Vertify Features & Capabilities

Vertify Features & Capabilities

CONTENTS What is Vertify?

The Overview Page Users and Groups

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Users Groups

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Environments and Workspaces Environments Workspaces

Systems Movements Mappings Field Transformations Format Transformations Move Actions Filters Merge Rules

Schedules and Email Alerts Error Reporting and Data Diagnostics

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What is Vertify?

Vertify aligns your revenue teams, helping to strategically orchestrate the data flow between your marketing, sales, customer support, and finance platforms. It automatically manages the flow of information between your applications so you can eliminate data silos.

The primary navigational points in Vertify are: Overview, Workspaces, People, Configure, and the Help Center.

The following sections dive deeper into the features and functionality of Vertify and its tools.

The Overview Page One of our mantras here at Vertify is “transparency and accuracy”. Via the Overview page, up-to-date information can be viewed about your active integration, including the movements that are currently running, what’s scheduled to run in the future, and record counts. Our customers use this page as a bird's eye snapshot view of their integration’s performance.

Users and Groups Within the People section in Vertify, there are two distinct areas: Groups and Users. A User is anyone who accesses the Vertify platform, while Groups are used to organize together Users who have the same access and permissions.

Users Each user is given their own respective username and password. Vertify supports both Multi-factor Authentication (MFA) and password expiration for individual users.

A user can be assigned to one or more Groups. Additionally, primary Vertify Users can be given Admin access, allowing them to delete records, create and assign permissions for other Users, and adjust a record’s metadata in Vertify.

Groups Groups allow you to tailor Workspace access to a select group of Users. Additionally, Groups can be used to define who receives Email Alerts about the integration (more on Workspaces and Email Alerts later). Group names are customizable, and there is no limit to the number of Groups you can create.

Environments and Workspaces Environments and Workspaces are set up within the Configurations area of Vertify and provide a way to organize your business units and integrations within Vertify. The name of each Environment and Workspace is customizable to your business, and the number of Environments and Workspaces allowed is dependent on your Vertify license tier.

Environments Environments are used to partition business units within Vertify. For example, you might choose to have separate Environments set up in Vertify for your Europe, North America, and Asia divisions. Users with access to multiple Environments can toggle between them by clicking the Environment dropdown in the left hand menu.

Workspaces Workspaces live within Environments in Vertify, and multiple Workspaces can exist within a single Environment. For example, you may have a Production Workspace and a Sandbox Workspace within your Europe Environment. As mentioned previously, you can control which users have access to your various Workspaces via Groups.

Systems Vertify is designed to make moving data between your applications easy and efficient. Within Vertify, the applications we connect to are called Systems, and Vertify supports connections to over 80 different Systems.

Commonly, applications exist in the cloud, so Vertify is able to communicate with them via their API. If an API is not available, we are also able to connect to Systems directly via ODBC or SFTP. Each System has configurable parameters that allow you customize the way we connect to each of your applications. Additionally, each System comes with its own ReadMe file and Setup Guide with instructions on how to fill out the parameters and find the credentials you need within your applications.

Once a System is set up, Vertify will automatically pull in all available objects - including custom ones - that you can then map and use within your integration. Additionally, Vertify is able to collect all standard and custom fields, as well as the actual data, within the objects you want to integrate with your other System(s).

Movements The Movements page is the command center for your integration. Here, you can effortlessly move data from source to target systems either manually for testing purposes or automatically once you’re ready to go live.

You can also click into a specific movement to see the field mappings configured for that movement, view movement history, set up a new movement, and resolve sync errors from this page.

Movements are comprised of two essential mapping components: ●

Object Record Mappings: This enables the mapping of source records to target records, creating a structured data pathway. For example, CRM Accounts are typically mapped to the Marketing Automation Platform’s Company object, while CRM Contacts are typically mapped to the MAP’s Person object.

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Field Mappings: This allows you to zoom in to map individual fields within source records and target records, allowing for precise control over your data flow. For example, the Email Address field in your CRM is typically mapped to the Email field in your MAP.

*Note: Your onboarding specialist will start you off with a best practice set of object and field mappings for you to build off of and customize so you don’t have to configure your integration from scratch. We integrate with these applications all the time, so we know the best structure to start with to set you up for success!

Mappings Configuring a new object or field mapping is a simple drag-and-drop process - simply grab the source object or field from the source section and drop it where it needs to go within the target section to set up a new

one-to-one mapping. Handy search boxes at the top of each source and target section help you quickly find the objects or fields you’d like to map.

