I have had my fair share of successful and failed SAAS products. The products that went on earn revenue (and doing so till date) and products that didn’t make a buck.
Growing up I loved Sherlock Holmes. I would pretend to be a detective and analyse surroundings.
Well, last week I played Holmes again. But this time to reason why some products get killed while others thrive. During my reasoning I stumbled on one key metric that justified the outcomes. I am calling it DTV.
Distance to Value (DTV) = the time taken by product team (or a startup) to delivery value recognised by end users
It is natural to assume that customers pay for products that they realise value from. Especially in case of SAAS, this means positive displacement in R(Revenue), T(Tax) or C (Cost).
For most products that I started with a small team in basements or cafes, the distance was mountainous. Mainly because we made it so. But we didn’t realise it so because we had just one goal in mind.
Build something that addresses a problem
Reach potential customers and make a sell
To simplify this further, we would have a plan -
[build] hire developers that we can afford. Worst case hire part-time devs
[reach to customer] use social media
This is probably how most startup teams start their work. There are few things that were incredibly wrong about this. Apart from ignoring resource constraint, it did not account for actual goal we would want to achieve. It is to deliver a value good enough for a customer to start pay us.
I recently launched a storage service for a cloud service provider. The product started delivering value from second week. Yes, we had access to customers but a business mind will tell you thats not enough to make customers pay.
Approx. DTV for first customer = [dev effort: 4 weeks] + [documentation: 1 week] + [Customer outreach: 1 week] + [product trial time: <10 mins] + [Training: 0-2 hours] + [Production setup: 1 day] + [First upload: ~ <3 days]
To get to our first customer who used the storage service in production scenario we took approximately 6 week 2 days.
One good thing was we had access to customer so outreach was limited to a conference and a few emails/meetings.
When I look at hyperML, an enterprise grade ML product that I created. Its not just that I spent 8 months in development (mostly alone) but the generation of value was grossly dependent on the the value of technology itself. Most companies even today have a hard time getting value from machine learning and AI. They are further challenges by availability of data scientists / engineers in the talent pool.
The perceived value of hyperML is dependent on actual value generated by ML models that run in production. The TAM (Total addressable Market) is ever expanding, but the meaningful adoption hasn’t really progressed as fast as I thought except the hype around it. I say Meaningful because for me the TAM is only those who are generating revenue with use of ML/AI.
Magic Leap Vs SpaceX
This however does not mean products like hyperML can not be flipped around to generate immediate value. It can if the desired value is adjusted or split across. Take SpaceX vs Magic Leap for example.
SpaceX started with a hefty goal of putting boots on mars. But Musk being a realistic entrepreneur has started delivering immediate value by launching satellites in space. SpaceX isn’t profitable yet but it has already started delivering value unlike Magic Leap.
Spotify
Apart from development time, the trial period or the Onboarding period also plays key role in earning your first buck.
When I signed on to Spotify, I was offered 3 months trial. I chose not to signup at that point. After a few months of regular use, they started offering me one month trial. I was intrigued.
If you were to offer trial for existing user who watches platform every day what trial plan will you choose to offer?
If your answer is 1 month you are correct. For a everyday user, to realise the value of add-free platform will take more or less a month. But on the other hand, for infrequent user to get into habit of listening and then realise the add-free value could take 3 months or longer.
For our storage service, we offered just 10MB free space for trials. This is because our customers already knew what storage service would do, they just had to see ours can do the job.
DTV for product idea or feature selection
I think DTV can play an important role in selecting what features or products to build. You would start by observing value and then work backwards on the time it would take to achieve a perceived value. Personally, I would order the features by DTV and choose the ones that have shortest. Another additional parameter to this could be the weight the value itself. Which sometimes could get subjective and create bias in judgement.
In my decade long career, I have also worked with teams that end up being feature factories. They choose features because a competitor offers it, or it feels like a good feature to have but looking at the whole thing backwards definitely has an upper hand.