CommerceIQ is a fast-growing startup and in March 2022 it raised $115M in Series D funding led by SoftBank Vision Fund 2.
We pioneer in helping brands win through retail ecommerce channels such as Amazon, Walmart, and Instacart. Our unified platform applies machine learning and automation across marketing, supply chain and sales operations to help brands unlock the secret to gaining market profitability.
Brands require data. Therefore, they register with us, share the products they are interested in, and we collect public web data on omni channels such as Amazon, Walmart and others, to help them with website testing, brand protection and gathering relevant data surrounding products of interest.
Our customers include many brands, household names as well, and we are helping them improve their sales.
Let’s say you are searching for a toothbrush, you are bound to get a premium category brand in top result right? But for different reasons their ranking is going down.
Using public web data, we help analyze where our customers are losing out. What are the main drivers of their products? What are the top products? How can we optimize ad spending? How can we improve our outward facing marketing to climb up the search rankings? How can we further protect the brand?
Focusing on the latter, if our customers’ websites are experiencing issues or a third-party seller sells their brand with a different variation, eventually it ends up being a loss for our customers — considering their value is going down.
Prices might decrease due to the third-party markdowns because many retailers, for example, will surface the lower price. Items may appear out of stock mistakenly due to website complications or products may be sold to consumers that don’t achieve brand standards.
Overall, within these scenarios the brand loses, and it’s not just about losing the money, it might diminish the brand image as well.
Furthermore, the buying tendency online is continuously growing, which increases the problem multi-fold. All these increasingly growing issues are difficult to follow manually and at a large scale and that’s where we come in to help them get these things automated using data.
Right now, our team is gathering millions of public web data points to streamline these processes. Let’s say we are on a retailer page that a brand has given us – these are our most priority items. We ask Bright Data to give us the publicly available web data from the different e-commerce sites for this product — the product page, a search page for this product, all the attributes of this product, etc., in an HTML format.
We then read that web data and parse that data up. What is the title? What is the price? Who is the seller? What are the variants of that data? Is this variant complying to what the brand has asked for? Is there some rogue variant here? Is there some rogue seller here? Is this price not what the brand is expecting? So, these are the basic checks.
We then file issues automatically to the respective retailer. So, if there is something wrong, we ask them to check. For example: If we know an item is showing out of stock here but the brand is saying that it is available, we can identify a mismatch.
Considering the size of our operations, we chose Bright Data because we wanted a reliable, consistent solution working at scale. We didn’t want to end up in a situation where we have to play with fire all the time.
There are so many things that have to be done in order to deliver this data, and our insights, to our customers. So, we can not afford any mishaps — we need the web data to be accurate, we need a timely response, and we can’t afford poor success rates.
Our team hasn’t developed an in-house data collection solution and we are not interested in working in that domain at all, so we chose to use a third-party provider like Bright Data.
It has the best solutions at the scale that we want. Furthermore, Bright Data has shown prior success as a reputable web data provider, they have dealt with large scale projects before and the international reach of its network at a city level is bar none.
At the moment, we are working with the Web Unlocker and we are pleased with it. We are also looking forward to expanding our use of the Data Collector once this product gets mature.
Bright Data ticked all my check marks – it works well at scale and allows diverse geographical coverage. More so, we feel heard, and we do feel that the actions are taken to get things resolved when needed.
We rely on Bright Data for the data.
