How AI will transform social media customer service

Data suggests that 75% of companies will adopt AI technology between now and 2027.

Though the technology has been around for decades, it wasn't until recent breakthroughs that it was ready for public, high-risk, and high-value channels like social media.

Why?

AI-driven solutions for social media customer service are becoming smarter and more cost-effective.

Access to advanced technology and big data makes integrating AI into social media customer service easier than ever, with vast sources to learn from, such as public Facebook conversations and private Instagram Direct Messages. By analyzing customer posts, messages, and interactions, AI identifies trending topics, common customer questions, agent responses, and the sentiment behind interactions.

How are customer service leaders responding?

Customer service leaders are prioritizing:

• Knowledge management
  GenAI is only as good as the data it learns from. The quality of a company’s data and how it customizes GenAI software using its data set are key factors in creating a competitive advantage. Customer service leaders are working alongside other leaders in their company to break down knowledge silos and clean up their data.

• Financial investment in AI
  Customer service leaders realize that to stay competitive, they need AI capabilities that self-learn to enhance chatbots, personalization, self-service, and the overall customer and agent experiences. As the need for better social media customer engagement and operational efficiency rises, customer service leaders are shifting spending to prioritize AI-driven solutions. This is evident in research by CX Network, which shows AI is a top investment priority for organizations worldwide.

What about data security?

Brands are proceeding with caution.
Despite the advances made in AI, brands remain cautious about implementing best practices to keep their company and customers safe. Some of the most common concerns when implementing AI are:

• Data security: According to Foundry, data security is a leading barrier to AI adoption. Business leaders have concerns about the misuse of customer information, non-compliance with privacy regulations like GDPR, and the risk of data breaches.

• Unsupervised learning: Because GenAI learns from human interactions, it can develop biased responses or misinformation if there are no or limited guardrails. When integrating auto-generated knowledge or content, it’s important to always have secure guardrails to ensure they align with your brand values and voice.

• Rogue models: GenAI bots can make off-topic decisions if their learning models aren’t trained properly and they don’t have strict settings. It’s important to regulate GenAI bots to prevent this.

Ai-driven bots are getting better at understanding, classifying, and clustering conversations on social media.

With the data it gathers, AI-driven bots can recommend the next steps for your team members based on their knowledge. For example, it can suggest whether your team should reply to a comment or repost a positive brand-related post. It can also provide data-backed auto-generated responses and next-step recommendations for resolving a customer’s issue.

More companies increasingly use chatbots on social media channels like Facebook and Instagram. Chatbots help reduce the time to first response and enable self-service on social media channels. Though using chatbots on social media channels is not a new concept, they are becoming more accessible, cheaper to implement, and, thanks to AI, smarter than ever.

AI-powered chatbots are more savvy, with features such as:

• Auto-generated flows. In the past, creating a flow for bots was time-consuming and limited in capabilities, but that has all changed with GenAI. GenAI constantly learns from customer interactions, feeds that information into a knowledge bank, and turns it into an auto-generated flow.

• Emotional understanding. Though they don’t yet have a human level of emotional understanding, bots can generate empathetic responses on social media and even understand the sentiment and emotion behind a customer inquiry.

• Easy brand customization. Auto-responses can easily be customized to respond in the appropriate tone of voice for each social media platform and in a way that represents your brand well.

• Enhanced interaction features. AI-powered bots now offer more interactive features, such as clickable buttons and carousels, that can be implemented in social media private messages, making self-service options more engaging and user-friendly.

AI will help brands smoothly navigate through volume spikes of inbound inquiries on social media with the following features:

• Predictive analytics. By analyzing historical and current data and trends, bots can predict when spikes in volume are likely to occur and help teams prepare accordingly. For example, if your brand is launching a product or a holiday is approaching, bots can improve their predictions and response strategies by analyzing what worked and didn’t in the past.

• Real-time monitoring and alerts. AI-driven bots can continuously monitor social media activity in real-time and detect unusual spikes in volume about specific topics; beyond inquiry volume, this also includes public posts containing certain keywords relating to a brand. When a spike is detected, the bot can trigger alerts and implement pre-defined protocols to manage the surge. For example, if you are a telecom brand experiencing a service outage and inbound messages and public posts are increasing about the issue, the bot can recognize that and alert you to the spikes in volume.

• Generate a suggested social post. Following on from the above example, once the bot alerts you to the issue, it might recommend posting on X (even suggesting what to say) acknowledging the outage to help curb the influx of inbound messages.

With AI-powered assistance, new social media customer service team members won’t require as long a training process. AI-generated guidance will direct team members on what and how to respond to customers on social media in a variety of situations, with features such as:

• Auto-generated responses. Suppose a complaint from an angry customer comes in through Facebook Messenger that requires a response. Without AI, an agent might need human advice on what to write back to the customer. However with AI-generated assistance, it gives your team members editable auto-generated responses, eliminating the time and effort of retrieving a manager’s guidance.

• Resolution guidance. Based on their historical knowledge and understanding of customer interactions, bots can recommend to agents the best next steps toward resolution.

• Rich knowledge bank. A knowledge bank holds the information bots have absorbed from the self-learning knowledge loop with incorporated sources such as commonly asked questions or issues reported on social media and acts as a library for your team to reference. Say a customer messages a tech brand on X, asking about a specific functionality of their camera, but the agent needs to add more context than is given in the suggested response. They can easily refer back to the knowledge bank and do a quick search to see if the information they need is in there. Having a wealth of knowledge readily available and accessible significantly decreases response time and makes the agent’s job more straightforward.

As previously mentioned, data security is a leading concern when implementing AI capabilities. Enterprise brands need a trusted platform like Khoros that offers rich features for brands to:

• Protect data and governance: brands can decide what knowledge to include for customer-facing bots and agent assist and rest assured that data remains protected while in transit.

• Prevent bot hallucinations: brands can customize the built-in guard rails to ensure AI-generated content from social media channels is accurate and aligned to the brand voice to ensure it does not make off-topic decisions.

• Prevent bias, discrimination, and unethical behavior. Features that connect to industry-specific Large Language Models and AI services that have been pre-validated will prevent negative outcomes. This will give brands peace of mind as they implement AI for social media customer service.

The developments made in AI to enhance social media customer service are transformative. As companies move toward implementing AI, it’s critical that they clean and organize their data and implement strict governance and secure guardrails to optimize results.

If companies have done their due diligence before investing, AI should streamline mundane tasks, quickly turn data into useful information, and simplify customer service teams’ jobs. These advancements enable human agents to focus on more complex and personalized interactions and improve the overall customer experience.

Khoros Service is a solution that helps enterprise businesses scale their customer service operations quickly. It seamlessly blends synchronous and asynchronous modes of customer engagement. ​​

We are firm believers in the idea that every component, whether it is AI-powered bots or business applications, should work together to enhance the efficiency and effectiveness of customer engagement strategies.

Our customer service software allows brands to serve customers on their digital channel of choice with unmatched operational insight to boost satisfaction and reduce costs. When you unify multiple channels in a single solution, you empower your agents with the ability to engage across all touchpoints, including but not limited to:

• Messaging apps like WhatsApp, Apple Messages for Business, and Line

• Social networks like Facebook, X, Instagram, LinkedIn and WeChat

• Review sites, like Google Play Store, iOS App Store, Yelp, and Trustpilot

• Brand-owned channels, like web chat, in-app, Email, SMS, and Voice

• Owned communities, forums, and knowledge bases