How web data is transforming ecommerce

Online retail businesses are increasingly relying on insights drawn from web data to guide their pricing strategies as well as find the best time for product and service launches.  

A recent survey conducted by Bright Data and Vanson Bourne found some 87% of ecommerce businesses have increased web data collection and management budgets in the past 12 months – more than a third (38%) of them by over 10%, a significant increase of 25% from last year (2021). 

What can ecommerce businesses do with web data?

Broadly speaking, web data gives ecommerce businesses enhanced visibility over the competitive online market landscape. This set of information provides insight on anything from current sales offers to product pricing to positions to consumer reviews and more. While the applications for this vital resource are innumerable, online retailers typically collect public web data for the following core reasons:

Price comparison

Using web data, retailers can benchmark against their competition by comparing and monitoring the prices of identical products directly competing with their own site.

This helps answer questions such as: how much are their competitors charging? Do they have any sales or special offers coming up? What about the cost of shipping? Is there a pattern in how they raise and lower prices? 

Reliably knowing the answer to these questions is crucial for success in today’s fast-moving ecommerce landscape, which is why over a third (34%) of ecommerce businesses collect web data to compare competitors’ pricing against their own inventory. Some even automate this entire process to allow for the deployment of successful dynamic pricing models. 

Positioning and inventory 

In addition to revealing hidden insights into pricing, web data also provides information on how online retailers can best position their products to the public. 

Using this information, online retailers can work to identify specific keywords or messaging that could help move their products up higher in search — essentially helping them to make smarter and strategic marketing decisions by learning from the best.

Some ecommerce businesses even take this a step further by using web data to discover new merchandising and product opportunities by tracking competitors’ online stock.

This tactic is particularly useful for multinational businesses looking to launch in a new, unknown market, and can also help smaller retailers identify new products to sell that are currently trending on popular online marketplaces.

Search engine strategy

Many ecommerce businesses – around 58%, according to Bright Data’s research – continuously collect SERP (search engine results page) web data, which focuses on both the paid and organic search results of different keywords and queries typed into search engines. 

SERP web data is generally used by digital marketers to strategize for brand sentiment, online reputation management (ORM) and improving keyword rankings to modify their positioning as well as visibility in search engines. 

It also allows businesses to monitor their competition, uncover hidden trends, improve paid advertising, expose content gaps and, more importantly, understand how their content performs from region to region.

Overall, SERP web data enables businesses to outperform their competition on the search engine results page, as well as the ability to immediately take corrective steps in their strategies if further room for improvement is needed.

Social sentiment

Each day, millions of consumer interactions take place on marketplaces, social media, and different forums. Increasingly, ecommerce brands are looking to tap into this information, with Bright Data’s research revealing 66% of brands currently collect public web data from social media. 

This specific dataset helps social media teams spot shifts in consumer behavior, as well as anticipate the popularity of products and campaigns. It also provides an edge to be able to adjust strategies in real-time, helping companies to publish relevant social media content in the moment –  as what was relevant today may no longer be relevant tomorrow.

Overall, the benefits of understanding what consumers are saying online are many. It can be as simple as learning that you should change the wording on a product description to specify that batteries aren’t included. Or it could be as complex as uncovering an opportunity to create a brand-new product range. 

But when it comes to social-media-fueled trends, those ecommerce businesses that can react to the market in real-time gain a substantial advantage over those who don’t.

Web data collection strategies: in-house web data collection vs pre-made datasets

Online retailers are increasingly finding they often can’t manage the demands of data collection internally. Bright Data’s research found over half (55%) of respondents are looking to make acquisitions or find external partners to support their web data collection efforts – up 25% compared to just two years ago.

Broadly speaking, ecommerce businesses have two options at their disposal. The first is to collect data at scale themselves, and more than half (52%) of Bright Data’s survey respondents say this is their primary data collection tactic. Elsewhere, 88% report using web scraping applications or technologies to assist them, rather than relying on a manual approach. 

This kind of mass-scale web data collection necessitates an internal team to clean, structure, and analyze the data, which can be time-consuming and resource-intensive. However, this approach generates up-to-the-minute insights, which are crucial in helping ecommerce businesses make shrewd decisions in areas like pricing. 

The second option available to online retailers is using pre-made data sets – which are growing in popularity. Over a third (36%) of ecommerce businesses surveyed by Bright Data say these are their primary sources of web data. 

Datasets are essentially large sets of data or information that focus on a single subject, collected from either single or various sources. These sets are then structured into readable tables or formats from which valuable insights can be easily drawn.

Pre-made data sets can be purchased ‘off the shelf’ as a package – and often include enriched insights to aid strategic decision-making. This allows companies to still be able to use data without investing the time and resources it takes to collect it.

The disadvantage is that these are typically updated periodically, so they don’t offer the minute-by-minute accuracy of mass-scale web data collection. However, the price point can often be more attractive. 

Conclusion

Almost every industry now relies on insights from web data to support decision-making – and ecommerce is no different. It’s no surprise then, that 91% of ecommerce businesses surveyed by Bright Data rank web data collection as either ‘crucial’ or ‘very important’ to both day-to-day operations and strategic decision-making.  

The smartest players are automating this process as much as possible, but are also utilizing a tactical combination of mass-scale data collection and targeted pre-made data sets to give themselves the right breadth and depth of information for their needs.