Filter Contact

Use filter options to narrow down your search for preferred contacts, say, based on first name, last name, city, zip code, or customer attributes.

These are only a few; Chatman offers a lot of filter options along with various conditional logic to search the preferred audience. Here is a list of the same.

Different Filter Options

User attributes

These are the basic information about the user, such as name, email, phone number, location, customer id, etc. You can use this filter to find users who match certain criteria, such as those from a specific city or country.

First Name

Suppose you have a database of contacts and you want to segment them based on their first names, for example, to send personalized emails or offers. You can use the filter option 'first name’ to do that. Here are some examples of how you can apply different conditional logic to this filter:

  • Is: This option allows you to match the exact first name of the customers.

For example, if you select ‘Is’ and enter ‘John’, you will get a list of all customers whose first name is John.

  • Is not: This option allows you to exclude the customers who have a specific first name.

For example, if you select ‘Is not’ and enter ‘John’, you will get a list of all customers whose first name is not John.

  • Contains: This option allows you to match the customers who have a first name that contains a certain substring.

For example, if you select ‘Contains’ and enter ‘an’, you will get a list of all customers whose first name contains ‘an’, such as Anil, Rani, Manish, etc.

  • Not contains: This option allows you to exclude the customers who have a first name that contains a certain substring.

For example, if you select ‘Not contains’ and enter ‘an’, you will get a list of all customers whose first name does not contain ‘an’, such as Raj, Priya, Amit, etc.

  • Starts with: This option allows you to match the customers who have a first name that starts with a certain letter or letters. It is case-sensitive, so use accordingly.

For example, if you select ‘Starts with’ and enter ‘A’, you will get a list of all customers whose first name starts with ‘A’, such as Abhishek, Aarti, Arjun, etc.

Last Name

Suppose for a particular occasion of Punjabis you want to create a segment and interact with them for lucrative offerings. Since last name often helps identify the religion it can help you while creating a segment. Here are some examples of how you can apply different conditional logic to this filter:

  • Is: This option allows you to match the exact last name of the customers.

For example, if you select ‘Is’ and enter ‘Singh’, you will get a list of all customers whose last name is Singh.

  • Is not: This option allows you to exclude the customers who have a specific last name.

For example, if you select ‘Is not’ and enter ‘Kumar' you will get a list of all customers whose last name is not Kumar.

  • Contains: This option allows you to match the customers who have a last name that contains a certain substring.

For example, if you select ‘Contains’ and enter ‘pat’, you will get a list of all customers whose last name contains ‘pat’, such as Patel, Patil, Patnaik, etc.

  • Not contains: This option allows you to exclude the customers who have a last name that contains a certain substring.

For example, if you select ‘Not contains’ and enter ‘pat’, you will get a list of all customers whose last name does not contain ‘pat’, such as Sharma, Singh, Khan, Gupta, etc.

  • Starts with: This option allows you to match the customers who have a last name that starts with a certain letter or letter. It is case-sensitive, so use it accordingly.

For example, if you select ‘Starts with’ and enter ‘K’, you will get a list of all customers whose last name starts with ‘K’, such as Kumar, Kapoor, Khan, etc.

Customer ID

Suppose you have a database, and each customer has a unique ID that are random alphanumeric given by the system. You want to segment your customers based on their IDs. Here are some examples of how you can use different conditional logic to filter your customers:

  • Is: This option allows you to filter customers who have a specific ID. Use this option only if you have the full customer ID.

For example, if you select ‘Is’ and enter ‘77fff6a6-ee43-4086-8696-ef6022e4248a’, you will get only the customer who has the ID 77fff6a6-ee43-4086-8696-ef6022e4248a.

  • Is not: This option allows you to filter customers who do not have a specific ID. It works only when you provide the full customer ID.

For example, if you select ‘Is not’ and enter ‘13f09074-00ee-430e-87ae-d0d074589f09’, you will get all the customers except the one who has the ID 13f09074-00ee-430e-87ae-d0d074589f09.

  • Contains: This option allows you to filter customers who have an ID that contains a certain alphanumeric characters.

