Identity Resolution

Your sales and marketing teams use specialized tools (e.g. Salesforce for sales; Google and LinkedIn for ads; Eloqua, Marketo and Pardot for your emails; etc.) to manage how customers and prospects interact with your business. These tools store a snapshot of the customer’s engagement, leading to data fragmentation.

Consolidating this fragmented customer data into a customer master enables your team to use all the data about your customers at your disposal to create personalized sales and marketing campaigns.

Identity resolution helps your team quickly combine data from your systems to create a customer master.

What does identity resolution engine do?

Data about your customers and prospects can be categorized as:

• Meta data – This provides more information about your customers and prospects. Examples include company information (name, domain, address, phone number, etc.) and user information (contact and lead information, such as email, phone number, name, title, department, etc.).
• Engagement data – This category represents information on how your customers and prospects engage with your business. Examples include transactions (what products and services your customers have bought and when), web visits, sales and marketing activities, etc.

Lattice organizes data as Accounts and Contacts within these accounts. Meta data and Engagement are added as additional attributes to Accounts and contacts.

With Identity resolution, Lattice can create a customers master by

1. Matching accounts from multiple systems to create a unified account
2. Matching contacts from multiple systems to create a unified contact
3. Associating contacts from multiple systems to accounts (lead to account matching)
4. Creating new accounts if the contacts do not match to an existing account

How does identity resolution work?

At the core, identity resolution involves matching and merging accounts and contacts from multiple systems to create a customer master.

The Matching process involves detecting if accounts and contacts from multiple systems represent the same account or contact.

The same account or contact could have different values across systems (e.g. A contact’s title could be different in multiple systems). The Merging process involves ensuring the value in the customer master is from the system that is most accurate.

Matching Accounts

The above examples illustrate how identity resolution can match accounts from multiple systems (CRM, Data Lake & 3^rd Party Data) to a single account in Lattice.

CRM and Data lake system share a common ID (CRM_ID). Lattice can use a shared ID across systems to create a deterministic match. This guarantees that identical accounts from your system continue to be represented accurately in Lattice.

Identity resolution can also match data when a deterministic match is not possible. The 3^rd party data does not have an ID, but has additional information (Name, Website, Country – Match Attributes) that can be used to find a matching account. In this example, Lattice is able to use this information and match to an existing account.

The resulting Account in Lattice combines data from all the systems to create a master account. In addition to retaining all the system specific IDs, Lattice also assigns a global ID for the account that can be used in the future to identify this account.

Lattice uses the following rules to match accounts from multiple systems:

1. Deterministic (based on ID) matching has the highest priority. If two systems share a common ID, Lattice will automatically match based on their IDs.
2. A system may have a unique ID to identify unique records from each other but may not share a common ID with another system. Lattice relies on non-deterministic matching for such a system. With non-deterministic matching, Lattice relies on other clues (also known as Match Attributes) to determine the account. Lattice uses the following matching keys: Account Name, Website or Domain, Location (Country, City, State, Postal Code) and DUNS. Lattice uses the following criteria to find a matching account:
   1. If domain/Website and Country is available, Lattice tries to find a matching account with the exact domain/Website and country in the customer master. Lattice automatically uses USA as the default country if no country is provided by the system providing new data.
   2. Next, Lattice tries to find a matching account with the exact name of the account and country in the customer master.
   3. Next, if the new system provides DUNS, Lattice uses DUNS to find a matching account with the same DUNS in the customer master.
   4. Next, Lattice uses fuzzy matching using Name, Website and location information to find a matching account.

Matching Contacts

The above examples illustrate how identity resolution can match contacts from multiple systems (CRM Contact, Lead from Marketing Automation & click from Advertising) to a single contact in :attice.

CRM and Marketing automation don’t share a common ID, but Lattice will match them based on email while the ad click and lead are matched based on cookie ID.

The resulting contact in Lattice combines data from all the systems to create a master contact. In the example above, the contact does not have a corresponding account and thus a new account is created in Lattice. The resulting account is created based on the email domain, as that is the only information available about the company of the user.

Lattice uses the following rules to match contacts from multiple systems

1. Deterministic (based on ID) matching has the highest priority. If two systems share a common ID, Lattice will automatically match based on their IDs.
2. A system may have a unique ID to identify unique records from each other but may not share a common ID with another systems. Lattice relies on non-deterministic matching for such a system. With non-deterministic matching, lattice relies on other clues (also known as Matching Keys) in the contact to determine the contact & account. Lattice uses the following matching keys: Email Address, First Name, Last Name, Phone Number and Account Info (DUNS, Name, Website, Location). Lattice uses the following criteria to find a matching contact:
   1. Lattice does an exact match using the exact Email and account Information.
   2. Next, Lattice does an exact match using the exact First Name, Last Name & account Information.
   3. Next, Lattice does an exact match using Email to find a matching contact.
   4. Finally, Lattice does an exact match using First Name, Last Name and Phone to find a matching contact.

Merging data for accounts and Contacts

Any new data coming in to Lattice first goes through the matching process. If the system finds a match, Lattice then merges the new account or contact to the account and contact already in the customer master in Lattice.

The merging process could result in

1. New attributes (fields) added to existing account or contact
2. Overwriting data of existing attributes if the new system also provides new value for an attribute that already exists in Lattice.

New Attributes

Type, Product Usage, Employee Range, Country are all examples of each system providing new data. Lattice adds all of these attributes to the account in Lattice.

Merging data

In this example, both CRM and the lead from Marketing Automation provide Title information. The values from these systems are different. Lattice keeps value from only one system. Lattice relies on System Priority to choose the value from the system that has the highest priority.