Promising Early Results for Data Quality and Marketing Performance
What do you like best about the product?
DQE is helping us improve our data quality and the performance of our marketing campaigns. We are still finalizing the implementation, but the first results are very promising. The team is responsive and attentive.
What do you dislike about the product?
The integration process can be slightly time-consuming.
What problems is the product solving and how is that benefiting you?
DQE One helps us identify duplicate records and merge them efficiently, ensuring a cleaner and more reliable database. This directly improves the quality of our data and the effectiveness of our marketing actions.
A reliable data quality solution that pays for itself through fewer delivery failures.
What do you like best about the product?
The real-time address autocompletion and validation drastically reduces checkout errors and failed deliveries, which directly improves our clients' conversion rates and logistics costs.
What do you dislike about the product?
The admin interface could use a more modern refresh
What problems is the product solving and how is that benefiting you?
It eliminates invalid addresses and incomplete customer data at checkout, which reduces failed deliveries, lowers support costs, and improves overall conversion and customer satisfaction.
Enterprise grade data quality solution
What do you like best about the product?
Enterprise-grade scalable data quality solution
What do you dislike about the product?
Not all countries / regions are supported to my knowledge.
What problems is the product solving and how is that benefiting you?
High‑performance data quality management that validate, correct, and unify customer data in real time. Their platform excels at deduplication and contact data enrichment, helping maintain clean, reliable CRM databases.
DQM - efficient and robust
What do you like best about the product?
What really stands out to me is the quality of the Customer Success and technical teams. They’re responsive, knowledgeable, and genuinely helpful at every stage of the lifecycle—from implementation through ongoing improvements.
What do you dislike about the product?
Some configurations can take a bit of time to fully fine-tune, especially when your data model is more complex, but the support team helps make the overall process smoother and easier to manage.
What problems is the product solving and how is that benefiting you?
For us, data quality and reliability are key. We’ve seen an improvement in lead conversion thanks to having correct email, phone, and address details.
Smooth Salesforce integration and very responsive DQE teams
What do you like best about the product?
Very high availability and responsiveness of the DQE teams. A deduplication solution that integrates perfectly into our Salesforce CRM.
What do you dislike about the product?
The deduplication rules cannot be as advanced in real-time as they are on a static database.
What problems is the product solving and how is that benefiting you?
The quality checks of our contact data have allowed us to clean up our database and increase the contactability of our clients. The deduplication of our different portfolios within a single CRM has allowed us to have a 360-degree view of the portfolio of our multi-equipped clients.
Reliable tool for maintaining high-quality CRM data
What do you like best about the product?
DQE One is a reliable and essential tool for our CRM. It allows us to quickly identify whether postal addresses, phone numbers, and emails are valid or incorrect and correct them when needed. It integrates well with our workflow and helps maintain high data quality.
What do you dislike about the product?
There is nothing significant to report. The tool meets our needs and performs reliably.
What problems is the product solving and how is that benefiting you?
DQE One helps us detect and correct inaccurate contact information in our CRM. This ensures cleaner and more reliable data, which improves the efficiency of our teams and the overall quality of our customer database.
Very Good Experience
What do you like best about the product?
The data quality is strong, and the overall experience feels smooth and fluid.
What do you dislike about the product?
I ran into some issues during the backup on my existing client. Even though the data quality in our Salesforce wasn’t perfect, I still think DQE should improve its matching.
What problems is the product solving and how is that benefiting you?
DQE accelerates our sales process by helping our sales agents quickly find client information without having to ask the client for additional details.
DQE: an effective solution, supported by a responsive and trustworthy team
What do you like best about the product?
DQE is a truly effective solution, but what makes all the difference is the team: responsive, available, and always ready to assist. A true trusted partner.
What do you dislike about the product?
Nothing blocking, but the interface could be even more intuitive on certain paths. Some features deserve to be simplified to improve fluidity.
What problems is the product solving and how is that benefiting you?
