8 min read The logistics and supply chain industry is working at a breakneck pace today.
With the rise of e-commerce, globalized trade, increasing customer expectations, and the need to deliver instant gratification, businesses in the sector are now facing much higher volumes of customer inquiries than ever before.
From order updates to issue resolution, customer support teams are struggling to keep up with queries across channels.
This is where AI-powered customer support automation for logistics and supply chains comes in. In this post, we’re going to go over the status quo, challenges faced by businesses, must-have automation, and how AI can bring far more intelligence into the process.
Table of Contents
The status quo of customer support in logistics and supply chain
Most logistics and supply chain companies still rely on traditional processes to handle customer support:
- Call centers – Customers rely on phone calls to get updates on shipments, track orders, and resolve issues.
- Email support – Customers are required to reach out for updates on a support address which is then handled manually.
- Ticket-based systems – Companies are still using ticketing tools to manage requests, requiring human agents to organize, process, and respond to requests.
- Knowledge bases and FAQs – Many businesses provide customers with self-service FAQs and knowledge articles that are often generic and do not address queries in real-time.
While the status quo measures are functional, they still rely on manual efforts. They lack efficiency, effectiveness, scalability, and the real-time responsiveness that customers expect from modern-day logistics providers.
Challenges faced in customer support for logistics and supply chain companies
Here are some of the challenges companies struggle with:
1. High volume of customer inquiries
With thousands (and sometimes, millions) of shipments being processed daily, logistics companies often face a massive volume of inquiries like ‘Where is my order’, ‘Why is my delivery delayed’, ‘How can I change my delivery address’ and similar. Relying on manual responses to these questions often requires jumping from one platform to another to gather data, leading to high response times.
2. Inability to deliver real-time responses
According to a study by Salesforce, 83% of customers expect immediate responses when interacting with support teams. However manual tracking automatically adds to the time it takes to respond to queries, leading to frustrated customers and a negative brand perception.
3. Operational inefficiencies
Manually managing support inquiries increases operational costs for businesses. Repetitive tasks like tracking shipments or answering FAQs can quickly eat into the time of human agents, increasing their workload and taking their attention away from more complex inquiries.
4. Scalability challenges
Traditional support systems are hard to scale when the business needs to establish multiple customer touchpoints or channels. This can also be more challenging during peak sales seasons like BFCM and the holidays, leading to compromised service quality. It gets further challenging if the support needs to be delivered in multiple languages.
5. Lack of personalization
85% of consumers today expect personalized responses from businesses. However the inability to gather and process past interactions, queries, purchases, and other information in real-time, can lead to using generic responses only.
6. Increased competition
Delays, inaccuracies, and poor communication can quickly lead to customer churn and loss of reputation. In competitive markets, this can make it harder for businesses to scale sustainably.
And that’s exactly why customer support automation have become a must for logistics and supply chain businesses.
Must-have customer support automation for logistics and supply chain companies
Here are some essential automation that can help logistics and supply chain companies streamline their support functions:
1. Shipment tracking
Customer support tools can integrate with logistics management systems to provide real-time updates for shipments. This can include information on delivery times, route updates, delays, and similar updates.
2. Delivery rescheduling
Many consumers today seek rescheduling of their order delivery. Instead of managing the requests manually, businesses can automate the workflow by verifying customer identity and shipment details, processing new delivery time requests, and updating logistics teams in real-time.
3. Address changes
Similar to delivery rescheduling, some customers may reach out to request delivery address changes. An automated workflow can verify their details, process the address changes, and update the logistics teams to prevent non-delivery or RTO.
4. Issue resolution
Common issues like delivery delays lost packages, or damaged goods can be resolved through automated workflows. The system can automatically gather customer and shipment details, verify the same, process claims, generate tickets, or route requests to the appropriate teams while responding to customers proactively.
5. Proactive communication
Multi-channel customer support tools can also help set up automated alerts for shipment delays due to weather or traffic disruptions. This helps address customer concerns before they turn into queries.
6. Automate FAQs and self-service
Customer support automation tools can help provide instant answers using canned responses or direct consumers to self-serve portals. This can include questions like ‘How do I track my package’, ‘How can I initiate a return’ and similar queries. Automation can help reduce the time spent on repetitive and standardized tasks/ responses.
While the above automation are bringing efficiency into how logistics and supply chain companies handle customer support, there is still a lack of intelligence on the process.
Businesses are losing out on insights they can derive from conversations to improve their operations or change their strategy to boost brand perception in competitive markets.
This is where AI comes in.
Why traditional support automation workflows are not enough and how AI can help?
Here are some ways in which traditional automation are failing to deliver positive customer support experiences in logistics and supply chain:
1. Lack of context awareness
Traditional automation systems operate on predefined rules and workflows. This makes them rigid and unable to adapt to real-world scenarios. AI-powered solutions like Auralis AI, use natural language processing and context-awareness to understand customer queries on a deeper level. This helps provide more accurate and personalized responses.
2. Limited scalability
Rule-based automation systems can be challenging to scale as the volume of inquiries increases and diversifies. AI customer support systems can handle thousands of requests simultaneously while ensuring consistent and contextual responses even during peak seasons. This also holds when tackling support inquiries across multiple channels.
3. No personalization
Traditional workflows provide one-size-fits-all solutions. AI-powered customer support tools use machine learning and data analytics to deliver personalized responses in real-time based on past interactions, customer history, and preferences. Solutions like Auralis AI can also further help personalize by responding to queries in preferred languages.
4. Not proactive
Traditional support automation are triggered by query inputs. This means the system is only able to react when an issue arises. But with AI-powered tools, businesses can use predictive analytics to anticipate problems and proactively engage customers, leading to better engagement and retention, without disruptions in their journey.
5. Inefficient data utilization
Rule-based automation systems cannot analyze large datasets. AI tools on the other hand can process and extract actionable insights to help businesses optimize operations, predict delays, and improve customer support.
6. Inability to handle complex queries
Queries or requests that require a multi-step process often become harder to handle through traditional systems. Well-integrated AI-powered automation tools can understand issues, route them appropriately, and create a tailored path to resolution without the friction of back and forth with generic messages.
7. Lack of sentiment analysis
Traditional customer support systems simply automate repetitive tasks. While they are efficient at responding to queries, they are unable to understand the intent and sentiment behind the requests. This is where AI-powered tools help, diving into the conversations in real-time to understand emotions like frustration, happiness, confusion, and others – which helps prioritize inquiries better and respond to customers with more empathy.
8. Inaccurate feedback analysis
Traditional systems typically analyze performance based on the number of queries resolved through automation. But AI-powered tools like Auralis AI can analyze customer feedback to identify trends, pain points, and areas of improvement by assessing chats, emails, and surveys in real-time.
Conclusion
In times when ‘prime delivery’ is becoming more and more popular, logistics and supply chain businesses need to keep up with increasing customer expectations – and this includes their support experiences.
While customer support automation has been around for a while now, it is time for businesses to pay closer attention to their unique processes and relationships with customers. This can help them create custom automated workflows using tools like Auralis AI, delivering higher levels of personalization to resolve queries faster and boost customer experiences.
Want to know more about AI-powered customer support automation for logistics and supply chain companies?
