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DKI Email & Website Engagement Report Published August 2012


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 the beginning, 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 email engagement 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.


A new approach Using the past to guide the future


What’s 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


Larger Sample Size & Broader Scope

21 RM Programs

877,000 Patients

9.3 million emails

1.3 million interactions*

*opens and clicks

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


Topline Findings: base email metrics

 Results from longitudinal analysis is consistent with reports from previous years  Oncology programs have the highest response rates, driven by higher urgency of patients to seek out information due to fears about cancer  Specialty care programs have lesser engagement, likely due to their more chronic nature and generally higher patient populations


Five learnings that will improve your business Fact

Action

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 don’t wait to open emails. 47% of opens occur within 12 hours. 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.


Median Open and Click Rates

Open Rate = 20.0%

Click Rate = 5.3%

• •

• •

Oncology = 28.0% Specialty Care = 13.6%

Oncology = 7.5% Specialty Care = 3.1%

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


Median Open and Click Rates by media source

Source

Open Rate

Click Rate

Co-Reg

11.5%

2.7%

Other

29.7%

7.3%

Median

21.0%

4.8%

Non co-reg enrollments have Open and Click Rates that are over 2.5x higher than leads from co-reg sources.

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.


Open and Click Rates by Media Mix

Median Click Rate by Media Mix

Median Open Rate by Media Mix Open Rate

Co-Reg Open Rate

32.5%

30.6%

Click Rate

Low/No Co-Reg Open Rate

Co-Reg Click Rate

Low/No Co-Reg Click Rate

12.5%

31.6%

28.0%

10.4% 9.1% 20.0%

20.0% 13.6% 12.9%

7.5% 13.6%

5.3%

5.3% 3.1% 2.6%

Oncology Median

Speciality Care Median

Overall Median

Oncology Median

Speciality Care Median

3.0%

Overall Median

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. 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.


Charts and slides on the previous pages refer to lower engagement metrics provided by co-reg leads relative to paid or natural search.

The Case for Co-Reg

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 per action” (cost per enrollment divided by total opens & clicks per enrollment) is lower than that of other media sources.

 Brings in high lead volume at low cost  Goals should be set based on program design such as:  Condition type

Benchmark metrics are useful to set expectations for engagement based on the media-mix that is in place for the program.

 Size of patient population

Program goals should be set based on an analysis of various factors including condition, patient population, and media mix.

 Media strategy

 Target demographics

11


Programs show variance in engagement by condition

Open Rate by Program

52.1% 36.4% 32.7% 32.3% 30.9% 30.4% 28.2% 28.0%

O4

O11

S9

S7

O3

O6

O1

O8

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% O5

O7

Median

O2

S1

O9

S4

S2

S3

S8

S5

S10

S6

O10

Click Rate by Program

23.7% 19.0%

15.1% 10.9% 9.8%

O3

O4

O11

S9

O8

7.9% O5

7.5% O1

7.3% S7

6.9% O6

6.8% O7

5.3%

5.3%

4.3%

3.8%

3.4%

3.2%

2.8%

2.6%

2.5%

2.2%

2.1%

2.0%

Median

O2

S1

S6

S3

O9

S5

S4

S10

O10

S8

S2

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.


Two Examples Low Open / High Click Rate

High Open / Low Click Rate

  

O3 program, modified version of an traditional RM program for a rare type of cancer Patient acquisition driven primarily by paid search Moved to a Web RM model to improve engagement 3 Segments, 8 communications per segment 

Emails featured streamlined text with links driving to a personal page

Insight: New strategy was created based on original program results. More focused communications with strong calls to action drove high click-rates.

 

S2 program, for widespread chronic condition with a very large patient population Patient acquisition driven by coreg sources 5 Segments, 18 communications for the largest segments   

Some emails offered few links Few call outs were featured outside of the main body text Additional emails were added to existing streams as program progressed

Insight: Successful program ran for multiple years. Opportunity to improve email results by focusing on fewer communications with more dynamic links.


The majority of email actions occur within 24 hours of deployment

 People don’t 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 within 24 hours of deployment  86% of opens occur within 3 days of deployment  The above data show that delivery of information can be timed around important events


Close to 50% of opens occur within 12 hours of email deployment % Emails Opened From Time Sent 80%

68.8%

70% 60.3%

60%

46.8%

50% 40.3%

40% 30% 20% 10%

26.7% 19.7% 10.0%

0% <1 <2 <3 <4 <5 <6 <7 <8 <9 <10 <11 <12 <13 <14 <15 <16 <17 <18 <19 <20 <21 <22 <23 <24

ď&#x201A;§

Almost 70% of opens occur within 24 hours of deployments Action: email deployments can be timed to coincide with important enrollee events such as doctorâ&#x20AC;&#x2122;s appointments or treatment milestones.


