Tag Archives: big data

Why Startups don’t do market research (but should)

Startups are great at coming up with innovative ideas, but why don’t they ever do market research?

“A startup is a human institution designed to create a new product or service under conditions of extreme uncertainty”, said Eric Ries in The Lean Startup. Extreme uncertainty is a defining feature of the startup experience. Uncertainty about the product, the supply chain, the customer, the business model. Two key success factors are experimentation and customer orientation. They enable the startup to achieve product-market fit and to creative a product that can eventually be commercialized.

Getting input from target customers is essential in developing a great offering. Yet, when I talk to startups about conducting market research, many dismiss the idea.

Often, startup founders believe market research is only for large multi-nationals, or that it comes later in the evolution of a company, when a company is established and has multiple successful product lines. Some think it is too expensive or they don’t fully understand the ROI. In addition, many founders tell me that they already have all the customer information that they want.

Let’s look at how startups typically gain information about their market, and what they are missing out on by not conducting market research:

1. At the early stage, founders’ market research typically consists of talking to ‘friendly individuals’ who are willing to give some feedback on the startup idea. The problem here is that the selection of individuals is very likely biased towards people who have a positive affinity to the founder and/or to the product to begin with. It is simply easiest to reach out to your existing network. How objective is the feedback of these individuals going to be?

In addition, we tend to connect with people who are similar to us – similar in age, in gender, in ethnic background, in social status – as it lets us stay in our social comfort zone. How representative are these people for potential users of your product? Particularly if a startup is developing a health-related product or service, potential users are likely very different from the twenty-something healthy males who tend to populate the startup community.

Plus, the ecosystem within which founders operate tends to be highly tech savvy. Getting feedback only within their own ecosystem gives founders a rather poor idea of how regular people would see their product. Granted, tech savviness is going to increase in the future. But do you really have enough time (and cash reserves) to wait for fifteen or twenty years until the majority of the population has caught up with you?

Opportunity missed: Conducting market research early on may help a startup discard an idea more quickly that won’t be popular outside their immediate circle of friends and like-minded acquaintances (‘fail early, fail fast’). Real market research means soliciting feedback from individuals that are not personally connected to you, and who belong to the intended market segment for your product.

Many startups use Kickstarter/Indiegogo as a means to assess if there is really a market out there for their product. While it is comforting to know that two thousand people are backing your campaign and are willing to pay good money now for something great to materialize in the future, this is not enough to build a successful company on. Also, let me tell you a little secret as a market researcher and anthropologist who is in touch with the ‘common man/woman’: Many people have never heard of Kickstarter or Indiegogo.

2. As startups mature, products typically go through many iterations and user experience is incorporated in a continuous feedback loop in the product development process. The UX lead will bring in users, expose them to the latest version of the product and propose adjustments accordingly. In addition, the product itself, assuming that it has a digital component, sends back usage data, which allows the startup to assess how well certain features are performing and conduct A/B tests.

Having a mountain of data that streams back through the device or app makes founders confident in their ability to optimize the product. While this is certainly the case, at times it is hard to ‘see the forest for the trees’. As startup guru Steve Blank said, you need to ‘get out of the building’ to understand your potential market and to learn about your potential customers.

Usability research and user experience research are essential for product development from a technical standpoint and from a design standpoint. In contrast, market research helps you understand the broader picture, beyond your immediate product to prospective customers and their evolving needs and pain points for which your product (along with many others) may provide a solution.

Some methods employed for market research are similar to user research, and some are different. Market research consists of the full gamut of large-scale, quantitative surveys, mobile quick check-ins, trade-off exercises, ad tests, focus groups, location-based research, ethnography, online discussion boards, co-creation labs, in-depth one-on-one interviews and many more.

Opportunity missed: User research looks at, well, users. Market research looks beyond. Only input from a wider target audience will help your startup understand where your product is missing the mark in a fundamental way.

