Setting competitive pricing has become a major challenge for businesses. In the era of massive competition, it’s hard to come up with a price that will be effective both from the profit-making perspective and satisfactory for customers. That’s where price optimization comes into the game. Price optimization uses mathematical analysis to determine how customers would respond to different prices via different channels, as well as the price that would maximize the operating profit of the company. It’s not about price monitoring, but rather, it’s the process of using data to make analysis and determine the price based on the willingness to pay (WTP) of customers.
Price Wars in E-commerce
Nowadays, customers can easily go online and compare the prices of similar products with the help of search engines and online catalogs. So the tough competition definitely plays a major role in the process of setting a competitive price. Besides competition, retailers need to pay attention to factors such as product costs, distribution costs, and market positioning. All of the challenges for price setting bring to a situation called price war. A price war is a hard time for retailers. During the times of severe competition, companies start lowering prices to undercut competitors and find themselves in price wars. The purpose is to attract as many customers as possible to win the biggest market share.
With the rise of the internet, it seemed that the price wars would diminish. However, managers have a different view of what’s happening. Price changes are seen as an easy, quick and reversible actions. In reality software, different tools, artificial intelligence, and big data offer a great opportunity to e-commerce and retailers to change their prices instantly. But you have to be cautious of all the actions you take when it comes to price changes. A simple wrong move and you’ll be out of the game in no time. Business is a severe activity that always needs to have winners and losers. In the rest of the article, we will introduce you to different price optimization tactics, as well as how you can leverage data scraping technology for optimizing your prices.
Price Optimization Tactics
Dynamic Pricing
With the ever-changing e-commerce environment, dynamic pricing has emerged and became the most-used pricing strategy of businesses. Dynamic pricing is the contrary tactic of previously loved static pricing strategy. It’s the practice of changing the price of a product or service to reflect the changing market conditions. For example, when the demand increases, so do the prices of products. Most of the businesses that used static pricing before have switched to using dynamic pricing, mostly on online platforms. Price fluctuations happen due to different market factors.
World’s largest online retailer Amazon uses this pricing strategy. Amazon’s algorithms change prices millions of times per day depending on the demand. On their website, a price for a certain product can change even after the person has added it to the cart. Prices can lower based on demand, promotions, other retailers’ prices, customer intent, and current pricing patterns. A lot of retailers set their prices according to Amazon’s policies, so Amazon is definitely winning the pricing game. Dynamic pricing can help a retailer effectively boost sales and profits by simply adjusting prices. Prices can also be adjusted according to the segment base, time-based purchasing, and peak hours.
Value-Based Pricing
This pricing tactic is based on the idea of setting a price that relies on the customer’s perceived value of the product or service. A payable customer is ready to pay a higher price for products that offer more value. So value-based pricing strategy takes into consideration the WTP of customers, and that’s why this method has a competitive advantage over the rest of pricing strategies. The value of the product is identified based on:
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- Price Sensitivity Analysis: understanding how much a person is willing to pay and thereby, identifying how they value the product or service.
- Product Preference Analysis: collecting data on factors such as customers’ concerns, motivation, or willingness to buy a certain product.
- Market Research: gathering and analyzing the data of the customer base, such as demographic information (e.g. age, gender, occupation, location, etc.).
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Behavioral Pricing
This pricing strategy is a newer practice that has emerged with the growth of e-commerce business. Prices can be changed and adjusted based on the behavior of the person online, thanks to the data available on each user. For example, the algorithms can analyze the data available from the user’s past browser search history, online shopping or social network engagement. In some countries, behavioral pricing can be considered price discrimination because companies take advantage of the data they have a person and use it to adjust the prices.
Charm Pricing
Charm pricing is a type of psychological pricing that works on the subconscious of the customers using psychological actions to persuade them to make a purchase. You’ve surely seen how products often retail for a price that ends at 9 or 99, haven’t you? With charm pricing, the left digit is reduced from round number by one cent so our brains would process the price cheaper. For example, our brain perceives $2.99 cheaper than $3.00 because we tend to only interpret the digits on the left side. So price optimization can be also employed by leveraging the power of human psychology. Go to Apple’s official website now and check out their prices. You won’t be able to find a single price that doesn’t end at 9 or 99.
