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FINAL PROJECT – PROMEDICA CME

Anqi Wu (Chloe)

Lingqi Zhou (Amber) SPRING 2015

Niveditha Kumar

Qianqian Lin (Hilda)

AGENDA

¤  INTRODUCTION

¤  MODEL

¤  TESTS & INSIGHTS & PREDICTIVE MODELS

¤  RECOMMENDATION

¤  GAPS

INTRODUCTION

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

ProMedica CME

INTRODUCTION

Opportunities of Expansion

Customer data

Registration data

Meeting data

Campaigns data

Events data

Links

What we did

INTRODUCTION

Conceptual model

Gaps

Recommendation

Operational Model

Predictive models

Tests for insights

MODEL

Conceptual Model

Model

Defining Target Market

Marketing Efforts Attendence Revenue

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

TESTS & INSIGHTS & PREDICTIVE MODELS

Customer & Country

INSIGHTS

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

!

Customer & State

INSIGHTS

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

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%

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 !

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%)

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

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%!

!

Email campaign

INSIGHTS

¤  Length of Subject, url

¤  Date Sent

¤  Time & Day the email was sent

PREDICTIVE LOGISTIC MODEL①

Model

COMBINED

DATASET

Registration

Events Campaign

Meeting

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

PREDICTIVE LOGISTIC MODEL①

Model

Predictors

¤  Registration type

¤  Specialty

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

PREDICTIVE LOGISTIC MODEL①

Model

Training Data

50%

Testing Data

50%

PREDICTIVE LOGISTIC MODEL①

Model

Training Data 80% Accuracy

significant

Testing Data OVERFITTING

PREDICTIVE REGRESSION MODEL②

Combined Data

Training Data (50%)

Testing Data (50%)

Model

u Predict how many people are likely to open the emails

PREDICTIVE REGRESSION MODEL②

Model

Target Variable Predictor

Email Opens

Sends

Bounces

Date Sent

Length of Subject

PREDICTIVE REGRESSION MODEL②

Model

Descriptive Statistics

N

Predicted Value 363

Opens 391

Valid N (listwise) 363

RECOMMENDATION

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%)

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%)

Meeting types

¤  Most popular meeting

RECOMMENDATION

Higher frequency:

1-3/year

Shorter duration:

2 days

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)

Direct Post Mail

¤  Undeliverable addresses

¤  Delete: undeliverable email & mail addresses

¤  Ask customers need both contacting method

RECOMMENDATION

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

GAPS

ROI

GAPS

¤  ROI: Return on Investment

¤  Important Indicator

ROI

GAPS

Cost

Email Marketing

Labor

Facilities

…

Direct Mail Marketing

Labor

Letters

…

Hosting a conference

Rent

Labor

…

ROI

GAPS

Revenue

Registration fee

Partner hospital

Advertisement & Sponsorship

ROI

GAPS

¤  Only have REGISTRATION FEE

¤  Missing data: Registration fee paid by hospitals

Contributors for participation

GAPS

¤  Attracted by email marketing

¤  Attracted by mail marketing

¤  Required by hospitals or organizations

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

Data collecting process

GAPS

¤  Increase accuracy

¤  Increase efficiency: save time

Data collecting process

GAPS

Typo • Choose rather than input

Wrong Email Address • Email verification

Data Input • Start with related Meeting ID for campaign name

THANK YOU! Q&A