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Reseller abuse is damaging your brand loyalty – here’s what you can do

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Cover of the Signifyd State of Fraud 2023 report

The rise of AI-powered bots in ecommerce has revolutionized retail, making buying and selling online more efficient and convenient for both consumers and businesses. But this innovation has a dark side. Unscrupulous reseller sites are exploiting bots to manipulate markets, siphoning profits from legitimate retailers and making in-demand products more expensive and harder to purchase for consumers.

Taylor Swift fans know this first-hand. Demand for tickets for concerts on her highly anticipated The Eras Tour far exceeds supply. Fans have reported logging onto Ticketmaster minutes after tickets go on sale to find that they are already sold out, only to find them reappearing on secondary market platforms or reseller sites at much, much higher prices. Some Taylor Swift fans pay 70 times the tickets’ original selling prices, while many can’t get access under any circumstances due to this retailer-versus-reseller battle.

Ticketmaster and other ticketing platforms are attempting to combat this problem using CAPTCHA codes and queueing systems to deflect bots and ensure fair access to tickets for real human beings. But resellers constantly evolve their strategies, creating ongoing challenges for retailer sites.

Reseller abuse is growing as fraud continues its digital transformation

The high-profile incidents of digital scalping and price gouging are simply the best-known cases of a trend that Signifyd data shows has been growing significantly for some time. As organized crime rings industrialize their ecommerce fraud operations, establishing Fortune 500-like enterprises with experts in commerce, fraud, fulfillment and post-purchase returns and refunds, reselling has become a lucrative revenue stream.

In the past year, the increase in orders from unauthorized resellers increased year-over-year by an average of 10%. Month-by-month the increase in attempted reseller orders — identified by a high number of repeated orders bearing the same digital identifiers on the same day — increased from 4% to an April spike of 35%. In no month was the pressure from unauthorized resellers on Signifyd’s Commerce Network lower than in the same month a year before. 

Increase in reseller abuse year over year

 

A chart showing the increase in reseller abuse in 2024 to illustrate Signifyd's blog post on reseller abuse

 

 

Bots power resellers’ business 

Bots are at the root of this problem, though some reselling schemes rely on humans to get the job done. First, what are bots? The term is short for “software robots,” and refers to AI-based applications that automate digital tasks, typically focusing on the repetitive or mundane aspects of computer-dependent desk jobs. They often simulate humans’ interactions with devices, software, websites or online forms. In retail, such bots can be programmed to speedily navigate through even the trickiest online checkout processes, vacuuming up whole inventories of the most in-demand items on a site before genuine customers have the opportunity to make their first click in retailers’ buying processes. 

Resellers also use bots in other ways. For example, they exploit discrepancies in pricing across different online platforms. They scan competitors’ prices and adjust the ones on their reseller sites accordingly. This results in a no-win race to the bottom that can significantly erode retailers’ profits.

Smaller businesses are disproportionately affected by bots, as they don’t possess the money or expertise to invest in the necessary sophisticated anti-bot technologies or business strategies – or to absorb any losses that occur. Market consolidation often ensues, with large reseller sites gaining more and more control and pushing out independent retailers, which inhibits competition and limits consumer choice.

How retailers’ performance is impacted by reseller targeting

The above types of reseller behavior significantly impact retailer performance and brand reputation. Consider, for instance, the great Sony PS5 Christmas disappointment. With the holiday season in full swing, a series of bot attacks cleared the digital shelves of the popular gaming console, leaving parents to pay a premium on the secondary market. Or worse, it left parents explaining to their kids that Santa didn’t see himself clear to drop one of the coveted gizmos at their house. 

Either case leaves consumers frustrated and disappointed or even angry with the retailer that couldn’t keep in stock the PS5 — or in other cases whatever popular item was scooped up.

“I think it’s ultimately about consumer trust and losing that trust has serious repercussions for a business,” said Signifyd Vice President, Strategic Initiatives Gayathri Somanath. “You want to bring consumers to your site and you want to create a trusted experience for them that keeps them coming back to you. These kinds of scalping attacks usually mean that your site has been compromised, a much-desired product is unavailable, and these goods are going to be sold somewhere else. It leaves consumers with a lack of trust in your site. For the retailer, you’re losing good customers and it diminishes your brand value.” 

Both the retailer and the brand — Sony in the PS5 example — lose control of the customer experience and miss the opportunity to build a relationship with the buyer — one of many damaging effects of unauthorized reselling.

