Life Science Marketing Personas for sales support
/Title: Clinical Scientist
Role: Influencer
Demographics & Titles:
Age range spans whole working life as there is excellent room for job progression and specialisation.
Gender split is approx. 60-40 to female. University grads in recent years follow this trend so gap will widen further.
‘Clinical Scientist’ is a protected title and requires very extensive training and expertise to achieve. The title may only exist in the UK but other regions have their own analogues, Medical Scientist in the US for example. China has no equivalent and only 2 uni’s in the whole country capable of training people to a relative standard.
Usually live in big cities with major hospitals or life science sectors. Often work in hospitals which mixes friends, peers etc. into one group.
Pay range is large, from £25k for recent graduates to £100k+ for experienced, specialist FRCPath level positions though highest wages are in Pharma.
However, NHS work is attractive to these people as it offers stability with good benefits, pension & maternity packages. Also maintains altruistic ideals.
Values & Goals:
They value their work and role in the wider infrastructure that underpins the delivery of any modern healthcare system very highly. “Even on the worst day at work I still know I’ve made a difference.”
These values come from a sense of deciding a patient’s whole future. Genetic testing is one-off, if they say ‘all clear’ or make a mistake, no-one is getting retested.
They appreciate methods and protocols being in place and followed because they value their professionalism and reputation.
The ultimate goal of everything they do is to help patients. Factors such as raising diagnostic yield or deploying new technology need to be justified and validated by this first and foremost. They do embrace tech though based on evidence.
They value their professional reputations, and that of their labs, extremely highly hence their appreciation of methods, protocols and their adherence to them. They prize good, clear science that helps people. They carry these macro goals with them.
Surveys show a decent level of job satisfaction (68%) and a high level of job meaningfulness (83%). Many talk of personal or familial contact with disease or conditions which motivates them. These are commonly Alzheimer's and cancer.
Most Lab Directors used to be Clinical Scientists, hence they are respected and listened to.
Average Day:
Have regular routines, however, considerable deviation between different CS’s routines depend on the nature and location of services being delivered.
Work with complicated equipment regularly and confidently, commonly communicating with colleagues by telephone, email and fax but extremely rare for them to see patients. “I get to help people without having to see them.”
If they are not doing lab work they are looking at a computer screen
Commonly involved in MDT’s
Interpret and evaluate data and write and authorise clinical reports.
Work with realia everyday which underpins their ‘real-world’ outlook.
Undertake daily monitoring of audits, health and safety and quality protocols.
Common Objections & Obstacles:
We don’t have budget
We have our own solution/pipeline/platform in place
We are using X product and don’t want the cost and time to validate and implement.
We don’t like black boxes
We don’t trust cloud based solutions
It's not as comprehensive as they’d like, eg . missing CNV’s.
“I have patients to care for, I don’t have time for this.”
Challenges and Pain Points/problems:
Staff spread too thin. Recruitment freezes. Not enough bodies.
They are almost constantly under financial pressure in; “a system which doesn’t understand spend to save.”
Needs reliable, accurate diagnoses as swiftly as possible
Does a lot of repetitive and time consuming tasks
Push for less qualified staff to do legwork, risk of deskilling.
Has a distrust of new technology and buzzwords, wants results, proof and source.
Spending money on a better and more efficient clinical decision support solution such a Sapientia may save the health service as a whole a lot of money (e.g. less tests, less stays in hospital etc etc), but the budget for Sapientia would come from the Regional Genetics Lab, and the savings would be realised in someone else's budget.
Biggest Fears:
Lab makes mistakes which puts patients/projects at risk and harms reputation of lab and those who work there.
Reconfiguration of NHS labs (21 down to 6) there will be job losses, downsizing. Unknown as to how they would react. May face pay cuts.
Maintaining quality, balancing benchside and budget
That something happens which affects the patient
Experience she/he wants:
A streamlined system which makes their working lives more efficient
To be assured in the accuracy of the process and reliability of its results
To be able to hand-off repetitive or tedious tasks and have more time for complex or interesting problems.
He/She has chosen to stay in this role and specialise rather than entering admin/management roles and thus they want to keep doing ‘science’ not paperwork.
To maintain a highly respected professional voice.
Solutions which prize function over form, are validated and can be used with confidence.
More value for the average patient and more insight and time to work on the more complex cases
A solution that allows historic cases to be reanalysed as our knowledge improves over time (e.g. a VUS is upgraded, so earlier cases that didn't originally receive a diagnosis, might now be diagnosable).
Info Sources:
They prize scientific journals the highest, then the niche press, popular science, industry forums and chat rooms and lastly the mainstream media.
OMIM
PubMed
Nature Genetics
American Journal of Human Genetics
GenomeWeb
Twitter
Conference coverage
Various scientific journals
Individuals’ blog
[It is important to recognise that they often consume a lot of information throughout their working day and hence don’t often read about work related matters outside often preferring escapism.]
