Can The Problem Of Counterfeit Products On Online Marketplaces Be Solved By Artificial Intelligence (AI)? - Coffee with CIS - Latest News & Articles

Can The Problem Of Counterfeit Products On Online Marketplaces Be Solved By Artificial Intelligence (AI)?

It was not too long past when imitation goods such as footwear, watches, perfumes, handbags and much more were understood to be marketed from the back of trucks parked alongside dingy alleyways.

But like many areas of the industry nowadays, the selling of counterfeit products also has transitioned online after the development of the digital market, actually making its approach into platforms that are legitimate.

Many e-commerce sites nowadays are available marketplaces, meaning that third-party retailers (or vendors ) can record and market their merchandise on such platforms. This type of model helps online retailers enlarge their assortment of product offerings and bring more shoppers. Still, the identical version has unwittingly provided room for retailers to market counterfeits posing as real goods.

Reports suggest that large and reputed marketplaces such as Amazon are rife with knockoff products despite continual efforts to crackdown on defaulting retailers. Even products labeled as "Fulfilled from Amazon" on Amazon and similar equivalents along with other marketplaces are discovered to be counterfeits.

This dilemma affects all essential stakeholders in contemporary retail -- the online market, the customer, and the original manufacturer.

For marketplaces, the existence of counterfeits interrupts the customer's assurance in their stage, and perhaps the entire online retail program, which may potentially change buying behavior from online outlets in the not too distant future. For customers, a bad purchasing experience is the very least of the worries. At worst, some varieties of fake products may actually hurt the user, for example with substandard makeup that contains dangerous chemicals, electric and electronics with questionable security standards and much more. The initial brand producers risk having customers blame them to get an item which proves to be imitation, that is a massive setback to their new equity.

As a result of the scale of the issue, the chance of manufacturers dropping interest in advertising on e-commerce sites is actual. Already, manufacturers such as Birkenstock, Skechers, and L'OrΓ©al have, to different degrees have been at loggerheads with online marketplaces.

Consumer manufacturers now attempt to work out this dilemma by buying products from suspicious listings to confirm that the barcode of the product that is delivered. This is a costly, time-consuming procedure which is not really scalable and from the time the new response, the harm is already done. By way of instance, Apple recently spent a few million dollars to purchase over 100 iPhones and accessories also discovered that close to 90 percent of these were counterfeits.

The incidence of counterfeits nowadays can result from the online market model itself, on account of the simplicity by which third-party retailers can replicate the first product list pages. But this presents brands together with the very best chance to discover potential counterfeits. Modern artificial intelligence (AI)-based technology can identify inconsistencies within a combo of catalog content parameters and graphics on product list pages, which can be crucial indicators of suspicious merchandise listings.

The strategy is quite easy. Brands may compare the item list on an online market with the first product's descriptions and images to spot anomalies. This info can then be fortified with insights collected from assessing the prices (how much is the cost lower or greater than the highest retail price (MRP)?) , the trustworthiness of third-party retailers (is your retailer authorized from the manufacturer?) And client reviews and evaluations, to forecast if it's the item list is accurate.

Additionally, there are 3 Ways counterfeiting is performed:

β€’ Bogus products: Though there are not any surefire means of discovering these, it is possible to predict whether an item is an imitation with a mixture of variables, like the pricing, consent standing of these retailers and when there are disagreements in the catalog text and graphics (including the shadow and light ).

β€’ Picture theft: Online retailers sometimes steal pictures from first merchandise catalogs and contain them listings of different goods they are selling, which misleads shoppers throughout the purchase procedure.

β€’ Unauthorized white tagging: The first manufacturer's name is substituted with another from the online product list, while the other catalog elements like the item description and graphics stay the same. From time to time, the first brand's logo is filtered clean from the item picture.

Discovering such diverse kinds of counterfeits takes a strong AI-powered picture and text analysis engine that can feel minute variations between many different pictures and identify suspicious product descriptions. This special approach enables fixing the matter of counterfeits at enormous scale by covering some variety of online marketplaces simultaneously -- a massive leap forward in comparison to the present hit and miss process followed by manufacturers.

While most regulatory strain on controlling counterfeits is presently on the market, brands will need to take possession too. In the end, online marketplaces might not be overly keen or fast to blacklist a hoard of retailers so as to avert a sudden reduction from the width of the product offerings. But by always tracking cases of counterfeits, manufacturers may use marketplaces to blacklist defaulting retailers gradually over the years, or else they may approach a defaulting retailer directly to take care of the issue.

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