Here’s a comprehensive list of how unauthorized resellers damage retailers in the short term and the long term:

  • Revenue losses: When unauthorized reseller sites commit resale abuse by buying products in large quantities and selling them at inflated prices on secondary markets, retailers can lose big as customers are diverted from shopping legitimate sites where they often buy additional accessories and items that complement the popular item they were after in the first place. 
  • Customer dissatisfaction: Genuine human buyers who fail to purchase products through normal retail channels due to resellers’ shenanigans can grow unhappy with both the retailers and with the manufacturers of the products in question — especially when they have to pay a significant premium elsewhere. This potentially erodes trust and customer loyalty.
  • Deteriorating brand reputation: When customers perceive the purchasing process as unfair or manipulated, they can associate their negative experiences with your brand. This can damage your reputation, making it more difficult to attract and retain customers.
  • Disrupted retail markets: By creating artificial scarcity and driving up prices on secondary markets, reseller sites can completely discourage customers from purchasing certain types of products altogether, impacting overall sales and revenue for manufacturers and retailers in particular industries.
  • Regulatory constraints: The behavior of resellers has drawn regulatory scrutiny and calls for legislative intervention to address fairness and transparency. The onus could be put on retailers to implement more robust – and costly – measures to prevent reseller activities and safeguard consumers.

How AI technology – biometrics and machine learning (ML) – can minimize reseller abuse

But AI can be retailers’ friend, also. Behavioral biometrics and ML models can help prevent reseller abuse with advanced ways to detect and thwart suspicious activity. Here’s how:

  • Analyze customer behavior: Behavioral biometrics recognize suspicious patterns in the behavior of online visitors to retailer sites such as how mice and trackpads are used, typing speeds, and certain navigation tendencies to create profiles of individual users. By continuously monitoring these behaviors, the technology can recognize anomalies that indicate bots are at work.
  • Separate bot from human visitors: By training ML models on historical online data from multiple retailers’ sites, AI systems can learn to recognize bots. Patterns such as too-swift or repetitive clicking, unusual browsing or high-frequency transactions from a single IP address can indicate potentially malicious, non-human activity.
  • Automatically identify unauthorized reseller ecommerce fraud: ML algorithms can be trained to detect fraudulent transactions and combat retail fraud by noting the frequency of transactions,  purchasing history of individual site visitors, information about devices used and geolocation data. By identifying deviations from typical human purchasing behaviors, such models can flag those transactions most likely to come from reseller sites or their bots.
  • Use dynamic risk scoring: ML algorithms can be used to build risk-scoring systems that dynamically judge the risk associated with transactions or interactions with site visitors based on a broad array of factors. By continuously updating risk scores in real time, retailers can take action like requiring additional authentication or temporarily blocking suspicious accounts.
  • Deploy adaptive integrated security controls: ML models can be integrated into retailers’ existing security systems to adapt controls based on evolving threats. For example, if they detect a new type of bot attack, they can swiftly recognize and communicate to the security technologies already in place to stop it, making retailers’ defenses against reseller abuse more resilient.

Reseller abuse is a multi-layered challenge that requires a multi-faceted defense strategy. Signifyd’s Commerce Protection Platform relies on a Commerce Network of thousands of online merchants and AI-driven models to build an understanding of the identity and intent behind every online order. That puts Signifyd in the unique position to detect the tell-tale signs of evolving bot attacks while also giving it the intelligence to recognize sophisticated actors who develop schemes that avoid relying on bots.

While Signifyd’s AI defends merchants against a vast array of reseller attacks, its policy abuse engine, Decision Center, can be used to create customized and flexible rules using AI features to identify and manage resellers based on a business’ needs.

CurrentBody, which sells innovative beauty and self-care products, turned to Signifyd when its unauthorized reseller program became a growing problem.

“We were very concerned about the effect resellers could have,” said Lyn Carbine, head of trading at CurrentBody. “Controlling the distribution of our products is essential to maintaining successful brand partnerships.”

After setting up policies to deter unauthorized resellers, Carbine said CurrentBody’s unauthorized reseller rate “effectively dropped to zero.” 

“The impact of this on our brand and partnerships can’t be overstated,” she continued. “We’ve regained control of millions of dollars worth of product that would have flowed through the wrong channels.”

