How tribal nations can overcome data and AI challenges to enhance customer experience
The rise of AI and generative AI offers tribal enterprises transformative potential. When combined with search and analytics, these technologies can enhance marketing campaigns, boost customer spending and loyalty, optimize IT development efforts, and accelerate root cause analysis.
Below, we explore some of the challenges that come with these technologies and how Elastic’s search-powered and AI-driven platform can help tribal resorts, casinos, and entertainment businesses increase customer satisfaction.
Key data and AI challenges for tribal resorts and casinos
1. Incomplete customer data
When there are gaps in customer data, tribal casinos and resorts miss chances to boost revenue, personalize outreach, and predict customer needs. For example, not tracking a guest's preferences or frequent activities can result in missed upsell or cross-promotion opportunities. If a customer shows interest in specific games or amenities, the resort should use that data to offer personalized deals, upgrades, or exclusive services.
AI tools help fill these gaps by using predictive analytics to analyze behavior and forecast needs. The Elastic Search AI Platform aggregates data from many different sources, helping tribal businesses build complete customer profiles for personalized marketing and services.
2. Data silos
Tribal casinos and resorts often rely on multiple platforms — with different data types — that don’t communicate. These data silos can distort customer insights and waste IT resources on manual reconciliation. The Elastic Search AI Platform can ingest any data type, from any location, as well as normalize it for holistic querying and analysis. This unified approach provides a 360-degree view of the customer, enabling better decision-making, personalization, and experiences.
4. Smaller IT teams and budget
For medium to large businesses, cybersecurity requires a budget, adequate staff, and appropriate tools to protect and defend against cyber attacks. These tools include a security information and event management (SIEM) solution to analyze logs from devices in their environment. But for small businesses like smaller tribes, having access to effective security analytics can come at a high cost of either time or money.
Leveraging Elastic’s AI capabilities like the Elastic AI Assistant and Attack Discovery helps to strategically augment analysts’ capabilities, filtering out the noise, prioritizing attacks over alerts, and focusing the most critical customer-facing issues. These capabilities enable smaller teams to do more with less.
Revolutionizing customer experiences with generative AI
Elastic provides several key capabilities to help organizations adopt generative AI while safeguarding private data and minimizing the risk of AI hallucinations caused by false or inaccurate data:
Resolve issues quickly
Customer support can quickly retrieve documentation applicable to a customer service request, without knowing exactly what the search needs to be. Get relevant information quicker, saving employees’ and customers’ time.
Get answers faster
Rather than getting a list of results, customers can get that one answer they’re looking for. Need the nearest casinos having any event next Friday? Get one result that fits that criteria without being bothered by other results.
Empower your team with the right information
Deploy advanced chatbots and virtual assistants that can find relevant, timely information. Your team doesn’t want their search to result in a PDF they then need to search through. They want an excerpt from that PDF that tells them the exact answer they were looking for.
Hybrid AI approach
Generative AI with enterprise data: Elastic enables organizations to combine generative AI with their own enterprise data, rather than relying solely on public data sources, which may be prone to inaccuracies. By using high-quality, curated internal data, organizations can reduce the risk of hallucinations in AI outputs.
- Human-in-the-loop: Elastic’s workflow capabilities can integrate human review and validation into AI-driven processes. This ensures that outputs from generative AI models can be vetted by humans, reducing the risk of inaccurate or false results being acted upon.
Reducing AI hallucinations
Data provenance and confidence scoring: Elastic enables the tracking of data provenance, ensuring that AI models are using high-confidence, verified data sources. This can help prevent hallucinations by minimizing the use of unverified or inaccurate data in training or query responses.
- Pre-built model libraries: Elastic provides prebuilt models that are already optimized for accuracy, reducing the need to create AI models from scratch. By using trusted, tested models, organizations can reduce the risk of poor-quality AI results.
In summary, Elastic helps organizations adopt generative AI safely by ensuring data privacy, accuracy, and transparency, while providing governance controls to mitigate the risk of AI hallucinations from inaccurate data sources.
Moving forward
For tribal resorts and casinos, adopting a Search AI platform like Elastic opens new avenues to improve operations and provide exceptional customer experiences. By combining advanced search and AI capabilities, tribal enterprises can drive improvements in consumer analytics, program management, fraud detection, and customer support, ensuring they remain competitive in a rapidly evolving industry.
Explore related resources:
- Ebook: How Search AI is transforming call centers and citizen support
- Guide: An executive’s guide to operationalizing AI
- Root cause analysis with logs: Elastic Observability's anomaly detection and log categorization
Originally published on July 6, 2023; Updated October 2, 2024
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