You want to drive higher revenues and profits, and you rightfully recognize that pricing is a huge factor in achieving your goals.
Like any successful businessperson, you recognize that testing is the only way to deterministically discover your store's perfect prices.
However, you face a challenge: the world is changing:
- Your target audience drifts
- Your competitors change
- Your costs fluctuate (especially shipping)
- You optimize your ads
- Seasons change (that's a guarantee)
In a world of perfect data, you would travel to parallel universes and test different prices at the same time to determine which price maximizes your revenue or profit. Unfortunately, this is not yet a viable option (stay tuned for updates).
So, how do you test prices?
You have two options:
- You set a price and hope that it's right. About 10% of the time, it will be. However, e-commerce is hard enough; you can't afford to let "hope" fail you 90% of the time.
- Instead: You iteratively different prices, changing them periodically. Then, once you have sufficient data, you select the best performer until something changes enough to merit an adjustment.
Iterative price testing – the most powerful model of pricing optimization – faces a fundamental challenge: the world is changing. Product performance always varies from week to week. When you change a price, you cannot directly compare the product's performance before and after the change.
So, how do you compare price performance over periods of time?
You must leverage advanced statistical methods, machine learning, and/or artificial intelligence to probabilistically address the ever-changing factors that influence performance. Unless your team has dedicated data scientists and developers who spend their days analyzing data, developing models, and testing them at scale, this is neither feasible nor reasonable. Instead, you use Pricestack. Our platform leverages proprietary, tested technology to optimize your prices for success in a world of imperfection.
Here's a simplified view of our iterative pricing process:
- Select a price
- Collect visitor and order data until we achieve statistical significance (meaning that our results are 95%+ likely to be accurate – that's 9.5x better than hoping to pick correctly)
- Increase or decrease the price (based on trends)
- Repeat steps 2 & 3 until we've found your optimal price
- Listen for anomalies in the data, repeating the above steps when they arise (typically every few months)
This sounds perfect. How do I get started?
- If you've already installed Pricestack, then visit this brief article for quick steps.
- If you are not yet part of the Pricestack movement, then you can install our Shopify app or start a conversation with us via chat to learn more or talk about custom solutions.
Remember: iterative pricing takes time to unlock its massive benefits. Higher sales volumes across fewer products correlates with more rapid improvements. Your role in this process is to approve our suggested price changes & to focus on your core business while we collect data.