For example, if you select ‘Contains’ and enter ‘77fff’, you will get all the customers who have an ID that contains ‘77fff.'

  • Not contains: This option allows you to filter customers who have an ID that does not contain a certain alphanumeric characters.

For example, if you select ‘Not contains’ and enter ‘5f5’, you will get all the customers who have an ID that does not contain ‘5f5.'

  • Starts with: This option allows you to filter customers who have an ID that starts with a certain prefix. It is case sensitive so always use small letters while searching for customer ID.

For example, if you select ‘Starts with’ and enter ‘451’, you will get all the customers who have an ID that starts with '451.'.

External ID

Suppose you want to search for a particular customer who was referred from HubSpot. You don't have the name or any information but the external ID. So you can filter the contacts on the basis of external ID to find your contact. Here are some examples of applying the same with different conditional logic:

  • Is: This option allows you to filter the contacts with a specific external ID.

For example, if you select ‘Is’ and enter ‘1251’, you will get the user who has the external ID 1251.

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  • Is not: This option allows you to filter the users who do not have a specific external ID.

For example, if you select ‘Is not’ and enter ‘7053745783095’, you will get all the users who do not have the external ID 7053745783095.

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  • Contains: This option allows you to filter the users who have an external ID that contains a certain digit or sequence of digits.

For example, if you select ‘Contains’ and enter ‘537’, you will get all the users who have an external ID that contains 537.

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  • Not contains: This option allows you to filter the users who have an external ID that does not contain a certain digit or sequence of digits.

For example, if you select ‘Not contains’ and enter ‘34’, you will get all the users who have an external ID that does not contain 34, such as 5678, 9012, or 8765.

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  • Starts with: This option allows you to filter the users who have an external ID that starts with a certain digit or sequence of digits.

For example, if you select ‘Starts with’ and enter ‘70’, you will get all the users who have an external ID that starts with 70.

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Contact

Imagine you're managing a social app, and you want to send event notifications to users based on their phone numbers. Here's how you might use the different conditional logics for the "contacts (phone numbers)" attribute filter:

  1. Is: You have a special event for users with phone numbers ending in "1234." You set the filter to "Phone number is 1234," ensuring that only users with this specific ending in their phone numbers receive an invitation to the event.

  2. Is not: However, for a different event, you want to exclude users with phone numbers starting with "987." You set the filter to "Phone number is not 987," making sure that users with these numbers are not notified about this specific event.

  3. Contains: Now, you're organizing a city-wide meetup, and you want to invite users from a specific area. You set the filter to "Phone number contains 555," including users with phone numbers containing the sequence "555" in the event notification.

  4. Not contains: Yet, for a private gathering, you want to exclude users with phone numbers containing "000." You set the filter to "Phone number not contains 000," ensuring that users with these numbers are not informed about this private event.

  5. Starts with: You're planning a surprise event for your earliest users, and their phone numbers start with "800." You set the filter to "Phone number starts with 800," ensuring that users with phone numbers like "800-XXX-XXXX" are notified about the special surprise event.

Email

Suppose you have a database of users who have signed up for your online service. You want to filter the users based on their email addresses. You can use the filter option ‘user attribute- email’ to do that. Here are some examples of how you can use different conditional logic:

  • Is: This option allows you to filter the users who have an exact match with the email address you specify.

For example, if you want to find the user who has the email address ‘shubham.sharma@makerobos.com’, you can use the filter ‘user attribute- email is 'shubham.sharma@makerobos.com’.

  • Is not: This option allows you to filter the users who do not have an exact match with the email address you specify.

For example, if you want to exclude the user who has the email address ‘shubham.sharma@makerobos.com’, you can use the filter ‘user attribute- email - is not 'shubham.sharma@makerobos.com’.

  • Contains: This option allows you to filter the users who have an email address that contains a certain substring.

For example, if you want to find the users who have a Gmail address, you can use the filter ‘user attribute- email, contains Gmail’.

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  • Not contains: This option allows you to filter the users who have an email address that does not contain a certain substring.

For example, if you want to exclude the users who have an email address that contains ‘Gmail’, you can use the filter ‘user attribute- email, not contains Gmail.

