536_DKI 2012 Email & Website Engagement Report_v2-2

7/29/2019 536_DKI 2012 Email & Website Engagement Report_v2-2

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DKI Email & Website

Engagement Report

Published August 2012


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Background

Relationship marketing (RM) programs are a powerful educational tool that

empowers patients to make educated decisions about their treatment. Programs are

usually driven by an email component that either contains informative material or

drives them to a personal space where they can review content.

DKI has been creating and measuring RM programs for over 15 years. Since thebeginning, we have placed an emphasis on measuring results to ensure that

programs are successful and provide robust ROIs.

To that end, we have created and shared annual Normative Data reports with our

clients since 2006. The reports, released in Q4 of each year, have focused on results

over the previous 12 months and provided much needed benchmarks for emailengagement that are specific to the pharmaceutical industry.

This year, we have enhanced and expanded our normal report to align to the

calendar year and encompass multiple data points. We feel that the information is

too valuable to keep to ourselves, so we are sharing it with the wider community to

help shed light on expected norms and set meaningful goals for future programs.


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Using the past to guide the future

A new approach


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Whats New for 2012

RM Program Analysis Aligned to calendar year

Longer time frame look across six years of data (2006-2011)

New metric definitions

Unique clicks per link (clicks are based on unique clicks per link)

Additional slices to provide context

Oncology vs. Specialty Care

Metrics by media source (co-reg vs. paid, natural)

Launch year vs. year 2 and year 3

Time of day tendencies Omniture/Google web metric trends

Review of 2011 data across multiple websites

Visit trends

Overview of smart phone and tablet usage


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Larger Sample Size & Broader Scope

21 RMPrograms

877,000Patients

9.3 millionemails

1.3 millioninteractions*

*opens and clicks

DKI RM program metrics for 2006-2011 calendar years. All programs are U.S. based.


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Topline Findings:base email metrics

Results from longitudinal

analysis is consistent withreports from previous years

Oncology programs have the

highest response rates,

driven by higher urgency of

patients to seek outinformation due to fears

about cancer

Specialty care programs

have lesser engagement,

likely due to their morechronic nature and generally

higher patient populations


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Five learnings that will improve your business

Metrics can be

predicted

Strong correlation exists between email metrics and disease

state and media tactics. Set goals accordingly, and aim to

educate based on the competitive environment.

Email actions

occur within 24

hours

People dont wait to open emails. 47% of opens occur within 12hours. Time emails to coincide with important patient events.

Open & Click

rates moderate

over time

Multi-year programs are prone to engagement decline due to

outside competition for patients and new treatment news. Strive

to refresh subject lines and program content on a regular basis.

Website traffic

dips in the Spring

Traffic dips in spring, early summer and in December as people

spend time on vacation and with friends and family. Plan events

around high traffic periods the fall and winter.

Mobile is

growing fast

Though still a fraction of overall pharmaceutical site visits, traffic

grew by 83% over a 12 month time period. Now is the time to

optimize your sites for mobile.

Fact Action


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Median Open and Click Rates

Oncology = 28.0%

Specialty Care = 13.6%

Open Rate = 20.0% Click Rate = 5.3%

Oncology = 7.5%

Specialty Care = 3.1%

Based on data from 21 programs (11 Oncology + 10 Specialty Care). Data collected from 2006 2011.

Median Open Rate for DKI programs is 20%. Median Click Rate is 5.3%.

Oncology programs consistently have higher open and click rates than Specialty Care.


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Median Open and Click Rates by media source

Based on data from 15 programs where media deployment data was available (2.6 million co-reg emails and 4.3

million emails from other sources) Data collected from 2006 2011.

Non co-reg enrollments have Open and Click Rates that are over 2.5x

higher than leads from co-reg sources.

Source Open Rate Click Rate

Co-Reg 11.5% 2.7%

Other 29.7% 7.3%

Median 21.0% 4.8%


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Open and Click Rates by Media Mix

Median metrics for programs with primary emphasis on a particular media source. Co-reg programs have 60% or more enrollments from

co-reg sources. Low co-reg have 25% or fewer enrollments from co-reg sources. Data collected from 2006 2011.

Media source has a significant effect on engagement at the program level.Co-reg sources bring in a high volume of enrollees in desired segments at low cost,

however leads from these sources generally have lower levels of engagement.

Note: Co-reg rates are much stronger for Oncology vs. Specialty Care due to more specific

parameters used for pre-screening patients.

