Tracking the Impact of Clinical Trials on Social Media

 

While Pharma is still wondering how to harness Social Media, without opening the “pandora box” of adverse events, a number of specialized applications dedicated to the life sciences industry have recently emerged. In this post, I would like to discuss some projects where, by listening to social media conversations, we were able to measure the impact of publication of clinical trials on the medical population, business community and media.

INTRODUCING THE “OOL”

A first example would be in oncology. When monitoring specific “hot” subjects such as Biomarkers or PD-1, peaks of social media conversations were clearly observed around major conferences such as ASCO or ESMO where results of major clinical trials are published. Social Media tracking allows not only to identify who the supporters or the detractors of the trials results are, but also what are the publications at the source of these influences. This includes analyzing the sentiments linked to the publication: determining whether the reception of the medical community is positive, neutral or negative; and picking out the principal themes that are discussed. In many cases, names of top blog authors or specific postings are taken and rated for frequency of posting and influence, and often can be matched up with the name of a specific KOL.

Graph 1: Peak of discussion about clinical trial results around Medical conferences

It is interesting to note that some of these Opinion Leaders are not generally vocal in conferences or offline venues. Their turf is the Internet, and with thousands of followers on twitter or facebook, they can be quite influential there! We call them “Online Opinion Leaders” aka OOLs.

A CASE STUDY

In a recent project, we tracked for one of our clients, a vaccine manufacturer, the impact of various Phase 2 and Phase 3 clinical trials results publications. After every publication we were able to analyze the “burst” in details. Results were then presented in a cloud-based, real-time dashboard with drill down capabilities. As soon as “OOLs” posts were published, we could gauge how the messages were perceived, correct any misunderstanding or misconception, and understand what resonated well or poorly with the public or sometimes more specifically with a KOL segment. In this instance the client’s subsequent releases took into account the findings from the initial ones, amendments were made to the formulation of the messages, and the results re-analyzed.

Graph 2: Main themes being discussed

The real key to any social media monitoring is to read between the lines, and more than listening to actually understand and analyze. In our case, experience showed that a deep expertise combining social media and medico-marketing skills was necessary to more closely explain the buzz as if through the eyes of the company, carefully selecting relevant terminology, key threads and creating company/product specific word clouds. Big Data is any source of information, and data from other sources were combined with the company’s own data to draw conclusions

THE HUMAN TOUCH

By using highly detailed cloud based dashboards, we could look at more than 100,000 conversations first by country, then language, source of the information, and finally by sentiment and themes. But to dig further, more than 10,000 individual posts had to be analyzed by humans with medical training (not machines), who have a finer sense of the nuances of a language, how humor or sarcasm is expressed, and how to categorize posts according their tone and credibility:whether it is scientific, has valuable medical content, or on the contrary is perhaps not even relevant.

Based on these findings, we were able to get a clear picture of the actual impact of these clinical trial publications, first of all on the medical community, but more widely on the industry, the financial community and the general public.

Over the past five years, we have conducted several similar projects in immunology, diabetes, oncology, rheumatoid arthritis, vision impairment, etc…

Feel free to contact me directly if you are interested to learn more

How can a Big #Pharma save 168 m$

By Henry Gazay - CEO Medimix International

Who do you want as your sales rep? A Hunter or a Farmer?

Everybody has heard of the traditional division of the sales force into “hunters” or farmers”. We have bought into the belief that some people as “hunters” go after the wins even if it only brings short term results, while others, who are “farmers” and not as aggressive, can accept to maintain the status-quo and to sow their seeds of information with the hope of reaping future harvests. So who is the best for pharma and medical device manufacturers?

It’s more complicated than that!

When segmenting its sales reps, pharma is the exception to the rule and needs to be much more granular in how it classifies them. The process is complicated by the fact that the pharma field force is not “selling” per se, and the act of buying is not made at the moment of presentation. So for these reps, there is no immediate pressure to close and some can get away with just presenting and moving on. Others really enjoy building the customer relation and acting in a consultative manner. Some of these will also be good at the follow-up, understanding the markets and building ongoing relations, to make sure physicians promote the right drug to the right patient.

In the current context where management faces a lot of pressure to optimize sales, there needs to be a better categorization of the sales force and identification by a more detailed breakdown of sales styles.

NOT TWO BUT FOUR SALES TYPES

Based on cumulative interviews from 40,000 sales reps, Medimix promotes a model able to classify any sales force into not two but four types of selling styles or attitudes, represented in the image below.

