Active AI adoption is a huge trend in 2024. Recently Gartner asked a bunch of C-level executives from big companies with 1000+ employees about AI adoption and use in their organizations. Here are the most interesting insights:
- 62% of respondents believe that AI improves their efficiency.
- 51% of executives emphasize that AI boosts customer experience.
- 53% of respondents think that AI apps will improve their financial performance.
Taking into account these numbers I can say that AI is not just a trend. It’s a necessity for many companies and they are ready to invest in AI-powered apps development.?
Since my team is an expert in product development and AI integration, I decided to share with you a roadmap. It includes core steps that will help you build a high-quality AI-powered app. So. without further ado, let’s delve into it.??
Step 1: Discovery?
If you want to build a customer-centric AI product, you should not skip a discovery stage and market research. Here is what I always recommend doing:
- Opportunity analysis. Identify areas where your AI application can make a significant impact. It helps you understand the potential opportunities for addressing customer needs and pain points effectively.
- Competitive analysis. Study your competitors, examining their products, services, and strategies. This will help you gain insights into what your AI application needs to offer to stand out and provide superior value to customers.
- Industry analysis. Evaluate the industry or market in which your AI application will operate to understand the broader context and trends.
Also, it's crucial to learn about your target customers to ensure that the AI application will resonate with their actual needs.?
Create a comprehensive user persona portrait with the following elements:
- Demographics with age, gender, location, and income level
- Educational background, job, and career path
- Goals and objectives, both in their personal and professional life
- Challenges and pain points
- Specific needs, desires, and preferences
- Behavioral insights, both online and offline
- Motivations to make decisions and take action
- Direct quotes or statements that capture the persona's mindset and attitudes
- Media consumption, including social media platforms, news sources, etc
- Communication style
- Tech savviness
- Expected app features and benefits
- User journey
Then, you should define the specific problem or need your customer-centric AI application will address.
Step 2: Planning?
The planning phase sets the direction and foundation for the entire project. Follow these steps to make your planning effective:
- Create a comprehensive project plan that outlines the scope, timeline, and resource requirements.?
- Define the specific goals and objectives you aim to achieve with the project, ensuring they are customer-centric.
- Prioritize the features and experiences that directly cater to customer needs and preferences.
- Define the KPIs related to customer satisfaction, engagement, and retention.
- Develop a data strategy that outlines how you'll collect, store, and manage the data.?
- Identify the technology stack required for implementing your chosen AI technologies.?
- Allocate the budget and resources. This includes funds for technology, personnel, and any third-party services you might need.
- Identify potential risks impacting the project's success, particularly in meeting customer-centric goals. Develop a risk mitigation plan to address these challenges.
- Address any legal and compliance requirements relevant to your AI application, particularly those related to customer data privacy and usage.
Step 3: Design?
The design phase is crucial in creating an AI application that caters to customer needs and preferences. Here is what you need to do:?
- Design the visual and interactive elements of your AI application to prioritize customer preferences and ease of use.
- Incorporate personalization features like user preferences, historical behavior, and other data points to create a personalized journey.
- Create prototypes or mockups to visualize how the AI application will look and function.
- Design a responsive and intuitive UI that aligns with customer expectations. The interface should be easy to navigate and engage with.
- Conduct usability testing to ensure that the design meets customer-centric goals. Obtain feedback from real users to identify any usability issues and make the necessary adjustments.
- Refine the design based on feedback and insights gathered during usability testing.
- Ensure that the design aligns with the chosen AI technologies and that the user experience is enhanced by these technologies rather than hindered.
- Design with accessibility in mind, considering users with disabilities or special needs.
Step 4: Development?
In the development phase, you turn plans and designs into a functional and customer-centric AI application.?
- Implement AI technologies and algorithms that support customer-centric goals.?
- Create algorithms that allow for personalized recommendations and real-time support. Ensure data privacy and security measures are in place to build customer trust.?
- Deploy the AI models and algorithms that were selected based on the problem definition.?
- Integrate data sources and APIs.
- Seamlessly integrate AI into the user interface or customer touchpoints where it will be used.
- Implement monitoring and analytics tools to track key performance indicators (KPIs) related to customer satisfaction, engagement, and retention.
- Define processes for collecting, storing, and processing customer data.
Step 5: Quality Assurance and Testing
The QA and testing phase is essential as it helps to make sure that your AI application is reliable. By conducting thorough testing, you can identify and address any issues that may hinder the customer experience:
- Rigorously test the AI application to ensure its functionality, usability, performance, and security.
- Test the AI models for accuracy and fairness to avoid bias in recommendations. Ensure that the AI models provide reliable results.
- Gather feedback from real users or test groups during testing to make necessary adjustments.?
- Simulate real-world scenarios to assess how the AI application performs in practical customer interactions.
- Identify and resolve any bugs, errors, or issues discovered during testing.
- Assess the overall usability of the AI application. Is it intuitive, easy to navigate, and engaging for customers?
- Evaluate the performance of the application, including response times and system reliability.
- Ensure that sensitive customer information is protected and the application meets data security standards and regulations.
Step 6: Deployment and maintenance
This is when your AI application goes live. However, your job doesn't end at deployment. You should continuously monitor the performance, particularly in terms of user satisfaction.
It's crucial to maintain an open channel of communication with your customers. You should collect and process their feedback, and be ready to resolve any issues.?
Wrapping Up?
AI is a powerful tech trend that already disrupts many industries. Companies actively adopt it to improve decision making, elevate customer experience, automate repetitive tasks, and provide high-quality services.??
This year my team developed 5 AI-powered apps for different businesses that pursue all aforementioned goals. And I believe this is only the beginning of the AI hype.?
Soon a growing number of companies will implement AI. Some will begin with modernization of their current solutions, others will build new AI-powered platforms from scratch.?
In any case, the AI trend will stay with us for years.?
Ready to embrace it and build your own AI product??
