Brandon Anderson is the Chief Product Officer at Zingtree responsible for product vision and strategy, user experience, and delivering superior solutions and value to our customers.
Brandon has 20 years experience in Product across a number of companies. Prior to Zingtree, Brandon led Product, User Experience and Analytics at SportsEngine, a B2B and B2B2C SaaS company which was acquired by NBC Sports in 2016. SportsEngine products serve over 45,000 organizations and 15MM users.
Zingtree is the AI enabled CX automation platform that helps B2C enterprises automate actions, self-service and agent effectiveness.
Could you explain the core function of Zingtree’s AI-enabled support automation platform and how it differentiates itself from other solutions in the market?
Zingtree is an intelligent process automation platform with an easy-to-use interface designed for non-technical people so they can automate customer support interactions across enterprise application ecosystems.
Our key differentiators:
- No-Code Administration and Change Management: Features an intuitive, no-code interface for easy management and modification, accelerating deployment and reducing operational costs.
- No Database Required: Operates without a centralized database, minimizing data duplication and latency and enhancing security and compliance.
- Modern Integration and Object Modeling: Connects disparate systems and data sources, ensuring real-time data flow and visibility and enabling extensive automation.
- Platform Agnostic: Integrates seamlessly with any existing infrastructure, reducing downtime and costs. Includes out-of-the-box integrations with CRMs like Salesforce and Zendesk, ERPs, back-office, and EMR systems.
- Channel Agnostic: Provides a consistent customer experience across all communication channels, enhancing satisfaction and loyalty.
How does Zingtree’s platform automate actions and improve self-service and agent effectiveness for over 700 B2C enterprises?
Zingtree ingests and analyzes your data to automatically build workflows that integrate with enterprise applications to trigger contextually relevant actions and resolve customer support tickets faster. It understands complex business processes, policies, and compliance requirements, enabling seamless and intelligent automation.
Because most routine queries are resolved with self-service, agents can focus on more complex and sensitive requests, which is more mentally rewarding.
When a query escalates to a customer service representative, Zingtree delivers the right answers and suggests the next best actions. Reps don’t need to toggle through multiple apps and put customers on hold to search for resolutions. With its highly customizable workflows, the platform guides agents step-by-step through interactions, allowing them to quickly retrieve information and adhere to policies.
What are some common myths and concerns you’ve encountered about integrating AI into customer experience (CX), and how does Zingtree address them?
One of the biggest myths is the belief that generative AI and chatbots can solve all CX problems. Gen AI has enormous potential, but enterprises must first build a robust underlying action framework. That means integrating AI with all enterprise systems and establishing clear guardrails for the algorithms. Plopping an out-of-the-box solution into your workflow won’t deliver the desired results and may even generate surprise scenarios. For example, without the proper infrastructure, a customer might talk your bot into selling a truck for $1.
Many have speculated that Gen AI will phase humans out of the CX process. That’s impossible. Many complex and sensitive customer issues require critical thinking and human empathy, which AI cannot provide. Customers value human connection, and sticking them with an endless loop of AI answers creates frustration and poor experiences. Companies should always provide a direct way to reach a human, regardless of how advanced AI becomes.
Can you share strategies for seamlessly integrating AI into existing customer service workflows to maximize impact without disrupting current operations?
You can’t just implement AI and let it run. The technology requires clearly established guardrails to ensure it operates within company rules and performs as expected. Businesses must build a comprehensive, integrated system capable of interpreting data, applying predetermined rules and executing specific actions. This approach connects siloed applications and automates as many customer inquiries as possible without AI. Once companies firmly establish this system, they can more effectively layer AI into their operations.
As with most new processes, start small. Implement technology in a straightforward use case, perfect that process, then slowly expand to more complex applications.
In highly regulated industries like healthcare and insurance, what unique challenges does AI adoption present, and how does Zingtree navigate these while ensuring compliance?
Many AI systems are opaque. Users can’t audit decisions to understand the reasoning behind recommendations. Algorithms may amplify data bias or compromise privacy, but there’s no way to tell. The lack of auditability makes it impossible to prove compliance with regulations and introduces risk for patients and consumers.