- Operational time loss: manual corrections, customer feedback, additional processing.
Data quality has improved and compliance and deduplication workflows are now fully controlled
What is our primary use case?
I address and normalize customer data for validation and deduplication within our daily data pipeline, focusing on autonomy, compliance, and scalability. At Personnel, we use DQE One Standalone to clean, validate, and deduplicate addresses and customer contacts in our Points of Interest (POI) and customer databases. My goal is to ensure optimal data quality before integration into our CRM and ERP systems while maintaining full control over our infrastructure, including GDPR compliance and internal security.
DQE One Standalone has become a cornerstone for our R&D team, particularly because of autonomous deployment. Unlike other tools, it integrates directly into our infrastructure (Azure), eliminating external dependencies—a critical factor for sensitive projects, such as CAC40 customer data. The precision of the ADDRESS module reduced address errors by 22% compared to our previous solution, with real-time validation against official repositories like USPS and La Poste. Its user-friendly interface allows even non-technical teams, such as marketing and sales, to import, clean, and export datasets in one click, with minimal training.
How has it helped my organization?
Key improvements include time savings, as automated quality checks cut manual data cleaning time by 40%, freeing up resources for higher-value tasks. Enhanced compliance is achieved by operating on our internal servers, eliminating risks associated with third-party data transfers, which is a major win for our Data Protection Officer. Scalability is another improvement, as the tool handles peak loads during marketing campaigns without performance degradation.
What is most valuable?
The ADDRESS Module validates and standardizes addresses, including international ones, with a 95%+ match rate. Smart deduplication identifies duplicates even with minor variations, such as "Avenue" vs. "Av.", cleaning up 15% of redundant contacts. Azure, AWS, and Salesforce integration allow the tool to be deployed in two days, and it is seamlessly compatible with Salesforce and Power BI. Job history lets me reprocess previous datasets with the same parameters, which provides a huge advantage for audits.
What needs improvement?
DQE One Standalone could be improved with technical documentation that, while clear, could include more real-world examples for advanced use cases, such as Airflow integration. Adding native connectors for Snowflake or Databricks would also be a plus. Additional features that should be included in the next release include a real-time suggestion API to validate data at entry, such as web forms, similar to DataQ but in Standalone mode. Customizable dashboards to visualize data quality by segment, such as B2B vs. B2C customers, and business validation rules that allow users to create custom rules, such as the French SIRET format, would be valuable.
Which solution did I use previously and why did I switch?
I used a mix of Google Maps API for addresses and in-house scripts with Python. Issues included unpredictable costs, as pay-per-use pricing with Google was hard to budget. DQE One Standalone resolved these issues with an all-in-one, internally controlled solution. High maintenance was another issue, as scripts required constant updates to keep up with repository changes. The lack of autonomy was another issue due to reliance on external vendors for deduplication.
What's my experience with pricing, setup cost, and licensing?
Transparency in the licensing model, whether subscription or usage-based, is clear, with no hidden costs. For SMEs, ROI is quick, under 6 months in my case. I recommend starting with a PoC on a critical dataset, such as a customer base, to measure impact before scaling.
Which other solutions did I evaluate?
We tested Loqate, which is powerful but inflexible with limited customization. Experian Data Quality is expensive and complex to deploy. Open-source tools, such as OpenRefine, lacked support and scalability. DQE One Standalone stood out for its balance of flexibility, cost control, and responsive support.
What other advice do I have?
This solution is ideal for companies with compliance needs, such as GDPR and ISO 27001, or for those with large data volumes, such as in retail and banking. It is not ideal for startups with very basic needs.
Proactive Team, Solid Solutions, and a Clear Roadmap
What do you like best about the product?
The proactiviy, the solution, the roadmap
What do you dislike about the product?
Nothing so far - all team are really supportive
What problems is the product solving and how is that benefiting you?
Data management, data quality, dedup, data cleansing
