The core of every business organisation’s mission is to answer customer needs. In order to do so you must first identify and understand them.
Understanding your customers’ needs is essential but superficial knowledge is not enough to ensure your organisation’s profitability. To achieve product/market fit, the point where you answer needs better than your competitors, you must get to a deeper level of understanding of those needs.
Benefits of understanding customer needs
An added bonus to mastering customer needs (and providing a solution that fulfills them) is that every marketing dollar spent will yield higher returns than those of your competitors, who don’t have the same depth of knowledge.
A deeper level of understanding your customers’ needs will also ensure an overall better customer experience, which we already saw in a previous post on the customer experience journey, leads to higher profitability.
Ok, so now that you are convinced understanding customer needs is in your organisation’s best interest, the question you may be asking is how to go about mastering them.
First you have to identify the needs you will be fulfilling (hint; don’t stop at the needs attached directly to your product/service, also look at the ones surrounding the entire customer experience). Once you have zoomed in on the needs to fulfill, you must not only understand the needs but the whole story around them. This process requires lots of effort, time and knowledge of data gathering techniques. It isn’t as straightforward as it may seem.
As a marketer a huge part of my role, aside from finding the right customers, is to identify and understand their needs. Over the years, I learned that there are three steps to any quest aiming to either identify or understand customers’ needs.
Those steps are; Listen, observe, and empathise
The very first thing you should do when you have a business idea is to talk informally with potential customers. This mostly means listen to their answers. It also helps you figure out who your early adopters are. If it’s not possible for you to talk directly to potential customers, find people who know your potential customers inside out, and talk with them.
Don’t forget to set objectives for your conversation. Examples of conversation objectives are; to see whether the needs you think exist actually do, how they are being filled and the relative importance of those needs. In order to maximise the amount of information you take in, not only do you have to limit how much talking you will do, but you need the proper mindset. Your mind should be open and devoid of as many filters as possible. Always remember that explaining your project in length and your view of the world is just taking time away from achieving your goal. Listen.
On a side note, many of the entrepreneurs I meet are worried that someone will steal their idea before they get a chance to develop it. Unless you have a truly patentable solution (very few are), and potential customers can either beat you to market (they already operate a company in the same field) or spill the beans (to an existing competitor), you have nothing to worry about. Honestly, initial business ideas are very rarely marketable. Even if they were, almost no one wants to put in the blood, sweat, tears and go through the hell that starting a new business entails. Furthermore, even if they did, they’d most likely end up with a completely different business than yours in the end. Lastly if the threat of theft is real, there are still ways to explore the needs of potential corporate customers without spilling your own beans.
Please do not let the fear of someone stealing your business idea prevent you from engaging with potential customers.
Observation is essential to identify less obvious needs and understand all pertinent customer needs at a deeper level. Asking potential customers won’t yield the information you seek because people don’t or can’t always tell you the truth.
There are many categories of observation techniques.
Natural observation techniques allow you to observe your potential customers while they are naturally fulfilling the needs you want to address. Ideally, without them noticing you too much so their behaviours are not altered.
Such observation experiments will yield huge amounts of customer knowledge. Hence you need to ensure you set observation goals for your experiments. Your observation goals can pertain not only to your subjects’ actions but also their interactions, environments, and the tools they use.
You will most likely need to repeat such experiments many times to take in all the knowledge you will need. Alternatively, you can task multiple people to observe the same situation while giving them different observation goals.
Two of my favorite natural observation techniques are shadowing and A day in the life.
These techniques are associated with a goal of understanding a specific thought process or behaviour in a given circumstance.
They require putting the customer in a specific situation or assigning him, or her, a task and then observing. This can be followed by a question period to help interpret what you observed. It can be done face to face, remotely with cameras or on the web (such as A/B testing).
Third person observation
This technique is used in addition to one of the previous ones where the observer is someone who has a vision of the world that is significantly different from you or anyone in your industry. This technique yields much richer interpretation/insights from the data you collect.
Whenever possible, put yourself in your customers’ shoes or, even better; take the time to get to know some of your favorite customers personally. This will enable a relationship of trust and maybe even friendship (personal bonus for you) to develop over time.
Get involved in activities or causes your customers are passionate about. This will give you an even deeper understanding of their values and what is important to them.