The Zingtree platform offers complete transparency, giving you full control of your workflows. It ingests your knowledge articles, tickets and transcripts to automatically build and populate workflows into a no-code authoring experience. With the help of AI Co-pilot, humans finish the last ten to twenty percent to ensure compliance and guidelines.
Balancing AI automation with the human touch is crucial for customer satisfaction. Could you share tips for achieving this balance and examples of how Zingtree has successfully implemented it?
Companies must identify which tasks make sense to automate. For example, routine queries such as appointment scheduling, merchandise returns or troubleshooting can be accomplished with automation. Humans can handle more complex and sensitive tasks.
AI should empower customer service agents, not replace them. Technology can put information at the agent’s fingertips and guide them through company processes, allowing them to provide more efficient, personalized customer support than AI alone.
The connection between AI and humans should be seamless. No one likes giving a chatbot all their information and then having to repeat it when they finally talk to a human. Develop your systems so both algorithms and people can access and share necessary information. Businesses should establish a framework that empowers their stakeholders and agents to oversee AI interactions and step in when necessary.
What future trends do you predict in AI’s role in customer service, and how is Zingtree preparing to meet these evolving demands?
Consumers increasingly expect customized interactions across all channels, making personalized self-service experiences the next frontier of customer service. Companies can use large language models (LLMs) to understand complex queries and deliver precise, context-aware answers to users. Zingtree just launched its CX Answers and CX Actions, which unifies data and knowledge across a company’s system and incorporates the user’s context, business policies, permissions, and CRM data to get users the specific answers they need. These results will move beyond just delivering resources to actually generating conversational answers. Zingtree’s CX Action product combines with CX Answers to empower customers to solve more issues themselves and provides agents with contextual data to identify the next-best action based on the individual and the query.
Could you highlight how companies like Pearson, Groupon and Fleetcor have leveraged Zingtree to enhance their customer experience?
Zingtree helped Pearson manage customer service challenges created by their complex processes, varied product portfolio and diverse customer base. Pearson’s team built decision trees for their most complex workflows without training. During the first eight months of implementation, Pearson achieved:
- 60% increase in Net Promoter Score (NPS).
- 47% improvement in customer satisfaction.
- 33% reduction in agent ramp time.
- 24% decrease in time to resolve cases.
Groupon used Zingtree to streamline its customer service operations. Zingtree has become a one-stop shop for Groupon’s agents, empowering better service and faster resolutions. Groupon also built QA reports to provide detailed insights into customer service agents’ performance to pinpoint improvement opportunities. Zingtree has enabled Groupon to standardize processes across its global footprint.
Fleetcor used Zingtree to reduce agent ramp time from 12 weeks to three days and achieve a 92% decrease in agent errors. Fleetcor also enhanced its website self-service capabilities, and its NPS soared by 38 points.
How does Zingtree’s AI utilize customer data to personalize experiences, and what measures are in place to ensure data privacy and security?
Zingtree’s ability to unify all an organization’s data allows it to incorporate users’ context, permissions and CRM data to offer relevant and dynamically adjusted results that cater to individual user nuances. Agents and chatbots can access the up-to-date data and resources they need to help resolve queries.
Zingtree builds its platforms with data security in mind. We adhere to SOC2, HIPAA, GDPR, CCPA, and many other regulations.
Finally, for companies looking to adopt AI-enabled CX solutions, what initial steps do you recommend to ensure a smooth implementation and immediate impact on customer satisfaction and agent productivity?
The first priority is clearly defining your goals and objectives. If you don’t know what you want AI to accomplish, it can disrupt your workflow and create new challenges. Set clear goals to measure progress. You must also educate and train your employees on the new processes and technology.
Start small. Implement the solution in one basic workflow or process, such as automating appointment scheduling. You can optimize performance and deliver tangible results to secure stakeholder buy-in. This incremental approach also helps employees understand and acclimate to the changes. You can slowly add the technology to more complex and involved tasks.
The biggest thing to remember about adopting an AI platform: It needs supervision. The most effective implementation approach is building a robust system of action. If your foundational processes are sound, AI will augment functionality rather than break it.
Thank you for the great interview, readers who wish to learn more should visit Zingtree.
