quintessentialramble
New member
Every new SaaS or startup struggles with the question; how much should i charge for my service?
I have been vocal in the past about my own problems with pricing. Specifically, I have been told overtly that my low pricing gives off the impression of a service that is low in quality. For background, my service rents out competent remote developers for $6/hr. In reality, we have leveraged testing automation, Artificial Intelligence, and sourcing statistics at great lengths in order to offer the service at an attractive price point.
The problem with our pricing is that our margin is very tight. A thin margin works if we don't factor in huge costs like advertising . A search on Google Ads indicates that certain keywords like 'hire react developer' can cost as much as $76 per click!
That's a lot of guac. High bids on competitive keywords from big ticket competitors (in this case: Upwork, Turing) drive up the price of the keyword. We wanted to find a way to reward founders who found our site organically, while simultaneously increasing the price for those that found us through search ads in order to compete.
The solution? What if we could variably price our developers depending on what destination they came from. We did so using a multiplier in the params. For example, a URL with the paramatercould increase the base price of our developers by 20%.
The mechanism works like this;
(1) On page visit, the javascript of the page can record the multiplier value from the params and save it as a cookie
(2) Check for cookie multiplier value and use the value when calculating the price of the developer
(3) Save the cookie multiplier value on the user on a sign up event for the sake of consistency.
It only took me a few hours to code and setup. Once you have this deployed, you can use A/B testing to get datapoints on what is the optimal pricing. Many advertising services (meta, facebook) have A/B testing baked in via 'Ad Groups'. In this case, you can setup each ad group with a price multiplier and extrapolate which ad group would have yielded the most profit.
Note that this doesn't just apply to Ads. Plug in your variable pricing in an A/B testing service like VWO and observe the results of the experiment. Incredible, now you can change the price of your product without taking on any risk!
I have been vocal in the past about my own problems with pricing. Specifically, I have been told overtly that my low pricing gives off the impression of a service that is low in quality. For background, my service rents out competent remote developers for $6/hr. In reality, we have leveraged testing automation, Artificial Intelligence, and sourcing statistics at great lengths in order to offer the service at an attractive price point.
The problem with our pricing is that our margin is very tight. A thin margin works if we don't factor in huge costs like advertising . A search on Google Ads indicates that certain keywords like 'hire react developer' can cost as much as $76 per click!
That's a lot of guac. High bids on competitive keywords from big ticket competitors (in this case: Upwork, Turing) drive up the price of the keyword. We wanted to find a way to reward founders who found our site organically, while simultaneously increasing the price for those that found us through search ads in order to compete.
The solution? What if we could variably price our developers depending on what destination they came from. We did so using a multiplier in the params. For example, a URL with the paramatercould increase the base price of our developers by 20%.
Code:
website.com/?mult=20The mechanism works like this;
(1) On page visit, the javascript of the page can record the multiplier value from the params and save it as a cookie
(2) Check for cookie multiplier value and use the value when calculating the price of the developer
(3) Save the cookie multiplier value on the user on a sign up event for the sake of consistency.
It only took me a few hours to code and setup. Once you have this deployed, you can use A/B testing to get datapoints on what is the optimal pricing. Many advertising services (meta, facebook) have A/B testing baked in via 'Ad Groups'. In this case, you can setup each ad group with a price multiplier and extrapolate which ad group would have yielded the most profit.
Note that this doesn't just apply to Ads. Plug in your variable pricing in an A/B testing service like VWO and observe the results of the experiment. Incredible, now you can change the price of your product without taking on any risk!