You should also engage in market research as a ‘disaster check’ before going to market. While your product may be delightful and great in terms of functionality, perhaps you are not communicating something that you think is trivial, but that consumers want to know. Safety in wearable devices is a good example. It may be obvious to you that devices have to undergo rigorous safety testing before you are allowed to sell them to people, but the regular person may not be aware of this. If you launch a new wearable without a footnote on safety in your communications, you may be impacting your sales in a significant way. While safety may not be the reason people want to buy your device (unless it is a safety device) they want to be reassured that it is not going to harm them.

Then, after a successful product launch, your startup will only be able to continue expanding its market if you find out what non-users need and want, and if you understand their perceptions of the competition. A successful product fulfills a need better than other products. To find out what target customers need and how your product stacks up against others in addressing that need, you have to engage in market research.

Market research enables startups to step out of their comfort zone, go beyond speaking to the ‘enthusiasts’ and ‘evangelists’ and build an offering that resonates with a larger audience. Do not miss out on this opportunity to critically examine the appeal of your idea and to lay the foundation for exponential growth.

Market research for startups has clear ROI in the following areas:

  • Establish the size of your potential market (ROI: A key talking point when you approach investors at your next funding round)
  • Determine size of different segments within your market and prioritize them in terms of their potential for your product (ROI: Don’t waste money and effort on marketing to a segment that you have personal affinity to but that is tiny or less likely to buy your product)
  • Uncover needs and pain points of potential customers (ROI: Allows you to pivot early, and conserve precious early funding, if your product misses the mark)
  • Validate and refine user personas (ROI: Supports better product-market fit and sets you on a growth trajectory beyond current users to potential future users)
  • Optimize marketing and communications to focus on the product benefits that potential customers most care about (ROI: More bang for your advertising buck)
  • Get an understanding of competitive offerings, how your product stacks up and how to position your product for success (ROI: Stay ahead of the competition and get a bigger share of the pie)
  • …and last but not least: Obtain unbiased feedback on what people really think about your product (priceless 🙂 )

Some questions that startups may have about market research: Is it expensive? Can I do it myself? How do I go about it? There are many reasonably priced ways to conduct market research. Some components can easily be done by the startup itself. However, it is important to get expert advice on methodology and on the design of the research questions, to ensure your research is representative and unbiased.

If you’d like to get more information on what market research can do for your startup, please contact me. I am happy to give you an initial consultation free of charge. You can reach me at: barbara@creativeresearchdesigns.com

Also published on Medium

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Microsoft spitting into Google’s soup

Has your computer been sending you ceaseless reminders to update to Windows 10? I have just updated mine, and now I understand why Microsoft is so adamant that everyone gets the new operating system. Because it is not just an operating system.  

Pumpkin soup

If you choose the ‘Express Setup’ features, you will give Microsoft access to all sorts of data that would not normally be shared with your operating system provider. It will allow Microsoft to make the sorts of rich data connections that so far only Google with its web of interconnected and super-user friendly services has been able to gather (and profit from handsomely).

My new operating system is also very persuasive in getting me to use its search engine Edge and so far I have found it difficult to stay with Google as the default search engine. What a huge coup for Microsoft and major threat for Google! I read an article or two about Edge, saying what a great new thing it is, but who knows who pays these blog writers… Also, when you search on Edge, ominously the old Bing logo appears – not very reassuring, since nobody really liked Bing, right?

But…so far I have not figured out how to keep Google as my default search tool and perhaps I’m starting to like Edge. So what’s Google going to do about that?

Have you upgraded your Windows yet?

Disclaimer: I am not in IT, perhaps I am not fully understanding all the technical details, but the business strategy seems pretty clear…

Confessions of a First Time Wearables User

Since I started my business in healthcare-focused market research, I have been paying attention to wearable devices. Wearables devices have great potential for monitoring health parameters and improving care for certain chronic conditions.

The business press has been making a big deal of wearable devices, predicting exponential market growth over the next few years.

