In our last post we looked at various management approaches to reduce risks. One of them pertained to business experiments. In this post, we’ll dig a bit deeper to better understand this approach.
You have most likely heard of business experiments. The Harvard Business Review, as well as many other business management publications, published multiple articles on the topic in the last few years. They were mostly in the context of innovation.
What is a business experiment?
If you have not, a business experiment is simply testing a concept (idea, program, process, design, product, strategy, etc.) with stakeholders (customers, suppliers, distributors, employees, etc.). The experiment’s goal is to provide pertinent data to assist with decision making (usually with go/no go decisions or sometimes fine-tuning).
So yes, you do know what a business experiment is. It’s been around for, well, pretty much ever. Now you’re asking yourself; Why this article is drawing my attention to it?
The reason is that business experiments are no longer used as an occasional management tool, they are transforming into the way businesses are managed.
Why are companies experimenting at an increasing rate?
As we mentioned, business experiments are used to collect data that assists management with decision-making.
Decision-making in the business world is becoming a more demanding task (to say the least).
- Companies are significantly leaner (i.e. less resources and more work for everyone, including managers).
- The amount of information available, from secondary sources, is enough to make any manager’s head spin.
- There is a higher supply than demand for managers hence making bad decisions is a riskier proposition for your longevity in a given company than ever.
- In many sectors, markets are moving at a faster pace than ever before with competitors coming in from everywhere and customers’ choices exploding.
Hence managers are turning to ways to reduce the time and the risk involved to make the best possible decisions.
Running a business experiment to gather pertinent and timely data quickly answers the needs of over-burdened managers to reduce the risks of the decisions they make.
This explains, in part, why organisations are experimenting. What explains the increasing rate at which they are doing it, and transforming it into a management approach, has more to do with the following reasons:
- It’s cheaper and faster than ever to run business experiments (many can be done in minutes with free tools)
- An increasing number of employees or outside consultants have the skills to run experiments, analyse and interpret the collected data
- The costs to store, process and communicate the data/result are very low (compared to a decade ago) and falling constantly.
Business experiments and the Lean Startup framework
So how does an organisation go about implementing business experiments as a managerial approach? There is no one way to do so. There are however experimentation frameworks out there that can structure your approach.
One of these is the Lean Startup framework.
The base of Lean Startup is the experiment. The Lean Startup experiment is based on the scientific experiment model. It follows a build, measure, learn process.
Build (designing your experiment)
Building your experiment is a 3 step process
1. Identify the critical assumption associated with the concept to be tested
When you stop to think about it, there are thousands of assumptions we could test to assist with decision making when managing a business. If we tested all of our assumptions there would be no time or other resources left to run the business. Hence, you only want to test the critical assumptions. The ones that, if not validated, pose a business risk that you (or your organisation) are not willing to take.
2. Transform your critical assumption into a hypothesis statement
Your critical assumption was a thought you put into words. Your hypothesis statement is one sentence that can be validated (or invalidated).
3. Design the experiment that will validate (or invalidate) your hypothesis
Designing your experiment is only limited by your (and/or your team’s) imagination. The way you choose to render the concept of your hypothesis (how you present it or illustrate it) is called your Minimum Viable Product (MVP).
An important part of the MVP is the minimum part of it. In the design of your experiment, you will be aiming at spending the least amount of resources in order to obtain the maximum amount of learnings from your experiment.
This doesn’t necessarily mean bootstrapping your experiment. It simply means that you will make sure that whatever learnings you need to get from your experiment, you get by using the least amount of resources possible.
This can mean it will cost you nothing but a few minutes of the time of one person or tens of thousands of dollars, if that’s the only way to go about getting the information you need. Of course, the cost of your experiment must be proportionate to the financial risk associated with it.
The reason you are making the experiment is to get data that will help you with your decision making. Hence, you want that data to be reliable.
This is where you need a bit of knowledge about primary data gathering. You need to make sure the data you collect is not biased. You won’t be looking to get statistical quality data. That would take too long, cost too much and be an over kill for your purpose.
