All work by Micro has been completed, work for PI3 will be to release the Graduation Year Filter in Analyst for all BU’s.

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

When I try to research trends regarding recent graduates through profile data I need to be able to filter by graduation year to make sure that I am looking at profiles that fit my criteria. Knowing how recently a profile was updated doesn’t help, that could be them updating their job title or email address.

Migration (see my Regional Migration) - as an economic/workforce developer, I want to understand which alumni I am losing from my region, so I can create interventions to keep key talent

Supply: Profile analytics-ish: as a XXX assessing my local supply of talent, I want to segment that talent to look at recent graduates (for reasons x/y/z → lower cost, cutting-edge skills, other).

AO: As an Academic Program Manager, I want to hone in on the outcomes of recent alumni to help assess the success of my program

Value to Customers & Users

For Legacy LI customers the addition of the Graduation Year filter replicates functionality they are used to and have become dependent upon when using profile data.

The addition of the Graduation Filter to Profile Analytics would add the most compelling and direct use case of profile data to date. Users would be able to look at graduates from certain time periods and compare/contrast different trends they are seeing for their graduates vs competitive institutions, or certain regions, or nationally.

For example, a user could look at bachelor-level completions over the past 5 years for their institution to see what skills are most commonly listed and then run a different report for all institutions using the same criteria and compare the results. This could help them identify what skills their graduates have that differentiate them from other institutions or perhaps what skills they are lacking.

To make profile data useful users need to be able to segment their chosen cohorts over select windows of time to see changes and trends. We could make a similar comparison to job posting data in that if a user just looks at all the skills in job postings over the past 20 years what signals or trends could they spot that would be relevant? The value in job posting data just as in profile data is in being able to narrow the timeframe to identify new trends.

Value to Lightcast

We have not determined all of the locations where we utilize this data but there are several different options all of which provide value to Lightcast:

Graduation Year Filter in Profile Analytics: Helps with the transition of legacy LI customers and will add the most compelling use case of profile data to date. Not only would this help with renewals but we could look at selling a Profile Analytics + version that includes this and other features for an upcharge.

Regional Education Migration: See separate Epic which relies on this same data.

Target User Role/Client/Client Category

Institutional Researchers
Marketing
Online, Distance, or Extended Ed
Continuing and Professional Education
Deans

Delivery Mechanism

Analyst - this is already available to our API clients.

Success Criteria & Metrics

Users will be able to narrow and refine searches using the grad year filter to identify and find relevant trends through profile data.

Profile Analytics accounted for 14.31% of all analyst report runs in EDU. We believe that this feature will add value to the report and would expect to see the usage rise by ~1-2%.

I also believe this feature will improve renewals for profile analytics and help in new seller opportunities but have do not have any estimates on how much it might improve these.

Aspects that are out of scope (of this phase)

·       Any development to implement this in Alumni Outcomes 2.0. This epic will only address the implementation of this feature in Profile Analytics in Analyst.

·       Any additional features we would need to justify an upgraded or separate version of Profile Analytics.

Solution Description

Early UX (wireframes or mockups)

We will use one of the existing timeframe filters and adopt it for this feature.

Open

Non-Functional Attributes & Usage Projections

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

Dependencies

Data team

Legal and Ethical Considerations

No

High-Level Rollout Strategies
The rollout Strategy is somewhat TBD as we narrow down which applications will get this feature but this rollout assumes implementation in Analyst and Alumni Outcomes.

• In advance of rollout brief marketing on feature and use case to evaluate if we should prepare marketing collateral around the new use case and functionality.

• Initial rollout to internal Customer Success and Sales teams in Education to prepare them on how to train or communicate this to existing users and how to pitch this to potential customers.

• The feature will be released for all users across all BU’s.

  • Coordinate the release of the feature with a Pendo announcement that will include a short video communicating what the feature is and how we would recommend using it.

  • Will also check with Customer Success and see if this is something they think should get included in the next webinar after the feature release.

• Monitor feature usage and any feedback from users.

Risks

The largest risk is that adding this feature to Profile Analytics and the current Alumni Outcomes could undercut new sales for AO 2.0. This is something I have been discussing with Lendl Meyer but do not have a final answer on since he has been OOF.

Open Questions

Complete with Engineering Teams

Estimated Costs

Direct Financial Costs

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.