Title: Lab Director
Role: Decision Maker
Demographics & Titles:
Salary: High enough to not be listed - over £100k
A1’s/A2’s
They are highly paid and respected
May be driving force behind project choices, may be selecting them on personal influence or due to past study or research experience
People in these jobs tend to have had connections to the labs, institutes or colleagues with whom they work.
The money motivated gravitate to pharma, the project orientated tend to gravitate towards academia in the US and research institutes in the UK.
Values & Goals:
“Lead, grow and enhance research function of the business”
Detail oriented
Needs to provide value
Need to provide improvements/streamlining
There is quite high job satisfaction (75%)
Decent sense of job being meaningful (62%)
Methodical, systematic mind required to keep many factors in play at one time
They like to know the processes of things, black boxes are not going to meet their criteria.
They manage a lot of potentialities and have done throughout their careers. They are solution and workflow focused.
They value their time and effort. Streamlining has value to them.
They value oversight. Security and audit trails have value to them.
They are communicators, they have to liaise with many parties, they have to present data, write papers, pitch/critique projects. They are good active listeners and strong authoritative speakers.
Professional integrity underpins their reputation and attention to detail and compliance to protocol underpin this sense of integrity.
They must be flexible and adaptive throughout the projects etc.
They are committed to their work, maybe because they have the personal investments in their projects or teams, however this often leads to long working hours and they commonly take their work home - if not physically then in their minds.
They are persuaders, advocates - even devil’s advocates - they may be required to take risks or leaps of faith in their work but do so with a lot of due diligence.
Average Day:
“Lead, grow and enhance research function of the business”
Usually reports directly to C-levels
Work hand in hand with Principal Scientist/Investigator
Manages target lists
Plan, direct and coordinate the projects.
Ensure compliance
Must maintain records and compliance, including consent.
May also undertake testing etc themselves as they still like to ‘get their hands dirty’.
Common Objections & Obstacles:
There’s no budget
There’s no contingency
There’s no free lab staff
There’s no time for training
There are established protocols in place
There’s no need to rock the boat
Challenges and Pain Points/problems:
Find themselves caught up in an ‘executive’ life of meetings and titles and paperwork but may still be a scientist at heart.
There is a tacit understanding that spending should be ‘streamlined’, regardless of that, they will always be resistant to spending any money.
At the same time they are also under pressure to provide some tangible improvements during their time.
They have worked hard to get where they are and don’t want to risk anything by rocking the boat and doing something new.
GDPR
Biggest Fears:
There is low job growth and quite slow progression, some may feel trapped in their current role.
That they will not be able to fulfil their goals due to outside influence from the administrative or commercial sides of their businesses.
Mistakes or scandals coming out of their labs
Getting replaced due to underperformance
Getting replaced due to internal politics
That one of the various plates they have spinning will fall and break
Experience she/he wants:
They feel that they are the ‘bigwigs’ of the lab and research environment. They may not have the corner office and the cliched trappings of success but feel entitled to it.
Wants to drive their own lab. Would really like all of the red tape gone and to have the freedom of when they were scientists but with the agency they have now.
To be respected and listened to.
To put science, method and quality first.
To be able to make breakthroughs, write papers and raise profile.
To cure or treat something previously impossible.
Info Sources:
[Of the three personas this was one of the more difficult things to drill down into as they don’t seem to do this as visibly as the others investigated under this piece of work]
The most common sources of information are the top scientific and medical journals, eg: PubMed, Nature, NCIB .
They also gather information from within the niche press.
They are big sharers of articles and information and get a lot of leads and pointers on what to read from their peers.
They promote and share their publications, those of others in their institutions and their peers.
They are proactive networkers and attend a lot of meetings and conferences which empowers this as a proactive information source.
They will follow the work of big names and big institutions in which they are interested or who are parallel or relevant to their lab’s work.
Twitter
Citations from their own or peers works.
Arma
Title: Bioinformatician [NB – People consistently talk about a generational split in bioinformatics that happened around 2010 before which people would have studied an ‘ology’ before going into bioinformatics whereas afterwards people studied bioinformatics as its own thing.]
Role: Influencer
Demographics & Titles:
- Very highly sought after with seniority and experience on active projects outweighing administrative or managerial experience.
- Have value in their own right. One of the most saleable things about Congenica is that we have gathered a large group of talented bioinformaticians and data scientists in one place with overlapping skills and expertise; this is also attractive to them as they like to learn from analogue peers.
- Very highly skilled, need biology, maths and computer science
- Qualifications push them up ABC rankings
- Salaries from around £30k - £50k
- Working hours can be long and demanding especially in research and start-ups.
- Has wider applications outside of healthcare
- Becoming one is very very hard, due to skill range required and need to be seen to have ‘flair’ or ‘own way’. Computational yet creative.
- Job growth and progression is described by peers and industry publications as ‘bad’ due to limited field or options and a view that entering management takes you away from ‘the coal face’
- Need a number of qualifications or experience on a number of projects
- Industry sources disagree whether there is career growth
- Vastly male.
Values & Goals:
- They recommend technology based solutions for research or determine computational strategies.
- Desire stability.
