Duplicates – ain’t nobody got time for that

Duplicate Records: Every Administrator knows about this problem, and even each CRM user is facing this issue in his daily work. In the Spring’15 release salesforce.com has released a feature the CRM world was desperately waiting for: the duplicate management.

//Note: This blogpost is also available in german.//


Duplicate Records: Every Administrator knows about this problem, and even each CRM user is facing this issue in his daily work. In the Spring’15 release salesforce.com has released a feature the CRM world was desperately waiting for: the duplicate management (internal name: super de-duper). It prevents your users from entering duplicate records. Together with our “Aptly Data Quality Tool” an effective solution for a clean database.


One of the certification questions for the salesforce administrator exam is: “What should you do when importing new records into salesforce.com?” One of the correct options is: “The import file needs to be free of duplicates.

But the rather honest answer should be: “First I did an export of all my data into excel, then I have tried to use wired excel magic that I found on Google to identify duplicate records which I manually clean afterwards. I am not quite sure, because there are too many contacts named “John Smith” in my database. I have spent minimum 4 hours on these 100 contacts to avoid creating further duplicates”.

But as we know the data import is not the only source of duplicates. Each user is told during the training: “and please search first before creating a new record.

But the difference between theory and practice is that the usage of a CRM system is a pain for most of the sales representatives. Their job is to sell and not to take care of data administration. Another example is the call center agent who has no time to look for the right John Smith, who is actually right now on the phone. So it’s often easier to create a new record.


Duplicate Management in salesforce.com

The duplicate management in salesforce can assist you now. You define the rules to search for existing records, which will apply every time a record is entered (no matter if this happens via the user interface, through an import or via any other interface). And this works for standard- and custom objects. To do so you have to set up matching and duplicate rules.


Matching Rules

The first step is the configuration of a matching rule for  each object (Accounts, Contacts, Leads,…) that should be included in the duplicate search. Here, you define the fields that should be used to search for existing records. Using the exact or fuzzy method you can determine on field level if e.g. records with exactly the same email address or with similar first and last name are also chosen (meaning a record named J. Smith will appear when searching for John Smith).



Duplicate rules – but why?

The best practice case for duplicates is the use of leads and contacts. If you want to create a new lead named John Smith, you want to ensure that this person doesn’t already exist as a contact. Therefore you can created different duplicate rules so that you can compare a new contact with all existing contacts and also with all existing leads.

In addition to that you can configure:

  • when this rule will apply (on create and/or on insert)
  • if just a hint about existing duplicate should appear or if the user is blocked from entering the record
  • how you would like to proceed with existing sharing rules that you use to grant access to your database records
  • the user should be informed about potential duplicates when saving the record or if this information should be saved in an additional duplicate report. this way a data steward can work on this issue at a later stage.


All right, but my database contains already tons of duplicates. What can I do?

The duplicate management in salesforce is just a ”bouncer” who prevents new duplicates from getting in. But in most of the cases the bouncer was hired after the party has started and cannot check all the “guests” who are already at your party.

That’s exactly where the Aptly Data Quality Tool steps into the arena. With this powerful tool you can clean your existing database – even automatically if you like .


Finding duplicate records

Define your search criteria for all standard- and custom objects and apply a scoring for each of your criteria by importance.

After searching and comparing all your records you can check the duplicates, where the duplicate score that was calculated based on your criteria will help you to identify the most potential duplicates. You can even define a threshold so that records with a defined duplicate score will be merged automatically.

…and merging records

Here is what happens when it comes to merging your duplicates: related objects to your duplicates will be merged related to the unique record. But also the fields of each records are compared and merged where possible. But the biggest strength of the Aptly Data Quality Tool is the ability to customize the process of merging according to your business rules.

Here is an example:

When merging two account records into one golden record all tools usually merge all related records of both accounts. But what if both accounts have an existing bank account linked to them and your business rules define that only one active bank account can be related? Instead of simply merging those records which might break your payment process you can set up merging rules that will prevent the manual and the automated merging of records to protect your business processes.


Ok, got it. What else can I do with the Aptly Data Quality Tool?

With our tool you are able to standardize and harmonize your data. The most popular examples are:

  •    Country Names – You can standardize and harmonize your data, so that you cleanse all your records containing „Deutschland“, „Germany“ und „DE“ to only one valid option. It also allows you to fix incorrect records like „Deutschlnd“ or „Geramny“.
  •   Industry (Verticals) – also here you can use the tool to standardize and harmonize so that you can build better segments. The first step is a data cleanse which allows you to group the results and helps you to consolidate your records to relevant industries.
  •    Job Titles – There are many different Job titles and the Aptly Data Quality Tool to condense your data to enable to to aggregate specific job functions. Typical examples are „IT“, „Marketing“, „HR“ or „Management“, but you can even think of „Upper Management“, „Management“, „Assistance“, etc.

The Aptly Data Quality Tool can be connect via API to all common CRM systems like salesforce.com, but it can also be connected to Marketing Automation tools like Eloqua or Pardot. As a kind of data catalyst for your database the Aptly Data Quality Tool will help you to clean your contact database, to merge records and to isolate bad or incorrect data in your „data bad bank“.

By using an intelligent rule set the Aptly Data Quality Tool is able to analyse and optimize your data logically, e.g. set the country value based on the ending of an email address. This way you don’t need to buy additional data. The tool will help you to get the most out of your database.


Do you have any questions regarding the duplicate management in salesforce.com or are you keen to learn more about the Aptly Data Quality Tool? Contact us via connect@aptly.de!

The following two tabs change content below.

Heiko Jörgens

Heiko ist Business Consultant für CRM und Marketing Automation. Seine Schwerpunkte sind salesforce.com bzw. die force.com Plattform, Eloqua und Pardot. Er versteht sogar etwas von Programmierung und ist daher eine gute Schnittstelle zwischen Kunden und Entwicklung.

Schreibe einen Kommentar

Deine E-Mail-Adresse wird nicht veröffentlicht. Erforderliche Felder sind mit * markiert.