  • Starts with: This option allows you to filter the users who have an email address that starts with a certain prefix.

For example, if you want to find the users who have an email address that starts with ‘a’, you can use the filter ‘user attribute- email starts with a’.

Country

Imagine you're managing a global newsletter for an online community, and you want to customize content based on users' countries. Here's how you might use the different conditional logics for the "country" attribute filter:

  1. Is: You have a special announcement for users in India. You set the filter to "Country is India," ensuring that only users located in India receive this particular newsletter with exclusive information relevant to them.

  2. Is not: However, you want to exclude users from the United States for this specific update. You set the filter to "Country is not USA," making sure that users from the United States are not included in this particular newsletter.

  3. Contains: Now, you have a global event that you want to promote to users across Asia. You set the filter to "Country contains Asia," including users from various countries within the Asian continent for this event newsletter.

  4. Not contains: Yet, for a different newsletter, you want to exclude users from Europe. You set the filter to "Country not contains Europe," ensuring that users from European countries are not part of this specific communication.

  5. Starts with: You're launching a series of articles specifically for countries starting with "C." You set the filter to "Country starts with C," including users from Canada and China in the distribution list for this content series.

City

Imagine you're organizing a big event in India, and you want to invite specific people based on their cities. Here's how you might use the different conditional logics for the "city" attribute filter:

  1. Is: You want to invite people only from Delhi. So, you set the filter to "City is Delhi." This ensures that only users with their city listed as Delhi will receive the invitation.

  2. Is not: Now, let's say you have sponsors who are supporting your event, but you don't want to invite them. You set the filter to "City is not Mumbai," making sure that anyone from Mumbai won't get the invitation.

  3. Contains: Maybe your event is happening in multiple cities, and you want to invite people from all over Maharashtra. You use the "City contains Maharashtra" filter to include users from cities within Maharashtra.

  4. Not contains: However, you don't want anyone from Bangalore to receive the invitation. So, you set the filter to "City not contains Bangalore," ensuring that users from Bangalore are excluded.

  5. Starts with: Finally, you want to invite people specifically from cities starting with "K." You set the filter to "City starts with K," including cities like Kolkata and Kochi.

State

Imagine you run an online store, and you want to create targeted promotions for customers based on their locations. Here's how you might use the different conditional logics for the "city" attribute filter:

  1. Is: You have a special promotion for customers in Karnataka, maybe a discount on traditional Mysore silk. You set the filter to "City is Bengaluru," ensuring that only users in Bengaluru receive this specific promotion.

  2. Is not: However, you don't want to include customers from Tamil Nadu for this particular offer. You set the filter to "City is not Chennai," making sure that customers from Chennai are excluded.

  3. Contains: Now, you have a generic discount for customers in South India. You set the filter to "City contains Tamil Nadu," including users from various cities in Tamil Nadu for the promotion.

  4. Not contains: Yet, you want to exclude customers from Uttar Pradesh. So, you set the filter to "City not contains Lucknow," ensuring that customers from Lucknow are not part of this promotion.

  5. Starts with: You have a new product that you want to promote specifically to cities starting with "H." You set the filter to "City starts with H," including places like Hyderabad and Hubli in the promotion.

Zip Code

Suppose you're managing an online marketplace, and you want to provide special offers to users based on their zip codes. Here's how you might use the different conditional logics for the "zipcode" attribute filter:

  1. Is: You have a limited-time discount for users in a specific neighborhood with the zip code "110011." You set the filter to "Zipcode is 110011," ensuring that only users residing in that particular area receive this exclusive discount.

  2. Is not: However, for a different promotion, you want to exclude users from a particular region with the zip code "456789." You set the filter to "Zipcode is not 456789," making sure that users from this specific area do not receive this particular offer.

  3. Contains: Now, you're running a city-wide sale and want to include users from different neighborhoods. You set the filter to "Zipcode contains 600," including users with zip codes like "6000XX" in the promotion.

  4. Not contains: Yet, for a clearance sale, you want to exclude users from a certain district with the zip code "789." You set the filter to "Zipcode not contains 789," ensuring that users from this district are not part of the clearance sale promotion.

