Introducing Alumni 2.0 with Predictive Analytics

by Community Admin in Corporate Alumni   |    Last Edited: 25th October 2019

Alumni 2.0 is the ability to leverage AI and Machine Learning to better understand your community by aggregating multiple data sources to more effectively predict user behavior. Replacing the legacy approach of Alumni being an excel spreadsheet or a website with an address book and some company news.

By combining multiple data sources with your Alumni User Data and 3rd Party data such as social sites or public data sources, customers are now enabled to launch targeted engagement campaigns, more intelligently segment their community and drive specific behaviors or outcomes.

Leveraging our Predictive Analytics & Live Data Visualization tools our customers are able to include “likelihood” as part of their user segmentation or search criteria to enable more informed or targeted campaigns of content and calls to action.

Example: notify users on login with a Recruiting Index score of 80 or higher with “x” skills, languages, location, experience, etc. and invite them to speak directly with a recruiter about specific open job opportunities.

The four reasons predictive analytics and data deep business intelligence cannot be ignored when delivering your alumni platform and engaging your talent community:

  • Predictive Analytics can be used to identify potential behaviors and experience to form the basis of a pool of prequalified candidates for recruiting purposes.
  • Workforce Experience is the new customer experience and the next ‘no-brainer’ for organizations to truly understand their audience.
  • Profiling and segmenting with accuracy, deliver custom experiences to different users based on potential future behavior or current data intelligence.
  • Workforce planning and predictive analytics can identify the best new hires and understand the organization’s informal network of knowledge and influence.

How EnterpriseAlumni Delivers Analytics, Indexing & BI natively.

User Index assignment based on expectations of the user to engage in an action.

The implementation of unstructured data analytics enables customers to integrate third-party data sources in the platform to augment the existing analytics component. Whether it is CRM, Learning or even public data such as unemployment rates in a specific region.

The application currently supports four index variables:

  • Recruiting Index: The likelihood a user will engage in a conversation or opportunity to return to your organization.
  • Engagement Index: The likelihood a user will execute on a specific outcome or call to action.
  • CSR Index: The likelihood the user will engage around “empathy” driven opportunities (ERG’s, Volunteering, Mentoring, Diversity)
  • Sentiment Index: The brand advocacy index relating to their overall view of your organization (including NPS)

EnterpriseAlumni is rethinking what it takes to better visualize our customer’s data and insights to deliver a more meaningful user experience and accelerate conversions into the company’s defined objectives.

The ability to leverage 3rd Party Data Sources adds another level of intelligence to our platform, to deliver greater engagement and experience to your organization and Alumni.

Example: Highlight job requisitions with a certain skill requirement for users who live in a zone where unemployment is more than “x” %.

Combining Business Intelligence With Real Insights

Any data, at any time from across the EnterpriseAlumni platform, can be interrogated, drilled down and visualized to allow deep insight and understanding, which when combined with predictive analytics is able to make recommendations with an impact assessment.

From engagement into your recruiting programs to your e-mail newsletters, EnterpriseAlumni’s platform leverages data in simple dashboards to understand areas of opportunity and improvement.

Example: When reviewing email engagement across the platform, the platform allows drill down by any of the variables (time, gender, role, location etc) to enable recommendations and show potential areas of improvement on specific campaigns, to drive open and click rate based on past performance and market data.

Leveraging our platform analytics, customers are able to quickly identify what is working, and for who, whilst with cumulative data mapping, access the ability to show progress over time or over multi-campaigns such as A/B testing.

Another example of such insights driving our customers towards data-driven decision making includes our traffic and audience analysis as well as our recruiting throughput reports.