How companies in the eCommerce space are using web data to get ahead of the pack
In this article we will cover:
- These are the challenges that eCommerce businesses are grappling with
- Here is how companies in digital retail are using web data to overcome issues and scale operations in the process
These are the challenges that eCommerce businesses are grappling with
- Getting access to real-time consumer trends, and competitor activity so that they can more effectively compete and grab increased market share.
- Creating a tailored strategy to help expand businesses into new markets and appeal to a localized target audience.
- Dealing with target site blocks or data cloaking which either means that companies cannot access crucial information such as competitive pricing or are served the wrong information causing them to make fatal marketing decisions and bundle offers that push potential customers away.
- Gaining access to accurate GEO-specific data such as customer search trends, top-selling items in a region as well as social sentiment, and user engagement data.
Curious to experience what it feels like to run an eCommerce business without needing to deal with all of these issues?
Here is how companies in digital retail are using web data to overcome issues and scale operations in the process
Company #1: A men’s fashion brand looking to get in touch with consumer sentiment
The company: This is a household name brand that has been operating in the United States since the 1970s. They are used to doing business the ‘old-fashioned way’ but realize that they are missing a huge consumer segment by not consulting social media.
The challenge: Sourcing user-generated social media content in order to analyze trends, make better merchandising decisions, and appeal to new audiences by understanding their challenges and buying journeys.
The solution: Using Data Collector, an automated data collection tool in order to get a real-time feed of what fashions are trending on Instagram, viewing which items have the highest Sell-Through Rates (STRs) on a per region basis. As well as gaining access to and analyzing competitor customer reviews in order to learn consumer likes/dislikes enabling them to improve on these points early on in the production, marketing, and distribution cycles.
The outcome: The company’s designers, merchandisers, and marketing departments are all making operational decisions based on the web data that they are collecting. This has enabled them to discontinue 10% of their merchandise with low margins and interest. And instead, introduce new product lines based on consumer demand and competitor offerings. Sales among millennials and Gen Xers are currently up by ~50%.
Company #2: A vendor analytics tool seeking to provide better real-time insights to customers
The company: This is a tool that Small and Medium-sized businesses (SMBs) in the digital retail space use in order to better operate in their respective product categories. The platform assists with new/trending product discovery, competitor catalog scanning, as well as identifying real-time inventory gaps that can be leveraged.
The challenge: They often face blocks from target sites such as rate limitations as well as data cloaking, meaning they are served inaccurate product information. Sites do this in order to make it more difficult to compete with them. This is a major problem for the company as this is one of the major factors behind their above-average churn rate of 14% (similar b2b tools often have an average churn rate of 6%-8%).
The solution: This company has opted to use Web Unlcoker which is a tool that automates CAPTCHA-solving while customizing target site fingerprinting, as well as browser User Agents (UA) and cookies. It also helps manage the rotation of IP addresses and uses Machine Learning (ML) logic in order to circumvent ever-changing target site architectures and blocking mechanisms.
The outcome: The company is now able to collect much more accurate information that they then display to customers. Their customers are noticing that the tool is providing more accurate data and analytics, and churn rates are down to 9% nearly 8 months after implementing data unlocking technology.
Company #3: A small marketplace vendor wanting to up their competitive game
The company: This is a 10-person company selling cosmetics products on various online marketplaces, specifically in Southeast Asia.
The challenge: The company would like to better compete. The markets they operate in, especially India, contain consumers that are highly sensitive to price. In order to maintain current sales levels and grow, the company needs to be able to implement a real-time dynamic pricing strategy, taking into account competitors’ special offers and promotions. Before finding a solution, they were losing 1 in 5 customers to competitors with similar products, most likely due to a real-time price undercut.
The solution: The company has decided to buy Datasets, a cost-effective pre-collected file that maps out all of the cosmetics vendors on the marketplaces they operate in as well as the current pricing of each and every item. Their product team has opted for hourly ‘refreshes’ of the Dataset so that they can identify any competitor price drops/changes/special promotions and pivot where they deem profitable and necessary.
The outcome: The company has been able to significantly increase its market share and decrease the number of customers they lose to competitors. They now only lose 1 in 8 customers to competing vendors, i.e., they have decreased cart abandonment by 3 out of 5 or 60% of pre-Dataset levels.
The bottom line
Web data is becoming a necessary tool for companies that wish to set themselves apart from the competition and take their business to the next level. From consumer sentiment and product discovery to dynamic pricing and serving b2b users with more accurate vendor analytics – real-time data collection tools can offer an easy, affordable, and viable solution.