  5. Starts with: You're launching a new product and want to give a special preview to users in a specific area. You set the filter to "Zipcode starts with 123," including users with zip codes like "1230XX" in the exclusive preview offer.

Last Active

Imagine you operate an online store and want to run a re-engagement campaign to bring back customers who haven't interacted with you recently. Here's how you might use the different conditional logics for the "last active" attribute filter:

  1. More than x days ago: You want to target customers who haven't interacted with you in the last 30 days. You set the filter to "Last active more than 30 days ago," ensuring that you reach out to users who haven't engaged for a longer duration.

  2. Less than x days ago: For a different promotion, you decide to offer a discount to customers who have been active within the last 7 days. You set the filter to "Last active less than 7 days ago," ensuring that you focus on customers who have recently interacted with your platform.

  3. After: You're launching a flash sale and want to notify users who have been active after a specific date, perhaps to reward loyal customers. You set the filter to "Last active after January 1, 2024," ensuring that only users who have engaged since that date receive the flash sale notification.

  4. Before: However, for a clearance event, you want to target users who were last active before a certain date to reach out to those who haven't shopped recently. You set the filter to "Last active before December 1, 2023," focusing on users who were active before that specific date.

  5. Exact: You're launching a special event exclusively for customers who have been active within the last 24 hours. You set the filter to "Last active exact 24 hours ago," ensuring that users who have engaged precisely within the specified time frame receive an invitation to the event.

Created On

Imagine you're managing an online store and you want to welcome new customers with special offers based on when they created their accounts. Here's how you might use the different conditional logics for the "created on" attribute filter:

  1. More than x days ago: You want to offer a discount to customers whose accounts were created more than 30 days ago to encourage repeat purchases. You set the filter to "Created more than 30 days ago," ensuring that customers who have been with your platform for a longer duration receive the offer.

  2. Less than x days ago: For a different promotion, you decide to provide a special welcome gift to brand new customers who joined in the last 7 days. You set the filter to "Created less than 7 days ago," focusing on users who recently signed up to your online store.

  3. After: You're launching a loyalty program and want to invite customers who created their accounts after a certain date to reward newer members. You set the filter to "Created after January 1, 2024," ensuring that only users who joined after that date receive the loyalty program invitation.

  4. Before: However, for a clearance sale, you want to target customers who signed up before a specific date to include those who have been with your platform for a longer period. You set the filter to "Created before December 1, 2023," focusing on users who joined before that specific date.

  5. Exact: You're celebrating your online store's anniversary and want to give a special thank-you offer to customers who created their accounts exactly one year ago. You set the filter to exact and select 1 year ago date, say 1 dec, 2022, ensuring that users who joined precisely one year ago receive the anniversary offer.

  6. Not Exact: Additionally, you want to include users who joined around the anniversary date but not exactly on the day. You set the filter to exact and select any near about date, expanding the reach of your anniversary offer to a broader time frame.

  7. Has Any Value: You want to send a general welcome email to all users, regardless of their account creation date. You set the filter to "has any value," ensuring that users with any account creation date receive the general welcome email.

  8. Has Not Any Value: For a special reactivation campaign, you want to target users who haven't provided their account creation date. You set the filter to "has not any value," reaching out specifically to users whose account creation date is not available.

Created On

Imagine you manage an EdTech platform, and you want to reward students based on the anniversary of their enrollment. Here's how you might use the different conditional logics for the "created on" attribute filter, including the new filter options:

  1. More than x days ago: You decide to acknowledge the loyalty of students who enrolled more than 365 days ago by offering them an exclusive course extension. You set the filter to "Enrolled more than 365 days ago," ensuring that students who have been with your platform for over a year receive this special offer.

  2. Less than x days ago: For a different promotion, you want to welcome and encourage new students who recently joined. You set the filter to "Enrolled less than 30 days ago," focusing on students who have enrolled in the last month for a special welcome webinar.

  3. After: You're launching an advanced course, and you want to notify students who joined after a specific date to offer them early access. You set the date as January 1, 2024," ensuring that only students who joined after that date receive the early access invitation.

