The Startup Genome project has a lot of interesting data on what paths to success startups have taken, and while there are variations on the timings there is a consistent pattern around the stages all went through.
Stages more than time
If you are familiar with what startup means then you know that it's just a stage of a company and not a special kind of business.
Ultimately it's indeed about stages, not timelines, and while that search for a repeatable business may take longer in some cases than others hoping to jump it simply doesn't make sense.
Product adoption lifecycle
The main reason why stages matter is because you do different things at different stages and missing that context is just going to mean failure.
I've talked before about crossing the chasm, but here it is again in all its penciled glory:
That picture explains in a few lines what every product, and therefore company, goes through its lifetime (if it doesn't die trying).
As you go through those stages your product, your customers, your marketing, everything will probably be different, an evolution at times, just flat out something else in others.
We've talked about early adopters and how it's crucial that you nail that before you move on to the early majority.
This is true for any segment: missing the segment before will make the subsequent one impossible to reach.
Since I've had this question recently you should also bear in mind that moving from one segment to the next, when it happens, is not a pivot: you are not changing customers even if the traits of someone in the late majority will be probably different than the one of an early adopter.
Timing here is crucial: fail to move segment when the time comes and your growth will be too slow and you'll miss the numbers; do it too soon and you won't have enough critical mass to reach the early majority and your development and marketing money will be wasted.
Laying flat a startup's path to success
Recently I ran into someone who was trying to get a sense for Lean Startup and tried to summarize the life of a startup as follows:
- gather all assumptions and ideas into a document
- write each hypothesis down
- list the key functions and selling points
- seek conversational feedback from people to test your assumptions
- if you receive positive conversational feedback, build a very basic prototype to test
- if you receive positive feedback from your prototype, build an MVP with minimum functionality to test and validate your assumptions with data
- create experiments to test your value and growth hypothesis
- bring the MVP to the marketplace and sell the MVP to customers with the intention of getting as much validated feedback as possible
- tweak the MVP based on feedback and data until you have product market fit
- build new functions in small batches, while continuously running experiments to test and validate your assumptions with data
This is actually a pretty good list and does cover what most stages/steps a new product will go through. You may find it's lacking steps about marketing, sales and so forth, but that's missing the point.
If you look at the product lifecycle wouldn't you say those steps would be repeated when you go from one segment to the next? What about if you decide to lunch a new feature for your late majority?
The flat path is a lie! It's a loop!
It's understandable to be drawn to a sequential, straight path, but the truth is, that's far from reality: this is not a linear process.
And I'm sure you can see it yourself once you think about the core of Lean Startup, the build measure learn loop:
First of all if you go back to that list with the BML loop in mind you can see that actually a lot of steps are the same: you're building, running a test, measuring and then doing something else based on what you learned.
Even when you have found enough early adopters and move to the early majority it's the same story: what does that early majority persona look like? you need to validate they have and see the problem and that your solution as you sold it to early adopters fits their agenda.
And if we're talking about adding features after you have a running product it's the same again: those new features need to be tested the same way you tested your first, it's just another loop you're making in the same circle.
There are two basic cognitive issues at play here:
- when you hear a success story it looks like a flat path
- when you think about investing time in building something you visualize it with a beginning and an end.
I think that 2. is especially powerful/problematic as the loop makes people uneasy as they feel stuck, maybe like a hamster on a wheel, chugging away and getting nowhere.
Don't get lost in a local maxima
The loop has its problems and can become waste if you lose track of that timeline and keep running in circles at the same stage.
It's true that it's a loop, but it's also true that there's a timeline, somewhat sequential. Don't get fooled either way.