1 minute read
The Use Of Dynamic Pricing And Price Intelligence Challenges.
In Ecommerce: A Few
When businesses have powerful tools for keeping an eye on prices, they can set prices that are both competitive and based on what customers do. They are necessary to keep an eye on the most important competitors and use dynamic repricing to keep eCommerce growing. When retailers change prices, they often have to deal with these four problems:
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1. Accurate Competitive Data: Competitors Matched to Product Variant Level
The first problem with competitive price intelligence is matching products at the variant level. For example, if you are selling a pair of Adidas Size 9 shoes, you want to compare the price of your SKY to the prices set by other retailers who sell the same SKU. You don’t want to know how much Adidas or other brands of shoes in size ten cost. Many pricing solutions need help being precise and can’t compare apples to apples because they need to match at the SKU level.
2. Collect Competitive Data Globally from Different Platforms
Price competition in eCommerce is now a global thing. So, it is essential to look into prices around the world. Retailers with customers all over the globe must check the prices of their competitors in more than one country. In this situation, it’s essential to have a vital tool for monitoring costs and a strict way to check the data quality. Retailers, for example, want to get information from markets in the UK, USA, India, Mexico, the Far East, and other places around the clock and all year.
3. Robust Technology for Large-scale Data Collection and Invigilation
The best competitive price intelligence tools can keep an eye on substantial product catalogs with many SKUs from competitors daily on different marketplaces like Amazon, eBay, Walmart, and more. So, the pricing monitoring solution must handle vast amounts of data while keeping quality and scalability.
4. Product Automated Repricing for Stellar Dynamic Pricing
Lastly, competitive price analysis tools must have a robust price export engine and an advanced pricing rule engine. The best solution is strong enough. This will help to implement multiple price models. It can use different data points to develop advanced dynamic pricing strategies.
