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What is Nominow?
Nominow, a customer data platform with roots in the Netherlands, gathers touchpoint data from all operational sources within your business. It systematically refines and consolidates customer profiles into a unified data repository, which is essential for any marketing campaign, event, or customer interaction you plan to undertake. Given that every business has its own customized marketing technology stack, each deployment of Nominow is unique. We partner with your team to assess the current situation, contextual elements, and strategic objectives for which Nominow will be implemented. This process includes a comprehensive review of customer data sources, applications, the IT environment, and specific needs. The configuration of your Nominow system is tailored to fit your individual circumstances and requirements. Our primary goal is to enable you to effectively manage your customer data, ensuring that you can access genuinely actionable insights whenever needed. Generally, the implementation process for Nominow takes between 6 to 8 weeks, facilitating a quick integration into your existing operations. This timeframe allows your organization to promptly harness the complete power of its customer data, paving the way for enhanced decision-making and customer engagement strategies. By adopting Nominow, you position yourself to stay ahead in a competitive landscape.
What is Ignitho Customer Data Platform Accelerator?
With Ignitho's Customer Data Platform (CDP) accelerator, implementations can be finalized in as short as two weeks. This integrated solution framework prioritizes AI use cases, offering industry-specific capabilities and pre-configured AI models designed to address vital business challenges. Such a setup ensures that your implementations not only occur swiftly but also align with specific organizational needs. Furthermore, the accelerator can be easily augmented to incorporate additional AI models as required.
Beyond merely serving as a repository for customer data, your CDP implementation also features insightful visualizations and essential segmentations.
Key offerings include:
1. Ready-made AI models
2. API-based real-time integration for AI insights
3. Sophisticated what-if analyses
4. Prevention of data duplication
5. Quick data integration using predefined schemas
This comprehensive approach guarantees that your organization remains agile and responsive to evolving market demands.
Integrations Supported
Adobe Analytics
Domo
Facebook
Google
Google Analytics
Ingenta Commercial
Lightspeed Retail
Magento
Mailchimp
Microsoft Dynamics 365
Integrations Supported
Adobe Analytics
Domo
Facebook
Google
Google Analytics
Ingenta Commercial
Lightspeed Retail
Magento
Mailchimp
Microsoft Dynamics 365
API Availability
Has API
API Availability
Has API
Pricing Information
Pricing not provided.
Free Trial Offered?
Free Version
Pricing Information
Pricing not provided.
Free Trial Offered?
Free Version
Supported Platforms
SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux
Supported Platforms
SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux
Customer Service / Support
Standard Support
24 Hour Support
Web-Based Support
Customer Service / Support
Standard Support
24 Hour Support
Web-Based Support
Training Options
Documentation Hub
Webinars
Online Training
On-Site Training
Training Options
Documentation Hub
Webinars
Online Training
On-Site Training
Company Facts
Organization Name
Nominow
Company Location
Netherlands
Company Website
www.nominow.com/en
Company Facts
Organization Name
Ignitho Technologies
Date Founded
2016
Company Location
United States
Company Website
www.ignitho.com
Categories and Features
Customer Data Platforms (CDP)
Behavioral Analytics
Campaign Management
Customer Profiles
Customer Segmentation
Data Integration
Data Matching
GDPR Compliance
Personalization
Predictive Modeling
Categories and Features
Customer Data Platforms (CDP)
Behavioral Analytics
Campaign Management
Customer Profiles
Customer Segmentation
Data Integration
Data Matching
GDPR Compliance
Personalization
Predictive Modeling