6 data points successful eCommerce businesses collect about their competitors

Discover how analyzing large quantities of eCommerce web data on specific products, niches, as well as stock volume can reveal winning sales patterns that are then implemented by your company and/or clients. Identifying which products are top-selling in real-time is a by-product of this type of workflow
6 data points successful eCommerce businesses collect about their competitors
Amitai Richman | Product Marketing Manager

In this article we will discuss:

#1: Choosing the right amount of ‘item specifics’ fields

Based on an analysis of thousands of eBay listings, data reveals that items in the ‘fashion’ category with the highest Sell-Through Rates (STRs) contained 8 ‘item specifics’ fields filled out on average. While for ‘Home & Garden’ this number was 10 (25% higher). 

The takeaway from this data point for an eCom-focused business would be choosing the exact number of item specifics for each category they are selling in. Additionally, they could add another layer by collecting the same ‘item fields’ high-converting competing products are using and then implement that on their listings (e.g. model, make, color etc).

#2: Winning item description word count 

Listings with item descriptions with an average word count of 304 words correlated with the highest STRs in fashion-related eCom marketplace categories. For Home & Garden high STRs correlated with an average word count of ~397 per listing. 

The takeaway from this data point for an eCom business would be collecting data on top-performing listings in your niche and then tailoring your description length to that of the top-performing competitors. A step further would entail a Natural Language Processing (NLP) analysis of the substance of these listings, and then working to replicate the value provided shoppers in your own listings. 

#3:  Listing ‘text to visual’ ratio that resonates

Layout-wise, listings for ‘fashion’ categories that had the highest STRs showed 67% of listings had both text and visuals, while 33% were ‘text only’. For ‘Home & Garden’ category listings, 20% of listings/vendors with high sales volume were ‘text only’, while 80% had both text and visuals.

Based on this data point an eCom-focused business would conclude that Home & Garden shoppers are clearly more visual shoppers. They want more detailed descriptions as well as item specifics. Fashion shoppers seem to enjoy having enough information, and visuals but don’t like being inundated with item specifics, and descriptions. Identifying what visual to text ratio works best in your industry as well as the types of visuals/copy that work best can help companies drive conversion rates. 

#4: Analyzing marketplace entry thresholds based on geography 

Research of 232 million eBay listings by Title Builder provided actionable insights.

The first point is that eBay Germany has the highest Sell-Through Rates (STRs) of 38.3% (i.e. an item listing that generated at least one sale) while eBay Australia had the lowest STR (27.8%). 

The takeaway from this data point for an eCom-focused business would be that the entry bar for new sellers is higher/easier on the German version of the site meaning it may be an ideal market to roll out new items or for new sellers, to begin with. The Australian market is very overcrowded and might be best avoided. This information is, and of itself can help companies avoid challenging markets while capitalizing on ones with better opportunities.

#5: Discovering which product categories have the highest Sell-Through Rates

The second point worth looking at from the above-mentioned analysis is that the categories with the highest Sell-Through Rates include health-related items (87.66%) as well as fitness (82.13%). The categories with the lowest STRs include diamond engagement rings (3.41%), as well as adult t-shirts (3.43%).

The takeaway from this data point for an eCom-focused business would be that items related to health and fitness sell easily as they are in high demand, and there is a high level of trust when purchasing from afar. Diamonds/jewelry as well as certain clothing items require more in-person inspection, and/or ‘an element of humanity’. These types of insights can help a company decide if it is worth their while to roll out a new product line on their digital channels, for example. Saving both time, and money on a Proof of Concept (POC), while helping companies steer clear of ‘sinkholes’.

#6: Learning what ‘item condition’ shoppers are looking for

The third point worthy of turning your attention to is that roughly two-thirds of items sold on eBay are ‘used’ while only one-third are categorized as ‘new’. 

The takeaway from this data point for an eCom-focused business would be that when considering which channels to sell items on as well as what target audiences are looking for, understanding current market demand for ‘item condition’, is very important. Data from the web can help you map supply and demand, allowing you to come up with a product line and marketing strategy that appeals to a particular market.

The bottom line 

Oftentimes vendors want an absolute answer. Item ‘X’ is the top-selling product you should be focusing your sales efforts on. The reality is much more complex, which is where web data can step in, and help you take inventory of your market, niche, and competitive landscape.

Web data can help you:

  • Craft the ‘perfect’ item listing with the correct number of ‘item specifics fields’, an appropriate description word count, as well as a ‘text to visual ratio’ that actually resonates with target audiences. 
  • More accurately choose an online marketplace with an appropriate entry threshold.
  • Identify the item categories where your Sell-Through Rates meet business model expectations.
  • Stock items that are ‘in a condition’ that suits consumer expectations.

There is no ambiguity in these issues, they are easily quantified, and answered by utilizing a web data collection tool that scans the internet in real-time for this information. Web Scraper IDE is our solution that delivers the above data in an automated stream of data from both the front-end and back-end of digital commerce websites. 

Amitai Richman | Product Marketing Manager

Amitai is a Product Marketing Manager at Bright Data, responsible for the Web Scraper IDE product. He is committed to making public web data easily accessible to all, thereby keeping markets openly competitive, benefiting everyone.

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