Product Intelligence

Four Challenges of Gaining Accurate Competitor Price Intelligence Data and Running Dynamic Pricing in eCommerce

You need a powerful price monitoring tool to monitor your key competitors and implement dynamic repricing for consistent eCommerce growth. Based on our years of experience serving hundreds of online retailers, we are sharing 4 challenges that we have heard many retailers face when doing repricing due to challenges with their pricing software. As you evaluate and select your competitor price monitoring vendor, you must remain vigilant on these points to ensure you select the right pricing intelligence software for your eCommerce business.

Your Price Monitoring Solution Must Meet These Four Needs:

1. Provide Accurate Competitive Price Data with Competitors SKUs Matched at Product Variant Level

Variant-level (or child-level) product matching is the #1 challenge for competitor price intelligence in retail.

That means, if you are selling a pair of Red Nike Air Jordan Size 9 Shoes, you want to compare the price of your SKU with the competing price set by other retailers offering the same SKU. You don’t want the price of Red Nike Air Jordan Size 10 Shoes or that of a different color. Many solutions struggle to offer this precision and don’t give this apples-to-apples comparison as they can’t achieve this SKU level matching.

2. Can Collect Competitive Price Data Globally from Different Digital Platforms

e-Commerce Price competition is at a global level these days, and global price monitoring is necessary to develop powerful price intelligence. Retailers targeting customers around the world must monitor their competitors’ prices in multiple countries across digital channels. To track such competitor data globally, a powerful price monitoring technology and rigorous data quality control processes are crucial. Retailers may want to collect competitive data from US, Canada, UK, Far East, Mexico, South America, and other markets daily in English and non English languages. And, you want this data 7 days a week 365 days a year to power your repricing algorithms. The ability to get this data reliably is key. You must then import these raw competitive pricing data feeds into your data warehouse to run your advanced dynamic pricing AI models.

3. Built on Robust Technology that can do Large-Scale Competitor Price Data Monitoring and Ongoing Collection

Any price intelligence tools must have the ability to monitor large product catalogs with many SKUs from many competitors on a daily basis from marketplaces like Amazon, Walmart, Target, Best Buy & others, ad channels like Google and Bing, and their eCommerce stores. When monitoring prices, the solution must collect multi-dimensional datasets like inventory, shipping, online product reviews and rankings, which is crucial for your unique dynamic pricing strategies.

All this collected data online from digital channels form the basis of any advanced competitive pricing intelligence tool and pricing models. Thus it is crucial that the solution’s technology, people, and processes can handle the volume of terabytes of data and ensure quality at scale. You need the scale to trust the solution and rely on it to devise your day-to-day and long-term repricing strategies.

4. Enable Automated Repricing and Dynamic Pricing

The automated repricing capabilities include an advanced pricing rule engine and powerful price export capabilities that support multiple platforms like Amazon, Walmart, and Google Shopping and web stores like Shopify, Magento, BigCommerce, Yahoo, Volusion, WooCommerce, 3DCart, and others. The ability to interface with major retail digital platforms empowers you to efficiently offer right prices to your customers and win the sale at the best profit margin. The best solution should be powerful enough to implement multiple pricing models from various data points to develop advanced dynamic pricing strategies.

If you are searching for a powerful price intelligence solution to implement your Dynamic Pricing for Retail, talk to our experts.

Prasanna Dhungel

Prasanna Dhungel is Co-Founder and Managing Partner of GrowByData and drives the firm’s content marketing initiatives. Dhungel has 20-plus years’ experience in big data. Previously, he was Vice President at Valence Health (now Evolent Health) and at D2Hawkeye (now Cotiviti Health). He has an MBA from Kellogg School of Management, MEng from Princeton University and BS with Honors from Cornell University.