Data, data, and more data! Sales data, customer data, and product data are what online retailers rely on to be price competitive, reach the right customers, and maintain a healthy margin. The good news is, data is everywhere, but how it is acquired and applied is what makes all the difference. Retail companies utilize a process known as website data extraction to obtain data from a multitude of data sources for processing, migration, and analysis.
Once data is acquired by a website data extractor, usually from websites, emails, documents, forms, PDF’s, scanned text, databases, etc., it is imported into an extracting system before being processed and exported to the next step in the warehouse data workflow, or transformed, where it can be merged with relevant metadata. After this transformation bit, the data is then used for generating marketing and sales leads.
Pricing products for an optimal price margin means steadily having to adjust and reconsider one’s pricing method according to trends in the marketplace, customer activity, stockroom levels, etc. While some of the grounds on which prices are structured is based on internal factors, the figures charged by competitors for comparable products strike a massive impact on the sales quantity and profit margin to be realized by the retailer, and are commonly acquired by a data extraction and monitoring method called price scraping. Price extraction processes allow retailers to compile, extract, analyze, and apply this information in useful ways which permit a more efficient analysis of market conditions, like product abundance, customer demands, and competition. This allows the merchant to determine where to apply the most advantageous price point almost or actually on a consistent, real time basis.
One of the biggest factors in determining which products to devote time and investment to is the prospective demand for it, or how popular it is amongst your customer base. This sort of information is most beneficial, once again, by combining current sales and demand figures with those of consumers at large. Some of the usual suspects for this sort of demand analysis include online classifieds like Amazon, Craigslist, and others, where consumer activities are easily monitored en masse, and can be analyzed by product categories and regions.
Although useful on some of the highest levels, the price scraping method isn’t entirely foolproof, and can be subject to certain challenges. Some of the obstacles that can be experienced by some online retailers in data scraping include the fact that product names, model numbers, and descriptions can vary from one retailer to the next. Some retailers actively attempt to thwart potential competitors by hiding data from scraping services. Sometimes the data is itself inefficiently presented, many retailers seek to attach tailor made model numbers for the product in question in order to discourage comparing it against local merchants in an effort to drive a sense of uniqueness in their product selection.
Understanding consumer habits
Consumer data histories allow merchants to better understand their customers by maintaining data relative to the products viewed and purchase histories, which include the amounts the customer usually spends, when they spend it, where they spend, and on what they spend it, so as to better predict purchasing habits and interests in order to tailor their experience and promote product types and levels that the customer is likely to buy. In addition to helping retailers more efficiently promote their products, data systems help consumers save valuable time in searching for the right product at the right price to meet their need or interest both in being met with product promotions relative to their interests, and in meeting with products featuring competitive price points, relieving the consumer’s colorable need to consult multiple retailers for the bargains on the products they’re shopping for.
Data can be controversial
But big data isn’t always rainbows and butterflies when the data that is collected by retailers is retained, it brings with it certain liabilities. Controversy can sometimes ensue surrounding privacy and security concerns. Shoppers aren’t always thrilled about merchants collecting and keeping their personal information. The possibility of that data being leaked or hacked is an issue of the financial and personal information on patrons being acquired by unauthorized parties. The motivations for acquiring that data and potential uses for it can likely be less than above board and can even involve theft by compromising the financial accounts that customers used to authorize payment for purchases accomplished with online merchants, and where purchase histories can include sensitive information about end user’s habits
Governments all around the world have composed and passed legislation and continue to develop case law surrounding how long merchants are allowed and in some cases even required to maintain consumer data. Also included regulated by this legislation is the security practices and precautions they must follow in order to limit the potential liability of data breaches, and what types of data they must retain in the event of certain types of audits or investigations that may require access to these types of data. Both anticipating and responding to this issue, many software developers whose systems are utilized by both merchants and end users have begun to develop encryption and security methods and sequences in their systems in order to better protect their users against the potential risk of unauthorized access, making the online retail business more stable and secure by it.
To sign off
A couple of things to keep in mind when initiating a data scraping project include, following the rules and practicing a reasonable scraping frequency that respects server limitations. Most websites include guidelines on how bots are to interact with their site. Some sites block web crawlers outright, and some sites allow bots but restrict the pages that are allowed, and how often. The frequency of scrapes conducted on a given site should be maintained at a reasonable rate so as not to overburden site’s servers, causing its end users much ado by being slow to load or even causing the site to be down.
In addition, targeting quality, reliable sources can save much time and effort, since sites with lesser traffic levels can be prone to hosting outdated material. Of key importance, of course, is compliance in observing the copyright and intellectual data laws in use by the website being scraped and ensuring that reserved rights on a website’s material aren’t in any way infringed.
With data scraping services, you can generate leads for your business in a less time consuming, cost-efficient and effective way. So, get to it.