Sharing your customers’ values is a requirement to attract them into your community. If you are unsure of what I am referring to here, see this previous post on community marketing.
The 360 view of customer needs
Applying all of these techniques to understand your customers’ needs is required to get a 360 degree view of them. Using many different perspectives to master your customers’ needs will yield rich and actionable information. It will also facilitate innovation in your organisation.
Customer Feedback Flow
Striving to understand customer needs is a continuous process. Set up processes and assign resources in your organisation to make it an integral part of your business activities.
These processes can be as simple as a quick questionnaire you send out on a regular basis, or an automatic feedback one, after a certain task is completed. Analytics reports, comments on social medias summaries or a managed (live or online) community feedback or observation reports are all valid continuous feedback processes that can yield precious information on your customers’ needs.
Be aware that this feedback is highly valuable to your organisation, if you act on it. Hence, reward your customers adequately (often a simple thank you is enough) for sharing their thoughts and concerns.
Mastering the understanding of customer needs is no small task. Your rewards for listening, observing and empathising with your customers, will be a tighter product/market fit, greater customer satisfaction and higher profitability.
 Needs are always dependant other factors. E.g. The need for a given medicine will be dependant on experiencing specific symptoms at a level that requires relief and not being allergic or prone to adverse effects to said medicine.
 The following book describes these techniques : This is Service Design Thinking – M. Stickdorn, J. Schneider et al. – John Wiley & Son
This will be the second to last post of a series of how to apply the Lean Startup approach to a new business.
Until now in this series on applying Lean Startup, we started with an introduction, then looked at the ideation phase, the discovery phase and the pre-sell phase (also known as the Death Valley).
Either because you have made it this far in reading this series or, even more important, you have successfully crossed the Death Valley (pre-sell phase) and came out of it with the holy grail of a product/market fit (when the hockey blade becomes the stick on your revenue chart).
You now find yourself in the concierge phase.
What is the concierge phase
The boxes below presents a very high level summary of usual situations your start-up can expect in the concierge phase.
- Your core features all work pretty well
- You created your first (official) road map to additional features
- If you are outsourcing, you are either looking at optimizing your suppliers or taking steps to bring production in-house
- If you are manufacturing in–house, you are looking at getting decent equipment to start producing at a larger scale
- You are looking at more efficient tools to learn about your customers, markets, and environments
- You are exploring new customer segments
- You are aggressively growing your initial markets
- You are constantly reassessing the total size of your markets
- If you are an innovator in your market; you are keeping an eye out for the chasm (1)
 The saturation of the early adopters market and passage to the early majority (re. The innovation adoption curve)
- You are feeling the need to put processes down on paper so your teams has a more homogenous approach
- You realise you need a lot of processes and procedures but don’t want to bog down your agility
- You are on boarding team members at a rapid rate
- Job definitions are getting more specialised
- Your core team is trying to find a fit with their new, more limited, roles in the company (spoiler alert – some won’t adjust)
- Your core team feels as though they spend more time coaching new resources than getting work done
- Money is coming in at a decent rate from sales
- Labour costs need to be controlled as they are growing faster than your sales at times
- Extra office space and equipment mean increasing your bank margin or taking out (mostly) short term loans
- Investors are now calling you and want to hear about your scaling strategy
Too busy for Lean Startup
You are now running a small business that is experiencing the fastest growth rate it ever will, short of an acquisition.
It is easy and oh so tempting to abandon the build, measure, learn approach. After all, you know your initial market’s needs very well by now and you are crazy busy fulfilling orders, fixing issues and well, running a company.
It is a trap most entrepreneurs will fall into. Until their growth rate slows down, stalls and starts to plummet. The dirty secret of the concierge phase is that most companies’ revenues during this period don’t look like a straight hockey stick handle. That straight upward slope is just the trend of your revenues. The revenues themselves go up and down regularly. If you want your slope average to be positive and steep, you need to minimise those downs. Most times these down periods will happen for the following reasons:
- Your customer needs are changing due to a shift in the market (often due to a new competitor)
- You experience process or production failures
- Your initial early adopters market is getting saturated and you didn’t react quickly enough to open new markets
- Your early adopters markets are saturated and you haven’t figured out how to sell to the early majority customers.