Wearables market growth

I am interested in the user perspective – how useful are these devices, actually? Some statistics show that, similar to fitness club memberships, many people who purchase fitness tracking wrist bands abandon them after a few months of usage.

As an anthropologist, I believe the best way to learn about a certain area of life is to immerse yourself in it, to experience what it feels like and to understand how it works. So I started going to these meet-ups for people engaged in the world of wearable devices. They are awesome!

Run in Steve-Jobs-style corporate presentations by the inspiring wearables guru Tom Emrich, companies in the wearables space present their prototypes and the audience gets to try stuff out in the post-presentation mix-and-mingle. My favorite so far has been the mind-controlled beer tap.

I have met many people in the wearables community, and they are certainly very different in style and outlook to my usual clientele (executives from pharma companies). However, I have hesitated to take the plunge into trying a wearable myself.

I am a pretty fit person, working out two to three times a week, to maintain my health and my sanity, eating pretty healthy, and most of the time walking to public transit rather than taking the car. Whether I run 5 minutes less today than I did last week is not really important to me, as long as I get some exercise every few days. Competing with others along fitness goals does not interest me at all. But I realized that not trying out a wearable myself would deprive me of certain insights that could be essential for conducting the user research that I am so interested in doing.

So I bought a Garmin Vivofit last week. Three things enticed me to purchase this device rather than some of the other ones that are very popular (Jawbone Up, Fitbit, Fuelband).

  1. It shows the time. I am of a generation that still wears a wrist watch, and wearing both a fitness wrist band and a watch separately seemed silly.
  2. Its battery life is supposed to be one year. Charging devices is a big pain, and in my household we are competing for outlets and charger cables to charge the various cell phones, iPods etc for the next morning.
  3. It has a red progress bar that shows up after you have been sitting around for too long. My occupation requires a lot of sitting in front of the computer. I tend to get into a state where I push myself to concentrate only half an hour longer, then another, then another, and then become all tense because I have not taken enough breaks. So a little nudge to get up and walk around seemed like a very useful feature to me.

Garmin Progress Bar

Here are my first experiences with the device:

  • Putting it on is quite uncomfortable. You have to press down on this clip to go into these holes, and doing that hurts the inside of my wrist. Watch wristband makers have certainly figured that one out better. Maybe if you are a tough man you don’t mind. But I’m a lady.
  • The red progress bar is very useful. It has actually helped me take more frequent breaks when I am doing computer work, and I feel better after getting up and walking around for a few minutes.
  • The red progress bar is dumb. This so-called smart device apparently registers only walking activity, i.e. when I swing my left arm back and forth. I was frustrated to see the red bar show up after I spent an hour in the kitchen preparing dinner, and after I was in the back yard, raking and bagging leaves. Apparently, either the sensor or the algorithm don’t realize that these are physical activities.
  • The red progress bar can be fooled. Just for fun, I tried out swinging my arm back and forth for a minute while I was sitting at the dinner table, and it actually tricked the device into registering this as physical activity, so the red bar disappeared.
  • The dashboard that shows my steps and my sleep is kind of interesting. I have only worn the device for a few days, so can’t say yet how useful this data is going to be long-term, if at all, but it’s neat to look at in a narcissistic way – the same way I look at my Twitter account from time to time and delight in the fact that I actually have some followers.

Anyway, it has been a very interesting experiment so far, and definitely proof of the value of ‘walking in the shoes of’ to really understand something.

The true potential of wearables is difficult to tell at the moment. There could be all sorts of useful applications that have not yet been developed or that have not yet gained broad acceptance. After a lot of enthusiasm in the media, there seems to be a bit of a backlash now.

Here’s a recent page from The Atlantic, with quotes of tech opinion leaders all questioning the enthusiasm for wearables:

Atlantic article

And here’s an article written by a health IT consultant about the more technical challenges of integrating mobile health monitoring devices into electronic medical records.

http://medicalconnectivity.com/2014/11/04/challenges-using-patient-generated-data-for-patient-care/

While I share some of the skepticism, the wearables space is certainly an area worth watching, and with great growth opportunities for companies who ‘get it right’. I am excited to be part of this journey.

