Consider that you have a successful E-commerce store with an above average conversion rate. Now, in order to encourage your consumers to buy and take conversions higher, you decide to offer discount on your products. The discount leads to a spike in sales which in turn leads to higher sales.
The sale has ended and now you are reviewing the performance of your campaign. Your campaign’s sales curve looks like this:
The price points in the graph above have resulted from subsequent 5% discounts considering $100 as the base price. From the graph, you realize that your sales grew from 20 to 80 percent because of the discounts you offered on your products.
Discounts help you acquire more customers, sell off your inventory quickly and help fetch more revenue. Having said that, it is important to note that discounts also decrease your margin and has an impact on your profits. Hence, the ideal discount (and hence the price point) would be the one that helps you maximize your profits.
Coming back to our graph show above, let us try to see what the curve represents. This is the classic demand curve which shows that the Price Elasticity is negative since the sales increased with lower price. Rafi Mohammed, in his acclaimed book, “The 1% Windfall” gives an excellent analysis of the downward sloping demand curve.
I have summarized the key points from the book below:
- Different customers have different valuations
- Discounted prices attract customers with lower valuations as well as encourage repeat purchases
- A lower price leads to more units sold
Now since you are trying to understand which price point to go with in the future, we need to account for the above points namely: Customer’s valuation of product & Financial Motivations (Revenue Optimization, Profit Optimization). So now coming back to your example, how much should you price the product?
“Uh, $80, because then I sell the most units!”
Ah! Nope! You’re not trying to maximize no. of units sold, you’re trying to maximize profits.
Lets calculate profits, assuming that the per unit cost of your product is $80.
If we now plot the profits as a function of price points, we see a hump at the $90 mark.
Now we are getting somewhere. We have indeed found out the optimum price point that leads to highest profit. Awesome!
Constructing a demand curve for your products is a non trivial task. Firstly, you need data on your price points. You need an understanding of your customers, more specifically which factors do they value when buying your product? But if you were able to do it anyhow, you are able to gain a sizeable margin on your products. Doing this in the long run, gives you a scientific way of determining price points for your products. A way that is far more data driven, iterative and leaves you with a better understanding of your customers.
And by the way, if you ever want to know how many units you can sell at different price points, you can always try out our Product – E-commerce Price Discovery Engine