  4. Before: However, for a scholarship application, you want to target students who enrolled before a specific date to include those who have been part of your platform for a longer period. You set the date to September 1, 2022," focusing on students who joined before this specific date for the scholarship opportunity.

  5. Exact: You want to celebrate the anniversary of the launch of your platform by offering a special discount to students who enrolled exactly two years ago. You set the date to two years ago say 1st January 2022, ensuring that students who joined precisely two years ago receive the anniversary discount.

  6. Not Exact: Additionally, you want to extend the anniversary offer to students who joined around the same time but not exactly on the day. You set the date to 1st January 2022 ," broadening the reach of your anniversary offer to a broader time frame.

  7. Has Any Value: You want to send a general appreciation email to all students, regardless of their enrollment date. You set the filter to "Enrolled has any value," ensuring that students with any enrollment date receive the general appreciation email.

  8. Has Not Any Value: For a special onboarding campaign, you want to target students who haven't provided their enrollment date. You set the filter to "Enrolled has not any value," reaching out specifically to students whose enrollment date is not available.

WhatsApp Opted

Suppose you are managing a business that uses Chatman to communicate with customers. You want to filter users based on their WhatsApp opt-in status for targeted messaging. Here's how you might use the different conditional logic for the "WhatsApp opted" attribute filter:

  1. Is (True): You have a special promotion for users who have opted in to receive WhatsApp messages. You set the filter to "WhatsApp opted is True," ensuring that only users who have agreed to receive messages on WhatsApp will receive this specific promotion.

  2. Is (False): However, you want to run a separate campaign to encourage users who have not yet opted in to do so. You set the filter to "WhatsApp opted is False," targeting users who have not yet opted in to receive WhatsApp messages with a persuasive message about the benefits.

  3. Is not (True): For a general announcement, you want to include all users except those who have already opted in to avoid redundant messages. You set the filter to "WhatsApp opted is not True," ensuring that users who have not yet opted in, as well as those who haven't provided a preference, receive the announcement.

  4. Is not (False): In another scenario, you want to remind users who have not opted in that they are missing out on important updates. You set the filter to "WhatsApp opted is not False," targeting users who either have already opted in or haven't made a choice yet, to encourage them to opt in.

Referred

  1. In (Select Values): This option allows you to filter contacts based on the specific sources they were referred from. For instance, you might choose "Referred in Direct" to target users who were directly referred to Chatman, who clicked on an ad. It's a way to segment users based on their referral source.

  2. Is not (Select Values): This allows you to filter out users based on specific sources. For example, you might choose "Referred - is not - HubSpot" to exclude users who were referred from HubSpot.

  3. Has any value: This option filters users who have any value recorded for the "referred" attribute. If a user has any referral source mentioned, they will be included.

  4. Has not any value: This option filters users who do not have any value recorded for the "referred" attribute.

Conversation attributes

These are the information about the user’s conversations with the agents, such as status, rating, etc. You can use this filter to find users with different conversation attributes, such as users who gave a positive rating or who had a long conversation.

Conversation Status

Say you want to filter users for creating a segment based on their conversation status for a follow-up campaign. Here's how you might use the different conditional logics for the "Conversation Attribute - Conversation Status" filter:

  1. In (Select Values): You want to send a satisfaction survey to users whose conversations are marked as "closed" to gather feedback. You set the filter to "Conversation Status in (closed)," ensuring that only users with closed conversations receive the survey on creating the segment.

  2. Is not (Select Values): However, for a separate initiative, you want to reach out to users who are still waiting for assistance and have conversations with a status other than "closed." You set the filter to "Conversation Status is not in (closed)," targeting users with open conversations when segment is created.

  3. Has any value: You want to acknowledge and express gratitude to users who have engaged in conversations with your support agents, regardless of the specific status. You set the filter to "Conversation Status - has any value," ensuring that users who have had any conversation, whether open or closed are displayed on the audience table.

  4. Has not any value: For a campaign, you want to target users who have not engaged in any conversation or have not received assistance yet. You set the filter to "Conversation Status has not any value," reaching out specifically to users who haven't had any recorded conversations.

