Companies are always working to find that pricing sweet spot – the one that attracts (or better yet, converts!) their target shopper yet remains competitive with their peers on the shelf. And don’t forget the added layers of difficulty in adjusting this balance from country to country and retailer to retailer. This requires pricing and revenue management teams to create guidelines dictating pricing policy across different online retailers and monitor competitor prices, to make sure they are always appropriately priced against competing brands.
As you can imagine (or painfully know from experience), keeping track of this information across all retailers and markets where your product is sold is often a time-consuming and manual process. In addition to tracking yours and competitors’ SKUs, you also need insight into the wider online marketplace and new or emerging digital brands, which is no easy task as they emerge online.
Using eCommerce Data for Pricing Corridors
Simply put, monitoring prices online and benchmarking SKU prices against competitors is the first step in optimising your pricing strategy to grow sales and improve profit margins.
Creating price corridors or funnels that plot your own SKUs and brand families against competitors by country, category or median price, helps answer key questions such as:
- How are my competitors pricing certain SKUs compared to my SKUs?
- Should I keep my prices 5% lower than competitors and how can I make sure I maintain that threshold?
- What are my different pricing thresholds in specific markets?
- Is my product priced appropriately for a mass or premium offering in a certain market?
- How should I vary a SKU’s price across markets?
By asking these questions and creating a standardised pricing guideline, you can ensure that your prices are competitive but profit margins don’t suffer as a result.
How Web Data Extraction Helps
To say that tracking this manually is a time-consuming process is putting it lightly. Trawling websites yourself and entering prices and brand names into a spreadsheet on an infrequent bases will never provide a consistent and complete picture of an online marketplace.
Leveraging automated web data extraction is a good way to create pricing strategies that are dynamic and not static, constantly monitoring prices for competitor products and online assortment as they fluctuate from day to day.
It’s not necessarily a difficult process to extract all this data, but the difference in having a mass of millions of data points vs an actionable roadmap that makes sense to your business, is in its organisation. Properly harnessing AI and machine learning allows companies to structure this data in a way that aligns to a standardised category hierarchy and ensures products are matched to that hierarchy accurately. This allows pricing managers to filter data by product category and analyse aggregated market prices for SKUs and brands easily and on a daily basis.
Via Does This For You
Our latest pricing intelligence tool, Via, helps analyse millions of products and prices available in a market. Identify where brands sit in terms of price distribution by category and country, track competitor brands and SKUs and analyse the pricing and assortment of across retailers.
Pricing and revenue managers can utilise this type of platform to optimise their pricing strategy and increase the chance that a consumer will purchase their brand or product over that of a competitor.
To learn more about how Via can help you optimise your pricing strategy, download our white paper ‘Using Ecommerce Data to Optimise Pricing Strategy’ or request a demonstration to learn more.