Continuing to apply the Lean Startup approach during your concierge phase will ensure that any new features or internal processes will answer the needs of your customers (external and internal). It will also ensure that market changes are captured and acted upon. This does mean that many of your processes must incoporate Lean Startup elements in them. In some cases, it can also mean that the you will need the build, measure and learn processes themselves to be written down and into job descriptions.
Incorporating Lean Startup in your processes is the key to keeping your company innovative and agile as it grows.
Your product, processes, marketing and overall strategy will adapt continuously. When you need to cross the chasm to reach your early adopters, the Lean Startup approach will be your natural bridge to the other side.
In our next and final post of this series, we’ll take a look at the tools that are most useful in the concierge phase.
 The saturation of the early adopters market and passage to the early majority (re. The innovation adoption curve)
This is the third post of a series. It will try to show how Lean Startup can be useful at the discovery phase of an organisation’s life. The previous post dealt with the ideation or concept stage of a start-up which precedes the discovery phase.
The inspiration for this series comes from my own experiences, as well as those of entrepreneurs and intrapreneurs I have worked with throughout my career. Too much time is wasted on projects that never reach the market or never achieve profitability.
What is the discovery phase?
The discovery phase comes after you put serious thought and work on your business model. During the ideation stage, you asked yourself:
- Who will my customers be?
- What value will my project bring them?
- Who will enable my business?
- How will I connect with my customers?
- How will I make money and what are the costs involved?
All of these questions you answered yourself (or with your partner-s). This means that your answers are not facts but assumptions. These assumptions may be based on secondary data or past experiences but they remain assumptions as they aren’t the direct answers of your stakeholders. Hence, until your potential stakeholders answer these questions the answers you put down on your business model canvas will remain assumptions. Any future ideas you have for your business that significantly impacts any part of your business model should also be treated as assumptions.
You will need to verify all of the key assumptions in your business model to minimise your various business risks. Key means that if the assumption you are making isn’t verified your entire business could:
- Not take off
- Have much lower returns
- Take longer to take off (increasing the risk of running out of runway) or
- Suffer significant impacts (like serving a different clientele or being based in a different city)
This means you will have dozens of assumptions to test during the discovery phase and hundreds, if not thousands, over the lifecycle of your organisation. The two most important meta-assumptions (as they are composed of many assumptions) aka leap-of-faith assumptions, are the value hypothesis (which will lead to product/market fit) and the growth hypothesis (that will enable you to scale your business).
Risk reduction and other benefits of Lean Startup
All these tests on your assumptions are the cost to reducing your commercialisation start-up risk (as well as the product and financial risks by ricochet). Other benefits to using a Lean Startup approach are lowering marketing costs due to having a product/service that will meet the needs of your target markets more closely. You can also expect a better work environment as well as significantly higher levels of customer satisfaction and innovation in your company once it’s up and running.
So how does one go on to test an assumption to see whether it’s true or not? You do what any good scientist would do; you convert your assumption into a hypothesis, then design and conduct an experiment to validate it.
Our next post will show you how Lean Startup experiments are done during the discovery phase.
Ils deviennent omniprésents dans notre quotidien. Les objets connectés se retrouvent sous forme de gadgets telle la bouteille d’eau intelligente. De façon encore plus fréquente sous forme de bracelets ou maillots de sport qui gardent le compte de nos activités physiques et de notre rythme cardiaque. Leur point commun; ils amassent une masse grandissante de données sur différents aspects de notre quotidien et les transmettent à un serveur.
D’ici 2020, on peut s’attendre à ce que plus de 20 milliards d’objets connectés soient en circulation. Ils généreront des pétaoctets de données ayant la capacité de tracer un portrait de chaque minute de notre quotidien. Dans leur ensemble, l’analyse de ces données révélera des informations qui permettront aux fabricants d’optimiser leurs produits. Ce qui fait saliver les analystes marketing encore plus abondamment par contre est l’analyse au niveau de l’individu de ces données.
Nombreux analystes, dont ceux de McKinsey, évoquent une 4ième révolution industrielle. Ils prévoient une société où tous les produits et services vendus seront personnalisés afin de répondre aux besoins de chaque consommateur. Ce qui implique que le marketing de masse se fera au niveau de l’individu et non d’un segment.
