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FINAL PROJECT – PROMEDICA CME Anqi Wu (Chloe) Lingqi Zhou (Amber) SPRING 2015 Niveditha Kumar Qianqian Lin (Hilda)

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Page 1: Chloe Wu. Powerpoint sample

FINAL PROJECT – PROMEDICA CME

Anqi Wu (Chloe)

Lingqi Zhou (Amber) SPRING 2015

Niveditha Kumar

Qianqian Lin (Hilda)

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AGENDA

¤  INTRODUCTION

¤  MODEL

¤  TESTS & INSIGHTS & PREDICTIVE MODELS

¤  RECOMMENDATION

¤  GAPS

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INTRODUCTION

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ProMedica CME

¤  CME = CONTINUING MEDICAL EDUCATION

¤  Continuing medical education programs provider

¤  Cardiac surgery, cardiology, interventional cardiology

¤  Ultimate goal of all CME activities:

enhance the quality of patient care

INTRODUCTION

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ProMedica CME

INTRODUCTION

Opportunities of Expansion

Customer data

Registration data

Meeting data

Campaigns data

Events data

Links

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What we did

INTRODUCTION

Conceptual model

Gaps

Recommendation

Operational Model

Predictive models

Tests for insights

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MODEL

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Conceptual Model

Model

Defining Target Market

Marketing Efforts Attendence Revenue

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Operational Model

Model

Defining Target Market

• Practitioners associated with cardiology or other specialties as well?

Marketing Efforts

• retention/acquisition

• type of marketing activity

• Return on investment (ROI)

Attendance

• attendance count

• revenue (income from attendance)

Revenue

• Increased or decreased revenue from all of the previous steps

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TESTS & INSIGHTS & PREDICTIVE MODELS

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Customer & Country

INSIGHTS

Country! US! Germany! France! UK!Percentage! 68.4%! 3.4%! 3.0%! 2.6%!

!

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Customer & State

INSIGHTS

State! CA! TX! NY! FL!Percentage! 29.5%! 10.2%! 8.7%! 5.0%!!

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Customer & Specialty (1)

INSIGHTS

Specialties Unsubscribed

Cardiovascular Surgeon

Interventional Cardiologist

Industry Cardiologist Cardiovascular and Thoracic Surgeon

% 17.3% 14.1% 12.2% 11.1% 8.0% 5.5%

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Customer & Specialty (2)

INSIGHTS

•  Combined the “campaigns”, “events” and “customer” sheets

•  Deleted entries that marked as bounced, unsubscribed, undeliverable, do not mail and those lacked customer ID.

•  Deleted entries that are sent but never opened or clicked.

•  A data set with customers who actually would open or click emails from ProMedica - can be considered as existing customers.

Top Three specialty Interventional Cardiologist Cardiovascular Surgeon Cardiologist !

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Customer & Specialty (3)

INSIGHTS

Specialty Mail Deliverable

Cluster 1 (66.4%)

Cardiovascular Surgeon, Cardiologist

Do mail (100%) Deliverable (100%)

Cluster 2 (33.6%)

Unsubscribed (32.2%), Industry, Cardiovascular Surgeon

Do not Mail (89%) Undeliverable (98.7%)

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Meetings

! Duration! Attendance! Location! Month! Frequency!Cluster(1! 2"days"

(48.4%)!380! CA#(53.3%),#!

AZ#(20%)!Oct$(40%),!Sep$(20%),$Nov$(20%)!

1"3"times"a"year!

Cluster(2! 3"days"(25.8%)!

342! TX,$Houston$(100%)!

Mar$(87.5).!April&(12.5%)!

Once%a%year!

Cluster(3! 6"days"(25.8%)!

232! CO,$Snowmass$Village'(100%)!

Mar$(100%)! Once%a%year!

!

INSIGHTS

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Email campaign

INSIGHTS

! Sent! Open%rate! Click&rate!Cluster(1((48.8%)! 806.74! 26.60%! 2.81%!Cluster(2((47.3%)! 4229.25! 24.56%! 1.49%!Cluster(3((3.8%)! 7308.13! 26.50%! 2.18%!

