Brandon Anderson is the Chief Product Officer at Zingtree liable for product vision and strategy, user experience, and delivering superior solutions and value to our customers.
Brandon has 20 years experience in Product across quite a lot of firms. 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 the way it differentiates itself from other solutions available in the market?
Zingtree is an intelligent process automation platform with an easy-to-use interface designed for non-technical people so that 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 simple management and modification, accelerating deployment and reducing operational costs.
- No Database Required: Operates and not using 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 routinely construct 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 give attention to more complex and sensitive requests, which is more mentally rewarding.
When a question escalates to a customer support representative, Zingtree delivers the correct answers and suggests the following best actions. Reps need not toggle through multiple apps and put customers on hold to go looking for resolutions. With its highly customizable workflows, the platform guides agents step-by-step through interactions, allowing them to quickly retrieve information and cling to policies.
What are some common myths and concerns you’ve got encountered about integrating AI into customer experience (CX), and the way does Zingtree address them?
Certainly one of the most important myths is the assumption that generative AI and chatbots can solve all CX problems. Gen AI has enormous potential, but enterprises must first construct a sturdy underlying motion framework. Which 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 specified results and will even generate surprise scenarios. For instance, without the correct 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 is inconceivable. Many complex and sensitive customer issues require critical considering and human empathy, which AI cannot provide. Customers value human connection, and sticking them with an limitless loop of AI answers creates frustration and poor experiences. Corporations should all the time provide a direct technique to reach a human, no matter how advanced AI becomes.
Are you able to share strategies for seamlessly integrating AI into existing customer support workflows to maximise impact without disrupting current operations?
You’ll be able to’t just implement AI and let it run. The technology requires clearly established guardrails to make sure it operates inside company rules and performs as expected. Businesses must construct a comprehensive, integrated system able to 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 firms firmly establish this technique, they will more effectively layer AI into their operations.
As with most recent processes, start small. Implement technology in a simple 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 the way does Zingtree navigate these while ensuring compliance?
Many AI systems are opaque. Users cannot audit decisions to grasp the reasoning behind recommendations. Algorithms may amplify data bias or compromise privacy, but there is no technique to tell. The shortage of auditability makes it inconceivable to prove compliance with regulations and introduces risk for patients and consumers.
The Zingtree platform offers complete transparency, providing you with full control of your workflows. It ingests your knowledge articles, tickets and transcripts to routinely construct and populate workflows right into a no-code authoring experience. With the assistance of AI Co-pilot, humans finish the last ten to twenty percent to make sure compliance and guidelines.
Balancing AI automation with the human touch is crucial for customer satisfaction. Could you share suggestions for achieving this balance and examples of how Zingtree has successfully implemented it?
Corporations must discover which tasks make sense to automate. For instance, routine queries reminiscent of appointment scheduling, merchandise returns or troubleshooting might be completed with automation. Humans can handle more complex and sensitive tasks.
AI should empower customer support agents, not replace them. Technology can put information on the agent’s fingertips and guide them through company processes, allowing them to offer more efficient, personalized customer support than AI alone.
The connection between AI and humans must be seamless. Nobody likes giving a chatbot all their information after which having to repeat it once they finally discuss with a human. Develop your systems so each algorithms and folks can access and share mandatory information. Businesses should establish a framework that empowers their stakeholders and agents to oversee AI interactions and step in when mandatory.
What future trends do you are expecting in AI’s role in customer support, and the way is Zingtree preparing to satisfy these evolving demands?
Consumers increasingly expect customized interactions across all channels, making personalized self-service experiences the following frontier of customer support. Corporations can use large language models (LLMs) to grasp 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 an organization’s system and incorporates the user’s context, business policies, permissions, and CRM data to get users the precise answers they need. These results will move beyond just delivering resources to truly generating conversational answers. Zingtree’s CX Motion product combines with CX Answers to empower customers to unravel more issues themselves and provides agents with contextual data to discover the next-best motion based on the person and the query.
Could you highlight how firms like Pearson, Groupon and Fleetcor have leveraged Zingtree to reinforce their customer experience?
Zingtree helped Pearson manage customer support challenges created by their complex processes, varied product portfolio and diverse customer base. Pearson’s team built decision trees for his or her most complex workflows without training. In the course of the first eight months of implementation, Pearson achieved:
- 60% increase in Net Promoter Rating (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 support operations. Zingtree has turn into a one-stop shop for Groupon’s agents, empowering higher service and faster resolutions. Groupon also built QA reports to offer detailed insights into customer support agents’ performance to pinpoint improvement opportunities. Zingtree has enabled Groupon to standardize processes across its global footprint.
Fleetcor used Zingtree to scale back agent ramp time from 12 weeks to 3 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 make sure data privacy and security?
Zingtree’s ability to unify all a company’s data allows it to include users’ context, permissions and CRM data to supply relevant and dynamically adjusted results that cater to individual user nuances. Agents and chatbots can access the up-to-date data and resources they should help resolve queries.
Zingtree builds its platforms with data security in mind. We adhere to SOC2, HIPAA, GDPR, CCPA, and plenty of other regulations.
Finally, for firms trying to adopt AI-enabled CX solutions, what initial steps do you recommend to make sure a smooth implementation and immediate impact on customer satisfaction and agent productivity?
The primary priority is clearly defining your goals and objectives. Should you do not know what you wish AI to perform, it may disrupt your workflow and create recent challenges. Set clear goals to measure progress. You will need to also educate and train your employees on the brand new processes and technology.
Start small. Implement the answer in a single basic workflow or process, reminiscent of automating appointment scheduling. You’ll be able to optimize performance and deliver tangible results to secure stakeholder buy-in. This incremental approach also helps employees understand and acclimate to the changes. You’ll be able to slowly add the technology to more complex and involved tasks.
The most important thing to recollect about adopting an AI platform: It needs supervision. Probably the most effective implementation approach is constructing a sturdy system of motion. In case your foundational processes are sound, AI will augment functionality moderately than break it.
