Data Deduplication for On-Demand CRM

How to manage the growing challenge of duplication in your CRM system

In our portfolio of expansion stage software companies, the use of on-demand CRM systems such as Salesforce.com is very widespread. As a result, as part of our strategic consulting engagement — especially in sales and marketing support projects — we often consult on the proper setup and management of these CRM platforms and their associated add-ons.

One particularly challenging area of on-demand CRM implementation and management is data deduplication. While deduplicating any sufficiently large database is already hard enough, doing that to a database that is sitting in the clouds really takes it up a notch. Because of the large amount of records involved in each deduplication operations, we have to invariably use the platform’s Application Programming Interfaces, which can be limited and restricted as well. After each API call, best practices process also calls for verification procedures to ensure that the data is correctly modified according to the instructions and inputs.

Given the complexity of matching and merging data in on-demand CRM, it makes sense to focus more on the preventive measures to avoid duplicates from being created in the first place. These strategies include the standardization of import data (enforced by both rules and technologies), creating an audit trail for every batch of import as well as building duplicate-matching keys into the CRM record to make matching more efficient. Indeed, many of these measures should be thought of even at the very beginning of a CRM implementation — the design of data structure and the definition of the lead flow.

In looking for resources that would be helpful to our portfolio company’s CRM administrators, I found a couple of great resources that elaborated on these measures. This article is too brief for more to get into all of them in details, but on the whole, they really describe a number of great ways to best manage CRM duplication issue with systematic prevention. Explore these and hopefully they are equally helpful to you.

Sf.com Applied Data Quality Tutorial

Is your CRM at risk? (by Donato Diorio, CEO at Broadlook Technologies)

CRM Data Cleansing & Enrichment – Data Management Best Practices at ReadyContacts.com