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Web Scraping
Arpan Jha

You have just had a review meeting with the top management, and launching new products in the market seems to be the next goal. As a strategy champion for multiple business units in a consumer business, you have brainstormed and dissected the strategy with the BU owners, and have narrowed down what options make the most sense at this point. You begin to ponder about the best possible manner in which you could deliver on these key strategic initiatives. There’s a data theme coming out of all of these inputs you have on the table, and given the multiple options available in the market, you want to be absolutely sure about the industry’s best practices.

Why Data Scraping

In today’s ever-expanding web world, data is the new oil. And no strategy engine functions without this oil. This report on alternate data indicates huge potential in web data, with the market growing at 40% CAGR. It’s quite clear hence where the market is moving, and what businesses need to do. We need internal sales data to evaluate past performance. And then we need external market data or what we call today alternate data, to benchmark our performance.

The latter is an understatement of needs — what data to collect from the humongous web, how to dissect it, how to integrate it with operations, and finally to be sure about the insights derived, is a critical task for any strategist. Thank God for technology and its evolution, we could automate most of these steps to reduce the time from data to insights, and witness outcomes of these initiatives in the same breath.

One of the solutions that automate the data collection part is called web scraping or web crawling. These web scrapers replace the manual effort of fetching the right links, copy-pasting the data, cleansing, and formatting in a way that it can easily scale up to doing this for millions of web pages at the same time. So clearly there are savings on time, resource investments, and opportunity costs. The key here though is to find a reliable partner that you could rest the complexities of web scraping with, and continue to focus on deriving valuable insights from the data you’re ingesting into your systems.

Delving Deeper into the Data Collection Process

One of the most impactful steps in organizing the web scraper flow is identifying what data sources to crawl, what data points to collect, and how often to get this data. Enterprise-grade web scraping services like PromptCloud work closely with the strategists to identify the right sources. While taking into account the amount of data that needs to be collected to draw reasonable insights, as well as the variety. Thus ensuring that the data comes from multiple places, so as to maintain the sanctity of the information.

Owing to their experience with this space and with most of the relevant sources (think Amazon, Walmart, BestBuy, Target), the web scraping providers also know the bottlenecks that could come on the way to reaching the defined scale. Most of such solutions work through the operationalizing phase, wherein all of this cleansed and formatted data feeds into the analytics engine in-house, in an autopilot mode at set frequencies.

In certain cases, you’d want reviews to be fed in near real-time as and when the product gets reviewed to take the necessary steps. While you might want to monitor price points on the products being sold across these marketplaces daily, so you could tweak your product prices for increased revenues. It takes rigorous scraping efforts to get this flow right and it might take a few iterations to get to that penultimate point where this data drives your decisions.

How does Web Scraping Data Fit into the Overall Strategy

Web Scraping

Let’s say you have selected a data partner and have managed to get the data engine rolling. But the fundamental question remains — how do you even know that just automating the data collection process is going to ensure project success. There are multiple aspects that you’d need to consider as a strategy champion.

a). Ensure a reliable data partner for data quality, coverage, and consistency

b). Evaluate the insights the data is providing

c). Tweak the sources and data you’re collecting, or even how often you’re collecting the data, to better these insights

d). Add more sources as you see the data delivering returns

e). Fine-tune your analytics engine to ensure the most important insights come first

We are data partners to some of the biggest brands in the FMCG space and are always amazed by their vision. We have had the opportunity to work with some of the most interesting use cases through them — be it marrying the demand and supply data to have more control over the equation, or to be proactive towards sentiments in the market for their products and brands, or even going the extra mile to do a comprehensive market study to see what new products to launch and what might be the customer’s willingness to pay for the same.

Getting access to relevant and quality data remains prime to driving business success on any of the strategic initiatives you take upon. With the plethora of DIY scraping tools available today, it’s even more important to properly assess alignment between internal capabilities, and what these data scraping solutions have to offer. Data is more democratic today than ever, and we don’t see why any business should not make good use of it.

Conclusion

At PromptCloud, we also go one step further in delivering insights based on the data we collect on your behalf. The data is further enriched and dashboards are customized for each project in a way that they shout out the action items for you. It wouldn’t be wrong to say that to create an impact and be successful in today’s world, you need to supplement your hard work with data.

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