contact list for the results.
Note: If no contacts are found, try broadening your filters. For example, search "HR" instead of "HR Manager." You can also use the dropdown arrow icon in the Contacts Count column to manually explore people at a specific company.
The "Contacts Count" column in the companies table shows three elements:
Number of contacts — Total contacts associated with the company.
Add contacts to company — Shortcut to Get contacts from company action.
View contacts on table — Shortcut to Switch to contacts view action.
Important: If the company hasn't been scraped yet (so the Company URN field, used to identify the company's LinkedIn profile, is empty), a banner appears when you fetch contacts from that company: "Some results may be inaccurate." This happens because the company isn't linked to a specific LinkedIn account. If multiple LinkedIn companies share the same name, the results may come from any of them.
E.g of inaccurate results:
2. Enrich with AI
Displays all available company-type AI variables. Select one or more variables and run them on the selected contacts. You can also click Create New AI Variable from this panel.
To run AI enrichment:
Select the contacts you want to enrich.
Click Enrich > Enrich with AI.
Select the AI variables you want to fill in.
Click Run.
Tips:
To check or edit an AI variable's prompt, click on its column header and select Edit column.
For credit optimization, filter beforehand to enrich only records where the variable is currently empty.
Important: The cost of running an AI Variable depends on the model used, and it also includes the cost of any implicit AI Variables referenced in the prompt that need to be generated (if they haven't been generated yet).
3. CRM Sync
Sync with your CRM — During the CRM sync, Enginy compares the mapped fields between Enginy and your CRM. This comparison only runs when the sync mapping finds a match — when Enginy can link a Contact or Company to its CRM record based on the matching fields defined in the sync mapping.
You can click in Create new CRM field to create in Enginy a new CRM field, which later you will need to map it the integration settings. And you can even sync this new field with an existing field.
You can also switch on a toggle for the option Full resync, which reset all company data and sync from scratch.
Note: Free cost.
4. Enrich with Formula
Displays all existing formulas. Select one or more to run, or click Create New Formula to define a new one.
Note: Free cost.
Enrich Data with LinkedIn
If you imported companies or contacts from a non-LinkedIn source (e.g., CSV, CRM), you can locate them on LinkedIn to scrape additional information.
If you have the LinkedIn URL:
Select the records in your list.
Go to Enrich > Find data by LinkedIn URL.
If you do not have the LinkedIn URL:
Select the records in your list.
Go to Enrich > Find data by name (or Find data by name or domain).
Important: "Find data from LinkedIn by URL" uses the LinkedIn URL, not the company website URL. If the name search does not find the record, the system will attempt a search by domain (if available in the list).
When searching by name for companies it is Find data by name or domain, and you can apply additional matching filters:
Match only if the company name is similar — It will match results allowing a maximum difference of 2 characters. This is useful when the company name includes the legal form (e.g., SL, SA). However, we recommend running the default AI Variable Simplified Company Name first, which returns the common company name used on LinkedIn.
Match only if name is exact — Recommended in a first attempt, before trying with if name is similar.
Match only if the domain is exact — The system will search by domain if it cannot find the name. If you switch on this option the domain will be matched if is exactly the same.
Additional filters (to refine even more the matching criteria):
Headquarters Location
Industry
Company headcount
If the wrong company is matched, click the magnifying glass icon next to the company name to see other LinkedIn companies with that name and select the correct one to replace and scrape automatically. You can also select multiple which will create as many more rows selected.
Tip: After importing companies from any source (CSV, CRM), always run Find data from LinkedIn by URL (if available) or by name or domain to populate LinkedIn fields. Even with the LinkedIn URL, you still need this step to get the Company URN required to fetch company contacts.
Contact and Company Score
Enginy automatically scores contacts and companies based on how closely they match your Ideal Customer Profile (ICP) defined in the AI Playbook. Two columns are available in the data table:
Contact Score
Company Score
Each score classifies the record as High, Medium, Low, or Disqualified. Hover over any score to see the specific reasons behind the rating.
Contact Score Criteria
Score | Criteria |
High | Job title is the same or very similar to ICP targets; location is within the desired region; company score is High. |
Medium | Job title is the same or similar, same country, company score is Medium. OR same department but different seniority, same country, company score is High. OR same/similar title, different country, company score is High. |
Low | Same or similar job title, same country, but company score is Low. OR same department, different seniority, company score is Medium. OR same department, different country, company score is High. |
Disqualified | Contact meets a disqualifying factor (e.g., Freelancer when excluded); company score is Disqualified; job title belongs to a different department; contact is in a different country with Medium/Low/Disqualified company score. |
Company Score Criteria
Score | Criteria |
High | Company size approximately matches the ICP target; industry is an exact or very close match; location is within the desired region. |
Medium | Company size is equal to or larger than the target; industry is broadly related but not exact; country matches even if the city does not. |
Low | Company size is lower than target; industry does not closely match; company is outside target countries but may still be relevant. |
Disqualified | Matches disqualifying traits (e.g., B2C if B2C is disqualified); industry is clearly irrelevant; insufficient data to score confidently. |
Important: To access scoring, you must complete your ICP in the AI Playbook page. You can fill it in manually or use Fill with AI for a quick setup.
Notes:
If a contact or company is missing critical fields, the status will display NOT ENRICHED. Run Enrich Data from LinkedIn to populate the required fields. Required fields for scoring: Company — name, industry, description, employee range, number of employees, country, city. Contact — job title, company, location.
Job title comparisons are flexible — synonyms, role equivalents, and translations are considered. If a contact's information changes (e.g., job promotion), the score updates automatically.