By asking 60-70 questions of each rep, this very robust model plots each member of the sales force along two axes: their Selling Orientation or interest in selling and their Client Orientation (i.e., the reps interest in the physician). The four selling profiles obtained are classified as ‘seller’, ‘professional’, ‘presenter’ and ‘relational’.”

Benchmarking – The Best and the Worst

The sales people who bring the most to the table are the ‘Professionals’, so the ideal is to have the largest of your sale staff in the upper right quadrant. The actual number will vary by company, but benchmarks show that as a best practice we have seen up to 55% classifying as Professionals, or the ones who are and will continue to be your best producers.

On the other end of the spectrum, in the worse cases up to 43% are Presenters, or people who are not productive and either should be retrained or reallocated.

What Does It Mean? If we consider a sales staff of 1,000 people, this would translate to 430 reps who classify as unproductive, at a yearly cost of $200,000, which represents potentially a waste of $86 million!

A CASE STUDY

In the image below, taken from an actual case study within the United States, the segmentation indicated that 18% of the sales force was unproductive (Presenters) resulting in $168 million dollars wasted in direct operational costs, along with the loss of potential sales. Furthermore, 43% of the reps were underperforming (Relationals), which meant 479 M$ unoptimized.

For the “Relationals” group, the model also indicated specific needs in training and operational flaws that hindered their overall performance.

Corrective action was taken by reallocating “presenters” to other areas of the business and using a fraction of the savings realized to train the “Relationals” and to improve operations.

This successful strategy was confirmed by a new wave of reps interviews a year after.

Are you wasting your resources? Do you know how many “Professionals” are in your sales team ? What would you want to learn from your sales force?

Would love your comments about it...

 

#Pharma100 : To blast or to last ?

July 2013

On the top of the usual US and TOP5 Europe participants, this new edition of #pharma100 (the third one) brought a number of new names to the conversation, from countries as diverse as Turkey, Spain, India, Egypt, Brazil, Argentina, Venezuela, and was by far the most interesting in terms of discussions and point of views exchanged by both promoters and skeptical of the exercise.

As a reminder, #pharma100 was launched a year ago, on the model of #HIT100. A Wisdom of the Crowd contest to help determining who the main influencers in pharmaceutical social media are. To participate, twitter account holders needed to tweet “I nominate @xxx for #pharma100”. The rules are very simple: participants can vote as much as they want but they are not allowed to vote for themselves, and can only vote once for the same person.

From july 4^th to 14^th 2013, 513 participants casted 2,937 valid ballots. Some real time results were displayed in symplur, but to tally the final votes, we performed a manual count by:

-          Dedupping people who voted more than once for the same person (willingly or not)

-          Taking out any vote for oneself (to limit blatant self promotion)

In a democratic fashion, we decided not to exclude anybody from the list, although some participants (as last time) tried to abuse the system by posting nominations for themselves multiple times.

The results of this edition are presented in the following table, congratulations to the winner, @sertacdoganay, Medical Doctor, Pharma Marketer, Speaker, from Istanbul. It is refreshing to see a winner from Turkey, a country which clearly became very active in terms of pharmaceutical marketing over the last 3-5 years (as well as social media altogether the last couple of months). 

HealthcareSMM made it of the second position, which comforts what was seen last time.

Former # 1s @JohnNosta and @andrewspong made it to the 7^th and 14^th positions respectively and this despite Andrew’s call to “stop using Pharma100” (It seems people still voted for him !).

So, this edition of #pharma100 opened a fascinating debate on the value of such an initiative. We have absolutely no desire to pick a fight with anybody on that particular subject, and it is absolutely undeniable that such contest is perfectible. It would also really be naïve to think that it is just a matter of posting one’s name on twitter to make it the ultimate influencer.

It is great to see new names, new countries and new ideas exposed by this initiative.

To those who genuinely participated to this edition, I want to thank you, as you are contributing to give visibility to influencers who might be less known, less vocal or less visible than the ones who generally occupy the limelight.

To those who made constructive criticism, thank you. We progress by learning from one another: in “Social Media” there is Social, and this edition gave us the whole gamut of what our community socially looks like (for better or for worse).

To those who tried to cheat, sending mutiple RTs and DMs, beware, in “Social Media” there is Media, which is eventually unforgiving for such behaviors, and it is easy to see who did what in the glass door of SM. 

In other words, if you want to last… don’t blast!

