Hacker News Reader

Comment by orangethirty | Hacker News Reader

The ramp from free to paying customer is too high. Either remove the free plan or add a lower bracket. The way you priced things is cute, but shows that these are numbers that you made up. People might look at them and question you, your business, and the value you provide. The standard pricing model [1] works. Stick to it.

[1] - Use .99, .97, or .95 instead of whole numbers. Use odd numbers. Example: 127.99 or 129.99 for your lowest plan.

.99 is for regular prices. .97 is for lowered prices (but still considered regular). .95 is for promotional prices. Special prices may include either, but are ruled by different pricing options.

Edit:

Don't take my word for it and test it.

View on HN

> The way you priced things is cute, but shows that these are numbers that you made up

What it sounds like you're driving toward is better documenting the rationale behind the cost. To my untrained eye, the costs scaled with usage in a fairly familiar pattern.

What would you do to better illustrate the logic behind a pricing structure?

> The standard pricing model [1] works. Stick to it. [1] - Use .99, .97, or .95 instead of whole numbers. Use odd numbers. Example: 127.99 or 129.99 for your lowest plan.

When I see "x.99" prices I always think "annoying gimmick" and typically associate it with low cost consumer goods.

Is there any evidence this type of pricing is appropriate for B2B products?

I was just thinking that consumers of B2B products aren't as easily influenced with pricing gimmicks.

> When I see "x.99" prices I always think "annoying gimmick" and typically associate it with low cost consumer goods.

It doesn't have to be .99 cents, but there is a reason people do this: http://www.sciencedaily.com/releases/2010/01/100119111051.ht...

> The way you priced things is cute, but shows that these are numbers that you made up.

It really does. The events and calls are nice round numbers, so it's not like the worked though to match the silly price points.

A bigger problem I thought though was the type of work.. it's an analytics company that couldn't factor their costs + target margin and arrive at a reasonable, marketable price, without resorting to gimmicks.. doesn't fill me with confidence.

Interesting. I'm curious:

Do you find our prices themselves to be unreasonable or unmarketable, upon quantitative analysis? Or is it just because we put them in powers of 2?

I disagree completely. The prices act as a (slight) marketing tool giving a nod to their primary customer base, and adding .99 prices would feel like pandering. It's clean and simple, as a potential customer I appreciate that.

I really commend Keen for throwing consulting into the mix - Consulting prices are typically a black box to the customer that sales teams use as bargaining chips. This sort of openness is quite welcome as far as I'm concerned.

Thank you. That's how we feel about the pricing, but's it's definitely good to know that some folks are turned off by it.

This is pretty much what we're trying to do. We think the .99 pricing schemes dehumanize the relationship, and we're really all about humanity in our business relationships. Glad you appreciate it -- I'm surprised by the controversy, though, and we may have to reconsider after getting so much negative feedback on it.

Glad you like our published consulting stuff too! Openness is our core value, and it's good to hear that that is getting across to someone in the wild :)

Depends on their target market. B2B tends to be less influenced by pricing gimmiks and more on straight-up cost/benefit analysis. In which case, the numbers can be completely arbitrary so long as the analysis comes out in their favor.

I don't agree with the cents thing. I think stick to whole numbers for this but odd whole numbers. Like 129 vs 130

How do you feel about GitHub's pricing?

All of my data points that they are leaving money on the table.

It's hard to measure emotion and brand loyalty, especially since you can't A/B test something as long term as the latter.

I'm a data scientist, but I'm the first to admit that data isn't always the answer. I'll take sound data-informed intuition over mechanical data-driven decision-making.

Reply on news.ycombinator.com