Duduping a CRM is like an equation waiting to be solved. Just like a high school math, the more variables you know the values for, the easier the problem is to solve and the more likely you will come up with the correct answer.
CRMs include is a vast number of “Data Markers”. These markers are a literal road map to filling in missing data. For example, if 100% of the emails for a particular company have the email format of Firstname.Lastname@domain.com, then you can probably fill in missing emails for other contacts with confidence. If you have the email domains for contacts, but the account record is lacking a website, that can be filled in too.
A company’s website address is a unique identifier. It is more important than the company name. Look at Peoplesoft as an example: long after the company was acquired by Oracle, you could navigate to www.peoplesoft.com. A few years later, it was totally absorbed…but the website did outlive the company.
Done properly, leveraging data markers within a CRM allows the properly trained consultant to pre-fill data for a more complete picture…BEFORE deduping. In addition the data should be standardized (sometimes called Normalized) before the dedupe process is done.
If you take the correct measures of: (1) data normalization and (2) data fill before deduping, your dedupe process will be greatly improved.
Some definitions:
Field: is a single value like a name, email, phone, date or note.
Record: is a set of fields.
In a spreadsheet, it might be row or column of data, depending upon the structure of the sheet. In a CRM, for example, a record could be an Account or Contact.
When fields are incomplete or become outdated, quite often, the record gets deleted. This happens in CRM’s, databases, Excel spreadsheets and in Market Automation Systems.
This is an error. Never delete records.
Why? Think of each field within a record as part of a math proof.
Like high school Geometry, the more given values you have, the better your chances to solve an equation. For example, if you only have a first name and email where does that leave you? Lets look at an example:
Starting data:
First name: Donato
email: donato@broadlook.com
What happens if we perform a “data proof”?
After each step, the new fields found are in RED.
Step 1: Is the email a free email provider like gmail, yahoo, etc? If not, fill in the company domain. The company domain is unique. Once you have it, there are many options to find and add more detail to your record. If you have an entire list of emails, I’ve included a video demo at the end of the blog that steps through the entire process.
After step 1, we have:
First name: Donato
email: donato@broadlook.com
domain: broadlook.com
Step 2: Is the website alive, if yes, visit is and fill in the company name
After step 2, we have:
First name: Donato
email: donato@broadlook.com
domain: broadlook.com
Company: Broadlook Technologies
Step 3: Extract contacts from the website. This can be done manually, but is much more efficient using automation. The Profiler can turn 60 minutes of research into a click of a button.
After step 3, we have:
First name: Donato
Last name: Diorio
Title: Founder & CEO
email: donato@broadlook.com
domain: broadlook.com
Company: Broadlook Technologies
Bio: Donato Diorio is a pioneer in the field of Internet research. As software architect and the owner of a top billing placement firm, Donato envisioned applications that could automate many of the most time-consuming research functions performed by his recruiters. With the assistance of a team of developers, Donato created a series of innovative tools that immediately impacted revenue for his firm…
All of the above could have been derived from an email only, we did not even need the first name. Additionally, we now have 10 additional contacts that could also be attached to the single contact.
So if you are thinking about deleting incomplete or outdated records in your CRM. DON’T DO IT!
So if you are thinking about deleting incomplete or outdated records in your CRM. DON’T DO IT! Your outdated and incomplete records contain wonderful possibilities. In addition, if you’ve tracked the source of where that original data came from such as a trade show or web form submssion, it makes it all more valuable.
Lastly is there any circumstance to ever delete a record? Yes, if no value exists in any field, nor can any value be extrapolated from it, then it can be deleted. Example: a few times a month, we get “Bill Gates” from Microsoft filling in a web form.
Here is a video that steps through the entire process:
Follow Donato Diorio on twitter: @idonato
