ShopGrok is an Australian startup and provider of consumer insights and data analytics services to the retail and consumer goods market sector.
ShopGrok’s customers use our products for market insights, to help them optimize their pricing and their product range, and to make effective decisions regarding promotional activity, pricing as well as product offerings based on that information.
Most of our customers are currently based in Australia and New Zealand. In Australia, we serve at least a quarter of the top 20 retailers. We also serve some large global marketplaces to help them optimize their inventories and their pricing. And we’re growing fairly rapidly, so we’re looking to start entering other markets over the next couple of years and to improve the scalability of our products. This way, we can serve more customers in an efficient way.
The core users of our product are typically what you would call category managers within a retailer. These are people who are responsible for selecting the products that go on the shelf or in the ecommerce store and also setting the price of those products. Typically, these people know their market and customers very well. However, they need help with data. To address that, we’ve built a practitioner’s tool that helps our customers get insights really quickly without having to be a real technology or data expert.
A typical retailer might have 20,000 to 100,000 products in their product range. But there are probably only 100 or 200 products in that range that really matter to the customer price perception. What we’re trying to help our customers achieve is competitive pricing so that they increase both their sales and their own consumers’ loyalty. The trick is to be competitive on price but also maintain a healthy product margin or sales margin. So, it’s a very fine balance, and we help them to optimize that by giving them real-time insights about what’s happening in their market, which helps them make better, more data-driven decisions.
We’ve been in business for almost four years now. My personal background is in retail. I spent three years as the head of price strategy and price analytics at Australia’s biggest supermarket, Woolworths. Before that, I was working for McKinsey as a management consultant. This is why our core competency is in price strategy, price analytics, and also data engineering.
We started out just me building web data collection platforms of retail ecommerce websites. At that time, it was much easier to gain access to public websites. However, over the last four years, we’ve noticed that it’s becoming harder and harder to get public web data. So, we need to look for partners that can help us do that in an efficient way – to make sure we can focus on our core competency, which is really not the web data gathering as such, but, rather, what has been done hence, which is matching the data, building models, building insights and building analysis. This is what our customers expect us to do.
We started using Bright Data about a year and a half ago just to get access to the network, and we’ve slowly added additional products. We have a large data center, many Data Center zones, Residential zones, and then we’re also using the Web Unlocker.
We found that because Bright Data has these different tiers of products, it’s cost-effective for us. We can simply scale up or down depending on the website. Some websites require us to use more complex tools, like the Web Unlocker, and in others, we might just need to use Data Center IPs. So, we have options at each level of complexity, and it’s quite easy for us to configure those, monitor them, and track costs. Bright Data has saved a lot of time, effort, and manpower building our web data collection set-up and monitoring systems- we can rely on Bright Data to do most of that for us.
There’s a lot more to collecting product and price data than you might realize from the outside. In many websites, today pricing is very location-based and really dependent on the postcode. We use the Bright Data network, which has a sort of microgeographic focus on different regions to get geo-located prices in different areas. A definite use case where Bright Data comes in handy is that we can actually target specific regions, either state within Australia or other countries.
From the data point of view, we try to capture data from the source. Whether it’s an API on the website, we try to capture as much of the data as we can. In the past, we might have just tried to get summary data because the process was slower, but now that we’re able to access most of the public data on most public websites in a more efficient way, we can capture more data, and we can use that to generate more insights. So, for example, instead of just capturing the product name and the price, we’re also capturing ingredients and product specifications, country of origin, and nutritional information about different products. And then in terms of pricing, we’re capturing not only the current price but also the ‘was price’ and the ‘now price’ and any promotional pricing that’s going on. Therefore, we can access a lot more information than we may have been able to in the past. Doing so allows us to provide much better insights to our customers.
Our experience with Bright Data has been wonderful. Customer service has been great, very responsive, and always willing to respond to our queries.
Looking ahead, we are exploring the Proxy Manager solution that gives even more control to us for managing very precise information about different networks that are being used. We intend to install that at some point in the near future to give us even more control. Also, Bright Data has various other products which we haven’t yet tried, and we intend to try them at some point, for example, the Web Scraper IDE.
Web Data is critical to success in almost any industry, but for me, coming from retail, it’s absolutely essential. We know that in retail today pricing is so transparent and consumers can easily find the price of the product across any retailer that sells it. So, unless you’re in the consideration set for a particular product that you’re selling for your customers, if your prices are not within a certain tolerated range, the customers simply won’t buy from you.
Loyalty is at an all-time low in terms of retail sales, and pricing is currently the foundational aspect of retail. So, you need to get your pricing right before any other aspect of your offer is going to work.
In terms of volume of data, more is always better. Pricing is so dynamic now that a lot of our customers are exposed, for example, to Amazon, and we know that Amazon is changing prices up to 10 to 20 times a day on certain products. Therefore, unless you can keep up with the likes of Amazon, then you’re going to get left behind.
