Earlybirdy - Seattle, WA

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10

Amazon logo (vector)

As co-founder, Erik designed the semantic search engine Earlybirdy to help brands understand the 'why' driving their NPS.

With its proprietary emotion algorithm, Earlybirdy predicts repeat purchase intent by revealing leading indicators of customer acquisition, retention, and churn—with 95% accuracy.

Earlybirdy was originally built on the Twitter API but can be used on any unstructured data. If you would like to learn more, email erik@earlybirdy.com.

Earlybirdy screenshot

Role

Co-founder, Product Designer

Dates

January, 2015 - June, 2015  •  6 months

Accomplishments

  • Built a team of 6 developers specializing in A.I. and data science
  • Seed-funded a startup from concept to MVP in 3 months
  • Created a new approach to natural language processing (NLP)
  • Designed an algorithm to find signal in noise in unstructured data
  • Achieved a combined relevance and confidence of 95%
  • Applied the algorithm to global public data at 1B posts per week
  • Negotiated a 1-year global Twitter firehose partnership
  • Built an automated net prompter score (NPS) for brands
  • Inferred buying intent for user acquisition, retention, and churn
  • Learned the risk of building a product on 3rd party data

Earlybirdy - Seattle, WA

Earlybirdy logo (vector)

Role

Co-founder, Product Designer

Dates

January, 2015 - June, 2015  •  6 months

Accomplishments

  • Built a team of 6 developers specializing in A.I. and data science
  • Seed-funded a startup from concept to MVP in 3 months
  • Created a new approach to natural language processing (NLP)
  • Designed an algorithm to find signal in noise in unstructured data
  • Achieved a combined relevance and confidence of 95%
  • Applied the algorithm to global public data at 1B posts per week
  • Negotiated a 1-year global Twitter firehose partnership
  • Built an automated net prompter score (NPS) for brands
  • Inferred buying intent for user acquisition, retention, and churn
  • Learned the risk of building a product on 3rd party data

4

10

As co-founder, Erik designed the semantic search engine Earlybirdy to help brands understand the 'why' driving their NPS.

With its proprietary emotion algorithm, Earlybirdy predicts repeat purchase intent by revealing leading indicators of customer acquisition, retention, and churn—with 95% accuracy.

Earlybirdy was originally built on the Twitter API but can be used on any unstructured data. If you would like to learn more, email erik@earlybirdy.com.