As e-commerce and omnichannel share of retail sales continues to rise, knowing your market position and competitive landscape is increasingly more important to delivering your retail strategy. In the digital world, customers have more options than ever before and with a quick search on their smartphone can quickly compare prices for the products they want to buy.
Potential customers are already using a form of product matching for price comparisons. Shouldn’t you be one step ahead? Automating pricing decisions for margin and promotional strategies are already core to retail strategy, but the competitive landscape should also be accounted for or you will lose sales conversions once they do that quick search.
Product matching is one of the most important pieces of your price monitoring playbook, but what exactly is it and what makes it so important?
What is product matching?
Product matching is the secret sauce to a winning retail strategy. Product matching is finding the same or similar product to yours across the competitive landscape. It’s not always easy or straightforward. Some retailers can spend hours manually searching through competitors’ websites and still come up short to what the customer can see in their quick search across the web.
Fun fact OR Did you know? A person can match 80 images in an hour OR a person takes 16 hours to match 1000 products manually, something QL2 does in two minutes.
Why is product matching important for e-commerce?
- Understanding assortment overlap
- Ensure your catalog has the right amount of differentiation while still meeting parity with competitors
- Dynamic pricing
- Whether updating prices manually or through automated pricing optimization tools, keep your price position aligned with strategy and sales / margin targets
- Inventory / availability – stock status at competitors
- Make more informed decisions on price and promotions based on availability in the marketplace
- Create a unified source of product data
What challenges do companies face when making matches?
- Data is messy and non-uniform
- Non-normalized brand names
- Brand and manufacturer names on different sites
- Websites have gaps in important product information
- Upc and model number, easy to match on not readily available
- Manually matching products is time consuming
- Product attribute coverage varies by site
- Internal consensus on match definitions is tricky
- For Optichannel, understanding in store assortment and regional pricing trends doesn’t scale
- Oftentimes, people try to solve for product matching by sending people into stores to look at what products competitors are stocking on the shelves. This is difficult to scale and can limit your regional coverage. People also use expensive internal resources to manually search the web category by category, then manually matching products in spreadsheets. This can create inconsistent matching logic and takes up a lot of time that could be spent strategizing.
- Price changes are constant
- On average, Amazon products are changing prices every 10 minutes per day. Now most traditional retailers aren’t repricing that frequently, but if you are making decisions on stale data, you are already lagging the market.
- Matching shortcuts results in bad matches
- Model numbers are shared across products. Example:
Stay tuned to the next installment of our product matching blog series which will go into the “how”— how QL2 solves the product matching challenges that companies face when making matches.
For more information on the topics discussed in this blog series, check out our webinar, The Importance of Product Matching in E-Commerce.
Written by: Oliver Kuntz, VP of Product