Follow the yellow brick road to startup success

This is a guest post by Hubert, Palan, a good friend and classmate from Haas School of Business, UC Berkeley. Hubert (twitter: @hpalan) is the founder and CEO of, a platform for strategic product design and management headquartered in San Francisco, California. Prior to ProductBoard, Hubert was the Vice President of Product Management at GoodData, where he managed GoodData’s disruptive platform business, built the whole front-end product management team from the ground up and established and embodied modern principles of user experience designs.

An additional note – I see Hubert as the model for taking risks. He decided to launch a startup not because it was the only option available to him but when he was succeeding in his career and had multiple choices at his disposal.

Have you written your guest post yet?

yellow brick road
yellow brick road (Photo credit: hairchaser)

Let me tell you a short story. My wife, Jenna, and I went for a run early one morning in the Oakland hills. We had an idea where we wanted to go, but we didn’t have a map so we didn’t know how to get there. As we ran we asked several dog-walkers for directions along the way. Since it was after a rainy night, and I was running in very thin-soled running shoes, we asked if their recommended path would be muddy or not. As it turns out, different people have conflicting opinions about both the directions and the quality of the road. Eventually after a few wrong turns we found the right path, but of course contrary to what people said, it was pretty muddy.

Why am I telling you this? I recently quit my job at GoodData and started working on my own startup. Our morning run got me thinking about the challenges you have as a founder building a startup, or a new product. You have an idea of where you want to arrive – your dream target audience with a great need, that your perfect solution will satisfy.

You need to create a product roadmap that would navigate your team. Not only do you not have a map, you don’t even know if there are any roads out there. Muddy or otherwise.

So you head out and start asking for advice. You talk to advisors, investors and one potential customer after another trying to discover the roads and choose the best and shortest one. Advisors and investors give you conflicting advice about the best way, because even though they are great runners, they never ran quite the same route. Various potential customers suggest different features they would want, though they are not really sure if they even need them. They are like the dog-walkers, who are not sure about the route either, but since you ask, they make up an answer.

So you run in circles and take many wrong turns. You hope for smooth paths, and they turn out to be muddy. Hopefully though, you end up finding the right way and reaching your goal.

My friend and mentor Arthur J. Collingsworth always said: “Persistence, persistence, persistence.” So no matter if you are running in some hills, building a startup or working on a new product, persevere and keep on running.

It’s not a product until …

When you think of a product what comes to your mind? When does a product become a product?
Take a moment and and complete this sentence

It’s not a product until ______________________

I saw what I believe is the most correct way to complete this sentence. I am not sure if I would have come up with that in my first attempt. The answer comes to us from a Times case study of a small business trying to sell their current product into newer markets.

Here it is, I used white for text color to help you not see it before you came up with your own answer. Highlight the next line to see it.

It’s not a product until you define a set of customers whose needs you meet and who want to pay you.

I agree.

Pricing Always Comes First

In the Japanese animated movie, Kiki’s Delivery Service*(see note below), the little witch, Kiki, decides to start a delivery business using her broomstick flying skills. For one thing, that was the only magical power and there was no other witch in the town. That’s a very good start,

  • playing to her strength
  • delivering a magical (pun intended) and innovative service
  • picking a market where there are no competitors.

Is that enough? What is the plan for monetization?

Her very first interaction with a customer goes like this,

Customer: So what do you charge for your service?
Kiki: I don’t know. I have not thought about pricing yet.
Customer: (stuffing some cash in Kiki’s hand) I think this ought to cover it.
Kiki: (pleasantly surprised) Oh this much for delivery!

Be it a delivery service on a flying broomstick or a product that will change the way we do XYZ, pricing it cannot be an afterthought – a chore to take care of after the fun part of product development.

When you neglect to find the price customer segments are willing to pay before you go to market you end up doing pricing based on cost. Simply tack on a percentage margin to wrongly calculated cost per unit and you have a price. To quote from Henry Ford’s autobiography,

what earthly use is it to know the cost if it tells you you cannot
manufacture at a price at which the article can be sold?

Or paradoxically you act rationally yet not profitably by correctly viewing the cost you have already spent on your data center, product development etc. as sunk cost and decide “free” is the best price. This is based on the assumption that, “customers don’t know they need this product yet. Once they start using, they will fall in love and will pay for it”.