While a simple one-to-one mapping can address many needs, sometimes you require more precise control over how the data is moving. This is where transformations come into play. There are two types of transformations in Vertify: ●

Field Transformations: Field transformations play a crucial role in data integration and mapping processes, allowing you to manipulate, convert, and set conditions on individual fields as data moves from a source system to a target system. These transformations enable you to tailor your field mappings to meet specific business and system requirements to ensure your data flows seamlessly into the target system.

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Format Transformations: Format transformations are designed to ensure your data is polished and formatted to fit into your target system. These transformations help you to standardize and harmonize your data for your business processes and system requirements.

Field Transformations The below field transformation types are available in Vertify, and you can stack the transformations on top of each other to configure an advanced transformation (i.e., you can configure the mapping to do a Lookup transformation to another object and then default to a static Value transformation if no match is found). This provides you with flexibility and control over your integration and makes field mapping a dynamic and adaptable process.

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Map Transformations: The Map transformation is the default transformation type and allows you to assign values from a source field directly to a target field without any alteration. The drag-and-drop process outlined above sets up a standard Map transformation. ○ Use Case: Map transformations are useful when the source and target fields have compatible data formats and contain the same information (i.e., Email Address, First Name, Title, etc.).

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Value Transformations: Value transformations allow you to assign a custom value to a target field, irrespective of the source data. ○ Use Case: Value transformations are handy when you need to enforce specific values in a target field (i.e., setting a checkbox field in the target system to “True”).

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Translate Transformations: Translate transformations are used when the data stored in the source field differs from that in the target field. It involves the use of Translation Tables that are loaded into Vertify to convert values from one format to another. ○ Use Case: Translate transformations are valuable when you need to convert source data into a format that matches the expectations of the target system (i.e., converting Ids or country codes into their friendly names).

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Lookup Transformations: Lookup transformations allow you to associate a field in your mapping with a field that exists on a different, related record, either within the source or target system. ○ Use Case: Lookup transformations are beneficial when you need to create relationships between different records (i.e., associating a CRM Contact’s Customer Id with the corresponding Account Id in the Marketing Automation Platform) or when you need to pull a field into your mapping that exists elsewhere in your source system (i.e., looking up the Sales Rep that’s assigned to the CRM Contact’s associated Customer record and feeding that through the CRM Contact → MAP Person movement).

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Split Transformations: The Split transformation is used to divide data from a single field in the source system into multiple fields in the target system. ○ Use Case: Split transformations are handy when your source system stores data in a way that makes it necessary to be separated into distinct fields in the target system (i.e., splitting a full

name into first and last name fields).

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Combine Transformations: Combine transformations merge values from multiple fields into a single field in the target system. This can include adding characters or custom separators, as well. ○ Use Case: Combine transformations are useful when you need to consolidate data from multiple source fields into a single, readable field in the target system (i.e., combining two different Id fields to create a new, unique primary key).

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Math Transformations: Math transformations allow you to perform mathematical operations (addition, subtraction, multiplication, division) between multiple numeric fields, altering the data during mapping. ○ Use Case: You can use Math transformations when you need to perform calculations or mathematical manipulations on data as it moves from source to target (i.e., calculating a lead’s

score change between the old score and new score fields).

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Condition Transformations: Condition transformations enable you to specify a set of circumstances under which a mapping should occur. They are useful when the field mapping varies based on specific qualifications or situations within the source record. ○ Use Case: You can use Condition transformation to set rules for data mapping, and multiple conditions can be evaluated within a single field mapping. Condition transformations can be used to assign a default value on the target record if certain criteria are met or for evaluating multiple conditions to determine the final mapping (i.e., feed specific subscription codes based on what marketing materials a lead is subscribed to and unsubscribed from).

Format Transformations Format transformations are particularly important when integrating data into a target system with strict formatting requirements. They allow you to cleanse, standardize, and prepare data for seamless integration, ensuring that it not only fits into the target system but also aligns with your data format expectations. These transformations empower you to maintain data quality, consistency, and compliance with the target system's specifications. ●

Truncate Formatter: Truncate formatters are used to limit the number of characters in a source system field, ensuring it matches the length specified for the target system. ○ Use Case: This transformation is valuable when a field in the target system has a character limit, and exceeding that limit would result in sync errors. Truncation helps ensure data fits within the allowed length.