Man vs Machine

So, Big Data. The market research industry continues to struggle with the concept. It was one of the buzzwords of 2013. Some have come up with a big data offering. Some are searching for a point of view on it. Some counter with small data. Many still have only a vague sense of what we are talking about.

I have asked many colleagues and clients what this concept means to them, in the hopes of developing a brilliant solution that would make me wildly successful. Well, this seems to be taking some time, but anyway, I’d like to share with you what I have learned so far. As I am working in the healthcare sector, this is my focus below.

1. Big Data (in Pharma) is IMS data

For some of my pharmaceutical clients, all they can think of when asked about large data sets is IMS data. IMS captures and sells information about the prescribing behaviour of physicians at the pharmacy level. Through this data, pharmaceutical companies track the sales of their products.

2. Big Data (in Hospitals) is Patient Records and Interaction Statistics

Healthcare providers, particularly hospitals and other large organizations, capture myriads of data on patients flowing through the system. The analysis of this data is largely off the radar screen of traditional market research, and falls under the discipline of health informatics.

3. Big Data is Social Media data

This is a view that many market researchers adopted when social media first appeared on our professional horizon as another form of human expression. Last year’s MRIA NET Gain conference, dedicated to big data, featured a number of presentations in this area.

For those who do not want to develop their own proprietary solutions, subscription-based social media analysis tools are available and used by both end clients and market research vendors.

4. Big Data analysis is a different way of saying Data Mining

Some sectors have worked with large data sets for some time. I am thinking of scanner data in retail, and loyalty programs (Air Miles, Petro Points etc.). Fifteen or so years ago, the statistical techniques used to sift through such data sets were called ‘data mining’.

This practice is still ongoing, and the size of data sets ever increasing with more and more customer touch points being added. Some think of this type of analysis, when hearing the words big data.

5. Big Data is Data that is created by Machines

This type of big data is rarely mentioned and obviously not in the forefront of a market researcher’s mind. However, it has grown exponentially and is increasingly viewed and used as a source of customer information.

For market researchers, the question (and the fear) is to what extent human analysts are still needed, and to what extent ‘the machine’ can do it on its own. And how we can make sure we are still needed.

We say: “You need an expert to interpret what your data means.” We say: “A consultant is needed to guide the analysis process.” We say: “Meaningful data analysis is the development and testing of hypotheses, and only people can come up with those.”

And we are right.

How many times have I looked at the results of a statistical analysis and said, “This does not make any sense.” And then we discarded the analysis and started fresh, because results need to make sense. To another human. To your client. They need to lead to actionable insights and recommendations.

So we are still needed. But…

But many, many processes are now automated, from data analysis over producing charts even to highlighting key insights in charts. Far fewer people are needed to work with the data then before. Take a look at www.beyondcore.com – will get you thinking.

Some companies function with very little market research, in the sense of interactions between real live researchers with real live respondents. Machine-generated user data that streams back from devices guides the refinement of these products. New Apps are developed by split testing and seeing how early users interact with certain features, following the logic of clicks. Service companies integrate their customer interface and CRM software with their enterprise management system. Automated cues let managers at different levels know how they are performing, and notify them if there is a problem.

Technical skills are essential for survival. How can you tell a successful agency these days? If you look at their ‘careers’ page, most of the open positions are for developers (i.e. IT people). Those who win in providing business intelligence are either companies who are focused on the digitalization and automation of data collection and analysis, or companies who make intelligent use of available software products and platforms within the research process.

Do you know what Hadoop is? A wireframe? CSS? If not, perhaps it is time to google it right now…

Man vs Machine

 

Innovation, the new normal?