Most definitely price is not something you let your customers decide.  While the narratives we read about customers falling in love with products and paying what they value may capture our imagination, it is not realistic, scalable or repeatable.

The benefits you deliver creates value to your customers and pricing lets you get a fair share of the value created.

If we do not fully understand how our product adds value and hence price it accordingly how can we expect our customers to know what price to pay?

Note on the Kiki’s story: Used only to set the stage, for illustration and not as generalization. The need for effective pricing and how to do it is amply researched, documented and practiced. We do not need a movie for our pricing lessons. That said, it is a great movie, not just for children.

More of the Same or Some of New – Product Upgrade Strategy

In just over an year since the release of iPhone 3GS, Apple released  iPhone 4. Many of the iPhone 3GS customers are more than happy to pay another $199 to upgrade to  iPhone 4. In fact, Apple’s track record with iPod and iPhone has been to release new versions every year. Be it iPod or iPhone upgrades, each has become a bestseller. It is not all due to new sales, a good portion of the purchases are by owners of previous versions.   Customers upgrade to newer iPod and iPhones even when their current products have life left in them.

So what makes the  customer  to mentally write-off their past purchase even though it has not reached its end of life and open their wallet to upgrades?

The answer comes from product upgrade research published by Erica Mina Okada in the Journal of Marketing , 2006 (Upgrades and New Purchases ).

If the customer perceives the upgraded version as dissimilar to the version they own then they are more likely to upgrade despite life left in old product they already own.

For a marketer to convince existing customers to upgrade, they must position the upgraded version as a dissimilar product. For this positioning to be credible the upgrade needs to meet certain key criteria:

  1. The upgrade must have new features – not just enhancements of existing features. Customers tend to focus on features that are new and dissimilar over mere enhancements.
  2. Customers must be familiar with these features before you introduced them – if not then they do not know how to value them and hence are less willing to upgrade.
  3. The features must have high perceived value.

For example* in case of iPhone 4, it has front facing camera and  gyroscope that are new and it has improved screen and speed which are enhancements. The presence of new attributes that customers are familiar with make it a dissimilar product.  iPhone 3GS customers are more likely to perceive iPhone 4 as a dissimilar product from iPhone 3GS.

Apple’s iPod/iPhone upgrade success may be seen as part of Apple aura but the same cannot be said for its other products like iMac. iMac market share has not grown significantly and is nowhere near the explosive growth of iPod and iPhone. Notably, iMac line has not seen major upgrade since the dome shaped version.  Current iMac customers do not rush out to upgrade to the yearly new versions, illustrating the point that iMac upgrades are not seen as dissimilar to previous versions.

Apple has the resources, people and process to  introduce upgrades  year after year and have them perceived as dissimilar products. But  it is not possible for the rest of us.  One tactic for that situation is to position the upgrade as dissimilar product by magnifying the enhancements of select attributes. For example,  redesigned keyboard on Kindle upgrade.

That is a short term tactic, but for you as a product manager what should be your product strategy that will enable you maximize the uptake of your upgrades?

  1. Resist the temptation to deliver a fully loaded version. Find what is relevant to the segments you are targeting and deliver the Goldilocks version.
  2. Repeat this process for each upgrade, i.e., release a Golidlocks* version at each iteration not just for the first version.
  3. Do not attempt to delight the customer – there is no need to deliver more than what your customers are asking for. This is illustrated in the Value Step function I wrote about.
  4. When planning your next iteration choose features that are new over improving existing features. This may go against the iterative development philosophy of continuous improvement. But when constrained for time and resources, choose new over enhancements
  5. Proudly copy – new to your product does not mean unique. Select those features that are present in your competitor products and values highly by customers.

What is your product strategy?

Note1:  iPhone 4 is used only as illustration and not proof. A formal proof was provided by Okada in her work. When Apple releases iPad 2.0 look for new features and being positioned as dissimilar.

Note2: Goldilocks version is labeled as MVP in the Lean Startup community.

Positioning Your Product: What is Relevant to Your Customers?

Update 1/8/2012: Times reports a study that found frequent use of tanning beds affects brain activity.

Medical researchers, dermatologists and FDA have been worried about the dangers  of frequent tanning salon visits. FDA estimates that people who begin using indoor tanning before the age of 35 increase their melanoma risk by 75%.

