AI + Growth Marketing = Smart Marketing: Lean AI

Customer Acquisition 3.0

mediumThis post was originally published by O'Reilly Media at Medium [AI]

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 ways that 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 entire 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 interesting 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 most important methods of machine learning, is based on the idea of a neural network, modeling the structure and function of the human brain.

With ambitions to launch self-driving cars to the public in 2020, Tesla gets a lot of attention in the autonomous vehicle industry. But big automobile companies, startups, and tech giants are all working to deliver safe, self-driving vehicles to the masses.

To make sense of where artificial intelligence and automation is at and where it’s going, the industry trade association the Society of Automobile Engineers (SAE) introduced its autonomy scale. It helps the industry determine and classify different levels of autonomous capabilities for vehicles.

Level 0: No automation. The driver controls steering and speed (both acceleration and deceleration) at all times, with no assistance at all. This includes systems that only provide warnings to the driver without taking any action.

Level 1: Limited driver assistance. This includes systems that can control steering and acceleration/deceleration under specific circumstances, but not both at the same time.

Level 2: Driver-assist systems that control both steering and acceleration/deceleration. These systems shift some of the workload away from the human driver, but still require that person to be attentive at all times.

Level 3: Vehicles that can drive themselves in certain situations, such as in traffic on divided highways. When in autonomous mode, human intervention is not needed. But a human driver must be ready to take over when the vehicle encounters a situation that exceeds its limits.

Level 4 :Vehicles that can drive themselves most of the time, but may need a human driver to take over in certain situations.

Level 5: Fully autonomous. Level 5 vehicles can drive themselves at all times, under all circumstances. They have no need for manual controls.

I propose a similar scale for the purpose of evaluating autonomous marketing and marketing automation solutions.

Level 0: No automation. Marketers manage all tasks with basic tools and CRM systems that provide no real automation, but act as storage repositories for marketing data and results reporting (dashboards or “business intelligence” systems).

Level 1: Recommendation automation. Marketers leverage systems capable of following business rules (defined by the marketer) to make business recommendations for optimizing marketing outcomes. Examples include dashboards with recommendation systems for adjusting marketing spend by channel. The user must take the final step of making the recommended adjustments.

Level 2: Rules-based automation. Building on business rules set by marketers in Level 1, Level 2 rules-based automation goes the next step and adjusts marketing campaigns automatically (generally via an application or API) without user intervention or approval. Such systems rely on the user to create the rules. Dynamic market conditions shift on a daily, hourly, or even minute-by-minute basis; rules-based systems are rigid and not very flexible to adapt to market changes.

Level 3: Computational autonomy. Systems that use machine learning to observe, learn, and improve outcomes based on statistical analysis combined with marketing automation. No intervention is required by the user, apart from setting goals or broad-based parameters such as campaign dates or geographies for digital campaigns.

Level 4: Insightful autonomy. Systems that understand the contextual meaning of user interactions, content, behavior, performance data, and more to personalize 1:1 marketing messages across various channels and drive optimal performance for operators.

Level 5: Fully autonomous. Level 5 systems build insightful autonomy capabilities but generate their own unsupervised tests, creative variations, targeting parameters, and more with no ongoing intervention from the marketing team.

Most growth 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 is to advance from Level 2 to Level 5, to completely reap the benefits of the full superpowers of artificial intelligence to scale up your efforts into the world of Customer Acquisition 3.0.

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This post was originally published by O'Reilly Media at Medium [AI]

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