How to use Machine learning and AI in your app to attract more users?
January 29, 2020
In the next two years, the number of businesses implementing machine learning (ML) and artificial intelligence (AI) will double. Currently, market research shows that businesses using ML and AI are receiving funding more easily than the ones that are not.
Are you too traditional when it comes to developing and deploying apps? Then you must be missing out considerably on new customer acquisition, and retention in comparison to your rivals. More than 40% of all US companies are using ML and AI to upgrade their marketing and sales.
Here’s how you can implement AI and ML in your app too –
1. Find out what AI and ML can do for your app
AI and ML are taking over the world, but what benefits can the duo bring to your brand? Understanding the role they can play in your app development can be challenging. Here’s what you can do –
- Check the existing technologies and tools to gain an understanding of their capabilities and their potential contribution to your project.
- Consider the case studies in your segment to understand the proper way to implement the intelligence algorithms in your app.
- Consult AI experts and ML consultants to find out innovative ways to integrate intelligence algorithms in your work.
2. Determine where can AI and ML enhance your app
Do you want to integrate AI just because your rivals are doing it, or do you have specific challenges in mind that AI and ML can solve?
You should explore the list of capabilities and a list of different ways in which AI and ML can enhance your application. Perform market analysis, mock deployment and record the results of A/B tests for the app.
Focus on identifying the problems and potential implementation of AI and ML before you begin redirecting your resources.
- Estimate the feasible changes you can make
Begin with a feasibility test. It will help you estimate the benefits any future implementation of ML and AI can bring to your app.
Check if you can improve the UX of your app after the implementations.
See if you have the skillset in your team, necessary for the implementation of the intelligence algorithms.
In case you don’t have the internal capability, think about outsourcing or hiring new talent.
3. Involve experts for the development and upgradation
Once you have recognized the challenges, areas of AI-ML integration and the potential improvements in your app it is time to involve the AI-ML experts.
Choosing the right experts is the most crucial step since they will not only help with the development and deployment, but they will also revisit your market research, potential solutions and troubleshoot the challenges your team has been facing for the past few weeks/months.
Artificial intelligence and machine learning need to be integral parts of your app development if you want to provide personalized customer experience and cutting-edge services.
The integration of ML and AI is not as easy as adding a layer of new technology to an existing model. It involves the complete overhaul of the data organization model, complete planning and pre-deployment, and robust support in terms of security tools, backup, data storage, and cloud solutions.