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Round Formatter: The Round formatter is used to adjust numeric values in a source system field to a more explicit representation in the target system. You can round down, round up, or round to a specified number of decimal places. ○ Use Case: Round formatters are beneficial when the target system requires precise numeric values, and the source system provides data with excessive decimal places or precision that needs to be adjusted.

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Phone Formatter: Phone formatters adjust the format of phone numbers to match the specific format required by the target system. There are five phone formatting options available to choose from. ○ Use Case: The Phone formatter is useful when the target system expects phone numbers to be in a standardized format but the source system either doesn’t enforce formatting requirements

or uses a different format type.

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URL Formatter: URL formatters allow you to either add or remove the leading "http://" or "https://" from URLs, aligning them with the specific URL format expected by the target system. ○ Use Case: The URL formatter is beneficial when the target system necessitates URLs to be in a particular format to function correctly or to comply with system requirements.

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Case Formatter: Case formatters modify the casing of the data being synced to the target system.

There are four different casing options available to choose from. ○ Use Case: The Case formatter helps ensure that text data in the target system adheres to consistent capitalization rules, improving data readability and uniformity. This is particularly important for data that may be pulled into marketing or sales emails for personalization.

Move Actions Move Actions are another way to control when and how each field is synced. Move Actions define when data is allowed to be updated and overwritten in the target system, allowing you to maintain data quality and your source of truth for each field. There are four Move Action options available: ● ●

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On Add: Data points with this Move Action will only be synced if Vertify is creating a brand new record in the target system.

On Update: Data points with this Move Action will only be synced if Vertify is updating an existing record in the target system. If the current value in the target system is different from the data that is being synced, the field in the target system will be updated and overwritten.

On Add/On Update: Data points with this Move Action will be synced for all records, whether they are new or existing. If the current value in the target system is different from the data that is being synced, the field in the target system will be updated and overwritten.

On Add/On Update If Empty: Data points with this Move Action will be synced for new and existing records, but only if the field in the target system is blank. New data will be added into the target field, but data will never be updated or overwritten if it is already populated.

Filters While Transformations and Move Actions are configured on a field-by-field basis, Filters affect the sync rules for an entire record. Filters can be customized on a movement-by-movement basis.

Filters help you maintain the cleanliness and integrity of your target system by allowing you to selectively control which records from the source system make their way to the target system. Filters help to ensure that only relevant and valuable data reaches the target system. This precision minimizes the risk of cluttering your target system with irrelevant or erroneous data, leading to cleaner and more meaningful data sets.

If no Filter is defined for a movement, then all records will be eligible to move to the target system. If a Filter is defined on a movement, then only the records that pass the Filter criteria will be eligible to move.

Additionally, you have the option of setting up both “AND” and “OR” conditions within your Filter criteria (i.e., the source record must have an email address AND it must have a phone number OR it must have a lead

score of at least 50 points in order to be qualified to move to the target system).

Merge Rules Also known as deduplication rules, Merge Rules allow you to effortlessly link records between source and target systems and reduce the chance of duplicates being created in your target system.

Merge Rules are able to match records based on customizable criteria, such as identical fields like an email address or similar strings like a company name. When a match is found, Vertify updates the data on the target record it matched with. If no match is found, Vertify will create a new record for you.

Schedules and Email Alerts In Vertify, schedules allow you to automate the process of collecting and moving data once you’re ready to go live with your integration. Multiple schedules can be created that collect and move data in varying intervals.

These intervals can be configured to run from every one minute all the way up to once per month or year.

Schedules that only collect data for reference purposes, as well as schedules that both collect and move data, can be configured based on your needs.

Email Alerts to specific User Groups can also be enabled within each Schedule. These alerts give a synopsis of what occurred within the integration during the specified timeframe, including what sync errors happened, if any.

Error Reporting and Data Diagnostics Vertify not only surfaces sync errors that are occurring within your integration, but the platform also tells you which records are experiencing the error, why the error is happening, and how to resolve the error within the source system. Our Help Center is a fantastic resource for troubleshooting and resolving specific sync errors that may arise.

Most sync errors happen because of dirty data in the source system (i.e., a record has missing fields that are required in the target system or it has fields that have been entered incorrectly). So, surfacing these data issues also enables you to identify bad data processes, clean and update your data, and prevent dirty data from entering your applications in the future.