Other ways to combat reseller abuse

Technology isn’t the only way to fight back against reseller abuse. Business-model-based strategies can also work well. Of course, not every business-model strategy fits the business model of an existing brand. And while considering whether to adopt a business-model-based approach consider any additional effects, such as adding friction by inconveniencing consumers or causing frustration with limited inventory. That said, some business-model-based strategies include:

  • Surprise site visitors with unpredictable product selections and releases: Introduce randomness into your available inventory by changing product release times, limiting the number of products that can be purchased by each customer, or rotating what’s available at any given time to make it harder for reseller sites to easily predict and program their bots to exploit your retail site. You can also create “limited edition” offers that can generate hype and urgency among human customers while making resellers hesitate to invest in building bots for items with limited availability.
  • Verify accounts: Use techniques such as email verification or two-factor authentication to make sure that individual purchasers are legitimate human customers and not automated AI bots. 
  • Change to a direct-to-consumer (DTC) model: By selling directly to consumers through your own channels – for example, your own online store (as opposed to an aggregated retailer like Amazon) or branded brick-and-mortar locations – you have more control over pricing, inventory management, and customer relationships, reducing the influence of resellers. 
  • Offer subscriptions: By asking customers to pay fees for access to exclusive products, discounts, or benefits, you can stop resellers by limiting the availability of sought-after items to privileged – and guaranteed human – members.
  • Personalize customer experiences: Offering personalized or customized experiences can discourage resellers, as such products won’t be attractive to the mass market and therefore the revenue potential from reselling them will be low. Personalization also has the advantage of significantly boosting customer loyalty for retailers. 

Stopping reseller market abuse is a retail community effort

Reseller abuse is a serious threat to the health of online retailers. You’ll be more successful if you don’t act alone or in a vacuum. 

By sharing selective data, for example, retailers – even competitors – can collectively strategize to strengthen their defenses against reseller sites. After all, you face common adversaries. You will all be more resilient if you present a united front against the destructive influence of reseller sites and their bots. Signifyd’s vast Commerce Network essentially provides this sort of advantage without sharing data among merchants.

Don’t neglect building strong partnerships with online marketplaces, either. They’re very powerful and working with them to establish strict policies against reseller abuse can help you monitor and enforce fair trade, protecting both them and you—guarding your respective brand reputations as well as customer experiences.

By adopting the above technologies, business models and strategies, retailers can minimize the impact of reseller abuse while fostering stronger relationships with their valued human customers. All of which leads to maintaining better control of their brands.

Photo by Getty Images


Are unauthorized resellers taking your profits? Let’s talk. 

The trouble with unauthorized reselling: A merchant’s perspective

Signifyd caught up with Devanshu Agarwal, the payment and risk manager for On sportswear. We asked him about the kind of fraud and unauthorized reseller pressure that online brands face when selling scarce, highly coveted and valuable goods — such as that very special pair of sneakers. 

 

How AI technology – biometrics and machine learning (ML) – can minimize reseller abuse

But AI can be retailers’ friend, also. Behavioral biometrics and ML models can help prevent reseller abuse with advanced ways to detect and thwart suspicious activity. Here’s how:

  • Analyze customer behavior: Behavioral biometrics recognize suspicious patterns in the behavior of online visitors to retailer sites such as how mice and trackpads are used, typing speeds, and certain navigation tendencies to create profiles of individual users. By continuously monitoring these behaviors, the technology can recognize anomalies that indicate bots are at work.
  • Separate bot from human visitors: By training ML models on historical online data from multiple retailers’ sites, AI systems can learn to recognize bots. Patterns such as too-swift or repetitive clicking, unusual browsing or high-frequency transactions from a single IP address can indicate potentially malicious, non-human activity.
  • Automatically identify unauthorized reseller ecommerce fraud: ML algorithms can be trained to detect fraudulent transactions and combat retail fraud by noting the frequency of transactions,  purchasing history of individual site visitors, information about devices used and geolocation data. By identifying deviations from typical human purchasing behaviors, such models can flag those transactions most likely to come from reseller sites or their bots.
  • Use dynamic risk scoring: ML algorithms can be used to build risk-scoring systems that dynamically judge the risk associated with transactions or interactions with site visitors based on a broad array of factors. By continuously updating risk scores in real time, retailers can take action like requiring additional authentication or temporarily blocking suspicious accounts.
  • Deploy adaptive integrated security controls: ML models can be integrated into retailers’ existing security systems to adapt controls based on evolving threats. For example, if they detect a new type of bot attack, they can swiftly recognize and communicate to the security technologies already in place to stop it, making retailers’ defenses against reseller abuse more resilient.