- Very technical when you get into what they do
- Surveys show fairly high job satisfaction (69%), in areas such as Cambridge this could be even higher as being in demand gives them significant ‘buying power’ when job hunting.
- Need to be an active listener and a consultative problem solver with strong critical thinking and organisational skills and a person who likes to learn from doing.
- Need to have a personality with persistence, integrity and dependability. Doing the job ‘properly’ and ‘respecting the data’ are very important.
- A moderate sense of the job being meaningful (65%). Research will be lower, start-ups about this level but would be higher in established and targeted company.
- Undertake personal projects throughout their with hardware, software, programming etc.
- Raspberry Pi ownership is very high and they have an element of ‘dev-ops’ in their thinking.
- They inform management and higher research types to empower them to make better strategic decisions. Given the volume of data they are often seen as having highly valuable insight unattainable outside.
- Need patience and perseverance
- See themselves as ‘at the coal face’ or ‘in the trenches’ of the business, “essentially bringing the scientists from A to B or C or Z”.
Average Day:
- Always on a computer or in a meeting
- Code, process, analyse, review, debug, test, iterate, review, repeat.
- Integrate open source, in house or proprietary databases
- Work extensively with clinical, devs/engineers and dev ops.
- Develop novel software applications and pipelines to meet specific project requirements
- Working hours can be long and demanding
- Are often called upon to communicate research through conference presentations, publications etc.
- Deal with ideas and concepts that require sustained thinking hence it can be hard for them to ‘switch off’ after work.
- The work can tend to be procedural (implement, test, fix), reactive (bugfix, firefight) and creative (troubleshooting).
- In research settings they assess discordance between compressed and uncompressed NGS data. “The volume of data is becoming more critical which is creating new tasks around storage, back-ups, compression etc.”
- In service setting they provide; quality control , maintenance and improvements, pipeline assembly, archiving of annotated sequences. “You feel a shift in companies as they get closer to commercialisation.”
- “Best part is you never have to do overnight timepoints, no one is dying is bioinformaticians don’t come to work at the weekend.”
- Linux and Unix users
- May use Python, R, Perl, C++, Java.
- Work to tight deadlines
Common Objections & Obstacles:
- Will probably claim to have or to be able to do anything we have already.
- Bioinformaticians talking to bioinformaticians about bioinformatics can be really negative.
- Not a very mature field, some people may not be as skilled or knowledgeable as you might expect.
- Concerned about disruption to their data flow and ongoing projects.
- Worried that they may spend time fixing and troubleshooting Sap.
- They already often have to justify the tools and systems they are using, this can make them skeptical of new things or even jaded by being pitched ‘solution’ after ‘solution’.
Challenges and Pain Points/problems:
- Managers without clear grasp of the science often have unrealistic expectations.
- Sometimes feel they are asked to do too much with too little.
- Bosses or project heads often want ‘sexy’ results without realising all the hard work that happens behind them.
- Field of study/science is based upon trying to find definitive meaning but you have so little information and the error-rate is so high.
- Sometimes feel like they are “caught in the middle” of two side of the business and being asked to “swim upstream”.
- Often get vague or unreasonable briefs from higher ups who don’t understand what they do
- Under pressure to keep abreast of technology,
- Are required to improvise quite often, sometimes from scratch.
- The biggest problems they face are often linked to management, unrealistic goals and ‘legacy code’
Biggest Fears:
- Something will come along and make their pipelines, code and technology redundant.
- The open source tools they rely on will become closed source and other protectionist policies.
- What will are the other companies doing? Will we get left behind?
- Will I/the team/the company be able to keep pace with the competition or changes in methodology and implementation?
- You have to invest a lot of personal time into keeping yourself informed an up to date, this can build insecurity.
- The company needs to listen to and invest in its team, if this isn’t happening the fears around being left behind etc. are increased in relation to it.
- There is a trade off between maintaining what you have, management how it works, planning for the future and implementing improvements. This is a complex process that can have far reaching consequences if not done well.
- Unexpected errors which go undetected and effect results generated by their pipelines.
- People either trying to reinvent the wheel or asking them to reinvent the wheel.
Experience he/she wants:
- Fewer ‘dev-ops’ type tasks
- Integrated workflows, especially with clinical teams
- Their skills can sometimes feel like a ‘double edged sword’ to them, they would like more time on interesting and creative projects and less time on the procedural and repetitive tasks.
- To have full confidence in the results being accurate and stable.
- To be respected for their work and not feel like ‘code monkies’.
- To work in a close knit and collaborative team
- To be part of interesting projects
- To have a voice within their team and company
- To have the freedom to try new things
Info Sources:
[There is a lot of personal interaction spoken about and peer to peer knowledge sharing through events, meet-ups and forums plays a much larger role than the other personas]
They often crowdsource answers and support from their peers on sites like StackOverflow
Biostat
Attending inter-team meetings and team building exercises.
Maintaining a good physical and virtual network
Other dev’s and bioinformatician’s blogs
Digital Ocean
Internal documentation
Github
ReadtheDocs
Mozilla Developer Network (mostly Java)