Is 24hr_active

Suppose you want to create a segment with users who have been actively interacting within the last 24 hours. Here's how you might use the different conditional logics for the "Conversation Attribute - Is 24 hr active" filter:

  1. Is (True): You want to offer a quick response or a special promotion to users who have recently interacted with your support agents. You set the filter to "Is 24 hr active is True," ensuring that only users who have been active within the last 24 hours are displayed in the audience table for creating a segment.

  2. Is not (True): For a separate communication, you decide to send a follow-up message to users who haven't been active in the last 24 hours, aiming to re-engage them. You set the filter to "Is 24 hr active is not True," are displayed in the audience table for creating a segment.

  3. Is (False): You want to extend a special offer to users who have not been active within the last 24 hours. You set the filter to "Is 24 hr active is False," ensuring that users who have not interacted recently are displayed in the audience table for creating a segment.

  4. Is not (False): However, for a different scenario, you decide to send a thank-you message to users who have been active within the last 24 hours, expressing appreciation for their continued engagement. You set the filter to "Is 24 hr active is not False," ensuring that only users who have recently interacted are displayed in the audience table for creating a segment.

Custom attributes

These are the information you can define and assign to the users, such as age, gender, interests, preferences, etc. You can use this filter to find users with specific custom attributes, such as users who are interested in a specific product or who have a particular preference.

Scenario

Suppose you have run a website that sells books and you want to segment your users based on their reading preferences. You can create a custom attribute called ‘Favorite genre’ and assign it to each user based on interaction or purchasing on Chatman. For example, if a user has bought or asked for mostly science fiction books, you can assign them the value ‘Science fiction’ for the ‘Favorite genre’ attribute.

Now, you can use the filter option ‘Custom attribute’ to find users who match certain criteria based on their favorite genre. For example, you can use the following conditional logic:

  • Is: This will find users who have the exact value for the custom attribute. For example, if you select ‘Favorite genre’ is ‘Fantasy’, this will find users who have ‘Fantasy’ as their favorite genre.

  • Is not: This will find users who do not have the exact value for the custom attribute. For example, if you select ‘Favorite genre’ is not ‘Romance’, this will find users who have any genre other than ‘Romance’ as their favorite genre.

  • Contains: This will find users who have a value that contains the specified text for the custom attribute. For example, if you select ‘Favorite genre’ contains ‘Fiction’, this will find users who have any genre that includes the word ‘Fiction’, such as ‘Science fiction’, ‘Historical fiction’, ‘Fiction’, etc.

  • Not contains: This will find users who have a value that does not contain the specified text for the custom attribute. For example, if you select ‘Favorite genre’ not contains ‘Non-fiction’, this will find users who have any genre that does not include the word ‘Non-fiction’, such as ‘Fantasy’, ‘Mystery’, ‘Horror’, etc.

  • Starts with: This will find users who have a value that starts with the specified text for the custom attribute. For example, if you select ‘Favorite genre’ starts with ‘Bio’, this will find users who have any genre that begins with the word ‘Bio’, such as ‘Biography’, ‘Biological thriller’, ‘Biochemistry’, etc.

Shiprocket attributes

These are the information about the user’s orders and shipments, such as order ID, order status, tracking ID, courier name, etc. You can use this filter to find users with specific order or shipment details, such as users who have pending orders or who have shipped orders.

Shopify attributes

These are the information about the user’s purchases and products, such as product ID, product name, product price, purchase date, etc. You can use this filter to find users who have purchased certain products or have specific purchase details, such as those who have bought a specific product or who have spent a certain amount.

Survey attributes

These are the information about the user’s responses to the surveys, such as survey ID, survey name, survey question, survey answer, etc. You can use this filter to find users who have answered specific surveys or have given certain responses, such as those who have completed a specific survey or who have given positive feedback.

User tags

These are the labels that you can assign to the users, such as VIP, loyal, new, etc. You can use this filter to find users who have certain tags, such as users who are VIPs or users who are new.

Conversation labels

These are the labels you can assign to the conversations, such as resolved, escalated, follow-up, etc. You can use this filter to find users who have conversations with specific labels, such as those who have resolved or escalated conversations.

