Función del empleo: Marketing

Tipo de puesto: Permanent

Tipo de empleo: Full - Time

Localización: New York, NY

País: United States

Assistant Manager - Data Analytics (Color & Co.)

Work with digital and marketing teams to provide relevant analysis and recommendations to help improve on conversion and retention. Both on a regular base (recurring reports) and on specific ad hoc questions. (Color & Co.)

Operational reporting to digital head, functional reporting to GM.

 

This will cover 5 main areas:

 
  1. Funnel and Drop-off on site

This will mainly be done through Google analytics. The objective is to understand the main users paths and where the drop off mainly happens for each of them.

The type of required analysis is as follows:

 

Funnel analysis:

-Colorers vs non colorers

-Men vs Women

-by ethnicity

-by level of gray

-By desired end result

-by hair texture

-by source of acquisition

-by key word entered

-by geography (big/small cities)

-New visitor / returning visitor

-People picking recommended shade vs alternative one

 

Best conversion patterns:

-By time during a day / best day during a week / best week during a month / best month in a year, with recommendation of media and CRM investment phasing

-people who have used a toggle vs not

-people who have used live chat vs not

-people who have used modiface vs not

 

2. A/B testing monitoring / ad-hoc testing

Keep a monthly planning of A/B tests to be undertaken

Define right KPIs to track before each A/B test

Break down A/B test results by key users profile

 

3. Retention / Loyalty reports

  • Churn curve. Analyse moment / reason / profile of people most likely to churn
  • Churn by type of initial promotional offer ($10 off / $5 off / Free shipping…)
  • Reading of people skipping their next order

4. CRM efficiency

Monitoring of Opening rates / CTR / conversion of all emails in

    • Welcome series
    • Broadcast emails
  • Recommendation of best practice to follow based on above analysis

5. Media

  • Paid media efficacy by type of ad
  • Learning and best practices
 

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