Companies in many sectors are facing rapid change. Following Clayton Christensen’s terminology, established businesses are being disrupted by new technology, and new business models are developed around these technologies.

Whether it is 3D printing of medical implants, crowd sourcing of clinical trial data analysis, software that supports pre-clinical studies and identifies the most promising drug candidates, ‘big data’ capturing patients’ genomic profile or personalized health records that patients can carry from physician to physician, fundamental transformations are afoot in the healthcare industry.

Consultants to the healthcare sector struggle to stay on top of all the different angles that are emerging. How much reading can you do in a day? Should you rather update your skills in data mining (i.e. working with ‘big data’) or become an expert in social media platforms and the many ways they are being used by patients and physicians or study government initiatives to incorporate new technologies in reorganizing the way healthcare is delivered to the patient?

The state of confusion is pretty typical for market changes. Initially, there is a whirlwind of new ideas and approaches. Are electric cars going to be the way of the future or ceramic fuel cells? Or will biking emerge as ‘disruptive technology’ in a reorganized urban neighbourhood? Will patients carry their own health records around on a USB stick or will they become universally accessible through a (password protected) cloud? Will pharmaceutical companies find ways to make drug development cheaper or will fewer drugs be approved or will best supportive care with the bells and whistles of comfortable retirement living ‘disrupt’ the oncology pipeline? Will iOS, android or Windows 8 emerge as the dominant ecosystem for computer / tablet / phone or do we need to learn all three to know what works how in which environment? Etc, etc.

Should we wait until the dust settles before we decide how to focus our efforts?

I am not sure that the dust will ever settle. The pace of change is accelerating, with no sign of stopping or settling down. Then where should we pitch our tent? What should we hold on to? I believe that companies and individuals will succeed who develop mechanisms, routines, practices that allow them to deal with change. Not just once, but on an ongoing basis. Those who effectively survey what is going on in the whirlwind, who systematically capture their own ideas on how to ride the storm and who devise an easy process that allows them to test, develop and implement these ideas will have a chance.

Is big data transforming healthcare marketing research?

Yesterday (June 27, 2013), SAS and GSK announced a collaboration which puts clinical trial data ‘in the cloud’ in a secure way, respecting the privacy of trial subjects, and makes it accessible to other researchers. It is believed that other big pharma companies may follow suit and create an unprecedented shared data base that could potentially speed up the analysis process, make analysis more transparent and produce significant advances in medical discovery.

While this particular example of ‘big data’ pertains to clinical trials, many other big data sets exist (or are being created) in the healthcare space, awaiting data integration and analysis. One wonders to what extent this trend will impact the need for primary healthcare marketing research. Secondary data analysis is not new – it has been part of business intelligence for a long time. What’s new is the amount of data that is being collected, the multitude of platforms and interfaces through which it is collected and the ease with which the data can be accessed and analyzed.

Traditionally, primary marketing research has been faster than secondary data sources at delivering behavioural data such as prescribing of certain drugs. This is now changing. Mobile health apps, EMR, data warehouses for adverse event reporting, point-of sales data at the pharmacy level and many more points of data collection are becoming more readily accessible. Secondary data is going ‘real time’, well almost. On the other hand, primary data collection methods can also harness the power of ‘real time’, thinking of mobile surveys etc. Who will come out on top, or rather, which mix of primary and secondary sources will deliver the best insights?

Also, primary marketing research has been practically the only way to capture attitudes and beliefs and to explore how they relate to behaviour. Arguably, communicating with your target audience is still the best way to understand their motivations. However, social listening, drawing on tens of thousands of online conversations and powerful tools for text analysis, has made some inroads into this area as well. In addition, to what extent do stated opinions really drive behaviour, and how good is primary market research, even with creative methods and advanced analytics, at uncovering these drivers?

Big data is certainly transforming the primary marketing research industry, in healthcare as well as in other sectors. The question remains which solutions will bring the most value to clients and will become the new standard for companies who survive the transformation.