To these stakeholders, which one of the two side-effects of indoor tanning would be the worst case scenario and hence worth putting their de-marketing dollars behind?

  1. Getting skin cancer
  2. Getting wrinkles

It would appear it is skin cancer message.

Now consider the target customer segment – young women who are not satisfied with their appearance, want to look attractive and “hire tanning salons to improve their skin tone”. Which one of the above two outcome would connect with them?

In the research published in the recent issue of Archives of Dermatology, researchers found that,

They’re not worried about skin cancer, but they are worried about getting wrinkled and being unattractive

It is not a surprise that to the segment that hired the product to make them attractive, a message that the product does not really do the job well will connect better*. This might sound like hindsight bias but the study’s hypothesis included appearance focused messaging and the experiment verified the hypothesis.

Positioning is finding out what is relevant to your customers and what job they are hiring for and applying for it. This is something easy to overlook when we see products as a portfolio of features, results of our superior innovation and R&D and not as means to deliver benefits to our customers.

Even the biggest names in marketing (P&G)  have tripped up on this. In her book Soap Opera, WSJ reporter Alicia Swasey wrote about P&G’s  failure with their pain reliever Encaprin (Have you heard of it?), an innovative drug that was easy on the stomach.

P&G chose to highlight easy on the stomach message, but to its customers pain relief was more important than stomach comfort. P&G pulled the drug after poor performance.

It does not matter what message you think is important to your customers. The message has to be validated with your customers.

Do you know what is relevant to your customers?
Do you practice customer driven product development?

*Footnote: In the tanning salon case, there is availability bias among the young women. They see wrinkled skins around them more often and may assign higher likelihood and weight than they do to skin cancer.

The Long and the Short of Fidelity and Convenience Traps

In introducing the concept of Fidelity and Convenience Traps, I wrote that traps are where a firm is stuck in when its strategy and innovation are aligned with one factor while the market as a whole prefers another. These traps are a result of relatively stable preference (stable over a longer period of time)  of large segments of the market for fidelity or convenience while the firm’s resources are committed to and tied up with convenience or fidelity.

I also hypothesized that the market’s needs switch between  fidelity and convenience over time. This is not a high frequency switch that happens over a very short period time. The switch happens over a relatively long period of time (1 to few years) and in between switches there is a stability. It is the stickiness of the preference and the slowness of change that cause the traps.

These long run trade-offs are much different from the short run trade-offs we make everyday. These short-run trade-offs do not result in traps. Take for example eating pizza. It is a Friday evening, you and your family of four are considering dinner options. Your children decided it is going to be pizza. On a 0 to 100 scale, rate each of the following options (0 – extremely undesirable, 100 – extremely desirable)

  1. Pizza  delivery from local pizza chain for $25, delivered in 30 minutes
  2. Two frozen pizzas at $5 a piece, that you already have in your freezer, add fresh toppings of your choice. Total time 30 minutes.
  3. Make pizza from scratch, with all fresh ingredients including fresh buffalo milk mozzarella for a total cost of $12. Total time 2.5 hours.
  4. Head out to a highly rated pizza place that serves authentic Italian thin crust pizza in a wood fried oven with all fresh ingredients. Total price $55 and drive time 30 minutes, waiting time 30 minutes.
  5. Head out to local all you can eat pizza buffet place with all standard pizzas made with packaged and frozen ingredients. Total price $28 and drive time 5 minutes with no wait time

You can see that high quality ingredients and  special oven make the pizza very high quality – or high fidelity. A frozen pizza or a delivered pizza are not the highest quality but provide great convenience. There is also the price – that pushes people to til either towards the fidelity or convenience end of the pizza spectrum. The score people assign to these options is referred to as its totality utility. Different people get different utilities from the same option and even for the same person the utilities for a given option will vary with context. The choices are not stable, highly unpredictable and vary over short time periods (even within a week).

In other words different segments of the market, at different times (within a short time frame) switch between fidelity and convenience.  This is the short run cycle and does not represent a stable preference by a large part of the market over a relatively long period of time and hence there are no traps.

Short run cycles do not cause traps, only the long run cycles do.

In the coming weeks, I will write more on modeling the short run and long run cycles.