How to develop a data-driven brand protection strategy? 

Imagine that if you were Kim, an IP and brand protection specialist at a renowned clothing brand. Kim has faced an escalating issue of unauthorized resellers at marketplaces. Realizing the gravity and damage caused by this issue, Kim sees the opportunity to adopt a data-driven approach to address these pressing concerns effectively.

In fact, Kim’s problem is a common one. Counterfeiting poses a constant threat to businesses, and the pandemic further magnified this concern. As people increasingly turned to online shopping during the crisis, there was a remarkable surge in e-commerce sales, with an impressive 25.7% growth within just one year. Unfortunately, this shift also created opportunities for counterfeit traders to exploit online platforms and reap substantial profits. Consequently, professionals like Kim, responsible for brand protection, had to adapt and enhance the brand protection and IP strategy accordingly.

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What is a data-driven brand protection strategy? 

A data-driven brand protection strategy relies on data and analytics to safeguard a brand from counterfeiting and intellectual property infringements. This approach is founded on insightful research rather than guesswork. For Kim, adopting a data-driven strategy enabled her to identify and monitor potential threats and take proactive actions to protect her brand. Moreover, it helped preserve brand value and customer loyalty in a competitive and dynamic market.

Why is important to have a data-driven strategy for brand protection?

Efficient use of data

Data is an asset in the digital era. An effective data strategy empowers brand protection teams to make faster, actionable decisions. With the adoption of a data-driven approach, Kim can collect customer feedback through online forms and surveys, enabling them to identify counterfeits and brand misuse and take prompt action to mitigate potential damages.

Safeguarding sensitive data

A data-driven strategy also ensures the protection of confidential information such as customer data and product details. Through encryption and access controls, Kim can detect fraud patterns and prevent unauthorized use of their brand assets.

Uncovering valuable insights

By analyzing sales data and market trends, companies can identify regions or channels where counterfeit products are prevalent. This allows them to strategically allocate resources to combat counterfeiting. Kim can then leverage their data to uncover valuable insights, leading to improved financial performance and increased productivity.

Examples of data-driven practices for brand protection teams

Retail industry

Brand protection teams in retail can analyze sales data, customer reviews, marketplace transactions, supplier data, and social media mentions to identify suspicious activities. In Kim’s case, she can use data to identify sellers with a high number of customer complaints or products with a significant number of negative reviews, indicating potential counterfeit goods. With a projected global retail e-commerce sale of $5.9 trillion in 2023, the retail industry is acutely aware of the rising significance of implementing data-driven strategies. These strategies are crucial for proactively combating counterfeiters and maintaining a competitive edge in the market.

In fact, the e-commerce giant Amazon took advantage of this strategy in 2022 to utilize data provided by the brands enrolled in its Brand Registry program. The goal was to reduce the total number of valid notices of infringement filed by participating brands. As a result of this initiative, Amazon successfully decreased the number of such notices by more than 35%.

Pharmaceutical industry 

Data analytics techniques and artificial intelligence (AI) models enable brand protection teams in the pharmaceutical sector to track product movements and detect counterfeit drug activity. By integrating various data sources, they can proactively identify risks and target enforcement efforts, safeguarding public health and ensuring product authenticity.

Many government agencies have favored this data-driven strategy to protect their citizens. For example, the Food & Drug Administration (FDA) has implemented a system that allows people to report issues related to medication or device quality, authenticity, performance, or safety, thereby collecting necessary data for taking appropriate actions.

Consumer electronics industry

Data-driven decision-making plays a crucial role in combating unauthorized distribution and brand infringement. Brand protection teams in the consumer electronics industry leverage market intelligence, e-commerce data, and online monitoring tools to identify unauthorized sellers in the grey market and counterfeit products. For example, by analyzing pricing data across different online platforms, brand protection teams can detect abnormal price discrepancies or instances of unauthorized sales. These insights allow them to build strong cases against counterfeiters, such as sending cease-and-desist letters and collaborating with law enforcement to shut down unauthorized distribution channels. As an example, Apple removed over one million listings for counterfeit and fake products in 2020 after leveraging data from counterfeit reports and evidence.

How to become more data-driven for brand protection? 

With the recent development of AI technology, counterfeiters have also leveraged these applications to speed up their distribution of counterfeit goods. To confront this challenge, brand protection teams must adopt a data-driven strategy that aligns with the ever-changing environment and addresses the expectations of both brands and consumers for verifiable authenticity. Here are some recommendations to address this issue: Layer Image

Recognize patterns in your data

Analyze surveys, reports, and consumer complaints to identify patterns and derive valuable insights. Proactively address issues and mitigate risks by systematically analyzing recurring themes, commonalities, and trends that pose threats to your brand.

Tie every decision back to the data

Base brand protection decisions on data-driven analytics rather than gut instincts. Ensure that each decision related to counterfeit product identification, infringement cases, or preventive measures is firmly rooted in data analysis.

Visualizing the meaning behind the data

Data visualization is a powerful tool for understanding complex information and extracting actionable insights. Instead of being overwhelmed by raw data, utilize charts, graphs, and visual representations to bring clarity and meaning to your brand protection data. This visual perspective enables you to take appropriate actions based on the insights gained, ultimately strengthening your brand protection strategy.

Using data to answer critical questions 

A data-driven strategy involves extracting relevant insights that answer critical questions, rather than using all the collected data indiscriminately. Identify the key questions driving your brand protection efforts, such as identifying susceptible regions or channels for counterfeiting. Utilize targeted data analysis to find reliable answers. By focusing on relevant data and avoiding unnecessary complexity, you can make reliable decisions that optimize your brand protection efforts.

Why Hubstream?

Hubstream is a data-driven case management platform designed to assist brand protection teams in making informed decisions. It offers efficient data organization and transformation, advanced features for enhanced case management, centralized data storage, and AI-powered analytics and insights. Hubstream has gained recognition and adoption across various industries, underscoring the importance of data-driven decision-making. By leveraging Hubstream, brand protection teams can maximize their impact, protect their brand, and maintain customer trust.

Developing a data-driven brand protection strategy is essential for combating counterfeiting and safeguarding intellectual property. Brand protection teams can enhance their effectiveness by recognizing the value of data, tying decisions back to data analytics, visualizing insights, and answering critical questions. Tools like Hubstream can further empower these efforts, enabling teams to make informed decisions and protect their brands, revenues, and customer trust. 

Interested in learning more?

If you are interested in learning more about Hubstream, please try our risk-free software or contact us at to schedule a demo.