Today, artificial intelligence, sensors, and digital platforms have already increased the opportunity for learning more effectively—but competing on the rate of learning will become the critical difference between the startups that succeed and those that fail. Companies that embrace AI will be able to test, learn, and iterate much faster, raising the competitive bar for learning.
The benefits will generate a “data flywheel” effect, the idea that more users get you more data, which lets you build better algorithms and ultimately a better product to get more users.
Rinse and repeat—companies that learn faster will have better offerings, attracting more customers and data, further increasing their learning ability. This is similar to the Lean Startup premise, where every startup is in a constant flux of running experiments to create a feedback loop around “build-measure-learn” using data to answer critical questions on whether to preserve or pivot. But when it comes to concrete tasks or goals such as a product release or acquiring new users, all that matters is: do we have a strong hypothesis that will enable us to learn? If so, execute, iterate, and learn. We don’t need the best possible hypothesis. We don’t need the best possible plan. We need to get through the build-measure-learn feedback loop with maximum speed.
The same applies to customer acquisition, where the goal is to leverage AI to speed up the velocity of experiments at different stages of the customer marketing funnel to enable startups to learn or fail fast with minimum impact on cash burn rate. The goal is to figure out how to move new customers further down the funnel faster, powered by AI + data to get smarter by optimizing the right levers.
According to the eMarketer report “Artificial Intelligence for Marketers 2018,” the advent of new algorithms, faster processing, and massive, cloud-based data sets makes it possible for companies in all industries to experiment with AI. Here are the key takeaways from the eMarketer report on AI industry trends for marketers:
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Investment and interest in AI remain high, though large-scale adoption is happening more slowly. Still, many companies have ambitious plans for AI systems and are looking to improve their business operations.
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AI technologies—including machine learning, deep learning, natural language processing, and computer vision—are starting to show real promise, despite significant confusion in the marketplace.
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A robust ecosystem of prepackaged APIs, open source software, and cloud-based platforms is helping accelerate AI adoption, bringing new capabilities to speed up, scale, and personalize marketing campaigns more economically.
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Agencies and consultants are stepping up to the plate, beefing up their technical resources and forging technology partnerships to help their clients navigate the dizzying array of AI and marketing-tech solutions.
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Best practices for marketers include clearly defining business goals, thoroughly understanding the technology, planning for the future, having the correct data, and using AI ethically.
The 2018 AI in Marketing report from BI Intelligence shared insights on the key challenges and opportunities of leveraging AI in marketing:
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The digital marketing industry is already focused on streamlining operations and reducing costs; integrating AI takes it even further. Common uses and applications of AI in digital marketing are cost and ROI analysis for performance advertising on search, social media sentiment analysis, and chatbots for customer service.
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Marketers are increasingly incorporating AI tools into their strategies. Over half (51%) of marketers currently use AI, and an additional 27% are expected to include the technology by 2019. This represents the highest anticipated year-over-year (YoY) growth of any leading technology marketers wish to adopt.
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But the rapid pace of innovation contributes to marketers’ unpreparedness for AI implementation and future use cases. When asked to choose which trending technology they felt most unprepared for, 34% of global marketing executives chose AI, the most of any option, according to Conductor.
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AI is advancing beyond data analysis and moving rapidly into data generation as machines improve at automating two basic human senses: sight and hearing. AI technology has now developed to the point where gleaning insights from data-rich media like voice and video is possible, and humans no longer have to categorize or describe various types of media manually.
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AI will transform marketers from reactive to proactive planners. The enhanced analytics that AI provides will help marketers more efficiently plan and execute campaigns in three main areas: segmentation, tracking, and keyword tagging.
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Programmatic advertising will become more intelligent and more automated. Implementing AI and getting the most valuable insights depends on a reliable, consistent flow of data to train algorithms and help them learn and improve over time. Programmatic ad buying generates billions of data points. Over the next few years, AI will reduce the manual oversight of programmatic ad campaigns and help optimize ad parameters in real-time.
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AI will aid in content creation, but human marketers are still necessary. It’s still early for marketers to use AI to automatically create editorial content or stitch together the right image with the right messaging for display ads. Machines will help cut down on production time, but humans are needed for their creative juices and ability to inform strategy.
Both reports articulate that AI is at a critical point in its evolution.
The future of marketing trends in AI looks exceptionally bright if you can start to figure out how to leverage it to drive more growth in your business entirely. There is no denying that things will get even more exciting with the adoption of 5G to introduce marketers to retail apps that consider foldable displays, better-timed and longer ads, and tighter integration between mobile and store experiences.
As 5G reaches critical mass among consumers in most countries, the user data you can capture across many different touch points daily is limitless. It’s only going to get faster, cheaper, and more extensive. And if you’re not leveraging AI to make sense of all the data at your organization at such a high velocity, you’re likely to be left behind your competition.
The question is this: how will you best leverage AI to give your startup a competitive advantage to take better actions to scale up your user growth efforts to hit your success goals? Today, artificial intelligence, sensors, and digital platforms—and a proliferation of data—have already increased the opportunity for learning more effectively; but competing on the rate of learning is a necessity in the 2020s. The dynamic, uncertain business environment will require startups to focus more on discovery and adaptation rather than only on forecasting and planning.
The startups that move fast to adopt and expand their use of AI will raise the competitive bar for learning. And the benefits will generate a “data flywheel” effect—startups learning faster by attracting more customers and data, further increasing their ability to learn and scale up, growing faster than their competitors. For example, Netflix’s algorithms take in behavioral data from its video streaming platform and automatically provide dynamic, personalized recommendations for each user; this improves the product, keeping more users on the platform for longer and generating more data to further fuel the learning cycle to scale user growth.
AI + Growth Marketing = Smart Marketing
There are many exciting ways you can apply the power of AI and ML to streamline marketing processes across the entire customer marketing funnel to help growth teams work smarter by automating in the following areas to help them stand apart from the competition:
- Segmentation
- Personalization
- Media Buying
- Campaign optimization
- Predicting customer behavior
- Data analysis and reporting
- Customer support
- Better cross-platform attribution
- Fraud prevention
- Creative development and iteration
I’ve found plenty of examples of how AI is transforming growth marketing to allow us to achieve things that would never have been possible without it. With AI, you can work smarter and gain a holistic, real-time view of your customers and their relevant interactions throughout the customer journey.
AI lets you act quickly on your data and makes it easier to focus on the higher-value work by getting fast, actionable insights.
However, while the data to support AI is critical, data is nothing without a clearly defined business problem focused on cost reduction, risk reduction, and profit. Perhaps the most exciting thing about AI is that, while it can automate and do “work” at greater efficiency, it uses machine learning to “think” and “learn” over time, strategizing, designing, recognizing patterns, and making decisions. If that sounds a lot like a human brain, it’s because deep learning, one of the essential machine learning methods, is based on the idea of a neural network, modeling the structure and function of the human brain.
About the Author
Lomit Patel is a forward-thinking leader with 20 years of experience helping startups grow into successful businesses. Lomit has played a critical role in scaling growth at startups, including Roku (IPO), TrustedID (acquired by Equifax), Texture (acquired. by Apple), and IMVU (#2 top grossing gaming app). Lomit is a public speaker, author, and advisor, with numerous accolades and awards throughout his career, including being recognized as a Mobile Hero by Liftoff. Lomit's book Lean AI is part of Eric Ries' best-selling "The Lean Startup" series.