How many times you were browsing when you find the same product as yours in much lower price and you instantly understand where your sales are going. From the time customers started preferring online shopping than traditional shopping, they can have same product in multiple prices, some can be cheaper than other. This facility of comparison made customers more demanding and price conscious.
Hence, businesses have to be up-to-date about how many other companies are selling the same product and at what cost, so they don’t lose customers because of wrong pricing. But how can they do it?
Checking there every SKUs in countless platforms?
Or hiring someone for this laborious work but always have a doubt about data accuracy?
If none of these options you find enticing, here is when Product Automatch comes into picture. Where you are can get the lists of countless duplicates of your product with their prices and descriptions and with accuracy of a robot.
Never heard of something like this, lets talk about it and explore the term product automatch and how it can be a helpful tool in todays world.
Product Automatch is the process of automatically identifying the exact same or similar product across various e-commerce websites, platforms, and dataset. There are multiple parameters which can be used to identify the similar products, like descriptions, brand name, product code etc. It is more effective and efficient than traditional manual matching, which is time consuming as well as very laborious and prone to human errors.
Lets take an example for better understanding about the difference between product automatch and traditional product matching.
There is a business working in female fashion industry and they wanted to find out how many people are selling same shirts like them and on what price. They can either hire few people who will surf on every countless websites to collect data and analyze them or they can just try a product auto match tool from any Price Optimization Platform, which can collect information from countless platforms in the matter of seconds and provide you lists of the same as well as similar products.
I know what you would have opted between the two options and you are not the only one, the big e-commerce giants you seek for shopping are the biggest users of product automatch.
Ever wondered how you get the accurate recommendation regarding product you wanted to buy in amazon and eBay if they aren’t matching the products you are searching with their’s., it not only helps to improve user experience but also increases the sales rate of the websites.
Either its an e-commerce websites, online stores or search engines everybody is using product automatch in one way or another. But why? And why should you adapt this technology for yourself?
To answer all your whys, let see importance of product automatch.
Have you ever saw a fabric business competiting with food business?
No, right?
The comparison must have sounded funny or even stupid, but what if I say you are implementing these funny comparison on your business too, when you compare yours and others product, may the difference won’t be as explicit as the given example but it will be still there.
With product automatch, you will get the exactly matching products with its other details so you can know who your real competitor is and who is not. Figuring out your competitors could be a major step as after that you can monitor them and strategize accordingly.
When you get the list of products which are similar like your or fall into your category you can see the more variety of them by just keeping eye on your competitors, which can be a great step towards your catalog management. With product automatch list of exact same and similar product you can understand which product is more in demand with the proportion of dealers selling that product. In other words, product duplication can be the sign of raise in demand of that respective products.
Changing your product prices because of the product which aren’t even same as yours is like calling a chef for repairing your tab. Right its useless and might be harmful for your business too. Product automatch mostly provides you the percentage on product similarity of yours with others so you can decide the price fluctuation.
If a product is on every website and online shop then you can easily understand that customers are demanding the respective product and trusting the dealers who are dealing with them. You can even understand the customer behaviors during the trend shift to generate more leads and clients.
Knowledge is a great way to gain trust towards something, either it is a food recipe or just a process of creating an application, when you know about it you trust the process. So lets understand how does automatch work, so you can decide if you should rely on the product automatch or not.
Step 1 : Data collection
The first and most important step for any analysis tool is data collection and product automatch is no different. First it collects data from different ecommerce platforms, online shops, ERPs, catalogs, etc, so that it can analzye the data.
You should keep in mind that collection of data can be done in multiple parameters from product automatch, which differ from platform to platform.
We should keep in mind that all the platform have their own approach on making things works and everyone uses all these approaches in different proportions to get more accurate result.
Step 2 : Data Cleaning and Normalization
As we cannot write on an already written page, similarly machine cannot understand noisy data. Noisy data is uncleaned and unorganized data, with some records missing some attributes while other records containing repetitive data.
Through data cleaning we remove all the records with inconsistent and repetitive data, so the analysis would be accurate.
On the other hand data normalization is a technique of designing database to minimize data redundancy and prevent data anomalies. It also includes data structuring on the basis of certain rules or normal forms that optimize the accessibility of data and its storage.
through above processes data will be cleaned and ready for the next step.
Step 3 : Attribute Extraction
After data cleaning next step is data extraction which means taking or collecting useful data from the dataset. In other words, the data which is meaningful and needed for further analysis is extracted, for example brand name, product name, type of product, descriptions, images, etc.
This process is implemented through NLP. NLP stand for Natural Language Processing with comes under Artificial Intelligences. We will further discuss NLP in detail in this article.
Step 4 : Matching Logic
After extraction of data, next step is to match it from the products provided by you. For example if your business is about men formal wear, so all the shirts having pattern like your’s will be matched through matching logic.