You’ll simply need the clear direction that your data in headed for.
In business experimentation instead of gathering a lot of data once, you gather a small amount of data repetitively. Although not as precise as statistical data it does provide you with a sufficient amount of information to de-risk, to a great extent, your decision. It is also a more suited approach to an environment that changes rapidly.
When deciding on the data you will be capturing in your experiment, remember these three important rules.
Your data should be:
If it doesn’t go in the direction you thought it would then you can change something in your business strategy or product or program that will make the data go in the direction you want.
You need to be able to re-produce the exact same experiment, in similar conditions and get similar results. For example, if you are testing the design of a snow shovel and are doing it during the storm of the century, the data you collect won’t be accountable.
The more people who interpret the data you collect, the deeper and richer your learnings will be. So make sure that the data captured during your business experiments is shared throughout your organisation. Ensure that everyone knows they are welcome to share their interpretations on the data. Making your experiments, the data collected and the results accessible throughout your organisation will also accelerate business experiments process as some parts/resources of one experiment can be used for others.
The more experience one has at conducting experiments, the faster and more accurately they are done.
This part of business experiments, although it may seem like the easiest, is the hardest. Learning means you are either
- absorbing completely new information (rarely the case) or
- you are changing in some way (sometimes drastically) already stored information in your brain
The second type of learning is the hardest. The more contradictory the data you have is to the one you previously had, the more difficult it is to learn from it.
This stored information in your brain will create a filter that will impact how you interpret new data.
Also, the more resources that has already been invested in a project, the more difficult it is to pivot on a previous course of action.
The benefits of using business experiments to manage
The main benefit, as mentioned previously, is to reduce the risk of your business decisions. This in turn will minimise your losses on various projects.
Another benefit, that is not obvious, is the improvement in work relationships. This happens for multiple reasons.
First, employees get a sense of empowerment. If they submit ideas to upper management with supporting empirical data, they know their idea will be considered.
Also, managers don’t need to spend as much time justifying their decisions. They let the data speak for itself. They do however need to include questioning the quality of the data into their process.
Finally, as mentioned, organisations that use business experiments on a daily basis to manage usually encourage employees to share the results of their experiments. This not only improves internal communication and efficiency it also creates an environment where mistakes, that bring new learnings, are valued.
This type of environment is essential to not only foster innovation but pro-activity.
Getting started with business experiments
If you think that using business experiments may be a profitable management approach for your business, start with one project (which will be a meta experiment) during which all higher risk decisions will be taken with supporting data. The project you select should be one that has high inherent risk within it (like launching a product in a new and different market). It should also be a type of project that is somewhat recurrent in your organisation. This will help you have a baseline scenario in order to compare the results of the meta experiment. Make sure to identify the metrics you’ll be evaluating before starting your meta experiment.
Some metrics (there are many others) you may want to look at would be:
- How long the project took from start to finish
- Overall budget
- What % of the initial planed output was achieved
- Variables pertaining to team cohesion
- Variables pertaining to employee (the ones who worked on the project directly and indirectly) satisfaction
- ROI projected vs achieved on a timeline (3, 6, 12, 24 months)
Implementing any new management approach takes a while. There is no one-size-fits-all recipe. You need to…yes you got it…experiment and find the approach best suited for your organisation.
If you need coaching or help getting started with your first experiment Baker Marketing can definitely help.
 Although MVP most often refers to a prototype of a product, it also means the representation of your hypothesis you will present to participants of your experience.
This post follows Lean Startup Experiment – Discovery Phase. It will help you find Lean Startup tools that will accelerate your experiments significantly. Many of these Lean Startup tools increase productivity and can also be used on a daily basis in your business.
None of these tools, aside from the Javelin board and the experiment log template were developped specifically to be used within the Lean Startup approach. They are simply productivity tools that enable fast and efficient Lean Startup experiments.
Lean Startup Tools
Lean Startup tools make continuous experimentation throughout your startup feasible. Many of those tools are free or cost very little. None of the tools presented in this post were developed specifically for Lean Startup. They are simply productivity tools that are used by the Lean Startup community to increase their productivity.
