Reduce Duplicate Contacts in Marketo to Enable Accurate Personalization and Lower Costs
Challenge
Lely faced a persistent issue with duplicate contacts in their marketing database. Some duplicates were intentional, but many were not. This led to fragmented behavioral data across multiple records, making it difficult to understand customer intent and engagement history. As a result, marketing teams struggled to personalize communications and target the right audience at the right time. The growing number of duplicate records also increased database size, driving up license costs for both Marketo and Salesforce. Previous attempts to resolve the issue had failed, leading the team to accept duplicates as an unavoidable problem until a new approach was identified.
Solution
The chosen solution uses Make.com to automate the identification and merging of duplicate contacts in Marketo. The process starts by generating a list of potential duplicates based on key fields such as name, company, and email address. Make.com then evaluates each group to confirm if they are true duplicates. For confirmed duplicates, customizable rules determine which record should be kept as the ‘winner’ and which data fields should be preserved from each record. The solution is modular, allowing for adjustments to the winner criteria and field selection logic to fit Lely’s specific needs. The approach is practical because it addresses the most frequent duplicate scenarios first, rather than attempting to resolve all duplicates at once. This targeted method reduces risk and complexity, and the modular design means it can be adapted for use with other platforms if needed. No viable alternatives were previously available, making this the first credible solution for Lely’s deduplication challenge.
Impact
By consolidating duplicate contacts, Lely expects to gain a single, accurate view of each contact. This will improve data quality and enable more effective, personalized marketing efforts. The solution should also reduce operational complexity and lower licensing costs by shrinking the database size. While direct metrics are not yet available, the expected outcome is improved engagement and higher conversion rates due to better targeting and cleaner data.