Clients Who Have Used Our Data Quality Services
Data Quality Services Benefits
- Business Efficiency
High quality data streamlines business efficiency and enhances decision making by reducing errors in transactions and optimising delivery processes.
- Understand The Market
Unlock accurate customer insights which enable businesses to understand their target market, refine strategies, tailor product offerings and build relationships.
- Customer Engagement
Quality data provides accurate contact information which helps you enhance customer engagement, improve communication and ensures more effective outreach.
- GDPR Compliance
Our services enable GDPR compliance by providing high quality customer data, reducing the risk of processing incorrect data and helping to strengthen data privacy.
3 Ways To Cleanse & Validate Data With Hopewiser
1. Cloud
Maintenance Free Address Validation. Updated daily, gain access to UK PAF, Multiple Residence, Eircode and International data.
Free access to easy CRM integrations, Rest API and JavaScript client.
Management tool with free detailed usage reports and auto-renew.
Simple, fast and accurate online data cleansing tool.
Secure-by-design. Guaranteed secure data transfer and storage.
2. Software
No limitations. Benefit from multiple lookups and cleanses without being punished for usage.
Cost-effective for large users.
Bespoke. Tailor the software to benefit your user experience.
Ideal for Sensitive Data and Compliance. Data on site.
Works on Many Platforms. Includes a Developer’s Kit.
3. Professional Services
Access to data consultants, product specialists, data project management and integration specialists.
Knowledge to assist/run projects to make the most of your data and help you integrate solutions for you.
Bespoke service for more complex requirements including consolidation. (Single Source of Truth).
Bespoke service for more complex requirements including consolidation. (Single Source of Truth).
Optimise Business Decisions With Data Quality Services
Hopewiser's industry-leading data management services enhances businesses and helps you stay one step ahead of competitors. Take your customer data to the next level by utilising data quality assessments, data enrichment, data suppression and end-to-end support.
Datasets and Data Sources
We use a range of reliable datasets and sources to provide our data quality services like the Royla Mail PAF, Companies House and the Deceased Register, so you can trust us to provide accurate results, every time.
Datasets
Data Enrichment
We can enrich your data by adding missing, or extra information like SIC codes to support your business in its engagement and reach. This enables you to improve your target marketing, profiling, insights and relationship building.
Data Enrichment
Data Quality Guide
Our quick and easy reference guide is free to view and helps you understand the pitfalls of 'bad' data, learn what to look out for when buying third party data and provides easy steps for ongoing data maintenance.
Data Guide
End-to-End Data Services
Our experienced and reliable, in-house team is on-hand to manage the data so you can utilise the software to its fullest potential without falling short at the first hurdle. Get in touch with us today to discuss your data management projects and let us do the rest!
Data Quality Assessment
Suppressions
We use the best suppression dataset providers including MPS and TPS. Improve your data quality and customer privacy protection by removing deceased, gone away or invalid data from your database, and make your organisation a high performer.
Suppression Services
Data Quality Assessment
Take your data to the next level with a data quality assessment from the Address Experts. Reduce risk and costs by merging and purging single and multiple datasets against an agreed set of criteria to eliminate duplicate data and inconsistencies.
Data Audit Case Study
Major Insurance Provider
A major insurance provider engaged with Hopewiser as their preferred address software provider on one of the largest IT infrastructure projects in the UK. The project involved moving its entire IT infrastructure over to a hosted cloud platform including their Address Validation. On completion of the cloud platform, Hopewiser was invited to enter a tender to cleanse the entire book for Motor and Home insurance. The final address record figures are likely to run in to the 10’s of millions.
Hopewiser beat the competition to win the tender and become the preferred Data Cleansing partner. Our solution was more cost effective and utilising a Bureau service gives access to Hopewiser’s knowledgeable staff, tools, enrichment and suppressions without the expense of new software and training staff.
The Full Case Study
Data Quality Services FAQs
Why should I use Hopewiser for data optimisation?
Hopewiser is a trusted data optimiser with businesses across the country using our services. Data optimisation grants you a wealth of knowledge about your customers and target market, whilst fully complying with GDPR at the same time. Available as cloud and software-based, we tailor our platforms to work for you, and our in-house team has over 40 years of experience in data optimisation, and are ready to help you.
What datasets do we use at Hopewiser?
Whether data cleansing via cloud self-service or software & bureau service, you can take full advantage of our accurate, advanced & up-to-date datasets including: Goneaway Suppression, Mailing Preference Service, Mortascreen, National Deceased Register, Re-Mover, The Bereavement Register, Purifi Suppression, Telephone Preference Service, Corporate TPS, Multiple Residence Data, Mortaliti, Next Generation Mortality Screening, Fression gone away file Powered by Zoopla Property Group
What are the different types of data validation?
There are many forms of data validation, all designed to ensure your data is accurate and up-to-date. Some types of data validation include; range validation – entered data falls within a specified range or set of values, format validation – entered data matches a specified format, presence validation – required field is not left blank, length validation – entered data does not exceed a specified length, consistency validation – entered data is consistent with other data in the system, (such as the birthdate matching the user’s age) and data type validation – entered data matches the correct data type.