Initial emails are opened more quickly than the 2nd email in a stream Hours to Open <1 <2 <3 <4 <5 <6 <12 <18 <24

Email #1

Email #2

10.2% 20.7% 28.1% 34.0% 38.8% 42.5% 49.6% 62.8% 71.1%

9.3% 19.0% 26.0% 31.7% 36.3% 39.9% 46.3% 59.8% 68.5%

Action: subject line testing is a must to ensure that the maximum number of emails are opened. Urgent calls to action will cause people to open emails in a timely fashion.


Over 90% of emails are opened within 5 days of deployment

% Emails Opened From Day Sent 100% 85.5%

90% 80%

95.1%

90.8%

79.9%

68.8%

70% 60% 50% 40% 30% 20% 10% 0% <1

<2

<3

<4

<5

<6

<7

<8

<9

<10

Insight: messages from emails deployed within 7-14 days of each other will not overlap.


Over 95% of opens occur within 10 days of deployment

Days to Open <1 <2 <3 <5 <10

Email #1 Email #2 71.1% 82.0% 87.2% 92.2% 96.0%

68.5% 79.8% 85.5% 90.8% 95.3%

Insight: It is very unlikely that an email will be opened if no action has been taken within the first few days.


Open and Click rates moderate from launch to subsequent years Engagement - Launch to year 3 Open Rate 29.0% 26.8%

Click Rate 31.1%

Click to Open Rate 31.3%

22.3% 16.6%

6.3%

Year 1

4.9%

Year 2

4.4%

Year 3

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

ď&#x201A;§ ď&#x201A;§

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 Insight: refresh value propositions and subject lines, continue to modify media plans to fight for your fair share of active patients.


Traffic to pharmaceutical websites and enrollment forms show distinct trends

ď&#x201A;§ Seasonality patterns were noted across sites with distinct declines during spring and summer months ď&#x201A;§ Mobile represents a small portion of total visits, but volume grew 83% over a 12 month time period ď&#x201A;§ A clear opportunity exists to optimize websites for mobile


Review of data across 22 sites shows a wide range of volume for web visits Web Traffic (visits) Median 62,478 47,653

62,873 49,083

Min

60,527 55,701 62,054

Max 66,378 66,103 70,787 69,506 47,441

9,867 6,397 7,495 7,011 6,752 6,552 5,954 5,911 6,436 7,829 6,517 684 1,157 579 263 218 257 273 253 438 498 583 834

8,596

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 2011 2011 2011 2011 2011 2011 2011 2011 2011 2011 2011 2011 Source: Omniture/Google – median monthly visits across 22 pharmaceutical websites. Review of all visit data.

 

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


Review of natural traffic data shows seasonal influences, especially during Spring and Holiday time periods Month Over Month Normalized Page View Change F

M

A

M

J

J

A

S

O

N

D

J

N

+

-

N

-

-

+

+

N

N

-

+

Key: + = positive change -= Negative change N = not conclusive

Source: Omniture/Google – change in natural page views across multiple websites from January 2011 through February 2012. Month Over Month Page View Change

50% 40%

Pct. Change

30% 20% 10% 0% -10%

-20% -30% -40%

Paid Search Included Paid Search Excluded

Jun 11

Jul 11

Aug Sep 11 11

Oct 11

Nov 11

0% -17% 18% -2% -16% 1%

Jan 11

7%

-4%

-3%

7%

9% -29% 39%

-6% 33% -2% 17% -11% -17% 9%

10%

0%

16% -18% 2%

0

Feb 11

Mar 11

Apr 11

May 11

Dec 11

Jan 12

 Insight: many people surf the web at work. Traffic declines are noted during holiday month. Typical builds occur during back to school timer 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


The percent of mobile visits has risen by 83% over a 12 month time period Percent Mobile Visits 4.0%

3.4% 3.3%

3.5%

2.5%

2.0%

3.0% 2.9%

2.8%

3.0% 2.1%

2.4%

2.2%

2.4%

2.3% 2.5%

1.8%

1.5% 1.0% 0.5%

Google predicts that 26% of all Rx searches in 2012 will be from Mobile devices*

0.0% Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Jan 2011 2011 2011 2011 2011 2011 2011 2011 2011 2011 2011 2012 Source: Omniture/Google - median value of mobile visits divided by total visits across 16 pharmaceutical websites. (12 months from 2/2011 to 1/2012).

ď&#x201A;§ ď&#x201A;§

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 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.


Tablet devices now account for almost 20% of mobile visits to websites

% Mobile Device Usage 4% 18% Mobile Phone Tablet Other

78%

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

ď&#x201A;§

The explosive growth of tablet computers will continue in the coming years as people increasingly consume information away from their desktops Action: failure to optimize websites for mobile will lead to missed opportunities to educate and inform visitors


Appendix


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 across multiple 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 bias based on program size


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 keywords used on search engines Co-Registration – method of lead acquisition based on a flat cost per lead; partner sites 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 user segments; most communications are email based Web RM program – a modified version of relationship marketing where a patient is provided content on a personal web page; visits are prompted by invitation and reminder emails


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