February 3, 2020
By Lomit Patel
Launching and growing any new app has always been a challenging endeavor. Beyond having a great app and hiring a great team, one of the keys to success, is to figure out how you can leverage user acquisition to scale up app growth fast. Increasingly, the answer to smart growth looks like it may lie in AI.
If you are still manually optimizing paid user acquisition campaigns the same way it was done half a decade ago, you may find yourself among a quickly disappearing breed in the customer acquisition game. More than ever, artificial intelligence is being incorporated in one form or another into almost every level of the customer acquisition value chain, from distributing inventory more efficiently to allowing advertisers to scale their decision making. Any manual process is likely much less effective and far more prone to human error than the new solutions quickly emerging to attack inefficiencies.
The secret to app growth is about taking a rational and methodical approach to iterative learning by continuously running user acquisition experiments across different acquisition and retention channels to better acquire, retain, and monetize customers. This means that learning needs to happen faster, because decisions need to be made faster to compete. However, this is a big challenge because there is never an infinite supply of human resources to execute all these experiments. That’s where Lean AI comes in.
Lean AI is an innovative process to scale up app growth significantly faster when you combine a lean team with the judicious use of artificial intelligence and automation. It enables app growth teams to run tens of thousands of simultaneous marketing experiments across all their digital channels with a constant focus on delivering real business value to their organizations—without the overhead of manual processes or intervention—to usher in the new age of Autonomous Marketing. Conducting experiments at scale improves the likelihood of finding successful experiments, some of which you’d never have taken the time to test in a pre-AI world. Incremental experiments that otherwise would have been sidelined for cost or complexity are now valid for observation in the world of autonomous marketing.
The data to support AI is critical. But data is nothing without a clearly defined business problem focused on cost reduction, risk reduction, and profit. Before you can prepare a strategy you’ll need to understand what autonomous marketing is cable of — and what is still just a hope for the future.
There is no shortage of claims in the world of marketing automation — particularly when it comes to artificial intelligence. How can you systematically assess vendors and their claims, and get an accurate sense of the state of the art? We can take a look at how the automobile industry worked to make sense of all the autonomous vehicle technology coming to the market today and use its guide as a roadmap of sorts for the marketing industry. In 2018, the auto industry trade association SAE (Society of Automobile Engineers) introduced its autonomy scale (see below). It helps the industry determine and classify different levels of autonomous capabilities for vehicles for reference:
I propose a similar scale for the purpose of evaluating autonomous marketing and marketing automation solutions for app growth marketers, taking some cues from the SAE folks:
Most growth marketing teams are in the process of figuring out how to reach a level of proficiency to move from Level 0 to Level 2. However, the biggest challenge and opportunity for app marketers is to advance from Level 2 to Level 5, to scale up their growth significantly faster with the judicious use of artificial intelligence and automation in the world of Lean AI.
How can app marketers successfully scale customer acquisition and revenue growth with a lean team to get from Level 2 to Level 5? Out-of-the-box artificial intelligence acquisition solutions from Facebook, Google, and others provide a good start, but the innovative startups that can tailor those solutions to meet their specific needs, objectives, and goals will come out winners.
Sooner rather than later, your customer acquisition efforts will rely on artificial intelligence, machine learning, and automation to adapt, customize, and personalize cross channel user journeys and deliver optimal results in ways that would be impossible using last generation business intelligence and dashboards. Managing complex, cross channel campaigns with multiple targeting, creatives, and sequencing will require an “intelligent machine” operational layer above the out-of-the-box solutions to deliver great results—or settle for being average.
The future of paid user acquisition rests on the shoulder of intelligent machines, orchestrating complex campaigns across key marketing platforms dynamically allocating budgets, pruning creatives, surfacing insights and taking actions autonomously. These machines hold the potential to drive great performance with a far more efficient lean team, hands-off management approach powered by Artificial Intelligence.
Lomit Patel is the Vice President of Growth at IMVU. Prior to IMVU, Lomit managed growth at early-stage startups including Roku (IPO), TrustedID (acquired by Equifax), Texture (acquired. by Apple) and EarthLink. Lomit is a public speaker, author, advisor, and recognized as a Mobile Hero by Liftoff.
Lomit’s new book Lean AI, which is part of Eric Ries' best-selling "The Lean Startup" series, is now available on Amazon. Lomit is also a speaker at MGS20 and will be giving away copies of his new book at his session on a first-come-first-serve basis.
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