!

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Email campaign

INSIGHTS

¤  Length of Subject, url

¤  Date Sent

¤  Time & Day the email was sent

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PREDICTIVE LOGISTIC MODEL①

Model

COMBINED

DATASET

Registration

Events Campaign

Meeting

u Predict whether a customer would come to the meeting or not

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PREDICTIVE LOGISTIC MODEL①

Model

Predictors

¤  Registration type

¤  Specialty

¤  Email activity type: bounce, click, open, send, unsubscribe

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PREDICTIVE LOGISTIC MODEL①

Model

Training Data

50%

Testing Data

50%

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PREDICTIVE LOGISTIC MODEL①

Model

Training Data 80% Accuracy

significant

Testing Data OVERFITTING

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PREDICTIVE REGRESSION MODEL②

Combined Data

Training Data (50%)

Testing Data (50%)

Model

u Predict how many people are likely to open the emails

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PREDICTIVE REGRESSION MODEL②

Model

Target Variable Predictor

Email Opens

Sends

Bounces

Date Sent

Length of Subject

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PREDICTIVE REGRESSION MODEL②

Model

Descriptive Statistics

N

Predicted Value 363

Opens 391

Valid N (listwise) 363

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RECOMMENDATION

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Primary target customers

¤  Primary audiences

¤  Provide content suitable to US Market

¤  Follow the breakthroughs & new regulations

RECOMMENDATION

US local market (68.4%)

California (29.5%) Texas (10.2%) New York (8.7%)

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Primary target customers

¤  Top 3 specialty

¤  Provide more content in related topics

¤  Higher acquisition rate

¤  Expansion?

RECOMMENDATION

Cardiovascular Surgeon (14.1%)

Interventional Cardiologist (12.2%)

Related industry (11.1%)

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Meeting types

¤  Most popular meeting

RECOMMENDATION

Higher frequency:

1-3/year

Shorter duration:

2 days

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Email Marketing

¤  Relatively high bounce rate: wrong email address

¤  Delete & Update to save time and cost

¤  Create a VIP email list

RECOMMENDATION

ProMedica CME Benchmark Performance

Open Rate 29.06% 22.82% +

Click Rate 4.53% 2.92% +

Bounce Rate 7.10% 0.77% -

(Benchmark: MailChimp Research)

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Direct Post Mail

¤  Undeliverable addresses

¤  Delete: undeliverable email & mail addresses

¤  Ask customers need both contacting method

RECOMMENDATION

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Utilize social media

RECOMMENDATION

¤  Mobile is a driving force

(Laudenslager, 2013)

81% Use smartphones

62% Use tablets for professional purposes

90% Use social media professionally or personally

38% Use medical apps on daily bases

¤  Use social media for campaigns

¤  Create contents

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GAPS

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ROI

GAPS

¤  ROI: Return on Investment

¤  Important Indicator

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ROI

GAPS

Cost

Email Marketing

Labor

Facilities

Direct Mail Marketing

Labor

Letters

Hosting a conference

Rent

Labor

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ROI

GAPS

Revenue

Registration fee

Partner hospital

Advertisement & Sponsorship

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ROI

GAPS

¤  Only have REGISTRATION FEE

¤  Missing data: Registration fee paid by hospitals

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Contributors for participation

GAPS

¤  Attracted by email marketing

¤  Attracted by mail marketing

¤  Required by hospitals or organizations

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Contributors for participation

GAPS

¤  Data should be collected

¤  Improvement on the content/marketing

Meeting Data

Sponsored meeting? hospital partnered meeting

Customer Quick survey after attendance

Why they came

Rate the meeting

Email Content

Content analysis Relate it to open & click

Better insight of campaign

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Data collecting process

GAPS

¤  Increase accuracy

¤  Increase efficiency: save time

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Data collecting process

GAPS

Typo • Choose rather than input

Wrong Email Address • Email verification

Data Input • Start with related Meeting ID for campaign name

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THANK YOU! Q&A