28.0%

13.6%

20.0%20.0%

12.9% 13.6%

30.6%32.5% 31.6%

Oncology Median Speciality Care Median Overall Median

Median Open Rate by Media Mix

Ope n Rate Co-Re g Ope n Rate L ow/No Co-Re g O pe n Rate

7.5%

3.1%

5.3%5.3%

2.6% 3.0%

12.5%

9.1%

10.4%

Oncology Median Speciality Care Median Overall Median

Median Click Rate by Media Mix

Click Rate Co-Reg Click Rate L ow/No Co -Reg Cli ck Rate


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11

Brings in high lead

volume at low cost

Goals should be setbased on program

design such as:

Condition type

Size of patient

population

Target demographics

Media strategy

The Case for

Co-Reg

Charts and slides on the previous pages refer to

lower engagement metrics provided by co-reg leads

relative to paid or natural search.

This is not intended to disparage the importance or

effectiveness of co-reg driven programs.

It is our position that co-reg can be a very effective

driver of large quantities of leads at efficient costs

per enrollment. Oftentimes, the resulting cost peraction (cost per enrollment divided by total opens

& clicks per enrollment) is lower than that of other

media sources.

Benchmark metrics are useful to set expectations for

engagement based on the media-mix that is in placefor the program.

Program goals should be set based on an analysis of

various factors including condition, patient

population, and media mix.


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Programs show variance in engagement by condition

52.1%

36.4%32.7% 32.3% 30.9% 30.4% 28.2% 28.0%

23.5% 22.0% 20.0% 20.0% 19.7%16.3% 15.5% 14.2% 12.9% 12.8%

11.8% 10.2% 10.2% 9.5%

O4 O11 S9 S7 O3 O6 O1 O8 O5 O7 Median O2 S1 O9 S4 S2 S3 S8 S5 S10 S6 O10

Open Rate by Program

23.7%

19.0%15.1%

10.9% 9.8%7.9% 7.5% 7.3% 6.9% 6.8%

5.3% 5.3% 4.3% 3.8% 3.4% 3.2% 2.8% 2.6% 2.5% 2.2% 2.1% 2.0%

O3 O4 O11 S9 O8 O5 O1 S7 O6 O7 Median O2 S1 S6 S3 O9 S5 S4 S10 O10 S8 S2

Click Rate by Program

A correlation of .826 is noted between email open and click rates. High open, low click rate programs

should consider optimizing email content. Low open, high click rate programs should incorporate subject

line testing to maximize engagement.


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Two Examples

Low Open / High Click Rate

O3 program, modified version ofan traditional RM program for arare type of cancer

Patient acquisition driven

primarily by paid search Moved to a Web RM model to

improve engagement

3 Segments, 8 communicationsper segment Emails featured streamlined text

with links driving to a personal page

High Open / Low Click Rate

S2 program, for widespreadchronic condition with a verylarge patient population

Patient acquisition driven by co-

reg sources 5 Segments, 18 communications

for the largest segments Some emails offered few links

Few call outs were featured outsideof the main body text

Additional emails were added toexisting streams as program

progressed

Insight: New strategy was created based

on original program results. More

focused communications with strong

calls to action drove high click-rates.

Insight: Successful program ran for multiple

years. Opportunity to improve email results

by focusing on fewer communications with

more dynamic links.


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The majority of email actionsoccur within 24 hours of

deployment

People dont wait around to

open emails The growth of Smartphone

usage makes it easy to

check emails any time of the

day

69% of opens occur within24 hours of deployment

86% of opens occur within 3

days of deployment

The above data show that

delivery of information canbe timed around important

events


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Close to 50% of opens occur within 12 hours of

email deployment

Almost 70% of opens occur within 24 hours of deployments

10.0%

19.7%

26.7%

40.3%

46.8%

60.3%

68.8%

0%

10%

20%

30%

40%

50%

60%

70%

80%


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Initial emails are opened more quickly than

the 2nd email in a stream

Hours to

OpenEmail #1 Email #2


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Over 90% of emails are opened within 5 days of

deployment

68.8%

79.9%85.5%

90.8%95.1%

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%


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Over 95% of opens occur within 10 days of

deployment

Days to

OpenEmail #1 Email #2


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Open and Click rates moderate from launch

to subsequent years

Metrics moderate as patients fill out their streams , media expands, and competitors

enter the market

Click to Open Rate remains steady, illustrating that active enrollees remain

interested in program content

Median values by calendar year for programs that have been active for 3+ years.

26.8%

22.3%

16.6%

6.3% 4.9%4.4%

29.0% 31.1% 31.3%

Year 1 Year 2 Year 3

Engagement - Launch to year 3

Open Rate Click Rate Click to Open Rate

Insight: refresh value propositions and subject lines, continue to modify

media plans to fight for your fair share of active patients.


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Traffic to pharmaceuticalwebsites and enrollment

forms show distinct trends

Seasonality patterns were

noted across sites with

distinct declines during

spring and summer months

Mobile represents a smallportion of total visits, but

volume grew 83% over a 12

month time period

A clear opportunity exists to

optimize websites for mobile


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Review of data across 22 sites shows a

wide range of volume for web visits

Median data shows the norm is between 6,000 to 8,500 visits per month

Visitors typically view between 2.2 to 3.3 pages per visit

Source: Omniture/Google median monthly visits across 22 pharmaceutical websites. Review of all visit data.

