Today, data has become an indispensable tool in a business’s profitable functioning. Companies resort to data insights to understand theirs and their competitor’s standing in the market. In an age where organizations strive to find the right product to sell in a hyper-competitive market, data not only becomes quintessential to monitor your growth but also needs to be used to understand how your competitor is attracting a loyal customer base and mounting sales.
Brands need to not only monitor their own data but also drive insights from competitor data to gain a comprehensive overview of their functioning and discover their winning points
“If you know the enemy and know yourself, you need not to fear the result of a hundred battles. If you know yourself but not the enemy, for every victory gained you will also suffer a defeat. If you know neither the enemy nor yourself, you will succumb in every battle.”
― Sun Tzu, The Art of War
How to assess your competition?
There are a few important metrics you need to track in order to know your competition. There is a remarkable marketing theory called concept 4 Ps. It means that if you can put the right product in the right place, at the right price, at the right time, you can win over your competition.
Pricing analysts and pricing heads are having a hard time finding the optimal price in a very dynamic market. In e-commerce websites including your competitor’s, the pricing data is publically available. All you need to do is extract this data into a spreadsheet or connect to a business intelligence tool to dig deeper into your competitor’s pricing strategy.
But this process comes with its own set of challenges.
The prices change very frequently on most e-commerce websites and the pricing analyst needs to be updated with the changes instantly. This calls for an automated way for pricing analysts to receive updated data as soon as it changes in real time on e-commerce sites. Datahut’s web scraping services help customers acquire the competitor’s pricing data in real time without any coding or software intervention.
Pricing your products competitively doesn’t always ensure huge sales. E-commerce companies leverage time to time promotions through multiple channels of marketing like e-mail, social media, targeted ads, content etc to gain larger customer engagement.
Datahut scrapes promotional data over a period of time to understand how companies leverage promotions.
Look at how Amazon promotes its products in periodic deals. Keep track of the same products for a week and you will see drastic changes in the promotions they do.
The above data extracted over a period of 30 days can help you draw insights on how the promotions offered by competitors are evolving over time and if similar strategies could work for you. You can even benchmark your promotional plans against the promotions of your competitors to make sure that your promotions stand out.
How do you decide on which partner channel ( Place ) you are going to run a campaign? How do you determine the timing to do something in online retail?
Here is an idea that you can use: you can track the stock availability of your competitor’s products using the Datahut platform. Five of your competitor products on a partner website like Amazon are running out of stock. What is the right action to take at that moment?
- Shoot up the price: You can raise the prices of comparable products on your site
- Targeted promotions: You can run a promotional campaign in that specific partner website for just those five products.
Datahut’s Web scraping platform helps to draw these insights by supplying real-time data from competitor sites.
If you have a product similar to existing ones in the market, how do you develop a unique selling proposition?
This becomes an important task as similar products face close competition while fighting for a customer’s attention. What makes you stand out over the others and dominate sales in your niche?
Scraping product data feeds of your competitors and identifying gaps in their product lines can be the key. When you compare the findings, you’ll notice similarities in strategy. Analysis of the extracted data will throw light on spot patterns across the product line of one particular retailer and use that knowledge against them. Make sure your own products are as price competitive as possible.
Turn Data into Profit!
While the 4 Ps demonstrate how data extraction and analysis can encompass the power to steer the direction of your sales success, data extraction from e-commerce companies can be further leveraged to
How often do you check the star rating/reviews of a product before buying online?
A research done by KPMG suggests that 72% of all buyers and over 90% of e-commerce buyers read online reviews prior to making a purchase decision. The average star rating of the product is one of the most intuitive indicators of the quality of the product and plays an important role in buying decisions.
What you see below is a review given to a reputed fitness product. A major mistake that brands make is not responding back to the negative reviews. A solid promise of giving a return or a remedial course of action would pacify the situation even though the review is negative.
For reputation managemet, you need to improve your product’s ratings, which in turn require a deep understanding of the customer pain points. Extracting review data over multiple channels provides insights into customer sentiment which can be used to iterate on the product and service. This enables companies to create products and services that customers love, resulting in better ratings and better sales.
How do you get review data? Datahut helps enterprises get reviews refreshed every day in a ready to use format.
How often do you see typos and errors on the product pages in e-commerce websites?
According to B2X 80% companies are not confident in their data. This is one of the main reasons for product returns, negative reviews and losing customer loyalty.
One of our customers who are in the business of selling auto parts online suffered a huge monetary loss on a single day. An employee from his content team added the wrong diameter to an auto part and the item delivered had a different dimension. By the time they identified the issue, there were over 4000 items shipped to the customers and they lost a lot of money because of that single error.
The best way to deal with this issue is to get product data from the partner websites and compare with your own internal data to identify discrepancies early on. Losing the confidence of an existing customer can hit you harder than you think.
A typical Product information management system (PIM) process may miss out on such discrepancies and this is where web data extraction steps in. Datahut extracts product data from multiple websites to compare the supplier files with the extracted data following which, we discovered the differences in both forms of data. With the discrepancies in hand, a retailer can rectify any data discrepancy.
Struggling to find the right data for more profitable functioning? Contact Datahut, your web data extraction experts.