The following are some of the tools I find most useful and often recommend when entrepreneurs are in the discovery phase. Keep in mind there are hundreds if not thousands more of these tools out there. A bit of googling and asking around will yield you many options to accomplish the same task.
Lean Startup tools to organise
These applications are great as they often work as a checklist as well as organisers. The following Lean Startup tools are all free or have free parts to them. Click on the titles for links.
Ash Maurya has graciously made his Lean Canvas application, which is very well made, free for your first project. It will help you keep a record of the various iterations, enable you to share with other team members and print your canvas.
Free business model canvas application developed by Johan Steenkamp. It has some really great features such as various colours for your post-its, picture and sketching capabilities as well as communication features for your team.
This is a great tool to start figuring out your cost and revenue model. It will act as a check list of all the items you need to take into consideration in your revenue statement. As you progress in your startup, Budgeto will also take care of most of your accounting needs.
Lean Startup Tools to communicate/collaborate
If you don’t yet know about Slack, you must. It’s an instant messaging app, on stereoids, that allows you to connect just about any other popular productivity tool such as Dropbox, Google docs or Hangouts, Skype, Trello and hundreds more. It’s mobile friendly so it will enable you to keep in touch with your team wherever you are.
Trello is one of the many simple and intuitive project management tools out there. Trello is the only full application that still offers free access. It is very powerfull and still simple to use. Other project management platforms such as Asana and Basecamp are even more complete but don’t offer any free versions.
Definitely one of the best ways to share large files and documents. It’s as simple to use as can be and is entirely free unless you are a power user.
Lean Startup tools to run my first experiments
Javalin first developed the Experiment Board for the Lean Startup Machine a couple of years ago. They are now developing it in an app and are still in the testing phase. Until the app is out, you can get a Google docs version of it and print it out. Watch this great video tutorial, from Grace Ng, of how to use the Experiment board.
This book contains over a dozen techniques to help you conduct offline experiments. Each technique is well explained and illustrated with an example. If you’re not familiar with data gathering techniques, it’s the best place to start.
Powerful online survey creation and data analysis application. It’s free for basic forms and data crunching. It has more survey question options and data analysis capabilities than AYTM and GCS. You must provide your own participants list.
Google Forms enables you to create surveys that you can send to your own participants list. Google Consumer Surveys provides the participants and you only pay for completed questionnaires. Pricing starts at $0.10USD per completed survey.
Similar to Consumer Surveys AYTM offers highly targeted participants to answer your surveys.
Pricing starts at about $1USD per participant. AYTM boasts over 25 million survey or experts panel participants.
As of writing this post, I haven’t seen any experiment log templates or application to facilitate the keeping of a journal of your experiments.
Hence, I created one for my own use that I will share with you. It’s a simple Excel spreadsheet that you can modify as you see fit. The important part is to keep your rows constant over time so you can have a base to compare.
Keeping an experiment log is a pain and requires some time and effort. Hence, if you don’t plan on going to VCs for funding, it’s not a must to keep one.
An added benefit of the log is that of a training tool when you onboard other members. Careful reading of this journal will help your new recruits know about your young corporate history and learn from you previous mistakes and wrong turns.
Note: I will add the experiment log template to this post very soon.
Tapping into the Lean Startup community
Some of the most important resources found in Lean Startup are its local and international communities. It is by far the entrepreneurial community that is the most generous with its time and knowledge that I have encountered.
Locally, you have Lean Startup Circles members that meet periodically to learn, practice and exchange on Lean Startup experiments, tools and resources. Circles have experienced coaches that can help you with any part of your experiments.
You can locate the Lean Startup Circle nearest you by consulting the list on the Lean Startup wiki. Most of them, such as the Montreal LSC, have a Meetup page, Facebook page and/or website where you can register to become part of the community.
Once you are part of a Lean Startup Circle community you will gain access to the Lean Startup Slack channels by asking your local organisers. These channels encompass hundreds of members that form a help community.