8,5966,397 7,495 7,011 6,752 6,552 5,954 5,911 6,436

7,829 9,8676,517

263 218 257 273 253 438 498 1,157684 579 583 834

47,653

62,478

62,87349,083

55,701 62,05460,527

66,37869,506

66,103 70,787

47,441

Jan2011

Feb2011

Mar2011

Apr2011

May2011

Jun2011

Jul2011

Aug2011

Sep2011

Oct2011

Nov2011

Dec2011

Web Traffic (visits)

Median Min Max


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Review of natural traffic data shows seasonal

influences, especially during Spring and Holiday

time periods

Traffic decline in late spring and summer

months is most likely due to a decline in web

traffic as people across the country take

summer holidays

December drop is likely due to reduced traffic

during the holidays as many people are on

vacation or with family at this time

Data closely mirrors traffic trend information

from Google.com for sites such as cancer.org

and heart.org

Source: Omniture/Google change in natural page views across multiple

websites from January 2011 through February 2012.

F M A M J J A S O N D J

N + - N - - + + N N - +

Month Over Month Normalized Page View Change

Key:

+ = positive change

-= Negative change

N = not conclusive

Jan

11

Feb

11

Mar

11

Apr

11

May

11

Jun

11

Jul

11

Aug

11

Sep

11

Oct

11

Nov

11

Dec

11

Jan

12

Paid Search Included 0% -17% 18% -2% -16% 1% 7% -4% -3% 7% 9% -29% 39%

Paid Search Excluded 0 -6% 33% -2% 17% -11% -17% 9% 10% 0% 16% -18% 2%

-40%

-30%

-20%

-10%

0%

10%

20%

30%

40%

50%

Pct.

Change

Month Over Month Page View Change

Insight: many people surf the web at

work. Traffic declines are noted during

holiday month. Typical builds occur

during back to school timer periods.


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1.8%2.1%

2.4%2.2%

2.4%

2.8%

2.3% 2.5%

3.0% 2.9%

3.4% 3.3%

0.0%

0.5%

1.0%

1.5%

2.0%

2.5%

3.0%

3.5%

4.0%

Feb

2011

Mar

2011

Apr

2011

May

2011

Jun

2011

Jul

2011

Aug

2011

Sep

2011

Oct

2011

Nov

2011

Dec

2011

Jan

2012

Percent Mobile Visits

The percent of mobile visits has risen by 83% over

a 12 month time period

Mobile is becoming a more important method to view web content

We expect mobile share of visits to continue to grow significantly in the coming months

Source: Omniture/Google - median value of mobile visits divided by total visits across 16 pharmaceutical websites. (12 months from 2/2011 to 1/2012).

Google predicts

that 26% of all

Rx searches in

2012 will be

from Mobile

devices*

Insight: low share of visits across pharmaceutical sites is due to

lack of website optimization for mobile

* Data from 2012 custom Google report. Information provided by Convergence Point Media.


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78%

18%

4%

% Mobile Device Usage

Mobile PhoneTablet

Other

Tablet devices now account for almost 20% of mobile

visits to websites

The explosive growth of tablet computers will continue in the coming years as

people increasingly consume information away from their desktops

Source: Omniture/Google - median value of mobile visits divided by total visits across 16 pharmaceutical websites. (12 months from 2/2011 to 1/2012).

Action: failure to optimize websites for mobile will lead to missed

opportunities to educate and inform visitors


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Appendix


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Methodology

Data collected over a 6 year time period

Twelve the Twenty-one programs reviewed were active for at least 3

of the 6 years covered

Omniture/Google website data was reviewed for 22 websites acrossmultiple pharmaceutical companies

Email open data based on unique opens

Email click data based on unique clicks per link

Median values were used across program types to eliminate biasbased on program size


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Glossary

Open Rate measure of unique opens over emails delivered

Click Rate measure of unique clicks per link over emails opened

Click to Open Rate measure of unique clicks per link over emails opened

Website Visits total number of visits to a website over a given time period

Paid Search method of lead acquisition based on ads served based on keywordsused on search engines

Co-Registration method of lead acquisition based on a flat cost per lead; partnersites find prospects and offer them a chance to join a program after answering

qualifying questions

RM program relationship marketing based on serving customized content to usersegments; most communications are email based

Web RM program a modified version of relationship marketing where a patient isprovided content on a personal web page; visits are prompted by invitation and

reminder emails


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HEALTHCARE RELATIONSHIP MARKETINGwww.dkidirect.com

Documents

536_DKI 2012 Email & Website Engagement Report_v2-2