Proven Patterns to Start Your AI Journey

Pattern 1: Content Production

Problem: Marketing teams often struggle to consistently produce new and engaging content.

Solution: AI tools create effective drafts that are aligned to customer needs as well as repurpose engaging content for different platforms.

Pattern 2: Website & E-Mail Optimization

Problem: Keeping websites and emails optimized for user engagement and conversion is an ongoing, expensive challenge.

Solution: AI can check and overhaul your materials for common best practices as well as optimize according to your specific analytics.

Pattern 3: Sales support

Problem: No salesperson ever likes to fill in the CRM.

Solution: Let AI listen to sales calls and extract relevant info to pre-fill your CRM. After the call, the salesperson checks, submits, and is done!

Pattern 4: Customer Segmentation

Problem: Personalized communication performs much better, but is hard.

Solution: AI can help you create both the segmentation as well as the content adaption needed for these segments

Pattern 5: Ticket Prioritization

Problem: There’s never enough staff to help everyone right away.

Solution: Use AI to prioritize incoming emails and service tickets based on urgency, customer history or other criteria.

Pattern 6: First-level support chatbots

Problem: Same as above. Support staff should focus on the tricky cases.

Solution: Use interactive chatbots so customers can get first-level support on their own without talking to a human.

Pattern 7: Knowledge Bases

Problem: KB’s are great for self-service, but expensive to maintain. Also, they’re too often hard to navigate.

Solution: Keep your KB up to date by generating articles from selected support conversations. Then, use your KB to power your chatbots.

Pattern 8: Voice bots

Problem: Some customers will always prefer phone support.

Solution: Combine existing voice bot technology with modern language understanding capabilities to cut costs and improve user experience.

Pattern 9: Forecasting

Problem: Forecasting is hard.

Solution: Try different forecasting methods automatically, and pick the one that works best with AI. Use AI to create more data for better results.

AI Involved: AutoML, Generative AI

Pattern 10: Workflow Augmentation

Problem: Data-driven decisions should happen anywhere in the business, but most business users don’t want to be a data analyst.

Solution: Use AI to suggest relevant data points as needed, directly in the workflows that users are in.

AI Involved: Generative AI, AutoML

Pattern 11: Automated Data Analysis

Problem: Lots of data sources could easily be analyzed, but the analytics team doesn’t have capacity to do it.

Solution:AI writes code to quickly analyze large volumes of data in simple structures (log files, events, transactional datasets).

AI Involved: Generative AI

Pattern 12: Data Cleaning & Preparation

Problem: Incoming data is often messy and error-prone.

Solution: AI can document, detect, and enforce data governance rules during data collection and help fix obvious data errors.

AI Involved: Generative AI, NLP

Pattern 13: Domain Expert Chatbots

Problem: People need to know something, but don't know who is responsible, or the expert is unavailable.

Solution: Train AI chatbots for various export domains in your company which operate at scale 24/7 (e.g. Branding Bot, Pricing Bot, HR Bot, etc.)

Pattern 14: Process automation

Problem: A lot of business processes already follow a predefined path, but can't be automated because information is missing.

Solution: Use AI to label and categorize business objects for easier workflow automation.

Pattern 15: Process documentation

Problem: Lots of businesses lack clear process definitions and business process diagrams.

Solution: Create process documentation from historic artifacts like emails and help maintain the process library.

Pattern 16: Document processing

Problem: PDF and other documents are still essential for many business operations, but working with them at scale is hard.

Solution: Use AI to ‘look’ at the documents and extract relevant info to power downstream workflows and processes.

Pattern 17: Product Delivery

Problem: Tracking and planning product delivery is a complex, costly process.

Solution: Use AI to manage, forecast and improve your product backlog and improve agile delivery projects with simple interfaces.

Pattern 18: Product Strategy

Problem: Keeping your product strategy to market trends and customer expectations is hard.

Solution: Use AI to detect trends, support with customer research, do strategy design and write presentations to communicate your goals.

Pattern 19: Product Innovation

Problem: Bringing new products to market is incredibly hard due to uncertainties in market demands and the fast-paced nature of technology.

Solution: AI helps you analyze market trends, customer feedback, and competitive landscapes, allowing you to spot gaps and anticipate needs.

Pattern 20: Product Improvement

Problem: Focusing on the right features to ship is hard because customer needs change quickly and the market is often ultra competitive.

Solution: Listen to what your customers say at scale and let AI make suggestions for the most requested features improvements.

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