Almost every marketplace relies on chat as a fundamental tool to foster a trustworthy buyer-seller relationship. Establishing this trust is critical; every message exchanged could either solidify or jeopardise a potential sale, transaction, or any other value your marketplace intends to create.
The foundation of this trust rests on two pillars: clear communication and effective chat moderation. Without these safeguards, your platform could become a breeding ground for scams, eroding user trust and potentially leading to data breaches. Etsy's vast collection of scam narratives serves as a stark reminder of the importance of rigorous marketplace moderation.
Different marketplaces exhibit unique interaction dynamics. Platforms like Thumbtack, a specialised service app, foster ongoing relationships through consistent user-to-user conversations. Conversely, real estate marketplace like Nobroker often involve new interactions with different users for each transaction, resulting in diverse and varied engagements. These distinctive approaches significantly influence how users perceive and trust these marketplace ecosystems.
This article explores the important role of chat moderation in marketplaces, discusses different types of moderation and provides practical tips for designing a powerful moderation system for marketplace messaging systems.
Different methods of chat moderation and when to use them
Having engaged extensively with various marketplaces, ranging from expansive platforms to those with highly nuanced operations, it's become clear that the approach to moderation largely centres around balancing two crucial axes: scalability and rapidity on one hand, and complexity and nuanced understanding on the other.
AI-driven systems excel in swiftly managing high message volumes, crucial for the rapid growth of marketplaces. This automation streamlines routine tasks, maintaining pace where manual moderation struggles with expanding user bases and conversation loads.
Conversely, human moderators shine in their ability to grasp context intricacies and exercise subjective judgement. Their acute awareness of cultural nuances and language subtleties allows precise, empathetic interventions in content moderation, particularly in cases where standard rules might not suffice. This human touch remains indispensable in addressing unique circumstances.
1. The power of algorithms: AI and automated filtering
AI and ML in chat moderation aren't just revolutionizing the industry; they're becoming integral tools for platforms to ensure safe and engaging user experiences.
In our journey working across diverse marketplaces, our moderation capabilities have evolved significantly, especially with the integration of AI/ML filtering. AI-driven solutions have proven to be invaluable in addressing various scenarios within content moderation, some of which include:
Fraudulent links
Image moderation to detect explicit content
Hate speech detection
AI and ML processes vast amounts of textual data, identifies and flags harmful content with remarkable speed making them indispensable tools for ensuring online safety.
Spanning from large scale companies with hundreds of thousands of Monthly Active Users (MAUs) to more nuanced platforms, automated filtering has emerged as an essential tool.
Large-scale companies with extensive user bases require swift and effective automated filtering to handle the influx of content, conversations, and user-generated material. Nuanced and specialized marketplaces often deal with intricacies unique to their niche, where tailored moderation solutions are required. Even with fewer users, the complexities of interactions and content moderation demand efficient automated tools to maintain a safe and compliant environment.
2. The human touch: manual moderation and hybrid models
Despite the advancements in AI/ML moderation tools, the human touch remains paramount. It not only provides administrators with authority but also ensures effective moderation, particularly in scenarios where precision matters more than scale to prevent platform leakage.
In a diverse marketplace like Thumbtack, AI/ML tools organise service listings based on user preferences. Yet, the human touch is crucial. Human moderators grasp service nuances, ensuring provider authenticity and reliability, a task where AI may fall short. They also mediate disputes, resolving issues between customers and service professionals for a seamless experience.
In this context, while AI aids in initial screening and hate speech detection, the human touch remains indispensable in upholding the standards of trust, safety, and personalized support that define the marketplace experience.
Chat moderation strategies to implement in your marketplace
1. Data masking to prevent platform leakage
Platform leakage occurs when buyers and sellers bypass the marketplace platform by sharing their contact and banking information to make transactions offline. They do this to avoid the service fees of the platform.
Using data masking to hide or remove personal information such as phone numbers, mail ids, URLs and other payment details keeps the conversation and transactions on your platform.
2. Automated filters to identify and remove spam, profanity and other harmful content
AI-driven chat moderation systems are sophisticated enough to understand context and detect various forms of inappropriate content. These automated filters are not just keyword-based; they use machine learning algorithms to scan large volumes of messages in real-time and censor inappropriate language, including profanities, hate speech, or explicit material.
These filters excel in identifying various unwarranted intrusions, such as unsolicited advertisements or insidious phishing attempts. By swiftly removing these messages, moderators safeguard the marketplace's integrity.
Moreover, these filters can be finely tuned to align with the community's standards, often with inputs from human moderators. These inputs may include keywords like 'cash,' 'offline,' 'phone number,' or even examples of past conversations highlighting such concerning elements.
3. Ability for users to flag inappropriate or suspicious behaviour
By incorporating a simple 'report' button or flagging feature within the chat interface, users will be able to easily signal any suspicious or harmful behaviour.
This can be as simple as flagging the message that contains the inappropriate text, which will create a ticket for further investigation or can trigger a workflow that adds someone from the marketplace's moderator team to review the chat activity.
Once alerted, the moderator team can quickly assess the situation and take appropriate actions. These may range from directly messaging the involved parties to understand the context, to initiating sanctions against users found to be in violation of marketplace policies. In situations where a more detailed investigation is required, the ticketing system ensures that all relevant information is captured and systematically reviewed.
4. Leveraging persistent chat and message retention to offer context
Implementing persistent chat with message retention is a powerful strategy to maintain context across different conversations and mitigate the efforts of bad actors initiating multiple or varied chat interactions.
Keeping chat history helps to understand a user's past engagement. It makes it easier to tell conversations with genuine interest apart from potentially harmful ones. This makes it harder for bad actors to take advantage of the system by starting unrelated or fragmented conversations.
5. Strategic monitoring and moderation of buyer-seller conversations using role-based controls
It's essential to implement a robust monitoring and review system for conversations between buyers and sellers to create a controlled environment that maintains quality standards and assists users promptly.
Administrators and support teams need to be able to participate in or observe live interactions. This is important for quickly addressing potential issues as they happen. It also helps ensure that platform standards are always met. Additionally, it helps make sure that users are engaging appropriately and not trying to avoid paying platform fees.
Other team members should also be able to retrospectively access and review past conversations for the following reasons,
01.
Quality assurance
By analysing historical interactions, the marketplace can ensure that user engagements adhere to expected service standards.
02.
Training opportunities
Reviewing past conversations can highlight areas for improvement and serve as training material for both new and existing support team members.
03.
Incident analysis
When incidents are reported, having the context of previous conversations allows for a more informed and equitable resolution process.
This system of monitoring and reviewing involves integrating role-based access controls into the marketplace's chat infrastructure. These controls define who has the authority to engage, under what circumstances, and to what extent.
6. Empowering human moderators to review and take action
While automated systems provide a first line of defence, it is the discernment of human moderators that ensures nuanced issues are handled with care and precision. To support their efforts, a well-designed set of tools is essential,
Dashboard to keep track of all moderation specific activities
Centralized platform that offers a comprehensive view of all flagged messages and users, allowing moderators to quickly assess potential issues and identify trends that may require further attention.
When an individual repeatedly violates marketplace policies, human moderators should have the authority to ban them. Tools that allow for the easy identification and tracking of such violators are vital.
In-flight moderation: preemptive screening for safety
One of the most effective tools at a moderator's disposal is in-flight moderation. This feature allows potential harmful messages to be screened and held for moderator approval before delivery. Such preemptive control over message delivery is a powerful means of ensuring only the appropriate content reaches the recipient.
Aarathy Sundaresan
Content Marketer , CometChat