If you are stuck somewhere in your experiment, are looking for a tool, experiment design ideas, want to know how to go about testing a foreign market, your local and virtual Lean Startup communities will be there to help.
The next phase
Once you have acquired sufficient knowledge on your various stakeholders and have attained a certain level of validation with your business model, you will want to put it to the test.
The next phase will be about validating your business model where it counts; in the market. It is the true acid test. This phase is also sometimes referred to as the Valley of Death. It is when most start-ups end up dying in the Lean Startup approach.
This phase will also be when you start developing your product/service. The good news is if you can’t find any way to have your product/service fly in the market, you will not have spent months or years working on it.
The next post will guide you through this phase using Lean Startup. It will show you how Lean Startup can help transform, some (no, not all) ideas that would have died, into lucrative ventures. We will also present tools and tactics that can help you survive these difficult times.
This is the fourth post of a series that will try to show how Lean Startup can be useful at various phases of an organisation’s life. This post is the continuation of Lean Startup in the Discovery Phase – Part 1 and will show you how to conduct a Lean Startup experiment in the discovery phase of your project
Your first Lean Startup experiment
In Lean Startup all ideas that impact your business model are to be considered as assumptions to be validated. Hence, experimentation is the hearth of Lean Startup. A Lean Startup experiment can be summarised by the Build, Measure and Learn loop.
In order to build a Lean Startup experiment, you first need to transform your assumption into a hypothesis. A hypothesis has the form of a simple, objective statement that can be validated (or invalidated). This may seem simple but it is often one of the most difficult parts of the experiment. It entails that you already have a significant understanding of your experiment participants’ lingo, environment and mindset. Hopefully, you obtained some of this knowledge during your ideation phase when you informally discussed your project.
Your hypothesis must also produce results that will be actionable whether you validate or invalidate it. If, for example, you state your hypothesis as: Customer segment A will always prefer my product to the other solutions presented, all you need is one potential customer to choose another solution to invalidate your hypothesis. What action will you take if you invalidate your hypothesis? None; as your business doesn’t require 100% of a customer segment to adopt your product to be viable.
Simply dropping the word ‘’always’’ in your hypothesis statement will allow you to take action if you validate your hypothesis (you’ll go forward with the segment) or invalidate your hypothesis (you will either pivot on your segment choice or adapt your product further to fill the needs of this segment).
It is also interesting to note that this hypothesis statement contains an unverified assumption. You assume that the ‘’other solutions presented’’ will be the most important substitutes to your product. The experiment, if well designed, will allow you to verify this as well. You may find out that your target segment uses other substitutes that you didn’t account for.
Once you have stated your hypothesis clearly, you need to design a Lean Startup experiment that will enable you to validate or invalidate it. As you now know, you will have a whole lot of these Lean Startup experiments to conduct during your start-up process. Therefore you will be thinking of designing not just any experiment, but the experiment that will require the least amount of resources to achieve your goal. If your product requires expensive machinery to produce, you certainly don’t want to build the entire factory to validate your assumption. You’ll need to be creative and find ways to get your machine’s concept across to the people in your experiment in the least costly way (in $, time and other resources) possible.
The way you will have found to get your product concept message across will be your Minimum Viable Product (MVP). Hence, in this particular example, your MVP could take the form of a drawing on a napkin, on a computer (2 or 3D), in a video, a physical model with or without moving pieces or using a similar product that you supplement with explanations of what your product will do differently. Whatever you feel is necessary and sufficient (no more, no less) to get the message across.
You also need to keep in mind that your Lean Startup experiment should be replicable. This means that in a year from now, if someone else needed to audit your results, they could replicate your experiment and get similar results. In other words, don’t choose a period, a setting or participant profiles that will skew your results.
Once you have identified your MVP, you will need to decide what metric (data) you will be collecting and well as the standard it will need to measure against. In the example cited above, you would be collecting how many people in your experiment chose your product over other solutions that were offered to them. The standard, by definition, would have to be above 50% of your sample given your hypothesis states a preference. Any results below 50% of participants in the experiment choosing an alternative solution would not show a preference. If your hypothesis statement did not imply a comparison but simply an interest in using your product, the standard (% of participants in this case) could be set at whatever you feel would be sufficient to demonstrate clear interest.
