REDPOINT DATA READINESS HUB
Data that Delivers
The Data Readiness Hub gets your customer data ready to power any AI or CX initiative across the enterprise. It delivers the most accurate and complete customer Golden Records – data that is cleaned, enriched and unified.
3X conversion lift
from better match rates
80% reduced
manual data prep
97% reduction
in data processing time
1 million duplicate
customer profiles removed
Effortless Data Readiness with Proven Results
Redpoint customers improve outcomes, speed up results, and boost productivity — no code required.
Bad Data Means Big Problems
Bad data inflates costs, degrades AI performance and undermines CX and personalization. Redpoint ensures your customer data is clean, complete and ready for action — giving teams confidence in every decision and output.
The RIGHT Data Drives Smarter CX
- Automatically and continuously cleanse and standardize data across all sources
- Apply flexible, AI-driven identity resolution to unify records
- Keep Golden Records timely and current with real-time profile updates
Deliver Customer Impact Faster — Without Writing Code
- Launch production-ready data pipelines in minutes — no code required
- Process data sets of any size quickly to eliminate backlogs and accelerate time to value
- Empower teams with direct access to clean, high-quality data
Stay Flexible and Future Ready
- Run in SaaS, private cloud or on-prem environments — your choice
- Integrate seamlessly across your existing tech stack
- Avoid vendor lock-in and stay flexible as your needs evolve
Is Your Data Redpoint Ready?
Precision Tools for Trusted Customer Data
Redpoint gives you everything you need to create accurate, complete and unified customer data that scales with your business.
Automated Data Quality
Achieve flawless data quality with automated cleansing at ingestion. Continuously detect, correct and monitor data issues across all sources to maintain high-quality, unified customer profiles.
Robust Data Standardization
Standardize and validate addresses, geolocations, emails and names to ensure reliable, accurate records across your data ecosystem.
Custom Identity Resolution
Resolve complex identities and build relationships across households and accounts using deterministic and probabilistic matching.
Customer-Centric Profile Unification
Consolidate and enrich data from all sources to create a complete, up-to-date view of each customer, including calculated aggregates and household insights.
Flexible Data Ingestion
Bring in data from any source at the pace of the customer and route it where it’s needed using a cost-efficient, no-code environment.
See it in action
Take a tour to see how you can quickly and easily get your data ready for use across the enterprise.
“Having all of our data available to us in one place, with the confidence that it is accurate, timely and comprehensive, has been the biggest asset in partnering with Redpoint.”
CEO Regional Retailer
“We can only do effective analysis and create successful offers because we have strong confidence in our data. Redpoint gives us that confidence”
Daniel Mathieus
AVP Information Technology, AAA
“Being able to bring all the data together in one place, compare it, clean it, and provide a consistently clean piece of information – a single view of the truth – is critical.”
Leading Technical Analyst
Global Activewear Brand
Uncompromised Data Security
Data readiness means never compromising data security. With Redpoint, secure data behind your firewall, use your data cloud, or entrust it to us. Redpoint seamlesssly adapts to your organization's security requirements.
Enterprise-grade Security and Compliance
Data Readiness Resources
Frequently Asked Questions
What is data readiness?
Data readiness is a process and methodology for having customer data that is right and fit for purpose for all CX or AI use cases. Extending beyond basic data quality, data readiness is a framework for building and activating a unified profile and deep understanding of a customer, household or entity (product, business, supply chain). Data readiness extracts maximum value from customer data from ensuring that a unified profile is complete, accurate, timely, actionable, trusted and compliant.
Why is data readiness important?
Data readiness corrects issues related to inferior data: data siloes and fragmentation, unresolved identities, incomplete and inconsistent journeys, missing feedback loops, and poor visibility and auditability. Data readiness takes a strategic approach to data management versus viewing it as an operational cost. Robust data quality, semantic consistency, persistent identifiers and accurate matching set the foundation for successful AI model training and deployment, as well as streamlined operations and data-driven decision making. Data readiness provides a contextual understanding of a customer, household or business entity, capturing situational awareness of customer signals as well as contextual metadata to derive a complete understanding.
What is AI-ready data?
Producing AI-ready data is a key function of data readiness. AI-ready data is data that is complete, accurate, timely, actionable, trustworthy, and compliant. A strong data foundation is a key pillar of an effective AI strategy. AI-ready data initiates a closed-loop cycle where high-quality data leads to better insights and improved results. A platform that generates AI-ready data validates and connects three crucial types of data for AI use cases: the source data itself, the data produced by the AI process (such as recommendations and predictions), and the response/outcomes data, which is then fed back into the platform for further tuning.
What are the steps of data preparation/data readiness?
Data readiness best practices will vary depending on a business’s set of unique use cases, but a general framework entails making a unified profile complete, accurate, timely, actionable, trusted, and compliant. In creating a unified profile, data preparation steps include cleansing, enrichment, normalization, standardization, and matching (deterministic and probabilistic), ideally as data is ingested into a data readiness platform.