The First Data Cloud for Post-Sales CX Observability

Observe and act on AI-based customer signals and predictions directly in Snowflake AI Data Cloud

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Unified observability means end-to-end visibility of your post-sales CX data

SupportLogic Data Cloud accelerates AI value realization by normalizing all your data across CRMs, extracting the signals, and storing them back into Snowflake AI Data Cloud.

Turn Your System of Record into a System of Action

SupportLogic works with what you already use, unlocking the customer insights trapped within your ticketing system and providing actionable recommendations that can be used across your entire organization (support, product, engineering, sales, and customer success).

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Seamlessly Integrate with Your Existing Tools

SupportLogic acts as a force multiplier for your systems of record, unlocking actionable insights from unstructured data surrounding support interactions.

All CX data united under one schema

All data stays in your own VPC

Supporting every flavor of data movement

Deliver Insights to the Entire Business

Extract powerful business insights from your support interactions. Share product feedback, feature requests, and sentiment trends with product, sales and marketing teams with a single click.

Build more accurate customer health scores

Analyze sentiment at individual or group levels

Discover product usage trends and create benchmarks

Reduce data friction across the organization

SupportLogic Data Cloud makes the following use-cases easy and cost-effective:

  • Customer health scoring, churn risk prediction and customer journey mapping
  • Post-sales customer marketing and digital customer success automation
  • Building business intelligence dashboards and in-house AI applications
  • Migrating between CRMs with reverse ETL

Support for any CRM and BI tool

Extract and analyze customer signals directly from Snowflake, regardless of CRM platform, for seamless integration with existing business intelligence tools such as Tableau, Qlik, or Power BI.

With SupportLogic Data Cloud, you can consolidate CRM instances and move between CRM platforms by unifying the underlying data layer and managing the entire process with Snowflake.

Complete observability of post-sales CX

Analyze customer signals in near real-time using support-specific domain AI, while providing your post-sales CX teams with timely and relevant insights to enhance decision-making and customer engagement.

Frequently Asked Questions

What’s included in the SupportLogic Data Cloud?

SupportLogic Data Cloud is available for SupportLogic customers. We can send your data directly to your own instance of Snowflake AI Data Cloud, or establish a secure pipeline connection between SupportLogic and Snowflake.

We can support any number and combination of SORs. Contact us for a full estimate of annual pricing based on your initial case volume and selected use-cases.

SupportLogic is a layer of intelligence that sits on top of your customer data sources. We use natural language processing to extract sentiment signals from both your customers and your team and use those signals to predict which situations to focus on first. These signals are also tagged in the customer interactions for data analysis of trends and patterns. Your case history is also used to train the predictive machine learning models for accuracy customized to your environment.

You can use your own instance of Snowflake or we can provide one during onboarding.

New customers typically onboard and start seeing AI insights from core implementation within 45 days.

SupportLogic Data Cloud implementation is a short and straightforward process after initial implementation.

Implementation is a flat fee. Contact us for a price estimate.

SupportLogic employs a usage-based pricing model. We charge an implementation fee for each module and then the actions you take in the system incur charges based on usage and value. This ensures you only pay for the parts of the platform that you use.

Contact us for a full estimate of annual pricing based on your initial case volume and selected use-cases.