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Ask HN: How to get first 10 paying customers?
25 points by usersys on Feb 14, 2021 | hide | past | favorite | 20 comments
My own network is not tech savvy or suitable to try my product. I am digging up cold emails but chance of success is pretty low.

My product is partially complete. Before I invest further time and discover harsh truth, how can I find customers to try it and ultimately pay me in a month?

Reddit blocks any promotional posts and it’s hard to get traction here on HN without karma points.

Please suggest that has worked for you.

You say your "product is partially complete", how did you get there without speaking to customers? If you've spent time on HN in the past, you've probably read about speaking to customers before building, or building to solve your own problem.

Since you say you are offering ML models through a web-service, who else is doing that now? How do you think they find their customers? Can you leverage their customer base to find people that may be wiling to switch?

Step 1 is to identify who needs your product. Then find out where those people are. It's a bit more difficult with Covid due to lack of meetups, etc, but that doesn't mean it's impossible.

However, if I were you, I'd take a serious look at how you got to where you are? How did you build a product without knowing how you were going to get customers? How you are going to know if you've built the right product.

Rather than looking for "customers", at this point, I'd suggest looking for "advice", find somebody who has the problem, and show them your solution. Then ask them if it's something they need. If not, why not? Find out what they do need, etc etc.

Love the problem, not the solution.

So much this. Who were you building it for? What are their problems, and why won't they pay you to solve it?

Despite your progress on code, I would say you still only have an idea. A working idea, but you don't know if it's marketable.

Read Steve Blank - get out of the building and talk to people. Right now, you don't seem to know exactly what the problem is you're solving.

If your product is something that market already demands, one idea is to set up a site and run a small ad campaign.

"How to Kill a Startup Idea with Google Keyword Planner and AdWords: A Case Study"


Earlier HN discussion: https://news.ycombinator.com/item?id=22110004

I also recommend Rob Walling's book Start Small Stay Small. https://startupbook.net/

The book is mostly a practical marketing guide written for developers who are trying to bootstrap a business.

Walling argues for a market-first approach: identify a good niche market of potential customers first (enough potential customers, you have a practical way to reach those customers through search/advertising/niche community newsletters or forums or so on, not too much competition). Then, before building product, run experiment to validate or reject your product idea based on market demand & estimated conversion.

Edit: OP here. Since a few fellow hackers asked about product, I will mention it here. I can’t make edit my own post for some reason (on brave mobile).

My product is offering ML models (classification, recommendation, ranking) through web services. We are offering it for $149/month. You own your data. You can make REST api calls to get output of model. Let me know if you are interested. My email is aimlmodelfarm@gmail.com

Congrats! Make a video of how to use it? Talk to people who maybe have the problem youre trying to solve

> offering ML models (classification, recommendation, ranking) through web services

Your product may be valuable to an organisation when:

(i) the org has a standard kind of decision they need to make regularly - for instance, sales forecasting. (ii) the org makes that decision sub optimally, in a way that could be improved by ML. (iii) managers/executives in the org are actually aware there's a problem (i.e. their sales forecasting is poor), and that sub-optimal decision making has serious consequences for them (increased costs, reduced profitability, reduced revenue, increased churn of clients/staff, increased risk) (iv) there are skilled personnel available who can analyse the situation and join the dots to realise that an appropriate ML model could form part of an effective solution. (v) the org has an existing process to generate and record the relevant input data necessary to make better decisions. (vi) there's enough executive support to do a proof of concept to evaluate if applying ML will produce a good return on investment. (vii) the proof of concept suggests there will be a sufficently profitable return on investment if the project succeeds. (viii) there are skilled personnel available who can productionise the proof of concept - this includes writing the REST API calls to your ML hosting product, as well as doing the remaining 95% of development work to integrate into the org's processes, such as data pre-processing, model output post-processing, data ingestion, report generation, preparing training documentation & training the orgs staff (ix) the org can retrain existing staff or hire new staff to perform the new job of care and feeding of data collection & monitor that the model isn't producing garbage decisions

Here's my guesstimate:

Suppose there's a business making repetitive decisions so sub-optimally that if your ML product were to be successfully integrated, it could lift that business' top-line revenue by 2% . Suppose it costs the business $150k to hire consultants to do an initial feasibility study that demonstrates that an ML-based solution for sales forecasting can lift revenue by a few percent, build a rough prototype, and productionise it. Excluding your product, the ongoing costs to maintain the overall IT system that incorporates this bit of ML might be $70k / year -- mainly staff costs to collect data & execute decisions based on the model output, say. There might also be $20k / year in maintenance costs of related IT systems & maybe a $10k / year retainer to consultants who give periodic tune-ups & support.