Matching logic works on different parameters like brand name, product type, fabric type, description, color, etc. These parameters depends on field and product on which you are dealing.
Step 5 : Machine learning model
After the matching logic, it foes to machine learning model which was trained from previous data and are mostly accurate with all the trained data before, on every field.
Step 6 : Validation and feedback loop
After data had went through every step, it is organized in the list and displayed to you. From where you can validate the matching process and provide feedback for better accuracy and improved matching for future.
While there are countless methods and technologies used to make product automatch this efficient and accurate. There are some technologies which has been used dominantly to make it work. These technologies are explained in detail below.
NLP also called as Natural Language Processing is a large field in Artificial Intelligence and computer science. NLP is used to let the computers and machine recognize human languages and reply in human language through text and speech.
NLP is mainly used in language translation, speech recognition, text-to-speech / speech-to-text, etc. Google Assistance, alexa, and siri is a good example of NLP as they understand our command respond accordingly.
Machine Learning also known as ML is a subset of artificial intelligence in which a machine will be trained with data to classify things, like difference between animal and human, etc. There are three types of machine learning, Supervised Learning, Unsupervised Learning and Reinforcement Learning.
A great example of machine learning is chatbot which reply us accordingly and asks for feedback to improve user experience.
Computer vision works some as human vision. Like when we see something then we recognize it and then understand it. Similarly when computer analyze an image, it classify the content of image and does the operation requested. In automatch computer analyze your product and match it with given data of products through computer vision.
Computer vision is also used in generation of image and computerize editing in an image like removing background, etc.
Fuzzy matching also known as fuzzy logic is the part of artificial intelligence which is work to identify similar, not really identical string which might have same meaning. In product automatch it is greatly used in matching identifying similar description, titles and product types.
After knowing how product automatch works, its also very important to know where it will be used, so you know who else are it is using product automatch and how effective.
E-Commerce platforms and browser like google use product automatch for visual search where google extracts the same products as we search to compare prices or other factors of the same product.
E-Commerce platforms like Amazon, eBay, etc are also using product automatch as when we show interest in any product, the further recommendation from the platforms are of similar and sometimes same products with prices varying.
Today online market places like local webstore and google shows identical and similar product selling by different retailers in different prices can be grouped together with product automatch.
Data aggregation is the process of collecting data from one or more brand and prodcuts of similar field or category for further analysis. Many businesses these days implement data aggregation for maintaining databases and studying market trends and customer behavior. Product automatch is the tool used for data aggregations as it classify one product from another.
By using product automatch you makes sure that all the data you are using is accurate and had been extracted from the countless site, way too less time than any human can. Other than that its also free from human error and unintentional or intentional ignorance of relevant information.
How much time will it take for you to search lists of products similar to yours from top ten websites. Two hours? Four? Or whole day? Well product automatch can do it in minutes with accurate and organized result.
Working on non-technical like surfing website makes the labor force technical skills rough, you can use product automatch for operations like this for faster and accurate data aggregation. It as well frees the team of your for more strategic tasks.
Launching another product line or wanted to expand business geographically you don’t have to increase headcount or your team for analysis and market data collection if you have right tools with you scale your business with us. [[Book a Demo]]
Giving responsibility automatic tools and product automatch helps to get rich quality and quantity of data. As product automatch surf whole internet to collect all possible relevant data.
Everything which has light will be casting a shadow to and emerging technologies are no different, everything we are using right now even if its social media which snatched our rights of privacy or learning platform where there are distracting add, etc. So now we are going to discuss some of the factors which might not be very beneficial on your side.
Upload product are done by different people from different areas and languages making it possible to have a product many names and descriptions using abbreviations or different technical terms, making it possible for product automatch tools to skip the potential product of a competitors.
Ever saw a dress looking gorgeous from one side but doesn’t go will from another side, well images have many factors like resolutions, lighting, background, etc which can make the same shade look different. Because of which product automatch can be between same or similar products, because of which you can see some products in automatch and sometime it is classified in different categories.
As we discussed few points before, there are multiple language used in global market, which can make it difficult for product automatch to find similarities especially when more weightage or importance is given to product title or description rather than image.
Even the smartest algorithm is written by a human and where there is human there are chances of human error. So the algorithm we consider reliable might not be that reliable and to ensure accuracy of data you need to cross-check data from time to time, which can add an extra work in your routine work.
Hence after reading all the sides of product automatch we can say that even when there are some limitations of this technique its still a need of the time to adapt it, and platform providing these services are trying their best of shrink out the limitations. But after every limit we can still say product automatch can help a business expand through right knowledge same as fire expands in a forest and it’s benefits clearly surpasses it drawback, making it an obvious choice for every sector giants.