Handle	Votes	%Votes	Klout score
@sertacdoganay	88	2.2%	67
@healthcaresmm	62	1.5%	58
@clubfarmacia	52	1.3%	55
@anupsoans	49	1.2%	63
@lionelreichardt	44	1.1%	59
@epilkington	40	1.0%	62
@johnnosta	34	0.8%	71
@anaprietonieto	33	0.8%	54
@cefaumh	30	0.7%	44
@rafaelborras	25	0.6%	57
@pharmaguy	24	0.6%	61
@fxpowers	22	0.5%	55
@martatravieso	19	0.5%	52
@andrewspong	18	0.4%	60
@hgazay	18	0.4%	53
@susanagregoriom	17	0.4%	49
@jdcarballeira	17	0.4%	52
@fdalawyers	16	0.4%	54
@farmatornero	16	0.4%	47
@spitzstrategy	16	0.4%	50
@felidelso	15	0.4%	47
@rafaeliki1969	15	0.4%	51
@elfarma20	14	0.3%	50
@nheken	14	0.3%	61
@salilkallianpur	14	0.3%	59
@pharmaphorum	14	0.3%	61
@berci	13	0.3%	71
@farmajuanaloren	13	0.3%	53
@a5farma	13	0.3%	56
@jherrera006	13	0.3%	50
@thibaudguymard	13	0.3%	58
@sdorfman	13	0.3%	57
@cesarmartinezr1	12	0.3%
@inmariu	12	0.3%
@laboticadetete	12	0.3%
@jaimeacosta_	11	0.3%
@paul_sonnier	11	0.3%
@odimad	11	0.3%
@ninavillasusoco	11	0.3%
@chriscward	10	0.2%
@glengilmore	10	0.2%
@christianetrue	9	0.2%
@nacinovich	9	0.2%
@dinchin1	8	0.2%
@asthma3ways	8	0.2%
@alex__butler	8	0.2%
@johnpugh	8	0.2%
@veronicabotet	8	0.2%
@sefac_aldia	8	0.2%
@mcjm115	8	0.2%
@johncfierce	8	0.2%
@isabelmarinm	7	0.2%
@frm_farma	7	0.2%
@durbaniak	7	0.2%
@oscarpeninoscar	7	0.2%
@rohal	7	0.2%
@whadvocacy	7	0.2%
@ngsayago	7	0.2%
@pilarbarralm	7	0.2%
@andybiotech	6	0.1%
@apothecurry	6	0.1%
@erictopol	6	0.1%
@alecgaffney	6	0.1%
@jegarfor	6	0.1%
@wendyblackburn	6	0.1%
@teresamartingim	6	0.1%
@mikemarett	6	0.1%
@steve_l	6	0.1%
@pmolmos	6	0.1%
@matthewherper	6	0.1%
@vikasdandekar	6	0.1%
@elfarmajoven	5	0.1%
@dshaywitz	5	0.1%
@eyeonfda	5	0.1%
@farmaciabarbera	5	0.1%
@farmacarlos	5	0.1%
@eugene_lee	5	0.1%
@fjavierguerrero	5	0.1%
@farmaenfurecida	5	0.1%
@boehringer	5	0.1%
@drpenzesjanos	5	0.1%
@alcompaire	5	0.1%
@farmavalverde	5	0.1%
@acreviriego	5	0.1%
@mayramejiams	5	0.1%
@rafa_castillo73	5	0.1%
@tricosur1	5	0.1%
@reyesmenarguezc	5	0.1%
@pharmaguapa	5	0.1%
@sisacampo	5	0.1%
@ryanmfierce	5	0.1%
@lifescivc	5	0.1%
@maverickny	5	0.1%
@shwen	5	0.1%
@josetes	5	0.1%
@pallarsibruce	5	0.1%
@bootstrapped	5	0.1%
@higiacomunidad	5	0.1%
@factamfarmacia	5	0.1%
@factam_ss	5	0.1%

Pharma100 - July 2013

Here we go again

#Pharma100 contest!

This is the 2013 summer edition of #pharma100


The rule is simple : between July 4th and July 14th 2013, you have 10 days to nominate who 


you consider to be among the top 100 influencers in Pharmaceutical Social Media.

To do so, just post on twitter "I nominate @xxxx for #pharma100 top100 influencers in #pharma social media".

You can nominate as many people as you want, but not yourself.

The count will is tallied on symplur, you can have a look at it at http://www.medimix.net/content/pharma100

You can see here the Second Edition of Pharma100

Good luck to the winners!


Henry Gazay - Creator of #pharma100