Segment

These are the groups of users you can create based on specific criteria, such as users who have purchased more than 10 times, who have given a negative rating, etc. You can use this filter to find users belonging to specific segments, such as loyal or dissatisfied customers.

Scenario

Say you want to filter contacts on the audience table based on the segment they belong to. The segment name are such as ‘High-Value’, ‘Medium-Value’, ‘Low-Value’, ‘New’, ‘Returning’, etc. You can use the filter option ‘Segment’ to apply different criteria to the segment column. For example:

  • If you want to see only the customers who are in the ‘High-Value’ segment, you can use the conditional logic ‘Is’ and select ‘High-Value’ from the drop-down list.

  • If you want to see all the customers except those who are in the ‘Low-Value’ segment, you can use the conditional logic ‘Is not’ and select ‘Low-Value’ from the drop-down list.

  • If you want to see the customers who are in any segment that contains the word ‘Value’, you can use the conditional logic ‘Contains’ and type ‘Value’ in the text box.

  • If you want to see the customers who are in any segment that does not contain the word ‘Value’, you can use the conditional logic ‘Not contains’ and type ‘Value’ in the text box.

  • If you want to see the customers who are in any segment that starts with the letter ‘N’, you can use the conditional logic ‘Starts with’ and type ‘N’ in the text box.

  • If you want to see the customers who are in any segment that ends with the letter ‘G’, you can use the conditional logic ‘Ends with’ and type ‘G’ in the text box.

And OR Options

The AND and OR filters are used to combine multiple conditions in filters. They can help you narrow down or broaden your audience based on your criteria.

  • The AND filter returns only the results that match all of the specified conditions.

For example, If you want to see the customers with first name as Shubham and last name as Sharma, you can use the AND filter to see the relevant result.

If a contact has 'Shubham' in their first name and 'Singh' in their last name, they will not be displayed as result. AND displays results when the contacts fulfils all the filters applied.

  • The OR filter returns the results that match any of the specified conditions.

For example, If you want to see the customers with first name as Shubham and last name as Sharma, you can use the OR filter to see the relevant result.

If a contact has 'Shubham' in their first name and 'Singh' in their last name, they will be displayed as a result. OR displays results when the contacts fulfil any one of the filters applied.

Using Filter Options

  1. Click on the Add Filter option available on the Audience Page.

  2. Add a filter based on which you want the customer details to be displayed. A list of filter options appears from the drop-down. Choose that best suit your needs.

For eg: say you want to search for contact name with 'Vikas' as first name. So you select User attributes>First name.

  1. Once you have selected a filter option, a drop-down appears with different conditions.

For searching the name 'Vikas,' you should use 'Is' and then enter the values as 'Vikas.'

  1. You can add multiple filters by repeating steps 2 & 3.

While using multiple filters, carefully use AND OR options for relevant results.

  1. Once done, click 'Apply', and the filtered data will be displayed in the audience table.

By combining multiple filters, you can perform highly targeted searches and retrieve specific sets of contacts that meet precise criteria.

Search and Filter Options

Use search and filter options together to utilize the feature to full potential. Here is how you can use this:

Scenario For Using Search and Filter Option Together

Suppose you're looking for a contact named Sahil. On searching, you see that a list of contacts appears with the name Sahil.

How do you find your one?

Suddenly, you remember that you contacted him 3 days ago. So, you utilize filter options to omit the unnecessary 'Sahil' in the table.

For the same, you choose last active under user attributes.

insert

Select less than X days ago, enter the value as 3.

insert

The table will now show the 'Sahil' you're looking for.

insert

// Use multiple filter to further narrow down your search.

Using Multiple Filters

Combine multiple filters to see contacts that fulfils or matches with all your conditions. Here is an example where multiple filters can be used:

Scenario For Using Search and Filter Option Together

Suppose you want to create a segment for contacts who are:

  • From India

  • Have opted in for WhatsApp messages

  • Have not been active for more than 30 days

  • Have a birthday in February

  • Were referred by Google sheet

To filter these contacts, you can use the following user attributes and conditional logic options:

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