Le message sera personnalisé en fonction du profil de l’individu, de son environnement, du contexte voir même du moment. De toute évidence, il ne sera pas créé par un humain puisque nous n’avons pas la capacité d’assimiler et de traiter une telle quantité de données à la vitesse requise. En ce qui a trait aux divers modes de livraison des messages publicitaires, je vous laisse les imaginer.
En poussant cet exercice de prospective à sa limite on peut même en arriver à la conclusion qu’une intelligence artificielle filtrera les messages publicitaires et ne laissera passer que ceux qui correspondent à nos besoins et désirs conscients voir même inconscients.
Revenons du monde de la science fiction et regardons comment nous effectuons le marketing des objets connectés aujourd’hui en examinant les stratégies du bracelet Fitbit et du thermostat intelligent d’Alphabet (Google), le Nest.
On pourrait penser que Google, champion du big data, serait avant-gardiste dans la commercialisation du Nest. En fait, il n’en est rien. Alphabet a embauché en 2013 Doug Sweeny, ancien VP marketing de Levis (les jeans), afin de commercialiser le Nest. Non seulement Sweeny ne veut-il pas exploiter les données d’utilisation amassées par Nest dans sa stratégie marketing il opte pour une stratégie des plus traditionnelles pour un produit de grande consommation. Nest focalise depuis les dernières années, quasi uniquement, à croître son réseau de distribution physique (et non en ligne). Nest fait peu de publicité dans les médias et n’a aucune stratégie de marketing personalisé.
Quant à Fitbit, cotée en bourse depuis 2015, sa stratégie marketing est beaucoup plus évoluée et exploite, bien que de manière limitée, les données amassées par ses utilisateurs.
Fitbit utilise ses données pour développer sa gamme de produits qui compte près d’une dizaine de bracelets. Fitbit déploie également des campagnes marketing hautement personnalisées en adaptant le contenu de chaque courriel qu’elle envoie à ses millions de clients.
De plus, Fitbit inclut dans sa stratégie le marketing communautaire. Outre sa communauté Facebook principale, avec près de 1.5 million de j’aime, Fitbit anime également des communautés pour chacun de ses produits sur de multiples plateformes de médias sociaux. Fitbit commandite aussi de nombreux événements sportifs et créé du contenu numérique destiné à être rediffusé par ses utilisateurs.
Il y a plusieurs autres stratégies marketing particulièrement bien adaptées pour le marketing des objets connectés tel le marketing prédictif, le marketing en temps réel et le co-marketing qui ne sont encore que peu ou pas utilisées dans ce secteur.
Les principaux freins au déploiement de stratégies marketing plus avant-gardistes par les fabricants d’objets connectés sont :
- La perception des consommateurs de l’utilisation de leurs données à des fins de commercialisation
- La convergence requise des compétences statistique, informatique, analytique, psychologique, sociologique et marketing
- L’Absence de formation des analystes marketing dans les stratégies de commercialisation utilisant les données de masse (big data)
- Le coût élevé des infrastructures et applications nécessaires à l’analyse de la modélisation des données
Les trois derniers freins expliquent également pourquoi les fabricants d’objets connectés utilisent principalement des fournisseurs externes pour analyser les données et développer leurs stratégies marketing.
Il est évident que le marketing des objets connectés en est encore qu’à ses balbutiements. À défaut d’une innovation de rupture dans le domaine, il faudra attendre de nombreuses années encore avant de voir le marketing des objets connectés se différencier substantiellement du marketing courant.
Hey, psst Buddy! I can make you rich. I’ll have all the review sites say your product is the best. I’ll increase your web traffic by a gazillion percent. I’ll do this for cheap. Really, really cheap!
Have you ever heard this pitch before from a digital marketing agency? Maybe not said in such creepy words but the essence was the same. I really hope you ran the other way. Otherwise you don’t need to read this post. You have already shot yourself in the foot and know the pain.
Such agencies or marketers offer black hat or shady marketing tactics. They most often offer results that are too good to be true. They will even offer you proof which consist of short term results or big web metrics that will blow your socks off but, in the end, bring no or negative results for your business.
What is black hat marketing?
Black hat marketing tactics are those that are clearly against the law or search engine rules. They can also be legal marketing tactics that are meant to deceive the buyer in order to increase your sales.
The Competition Bureau of Canada and the US Federal Trade Commissioner (FTC) have regulations regarding deceitful marketing tactics. As a company, if you are caught not respecting these regulations it can cost you…a lot.
