Boosting Profits Using Price Optimization

“The moment you make a mistake in pricing, you’re eating into your reputation or your profits.” – Katharine Paine

Product price is one of the main areas of concern for any eCommerce business, and it frequently has a greater impact on the online market. A buyer in today’s internet marketplace is exposed to a wide range of related products at various price points, and even a small adjustment in price can result in conversions. Factspan has developed a solution to solve price optimization for critical value items for an omnichannel retailer since we recognize the significance of this pricing issue.

Challenges

Our client, one of the largest retailers, owns a virtual marketplace where it sells private brand products along with products of all competitor brands. The retailer wanted to use a price optimization platform to generate reports on the price elasticity of demand and supply & properly position itself in relation to competitors.

The retailer sought to maximize revenue and gross margins without creating any false perceptions of the brand (either as being very cheap or very costly) by optimizing the prices for the core value items.

We had to work around the challenges the business model presented before coming up with a practical solution, i.e.

Identification of Key Value Items (KVI)

Given unlimited online platform shelf space and thousands of products, pricing optimization produces product sparsity and necessitates the use of Key Value Items (KVI).

Seasonal Price Constraints

Many shops have seasonal pricing restrictions on the products, preventing them from changing the prices of goods in the near future.

Align to Product Price Perception

Customers’ perceptions of the prices of various goods vary. By product kind, it also differs. As an illustration, iPhone sells for more money than other mobile phones. If the company substantially changed the pricing of items, there will be an impact on the demand proxy for the goods and the product will go outside the customer’s price range.

While calculating optimal prices, we need to identify the threshold to which we can increase or decrease prices while making sure that the effective demand for the product remains the same.

Finally, we realized that in order to advance, we must first understand that we live in a world of global competition. It is crucial that the pricing of key items is kept competitive so that it meets the price range of customers and becomes the best choice in the marketplace.

Learn More with 3 Ways Big Data Is Making a Splash in the B2B eCommerce

Solution

Key Value Item Identification

With millions of items in the portfolio, it is crucial to pinpoint the ones that are most crucial to the company. It is useful to find those widely sought and frequented Key Value Items that produce more revenue by applying the Pareto principle.

We also discovered that there is a strong association between searched and explored products. Because of this, we developed the weighted perception index for products based on the searches and visits made for each SKU (Stock Keeping Unit) in the most recent 90, 30, and 7 days. This allowed us to identify the Key Value Items. After creating the weighted index, the products were sorted from high to low, allowing us to reduce the number of SKUs and identify the top items as key value items (KVI) based on revenue contribution.

Product Price Elasticity

Let’s talk about the price range and product demand now that we have a better understanding of the KVI products available in the market.

To determine the effective price range of the chosen KVI, we constructed a price elasticity curve across each product department. This aids in determining the range of price adjustments that the company can experiment with without affecting demand in order to maximize the gross margin.

Price Competitive Index

With KVI, we created a weighted index, a price competitive index, and a working price range. To determine whether the chosen KVI is currently competitive, overpriced, or underpriced in contrast to competitors.

We were aided by this in the following ways:

• Locating overpriced KVI products in the client’s market that may be contributing to the notion that the market is too expensive and needs a price adjustment.
• Locating underpriced KVI products that are reducing the client’s gross margin and need a price increase.
• Last but not least, we can employ KVI in price optimization engines at competitive prices

Price Optimizer

We built an automatic optimizer using inputs including key value products, current pricing, weighted perception index, accessible price ranges, revenue made from goods, and price competitive index. And there you have it. We received the appropriate price modification advice after running the optimizer.

Impact

We used the framework to optimize the price of almost 150,000 KVI per week, and we produced a weekly report to show the increase in demand, revenue, and gross margins.