In order to reduce the objectivity of standard setting, you should try to get the input from someone who is very familiar with the stakeholders in your experiment in respect to your product/service.
When measuring, you aren’t looking for statistically significant results. This would be ideal but too costly in time and other resources. Instead, you will simply be looking for a clear direction in the data. If your experiment data doesn’t show a clear direction, you will need to include more participants. Occasionally, your experiment will not show a clear direction. You gather whatever learnings you can from it and move on to designing another experiment to validate your assumption.
A word of caution here, despite wanting to go as fast as possible in your Lean Startup experiments you still want to conduct them in a way that will get you to validate or invalidate your hypothesis. If your data collection methods are not done properly and your results are seriously skewed, you will have wasted your time and energy. Hence, you still need to have some basic knowledge of primary data collection techniques. Here are a few good sources of basic information on data collection that you should take a look at if your knowledge on the topic is nil or very low.
During your first Lean Startup experiments, which should be conducted face to face with your participants (this would be the Get out of the building part), you will have the greatest amount of learnings.
While you conduct your experiment, you should always leave room for the unplanned. If a participant reacts in an unanticipated way, run with it and dig into it.
Try to avoid justifying your product/service. Embrace all the comments you will have, especially the negative ones. Dig as much as you can into those. They will give you the best insights. Let the participants talk and listen to the words used, observe body language and notice expressions they use. If at all possible video or tape-record your interactions.
Keep an open mind. It won’t help your start-up if the participants understand your point of view or for you to tell them how you understand their problem. It will however help you tremendously to understand their point of view and what they perceive their problems are or your solution to be.
Your first Lean Startup experiments will help you learn what your stakeholders think about your business model assumptions, as well as all the assumptions you didn’t know you didn’t know. On top of this, you are also learning how to conduct an experiment.
Expect to make mistakes, a lot of them, in the entire build, measure and learn process. That’s ok. Learn from them as quickly as possible and always keep your ultimate goal in mind. If you start an experiment and realise you didn’t state your hypothesis correctly, design it right or choose to collect the right metrics, make immediate changes. Don’t persist with 10-20 other participants with a flawed experiment. Your ultimate goal is to validate a hypothesis, not run an experiment. Similarly, if you had planned to involve 50 participants and you have a very clear direction after 15, stop.
The experiment log
If at any point in time in your start-up process you will be going to venture capital firms for funds, you will want to record your experiments in a log. Your Lean Startup experiment log will document your progress as a start-up. It will show how you dealt with the unexpected, all your learnings and the progress made towards a product/market fit. The data collected in your experiment log will also serve as input in your innovation accounting. Innovation accounting, developed by David Binetti, is one of the more complex but exciting component of Lean Startup. You can learn more about innovation accounting in these previous posts on how innovation accounting is changing the rules, how it’s done and on the concept of innovation options.
Practice makes perfect
As you may have figured out by now, applying Lean Startup requires effort, lots of it, and discipline. Well, that is the reality of starting a business. Lean Startup experiments have one purpose; to bring you closer to having a profitable business or perennial organisation.
You may not be very good at the whole build, measure, learn thing at first. That’s ok. Just keep at it and practice, practice, practice. It gets easier, much easier, I promise. After a few Lean Startup experiments you will start getting the hang of it. Not only will you already have a better understanding of the mindset of your stakeholders, you will develop tools and processes that will make experimenting much faster. You will also develop skills that will enable you to identify critical assumptions quickly, as well as spot, absorb and act on useful information more efficiently.
After a few dozen Lean Startup experiments, the build, measure, learn process will become second nature to you and others, applying it, in your organisation.
Using Lean Startup is similar to buying an insurance policy. It does require more efforts initially than if you simply build your product and service and take it to market. The benefits are that you won’t be building a product or service that will never lead to a profitable business.