Price Elasticity of Demand
In general, regardless of the pricing strategy you use, it’s important to conduct a price elasticity analysis. Price elasticity is the underlying phenomenon behind all the methods of retail price optimization. The idea behind price changes is basic and implies that sales increase when a product/service has a low price and decrease when the prices rise. However, businesses can’t simply reduce or increase prices without a legit reason, as it will result in a profit margin cut. Price elasticity of demand is an economic measure of the change in the quantity demanded of a product in relation to its price change.
Products have different elasticity of demand. Inelastic products do not change prices given the changes in their demand. These include necessity goods, which people will have to buy in the same quantity regardless of the price (e.g. food, water, gas). In the case of elastic goods, their prices increase or decrease based on substantial changes in the demand. Each of your products must go through a price elasticity analysis to identify how elastic it is. Effective and timely price optimization can happen only if you conduct a price elasticity analysis of your products or services.
How Price Scraping Helps with Price Optimization
Data scraping technology is a powerful tool in the hands of whoever uses it. Increasingly, businesses use data available on the web to get ahead of the competition. Ecommerce scraping is used by various retailers. Data scraping offers an innovative and simple way of collecting information from all over the internet. You can scrape information about your customers, competitors, market, etc. But most importantly, you get a chance of price scraping which will help you with price optimization. Leveraging the power of big data will lead to better pricing decisions. You need to learn to listen to the data, in order to make better decisions. However, you can simply get lost in the enormous amount of data available online. With the help of price scraping, you will get the opportunity to get the most relevant, accurate and reliable data out there.
Price scraping and e-commerce scraping offer many advantages to online retailers:
- Price optimization – the biggest challenge for e-commerce is how to increase prices and not lose customers. Price scraping will help you stay informed of all the competitors’ price changes so that you can optimize your store’s prices and proactively react to all the changes. You can also optimize your prices by tracking your competitors’ catalogs and spotting in-high-demand products that are missing. It would be a great opportunity to increase the prices of complementary products on your website.
- Effective dynamic pricing – price scraping is especially beneficial if you’re using a dynamic pricing strategy. We’ve already talked about how Amazon is changing its prices numerous times per day. So how to keep up with all those changes if you’re not updated regularly? Data scraping technology can deliver data whenever you want and as regularly as you want. That way, you’ll be able to use that data to change your prices accordingly.
- Staying updated on promotions – companies do not wait for special events to offer promotions as they did before. The dynamic industry of e-commerce makes retailers create new and attractive promotions regularly. You need to use price scraping to spot all the price promotions your competitors are running. Also, keeping track of the success of those promotions will help you get an insight into the most effective campaigns.
- Building a pricing strategy – if you are new in the market and you are still testing the best pricing strategy that works for you then leverage price scraping to get insights into what’s happening in the market now. Your pricing strategy should depend on a number of factors such as the market in which you operate, the WTP of your potential customers, the required profit, costs and the prices of manufacturers. All of these combined will guide you to decide on a pricing strategy. So you can leverage the power of data scraping to not only get insights into your competitors’ prices but into all the other factors as well.
- Research and analysis – it doesn’t matter if you’re new in the market or have been operating for several years, you need to constantly keep an eye on what’s happening in the market. Pricing strategy is not a one-time decision anymore. The dynamic and competitive environment requires you to always be ready for any changes. Price scraping can help you with price optimization in the long run. If your scrape data for specific periods of time and analyze that data, you might spot specific trends of prices. That kind of analysis will help you stay above the competition.
Case Analysis: How Walmart Uses Big Data?
Walmart is one of the leading retailers in the world that is in a constant fight with one of its most severe competitors – Amazon. Walmart has over 20,000 stores in 28 countries and is now in the process of building the world’s largest data cloud that would be able to cope with 2.5 petabytes of data per hour. Walmart has created its own Data Café, which is an analytical hub located within its Bentonville, Arkansas headquarters. Data Café allows to manipulate and visualize huge volumes of internal and external data. As the senior statistical analyst Naveen Peddamail noted, “If you can’t get insights until you’ve analyzed your sales for a week or a month, then you’ve lost sales within that time.”
Walmart has proven that having huge amounts of data creates not challenges but a bunch of advantages for business growth. Businesses need to learn to react to all that data quickly and make fast and reliable decisions. The data scraping technology can help your e-commerce always have data at your fingerprints to guide your decisions and win the competition. When creating your pricing strategy, price optimization must be an essential element. Price optimization is an ever-evolving solution and price scraping can help you stay updated on a regular basis and react to all the changes proactively.