In D2C, whether B2B or B2C, low ticket size just doesn’t make sense because you simply cannot get over your CAC with it.
You can see $5 to $20 products flying off the shelf with companies being profitable, but as D2C, it’s not meant for you.
Those companies doing all that business are piggybacking off retailers and other high-scale distributors that absorb and lower the CAC, which you cannot do.
So you have to solve B2C problems or B2B problems that are worth solving.
To rephrase it, you have to solve B2C problems that are big enough or any B2B problem that is worth paying for.
But whatever we do, we have to get the average order value above $500.
You can do it the Target Test Prep or GMAT prep company’s way by having a high ticket with absolutely fantastic value and charging $800 to $2,000 like they do.
Or you can make a B2B SaaS with a subscription north of $50 a month and sell annual plans for a discount, getting around $500+ per user purchase.
If you think about it, the Target Test Prep offer is a lot like an annual subscription given the prep cycle in GMAT because they don’t do it more than a year.
It’s kind of like an annual subscription only.
The customer acquisition economics of both Target Test Prep and a SaaS company peddling annual subscriptions are both kind of the same, and that’s why both of them work.
Another thing to keep in mind is to keep the tech side of things chill and reasonable.
You have to keep the tech stack reasonable.
You have to fight the urge to shove in an OpenAI API or some other AI bullshit.
You have to create value in a cheap way so that you can handle it both financially and tech complexity-wise.
You have to think about what’s the simplest thing you can create value with.
Before making complicated shit and selling it for $50, try selling simple shit for $50.
Simple works, and you can iterate and arbitrage better on it because there are a lot fewer variables to control for.
Keep thinking about API and infrastructure costs because those are the things that can kill your margin.
To avoid bullshit features, maybe first do some consulting in that niche and role-play like you are an organization from that side.
Simulate the workflows and identify what you can do to solve the bottlenecks and all.
You have to put yourself in their shoes.
Also, since a lot of players are just trying to solve each and everything by just plugging in some OpenAI API, it opens up a lot of ground for you to be seen and go and try to solve the problem using some normal API and have better margins and use that cash flow and dry powder to fuel your growth.
So solve a consumer problem worth more than $500 in a single swoop or go for a B2B SaaS with high knowledge of workflows to provide value.
To do this, you have to understand which are the biggest expense points in the life of consumers like college, marriage, etc., and try to make your place there.
Or extensively research and understand workflows and bottlenecks of the niche and sector you want to service with your SaaS.
Of course, you can do random sector studies to have some serendipity and Medici effect helping you.
In B2C, you have to solve for huge non-recurring problems where people go “you only live once” or “you have to nail it in one go.”
In B2B, you have to solve for constant recurring problems where the constant subtractive or restrictive nature of things compounds over time into huge cost and pain.
Model and problem type/scale to address.
B2C = Single Nuke
B2B = 1000 cuts
Funny enough, I see people trying to solve thousand cuts for consumers and a nuclear problem for a business with their D2C startups.
Customers are more likely to pay for big things in big amount, and businesses are more likely to pay for persistent recurring small problems because it’s a game of optimization.
Key Selection Criteria
For B2C ideas:
- Target major life decisions where failure isn’t an option
- Focus on one-time or rare events with high emotional stakes
- Serve customers who can afford premium pricing for peace of mind
For B2B ideas:
- Solve daily operational headaches that compound over time
- Target niches where simple solutions can replace complex workflows
- Focus on businesses that already spend money trying to solve these problems manually
The sweet spot is finding problems that are painful enough to pay for but simple enough to solve without heavy AI infrastructure or complex tech stacks.