The AI Framework for Rapid Mobile Growth

AI and Machine learning have today become a buzzword in our technologically advanced worlds. But how do they fit into a startup? What are some uses of AI? And have we confused AI and its benefits? 

Lomit Patel, VP Growth at IMVU, is also the author of “Lean AI.” His book shares insights for startups to integrate better AI practices. 

How Does AI Fit into Strategy? 

When it comes to growth, it’s always about the business.  These growth targets are set based on preempted goals. These can be factors like customer satisfaction, retention, or even revenue. 

One of the critical factors to constant growth is keeping an air-tight funnel. This change is possible with accurate A/B testing and reworking the methods for the best results. To enhance this process, the use of AI is very effective. 

In today’s day and age, we have more data than ever before. It’s hard to process this data correctly with just human calculations and tabulations. But using AI, you can process the correct information faster, smarter, and leaner. 

Also, if you do not use AI, you limit the number of tests you run each month. Most brands pick a handful of headings and channels to test weekly. “With AI, you do not need to prioritise; you can run all the tests you want all the time,” says Lomit. 

This also enables you to get the best result out of every test and helps your business grow faster. AI is not a tool that replaces human work; it’s just used to help them work more quickly than before. 

Mobile Growth with AI 

We can break down mobile-device growth into two classifications: 

Firstly, How can you use your user accusations budget adequately? Most brands have a decent budget for UA and find it hard to fragment them into investment channels. The challenge is finding the balance between spending and goals. 

Using AI can help you spend that money more effectively. They analyse all the avenues available for the business and generate the best possible outcome for your funds. This way, the UA budget provides the highest returns. 

Secondly, it balances out the research constraints of a business. “They allow you to do less with more resources,” explains Lomit. This change is in terms of the team size, running tests, managing campaigns, and much more. All of this, on a smaller budget and with fewer people. 

Misconceptions Of AI

If you are unaware of the AI market, there are many sceptics about this technology. Some misinterpret the role of AI in growth. Some of the prominent confusions are the difference between machine learning and AI. Smaller companies remain unaware of where they should invest in AI and what precisely the applications are. It’s essential to know more about the tech before they completely discredit its use. 

According to Lomit Patel, the biggest misconception is “the unknown.” There are multiple stories about AI impacting jobs or how the inaccurate results. In all of the noise, the real purpose of AI remains lost. 

The best way to adapt AI for your business is with defined use-cases. For example, if you are looking to achieve a particular goal and know that AI would be effective, it would help you get better results. “Think of the immediate low-hanging wins you can get,” Lomit explains. 

The other confusion people have is “Build Vs. Buy.” There are so many great platforms that offer AI. So, at the starting stages of a business, brands should leverage what exists. Once they notice visible results or find it feasible to build,  then you can develop in-house if needed.

Building an AI Framework for Startups 

Using AI for a startup needs methodical planning and smaller steps in the right direction.  

The first step is always the accurate integration of data. The data gathered from the users must be segmented and placed into usable formats to draw meaningful results. The data cannot remain in silos or abrupt stores. Step one is optimising the cloud of data into significant structures and a unified view. 

As Lomit said multiple times in our conversation: “Bad data will lead to bad outcomes.” 

As a provider of AI service, the aim is to use the data wisely and provide the companies with the best results. Some of the inputs to consider are bids, budgets, creatives, goals, and strategies. These numbers run through an AI program to derive outputs. 

The end goal is to optimise cost per acquisition and return on Ad-spends. Other outputs that help most startups are audience insights and creative insights.  The AIs have the power to work with a bulk of the data, cherry-pick what it needs and ignore the noise. 

For a company, it’s easier to use these tools to determine what processes work and what do not.

Retention With AI 

“It does not matter how many people you bring to the app if you have a leaky bucket,” says Lomit. Retention is one of the most critical ways to improve growth. 

A brand can use AI tools to determine the optimal user journey towards becoming a lifetime consumer. The first seven days spent by the user on the app will evaluate their retention on it. The use of AI tools can better streamline the process. 

Lomit gives the example of their work at IMVU, the social app based on Avatars. The first action is pushing the users to make an avatar. After which we move them to make friends, and later socialising

The aim is to use patterns and behaviour to loop them back into the app. 

Final Thoughts, 

Today we are living in a new decade of technology. Using tools of the last generation cannot be the way forward. Companies that can pivot into AI will be way ahead of those who fail to do so.  

Today this AI is all around us. For example, a newspaper app uses AI to check what categories the user reads more. This will encourage them to provide customised news and retain users. Or push notifications based on the user activity for better results. 

A hesitant brand should know that it will continue to learn more as the tech grows. But not making the shift is asking to fail.