PART 1

Customer/User Job-to-be-Done or Problem

The inaccuracy of current NAICS are leading to the client having to spend additional time cleaning up lists produced by Gazelle and is impacting the accuracy of the Gscore and together affecting the credibility of the platform

Value to Customers & Users

Less processing of company lists and more reliable Gscores used to prioritize companies

Value to Lightcast

Increased retention rates and potential to be market leader in NAICS accuracy with additional investments

Target User Role/Client/Client Category

Who are we building this for?

Delivery Mechanism

Gazelle software, Snowflake

Success Criteria & Metrics

All 22 industrial groups have been calibrated with respect to the AI training dataset to check and assign NAICS based on company description and keywords and determined to have >70% accuracy while keeping over >70% of NAICS (i.e. not resulting in too many companies without any NAICS)

Aspects that are out of scope (of this phase)

Implementation of algorithm on complete Gazelle platform or Lightcast products

PART 2

Solution Description

Early UX (wireframes or mockups)

<FigmaLink>

Non-Functional Attributes & Usage Projections

Consider performance characteristics, privacy/security implications, localization requirements, mobile requirements, accessibility requirements

Dependencies

Is there any work that must precede this? Feature work? Ops work? 

Legal and Ethical Considerations

Just answer yes or no.

High-Level Rollout Strategies

• Initial rollout to [internal employees|sales demos|1-2 specific beta customers|all customers]

  • If specific beta customers, will it be for a specific survey launch date or report availability date 

• How will this guide the rollout of individual stories in the epic?

• The rollout strategy should be discussed with CS, Marketing, and Sales.

• How long we would tolerate having a “partial rollout” -- rolled out to some customers but not all

Risks

Focus on risks unique to this feature, not overall delivery/execution risks. 

Open Questions

1. Identify resources from inside Gazelle or Lightcast Taxonomy to work with Nadine on further development or source outside Lightcast

Complete with Engineering Teams

Estimated Costs

Direct Financial Costs

Are there direct costs that this feature entails? Dataset acquisition, server purchasing, software licenses, etc.?

Team Effort

Each team involved should give a general t-shirt size estimate of their work involved. As the epic proceeds, they can add a link to the Jira epic/issue associated with their portion of this work.