In this blog, we will discuss how enterprise web scraping can help you automate your customer service, and your personalization when it comes to chatbots, and even help your artificial intelligence systems provide better recommendations.
As companies grow, they accumulate more customers which leads to an upsurge in customer service requests. Manually managing these inquiries can be tedious, and costly and may result in errors. Fortunately, enterprise web scraping technologies make it possible for businesses to automate their customer support operations while simultaneously providing exceptional customer experiences.
An example of this is web scraping Reddit data related to your industry and creating a chatbot that can answer questions without taking your customer service agent’s time. By scraping social media platforms, review sites, you can monitor customer sentiment and feedback. This data can identify pain points which help automate your customer service efforts.
Benefits of Customer Service Automation
Automating customer service is an increasingly popular way for businesses to enhance efficiency and cut operating costs. Utilizing automated chatbots and self-service customer service can simplify customer interactions, making customer support simpler and faster than ever. This type of customer service automation can vastly reduce the number of resources allocated to customer service departments, freeing up resources that can be redirected to other areas of the business. In addition, customers will appreciate the convenient access to customer service they are provided by automated customer support tools, which are available 24/7.
However, there is one issue, and that is the fact that some chatbots cannot solve specific problems, making them annoying to interact with. It’s important to build your automations with the right data and conditions, to display the perfect results. Finally, you should have the option to quickly switch to a live agent; as people may still prefer human interaction, even if it’s less efficient for them. With ethically sourced and scraped big data, your business can optimize its chatbots and AI systems to help its users.
Here are some ways web scraping and big data can help your customer service automation:
Personalization in Chatbots
With customer service automation on the rise, having large amounts of web-scraped data is essential for chatbots in order to offer personalization that customers appreciate. Some of the information gathered includes customer behaviours and sentiment, popular customer questions, competitor data, and key demographics. Combining your web-scraped data with your AI algorithms allows you to deliver a customer experience tailored to the individual customer rather than generic responses, taking your automated customer support to the next level. Finally, with purchase insights and data, your chatbots can make predictive product recommendations or blog topic suggestions, which we will discuss next.
Predictive Algorithms
Some companies utilize enterprise web scraping to improve their customer service automation and machine learning algorithms. Web scraped big data, combined with predictive algorithms, can help to reduce the user’s friction when adding necessary items, which results in a maximized cart size. This is why major companies like Amazon use big data and machine learning for real-time cart upsells and product pairings. Using web-scraped data and analyzing it will improve your customer experience, reduce friction and will increase your average order. Aside from products, your business can also automatically recommend articles that may assist your customer.
Price Monitoring
Web scraping is a useful tool for those monitoring competitor prices and offerings. It allows you to keep track of changes in cost, and make more accurate pricing decisions within your own business. Being able to have this kind of real-time info and analysis is essential; and is done automatically when using web scraping. This results in quick market adjustments which can lead to increased sales. Ultimately, by connecting competitor pricing data to your analytic algorithms or into a business automation tool, you can offer on-the-fly price adjustments or value-adds to win more customers, and make your business more profitable.
Managed Enterprise Web Scraping
Enterprise businesses can use web scraping for many reasons, from lead generation to SEO monitoring, or price monitoring as discussed. As AI and chatbots begin to take the main stage, your business should begin creating AI models to improve customer service efficiency, and other aspects of your business. Customer service and sales work in tandem, with good customer service, you will have better retention rates and more referrals, improving your sales.
Your business can create its own web scraping code, with Python for example, however, there are many obstacles in enterprise web scraping. ParseHub Plus makes gathering big data super easy, as our managed service includes sourcing, scraping and data validation testing. This ensures only the most accurate data is fed into your customer service algorithms.
Ready to improve your customer service automation with web-scraped data? Book a call with ParseHub Plus to get your free sample data export!
Happy Scraping!
