A Practical Guide to AI for Marketers

A Practical Guide to AI for Marketers


Casey Carey became interested in technologies for marketing when he worked at Customer Insight Company. It was the first company that decided to install a marketing database on a personal computer. Then he gained experience in sales promotion in the field of B2B and e-commerce in leadership positions in such companies as DoubleClick, Epsilon, Webtrends, Adometry. His last employer was Google, where he headed the promotion department of an advertising platform for business. In the blog of Marketo, he shared his vision of how artificial intelligence can be useful to marketers.


Marketers are still just beginning to change the usual ways of planning, conducting and evaluating campaigns through the use of artificial intelligence (AI) technologies. At the same time, customers, having already settled into the digital world, expect more personalized and complex interaction from companies. Artificial intelligence comes to the aid of marketing managers who strive to give customers what they want. Artificial intelligence can become a critical factor that increases the conversion rate and profitability of marketing. This applies to a variety of solutions: from chatbots that give personalized recommendations based on the analysis of previous consumer behavior, to intelligent systems that analyze a lot of data and help make more accurate decisions.


But against the background of the hype that now surrounds AI, disappointments are inevitable. This is a very common phenomenon: when too much is expected from a new technology, but in the end it is not possible to get what you wanted. Illusions are dispelled and replaced by skepticism. The research company Gartner in its model called Hype Cycle (“hype cycle”) this is what he calls this stage: “the pit of destroyed illusions”.


Errors, such as data leaks and incorrect personalization, can also alienate potential customers.


Let’s look at the areas in which AI helps marketers in their work.


It’s not about technology, it’s about strategy


The complexity of the tools, the need to write code and the endless stream of technical jargon around AI can frighten those who do not have a computer science education and experience working with data. But marketers do not need to know the specific algorithms that are used in AI solutions. It is quite simple to understand how AI can be used to achieve strategic results and how this technology helps to improve business performance.


Having understood what benefits these tools can bring to business, marketers can confidently choose, purchase and deploy the necessary solutions, work with teams of data scientists to improve the work of algorithms. That is, for a marketing manager, working with AI means identifying problems that contain great opportunities, and not creating solutions.


Using AI in marketing 101


Marketing in the modern world can be reduced to five main steps, each of which is useful for AI.

1. Audience


AI helps to better understand customers and be more adept at dealing with them, more accurately segment and select an audience. One common example is the analysis of billions of data points using AI to predict audience similarity, that is, to identify consumers whose characteristics are similar to those of existing customers. Armed with tools for analyzing data on previous consumer experiences, you can more accurately identify target audiences and make individual offers that are more likely to cause a response from potential customers.

2. Message


Customers want companies to have a deep understanding of their needs, so that interaction with them is adequate and exciting. AI, thanks to machine learning, is able to select and deliver content so that it has more value for potential customers. Moreover, it can take into account the design, format and essence of the proposals. Campaigns that use personalized messages created based on the analysis of past consumer behavior and what they chose before always cause a favorable response.

3. Channels


Channels are not just places where you distribute content. These are a kind of living organisms that can give unexpected results. The same message in the same channel can be received by the audience in different ways depending on the time and context. AI helps to determine the best time and place to engage potential customers, choosing them based on an analysis of past channel performance indicators and information about the audience.


4. Analysis


The intelligent platform can track the performance and determine the results of the entire set of marketing tools. This feedback allows you to quickly determine what is working and what is not, and change the settings so as to increase productivity and get a higher return on investment (ROI).

5. Optimization


AI constantly monitors campaign success rates and changing trends, helping to improve productivity and efficiency, both at the current time and in the long term. “Smart” algorithms analyze huge amounts of information collected over a significant period, learn from this historical data and give hints to marketers for making more accurate decisions quickly.


4 areas of strategic application:


1. Identify opportunities for using AI


Instead of trying to understand how the technologies underlying AI work, experienced marketers should focus on finding opportunities for their application. A” red flag ” for efficiency is any data that is not yet used for finding insights and making decisions. AI helps to cope with this task. The more complex your data set is, the more difficult it is to manually extrapolate the conclusions obtained from it. So, if you caught yourself thinking: “To understand how to use all this data,” try using AI.


2. Automate manual labor


Marketers need to constantly think about what they should do in the next step, and what they should not do. What if it would be possible to automate the process of making such decisions by analyzing historical data? If you use AI to automate manual operations or perform sequences of actions that are performed according to predefined rules, you can significantly increase productivity and reduce the number of errors that inevitably accompany manual processes. AI allows you to test every combination of parameters and options for publishing content to identify the ideal option and optimize it over time when conditions change.


3. Predict future behavior


AI allows you to predict user behavior and predict important indicators, such as conversion and customer value, throughout its lifecycle, and at the same time helps to provide customers with more personalized services. For example, the Marketo ContentAI product based on machine learning analyzes the past behavior of customers and helps them choose the most interesting content for them. The system can even predict in real time the 10 most interesting posts for a certain audience. The more the client is involved in interaction with the company, the more “smart” and personalized the technology becomes.


4. Know when to say “no”


Despite all the benefits that the strategic use of AI can bring, there are areas where these technologies do not make sense yet: where there is not enough data. No matter how good the model is, it will work inaccurately if there is not enough heterogeneous information for analysis to test all sorts of results of certain actions. AI is an artificial intelligence. It is as good as the data that is “fed”to it is good.


AI is an incredibly powerful tool for increasing the level of customer engagement. Armed with effective insights revealed through data analysis, companies can optimize internal operations and at the same time interact with customers more meaningfully. After all, isn’t that the most important thing?

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