Our next post will present some of the tools to help you run your experiments faster, cheaper and more efficiently.
 As long as your sample is not completely biased. Your participants sample has to somewhat reflect the overall population of the stakeholders of your experiment.
Have you ever presented (pitched) your disruptive business idea – one that had yet to be seen in the market – to a venture capitalist, a CFO or a gating committee? If so, you know you need to come prepared with a solid business plan (deck).
The one part of your plan your investor will be the most concerned with is the financial forecast. Detailing costs is usually not a problem. The part however that requires you to put your creative hat on is the revenue forecast.
When presenting this forecast, you can most likely do so with a straight face with the numbers for the first few months. You know very well, however, that any number past this time horizon is based on wishful thinking rather than any market facts. Market facts would require some kind of market history. The problem is that a disruptive innovation is, by definition, not found in the market. Hence, keeping a straight face in front of an investor requires serious acting talent on your part. Fearing that at any time you will be called out.
You can rest assured you won’t be called out. Why? Because your investor, if he or she has any experience at all with financing disruptive innovations, knows that the revenue numbers on your forecast in year 2 are probably less likely to be exact than the chance they have to win the jackpot with that lottery ticket they have in their wallet.
So why are investors and entrepreneurs still relying (or pretending to) on these financial forecasts to decide whether or not to invest in innovation projects? That is the question Eric Ries, author of The Lean Startup, asked himself.
As a serial entrepreneur he knew very well that forecasting sales revenue on an innovation project, never mind a disruptive one, with any accuracy was impossible until you achieved product/market fit (time when you have found the correct business model to generate consistent growth in your sales).
He also understood that investors needed to be reassured that the money they poured in the project, before product/market fit occurred, was used to achieve it and not dilapidated.
Those of you who are not yet familiar with the Lean Startup methodology, it requires the owner of an innovative project to do a series of market experiments in order to validate the underlying assumptions of his or her business model until the model that generates the maximum long term revenue is found.
These experiments, when done rigorously, generate reliable metrics. These metrics are measured against a standard to validate (or invalidate) the assumptions.
A multitude of experiments, done in rapid iterations, are required to test the large number of assumptions on which are based any start-up or project. When an experiment shows that an underlying assumption is not proven, this part of the business model must be changed. Experiments are conducted until the optimal business model is found and then continue during the entire life of the project to constantly adapt the model to market changes.
What is Innovation Accounting?
Innovation accounting is defining, measuring and communicating the process of innovating either in the context of a start-up or a project in an established organisation.
Innovation accounting uses the data generated by the experiments to determine, at a point in time, the maximum value of a start-up or project. The experiments data feed an econometric model similar to the ones used to calculate the value of stock derivatives in the financial sector. The maximum value of the start-up or project at a given time can be used by investors (venture capitalist or CFOs) to gauge how much they will invest given the returns they are targeting.
Now that we understand the why and what of innovation accounting, in the second part of this post, we will dive into how innovation accounting is done.
When is the last time you took a good look at what your customers’ entire experience is like when they deal with your company? If your answer is: Never or not in the last couple of years, you may want to read on.
What is a customer experience journey?
A customer experience journey (aka customer experience map) is the detailed (or sometimes not so detailed) analysis of the experience a specific customer segment has when interacting with your organisation for its entire life cycle, either through one of your employees or any media content you issue. If you really want to dig down, mapping your customers’ interactions with third parties representing your brand (suppliers, distributors, etc.) can also be examined. This information is then presented either graphically or via tables. If a customer experience journey needs to be communicated quickly to a large group of people, a video is sometimes produced to get the information across.
How a customer experience journey is done
The customers’ experience is mapped from the top of the sales funnel all the way down to the last segment of the retention and propagation pyramid. Additionally, specific actions such as purchase, usage and customer loss will be broken down to reflect any potential customer touch points.
Organisations usually task marketing management to accomplish the mapping. Idealy, it should however be done by a team of the top managers of every department that has customer touch points.