What's the smallest amount of revenue this business needs to have so it might possibly get a decent return on investment on this project? The business probably needs to have revenue of at least $7 million dollars.

Based on this kind of argument, your potential customers are:

* managers or executives of businesses with more than $7 million dollars in revenue that have opportunities where ML can be profitably applied. these people must be aware that they have a business problem and also aware that it might be possible to profitably apply ML to that business problem. they will only be able to consume your product if they have existing relationships with staff or consultants who can analyse, prototype, evaluate, integrate & deploy a ML-based solution for the business problem

* managers or executives of businesses with more than $7 million dollars in revenue that have opportunities where ML can be profitably applied but are not aware that they have a business problem where ML could help. it would be challenging to sell to these people as they would need to be shown that they have a problem/opportunity first, in language that they understand relating to their business's operations and goals. this would need to happen well before anyone talks about ML.

* consultancies who engage with businesses to identify and solve these kinds of business problems, that have in-house consulting expertise & ML modelling / feature engineering / domain modelling expertise, but lack the in-house software engineering & operations expertise to reliably run a web service that hosts a model

Here's some good news: the total cost to a business of deploying and operating an ML-based solution using your product is a lot larger than $150 / month. That means it is possible that you could increase your price by 5x to $750/month without it really changing the return on investment calculation from the business' perspective.

Less good news: the most profitable opportunities to apply these techniques are in the orgs with the largest scale -- large-huge enterprises, not small-medium ones. The complexity and cost of setting up an ML solution is often independent of the amount of volume going through the ML, but the benefits are proportional to the volume. These very large orgs may already have large internal IT teams with the in-house capability to do what your product does, as well as lots of enterprisey requirements around risks of their suppliers/vendors going bankrupt, compliance with data protection/privacy laws, auditability of decision making, encryption of data, network security policies, high availability, volume & latency of decision execution.

> How to get first 10 paying customers?

This is irrelevant without knowing the type of product.

It this is a $3.50 product that looks good relative to limited competitors: ~$50 and a day.

If this is enterprise software: a couple million and a year+

> it’s hard to get traction here on HN without karma points

Please dont try to turn HN into an advertising front.


Overall, take the time to write a decent post and you might get a decent answer. You need to write without namedropping for obvious spam reason, the type of product, what it does, why it has a place in the market, what you think customers are, are you targeting countries, price vs competitors, is there a significant onboarding if software etc etc

I'm >10 years of marketing products all over the world and happy to offer advice as I enjoy my work, but the quality of post defines the quality of answer.

You should have them before you build anything. And your first lines of code should be there to test that they exist. You don't get them via surveys and landing pages. You get them by observing something where there is a problem.

They're the ones buying some other app that solve the problem, or hiring someone to deal with it, or finding the problem a distraction to their real core business.

I've never used a network for this and I think relying on your network is handicap. Look for strangers. If a stranger is happy to talk to you about a product you're trying to sell them, you're on to something.

It's hard to understand from your post description whether you completed the in-depth customer development analysis or not. Did you manage to identify your market fit and test your hypothesis prior launching the first MVP? As a piece of advice, you may offer your product for testing / evaluation to the people you've initially interviewed for a lower fee or ask them to price the product.

As a practical tip, I find posting on Betalist helpful. On average, I would say you will get around 100-300 sign-ups.

Out of those sign-ups, you may be able to convert ~20% to actually register for your product.

And out of those, you may be able to convert some to paying customers.

That's exactly what I did with my product Newsy - https://www.newsy.co

I have yet to make my first dollar online from my saas side project. But one thing that I am trying out right now is SEO. It might take some time until you start seeing results. But if your saas is solving a problem for your target audience, you can try to create high quality content for that audience.

Find some guys who may need your product and ask them to pay 20% of the money your product shall save.

I’m reminded of this video https://youtu.be/WAXLTG9n7Kw

Usually - word of mouth and solving someones problem helps alot.

Can you share your product? Who knows, maybe you will get your first paying customer ;)

How about get your masterpiece working and post a Show HN instead?

(I generally prefer a product to comment on than a plea for customers).

Reddit has a paid advertisement feature. Has worked for me, at least to get a few initial customers.

Can you tell us a bit more about the product? B2C or B2B? Price point? things like that.

Make a landing page and create a real email. Set up a form to schedule demos.

give aways on reddit

> "Anyone--founders, managers, and executives--trying to break through to new customers can use this smart, ambitious book." -- Eric Ries

> https://www.amazon.com/Traction-Startup-Achieve-Explosive-Cu...

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