Reseller abuse is a multi-layered challenge that requires a multi-faceted defense strategy. Signifyd’s Commerce Protection Platform relies on a Commerce Network of thousands of online merchants and AI-driven models to build an understanding of the identity and intent behind every online order. That puts Signifyd in the unique position to detect the tell-tale signs of evolving bot attacks while also giving it the intelligence to recognize sophisticated actors who develop schemes that avoid relying on bots.

While Signifyd’s AI defends merchants against a vast array of reseller attacks, its policy abuse engine, Decision Center, can be used to create customized and flexible rules using AI features to identify and manage resellers based on a business’ needs.

CurrentBody, which sells innovative beauty and self-care products, turned to Signifyd when its unauthorized reseller program became a growing problem.

“We were very concerned about the effect resellers could have,” said Lyn Carbine, head of trading at CurrentBody. “Controlling the distribution of our products is essential to maintaining successful brand partnerships.”

After setting up policies to deter unauthorized resellers, Carbine said CurrentBody’s unauthorized reseller rate “effectively dropped to zero.” 

“The impact of this on our brand and partnerships can’t be overstated,” she continued. “We’ve regained control of millions of dollars worth of product that would have flowed through the wrong channels.”

Other ways to combat reseller abuse

Technology isn’t the only way to fight back against reseller abuse. Business-model-based strategies can also work well. Of course, not every business-model strategy fits the business model of an existing brand. And while considering whether to adopt a business-model-based approach consider any additional effects, such as adding friction by inconveniencing consumers or causing frustration with limited inventory. That said, some business-model-based strategies include:

  • Surprise site visitors with unpredictable product selections and releases: Introduce randomness into your available inventory by changing product release times, limiting the number of products that can be purchased by each customer, or rotating what’s available at any given time to make it harder for reseller sites to easily predict and program their bots to exploit your retail site. You can also create “limited edition” offers that can generate hype and urgency among human customers while making resellers hesitate to invest in building bots for items with limited availability.
  • Verify accounts: Use techniques such as email verification or two-factor authentication to make sure that individual purchasers are legitimate human customers and not automated AI bots. 
  • Change to a direct-to-consumer (DTC) model: By selling directly to consumers through your own channels – for example, your own online store (as opposed to an aggregated retailer like Amazon) or branded brick-and-mortar locations – you have more control over pricing, inventory management, and customer relationships, reducing the influence of resellers. 
  • Offer subscriptions: By asking customers to pay fees for access to exclusive products, discounts, or benefits, you can stop resellers by limiting the availability of sought-after items to privileged – and guaranteed human – members.
  • Personalize customer experiences: Offering personalized or customized experiences can discourage resellers, as such products won’t be attractive to the mass market and therefore the revenue potential from reselling them will be low. Personalization also has the advantage of significantly boosting customer loyalty for retailers. 

Stopping reseller market abuse is a retail community effort

Reseller abuse is a serious threat to the health of online retailers. You’ll be more successful if you don’t act alone or in a vacuum. 

By sharing selective data, for example, retailers – even competitors – can collectively strategize to strengthen their defenses against reseller sites. After all, you face common adversaries. You will all be more resilient if you present a united front against the destructive influence of reseller sites and their bots. Signifyd’s vast Commerce Network essentially provides this sort of advantage without sharing data among merchants.

Don’t neglect building strong partnerships with online marketplaces, either. They’re very powerful and working with them to establish strict policies against reseller abuse can help you monitor and enforce fair trade, protecting both them and you—guarding your respective brand reputations as well as customer experiences.

By adopting the above technologies, business models and strategies, retailers can minimize the impact of reseller abuse while fostering stronger relationships with their valued human customers. All of which leads to maintaining better control of their brands.

Photo by Getty Images


Are unauthorized resellers taking your profits? Let’s talk. 

Alice LaPlante

Alice LaPlante

Alice LaPlante is an award-winning freelance writer specializing in making complex information accessible to B-to-B and B-to-C audiences. She has deep experience writing brochures, white papers, blogs, case studies, books, video scripts and articles about a broad spectrum of technologies.