If this is your first time at doing a customer experience journey, you can start with the areas where you think there are issues. These will generally yield the highest returns for your organisation. Once you get the hang of it, you can add customer touch points to your journey progressively until you cover the entire spectrum of your customers’ experience with your organisation.
Benefits of mapping the customer experience journey
Returns! Yes, I did write returns. If you have read this blog for a while, you know I would not recommend any costly marketing action unless it has the potential to be profitable for your organisation. Your first endeavors into mapping your customers journey will generally yield the highest results. Those results can have a dramatic effect on your bottom line.
Managers and owners are usually aware of certain ‘’glitches’’ in the experience they offer their customers. Seldom are they prepared for the results a first mapping produces. Their initial reaction is often one of shame and/or impressions that their organisation is bleeding money unnecessarily. Their second reaction is to start acting to resolve the issues brought to light by the mapping exercise.
Typically, a customer journey mapping exercise and the implementation of action plans to correct issues identified yield:
- Reduced rate of customer churn
- Reduced customer service costs
- Increased customer lifetime value
- Better propagation (referral and advocacy), leading to
- Better reputation
- A marked increase in internal innovations of all types (usually non disruptive)
Each of these benefits brings sub-benefits which also yield financial returns.
A large proportion of these returns usually go straight to the bottom line. It makes sense given that improving your customers’ experience is equivalent to making your organisation more efficient at fulfilling its mission, which boils down to satisfying your customers’ needs.
If you are looking for lasting ways to increase your profits at a higher rate than your costs, mapping your customers’ journey through your organisation may be your answer.
Let’s face it. The vast majority of entrepreneurs don’t think they’ll need to do any marketing efforts, so my question may not be relevant to them. A few of them may be right, but only a very few. Those who were brilliant enough to create a disruptive product or service that is a perfect fit with the needs of a large enough market don’t need to put much effort into their marketing initially. The rest of us do. Hence if you’re in the second or third year of your start-up and your hockey stick still doesn’t have much of a handle, it’s a clear indicator that you needed to deploy marketing efforts and need the answer to the title question.
Do I need to do marketing for my start-up?
It would have been nice had someone told me how to know that I needed marketing at the very beginning of my venture you say? So here are a few indicators that show you will need to deploy, at least some marketing efforts, from the get go.
- You have more than a couple of competitors or substitutes in your market
- Your product or service is aimed at other businesses (businesses are not very good at finding even the perfect fit solutions)
- Your product or service is not self explanatory
- Your product or service is luxury priced or high cost
- You are targeting a market where information is not free flowing
There are many other situations but those are the most common ones.
So now that you know you need to do marketing for your start-up, how do you go about defining the pillars of your marketing; your customer segments?
What is a customer segment?
If you are new to the practice of marketing and you take a look at the definition of a customer segment, it won’t be terribly useful to you at best and may even lead you astray.
Defining your market segments solely as a group of customers with homogenous characteristics (whichever one you may think of) is not going to help you much in reaching your goals.
You need a purpose
In order for a customer segment to be of use it must be actionable and enable you to achieve whatever marketing, product or business goals you are going after. This entails of course that you are thinking a few steps ahead and define the goals (business, product or marketing) you want to reach in the near future and tactics you are likely to use to reach them.
Making it real
Let’s say your product is a mobile phone controlled smart night light, and you need to figure out what features to put in your mobile app. which controls the light, to maximise your sales. If you treat your early adopters as a segment it will not be very useful unless it so happens that they all have the exact same needs regarding the application. This is highly unlikely as your smart night light may attract initial interest from students, young professionals, parents and other types of customers who happen to be tech savvy. Although they are all your early adopters, their needs regarding the application features and marketing approach will differ greatly.
On the other hand, if your goal is to test a product feature that will not change across market segments, such as an on/off switch on the light, then using your early adopters as a market segment makes complete sense.
Can your early adopters be treated as a customer segment? The answer is, only if by doing so you can answer the questions that you need addressing at a specific time and place. Most of the time, you will need to refine your segmentation before it is useful to you.
 Shape of the revenue curve of highly successful start-ups