With the current COVID-19 crisis upon us, the world is changing rapidly. Many businesses are facing concerns of decreased sales and revenue due to lockdowns and a depleting customer base.
If you yourself are facing some downtime in your company, all is not lost. Instead of just focusing on the present, we should also be taking into account what happens after.
By taking the right steps and strategies now, your business will stay ahead of the recovery curve, post-virus.
One major way to do so is through using data scraping and analytics. By tapping into the almost endless pool of data available online and converting it into actionable information, you can gain insight into virtually any aspect of your business.
This means that you can take this downtime to work on bringing your company to the next level. By scraping data, you can spot inefficiencies in your operations, upgrade your products based on market demand, and even latch on to new opportunities before anyone else.
Data scraping and its benefits are already being recognised as an invaluable tool to various industries.
Studies have shown that companies driven by data are highly efficient, make better informed business decisions, and have improved levels of customer satisfaction. Research by McKinsey has also shown that data-driven organisations are 23x more likely to acquire customers, and almost 7x better at retaining those customers.
Many businesses are embracing data analytics to make informed decisions on inventory, pricing, risk management, hiring… the list is endless. By gathering data, companies would no longer have to take shots in the dark and go by their gut when making business decisions. The right data can help.
The first step in doing so is by digitizing company processes. Capturing customer interactions, operational data, and employee performance provides heaps of insights. You can then feed the insights into product development, business strategies, or marketing efforts.
This is our specialty at ThunderMetrics. We’ve worked with major clients to conduct market research, scrape for leads, and monitor company data.
As a result, customers can be pinpointed and targeted based on preferences or background. Marketing copy can be personalised to each customer segment. Resources can be allocated to maximise efficiency. Manufacturing can be planned to run parallel with demand.
Let’s focus on your customers. By understanding your customers thoroughly through market segmentation, analysing their data can show helpful insights into their preferences, buying habits, and motivations.
For example, a utility company can pull data on the amount of water and electricity used by each resident in a certain neighbourhood. By analysing this data, they can then pinpoint potential solutions to common issues, or even indicate an individual user’s wastefulness.
Similarly, major retailers are also taking advantage of customer data to improve operations. Walmart, for example, uses historical customer data to forecast when there would be longer lines at checkout. They then solve this issue by bringing in more staff during those peak hours.
On the other hand, Macy’s mines their own customer data to learn about their preferences, buying habits, motivations, etc. They then send out hyper-targeted marketing messages based on that data for maximum impact and reach.
They also use this data to create comprehensive personas of their online customers, which will lead to increased conversion and retention rates, and an overall improved online shopping experience.
Boost internal performance
With all that being said, what can data do for your company internally? Scraping your own data can lead to huge leaps in productivity, efficiency, and performance.
Using history as a resource to perform data analysis will give key insights into inventory numbers, price segmentation, or measuring key performance metrics. It can also be used to power machine learning programs, which can then illustrate trends throughout an industry’s history.
Let’s go back to Walmart. One of the major ways they are using data is to speed up operations and improve labor allocations. For example, by analysing the number of pharmacy prescriptions filled out in a day along with data of their peak hours/days, they are able to predict when demand will shoot up. This allows them to schedule their staff smartly, as well as reducing the time to fill up each prescription.
Comparably, Macy’s uses predictions from scraping to estimate the amount of inventory needed for each item, based on forecasted demand. This reduces wastage in unsold stock, and boosts revenue by pushing items that are guaranteed to sell well.
Scraping data can even be useful to improve your company’s supply chain. With analytics, you will be able to isolate hidden inefficiencies within the supply chain. This in turn will produce cost savings and generate room for improvement in managing channels, vendors, and logistics.
In the wake of the COVID-19 crisis, recovering two steps ahead of your competitors can make or break your business. ThunderMetrics offers custom data scraping services for any project, big or small.
Drive your business forward and never be left behind again! Get started here.
This article is part two of our blog series: ‘Keeping Business Continuity in the Wake of COVID-19’. Click on the links below to read parts 1 and 3.