The Competition Bureau handed down a fine of $1.25 million dollars to Bell Canada in October of 2015 for suggesting to their Bell Mobility employees to post glowing reviews of their services on social medias.
Bell Canada was found guilty of astroturfing; the practice of posting, yourself or via a third party who is not a customer, a fake review of your product or service on the web.
The term comes from the Astroturf product or fake grass. Online reviews are considered grass root marketing, hence the reference to fake grass.
Given current studies show that anywhere from 70-90% of consumers’ purchase decisions are somehow influenced by online reviews, astroturfing can seem like a harmless and a great idea to promote your business. In the long term, it really isn’t.
The reasons are quite simple. First it will incite your competitors to do the same thing. When most of the reviews are faked, customers begin to notice and discard them. The second reason carries a much greater risk. If you get caught either by the competition bureau or FTC you will be fined, which is bad enough, but your name will also be everywhere in the medias. Your company will be identified as a cheat and the trust relationship, necessary for potential customers to become customers, broken.
Asking your legitimate customers to post online reviews, if they appreciated your product or service, however is not considered astroturfing.
The grey zone begins when a business would somehow remunerate their customers to post favorable online reviews or, as it’s been observed, threaten retribution for unfavorable reviews.
Flogging simply means fake blogging.
Fake blogging entails you, or a third party you hired, ask a blog to write and or publish a post on your product or service, against remuneration. In order for it to be flogging, the site’s sole purpose must be to publish such posts. This is prohibited by the FTC (hopefully the competition bureau will follow suit) if the financial arrangement is not disclosed to the readers.
This same FTC restriction applies to advertorials (advertising disguised as a blog post) on legitimate blogs that do not disclose the commercial relationship between the sponsor and the blogger.
Undisclosed flogging or advertorials is subject to stiff fines in the US or a reprimand in Canada. Both of which are also published on their websites. This not only hurts the product or service but also the reputation of the blog that uses such tactics.
You are certainly familiar with this tactic as you have been a victim of it. Spamming is the act of sending unwanted promotional emails in very large quantities to mailing lists you have somehow acquired. Unwanted email means that the recipient did not willfully sign up or accept to receive emails from your business.
Spamming is prohibited under the Canadian anti-spam legislation (C-28 law) and the CAN-SPAM act in the US.
There are numerous other black hat marketing tactics which could fill multiple books, including black hat SEO tactics which are aimed at fooling search engines. Most of them have not yet been categorized as illegal. Using black hat SEO tactics can however get you delisted from a search engine which will kill your web traffic for up to a year.
Shady marketing tactics
Not all deceitful marketing tactics are aimed at your customers. Some are designed to fool you.
Rigging SEO metrics (not the same as black hat SEO) and click-through rates are two methods of choice that dishonest marketers will use to fleece their customers.
Surfing on the fact that most small business owners do not understand how to interpret their website metrics, SEO consultants will use various tactics to inflate the numbers. These tactics include not removing dark traffic from their numbers, making it appear as though visitors are spending more time than they actually are on your site or showing bloated goal conversion rates.
Cyber-rigging of click-through rates
If you or your agency are using a programmatics company to do web advertising you (or sometimes your agency if it’s not on top of things) can fall prey to tactics which are used to inflate the number of clicks on your ads.
Some of these tactics include pushing your ads on sites that are only visited by bots or by audiences that you did not specify (different age brackets or even different countries). It can also take the form of having bots and/or people click on your ads against remuneration. The lattter will usually be undertaken by website owners who get paid to run ads. If done in moderation, it is undetectable. Programmatics and web agencies do (or should) have standards or industry data however to validate whether the click through rates they are getting are legitimate.
This is why it is a safer option to pay your SEO or advertising agencies based on sales results, despite this being a more expensive option.
Campaigns aimed at other types of goals should, as much as possible, be done internally or with the help of a highly trusted consultant.
If you are undertaking a web campaign yourself and have little experiment, ask other similar businesses what type of results they are getting. Educate yourself on how to recognize anomalies in your metrics.
If you are dealing with a consultants or agency ask them to give you a detailed report of their results and explain them to you. If they refuse or tell you it would be too expensive then look for another supplier.
As in every other aspect of life and business, if the results you are getting with your marketing and advertising tactics are too good to be true, then they most likely are.
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.