How to Make the Transition from Data-Driven to AI-Driven Marketing Analytics

Data, we're told, is the key to business success. But how do we convert data into money?

It's a perplexing question for many of today's business leaders, who frequently find themselves drowning in information but struggling to apply it to practical business challenges.

Traditionally, the answers could be found in data analytics and related fields such as business intelligence. We learned how to use operational, customer, and external data sources to answer questions like where to find customers, how to make our products and services appealing to them, and how to keep them returning for more.

Today, however, artificial intelligence (AI) is paving the way to true value. AI has been described by none other than Google CEO Sundar Pichai as the most transformative technology of all time. And it is often in marketing that businesses discover new ways to create value with AI.

AI-Powered Marketing – Difficult and Expensive?

When we use the term artificial intelligence (AI) in business today, we usually mean machine learning (ML) - computer algorithms that get better and better at performing simple (or not-so-simple) tasks as they are exposed to more and more data.

If we are unfamiliar with the technology, it may appear intimidating, complicated, and costly. However, businesses of all sizes are discovering that it is surprisingly easy, simple, and inexpensive to harness its power and begin driving impressive, often transformational results.

Some examples of the way AI is used in marketing today include:

Personalisation: We've always used customer segmentation to create promotions and advertising that are tailored to specific groups, but AI allows us to take this a step further by approaching customers as individuals in a more granular way than ever before.

Chatbots and virtual assistants: Using natural language processing (NLP) technology similar to that used by Apple's Siri or Amazon Alexa, chatbots and virtual assistants provide advice, assistance, and support to customers.

Predictive analytics: Forecasting customer behaviour and market trends in order to identify patterns and clues that tell us where we should focus our marketing spend in order to get the best returns.

Sentiment analysis: AI algorithms can collect data on what your audience and customers are saying about your products, competitors, industries, or just life in general and turn it into insights that help you market more effectively.

Taking The First Steps

The first question any marketer should ask when trying to figure out how this revolutionary technology can help them is, "How can I use it to achieve my marketing goals?"

Signing up new customers (growth); better targeting of customers with personalised marketing and messaging; reducing subscriber drop-out and churn; increasing lifetime value of existing customers; and developing the ability to capitalise on fleeting opportunities to grab attention and convert audiences into customers that are only possible with real-time data are some examples of marketing goals that businesses are currently using AI to achieve.

These are covered in a guide to deploying and leveraging AI in business, recently published by Adobe. Titled Data, Insight, Action: Machine Learning & AI for Marketing Analytics, it also identifies three interconnected systems that need to be in place if an organisation wants to use AI in its marketing operations to turn data into revenue.

These are:

Data System - How can data be unified across multiple channels from where it comes in, so that it is available where, when, and in the form that it is most useful?

Insights System - These are the tools and services we use to extract insights - information that has value, serves a purpose, or can be used - from data.

System of Engagement - How do we apply these insights to achieve the business goals that we identified as critical when developing our AI strategy?

Quick Wins

When first embarking on this journey, it's often best to look for "quick wins" - initiatives that can be implemented quickly and demonstrate the value of AI to an organisation. Improving the open rate of an email campaign by optimising your messaging is a simple example. Another possibility is to reduce customer churn by improving the customer service experience when returning faulty products.

Choosing small, specific goals like these allows you to demonstrate the value of AI to those you need to bring on board.

Tools can handle the automation of critical but time-consuming tasks like data cleansing and preparation - according to Adobe, data scientists spend an average of 45% of their time on data prep. By automating this work, data experts can instead focus on the high-value tasks associated with extracting and applying insights.

Self-Service AI

Analytics and data science in business were once thought to be an arcane art dictated from on high by expensive and highly-trained data scientists.

Those days are long gone; today, self-service, low-code, and no-code functions are available on integrated AI and ML platforms. As a result, analytics can be "democratised" throughout an organisation. With the right system in place, any member of the marketing team can log in and generate reports tailored to their specific needs, containing the information they require to solve their specific problems. After this, teams can begin to identify additional ways that AI and ML can be used to grow the business and collaborate to make them a reality.

Marketing departments have always been early adopters of new data and technology solutions, as well as trailblazers in putting them to use and demonstrating value. With the new generation of AI-powered data-driven tools and platforms that are emerging today, this trend appears to be continuing.

Understanding the key use cases for analytics in marketing and advertising, as well as developing the ability to align this technology with marketing goals, is the first step towards creating real growth and value.

Beyond that, we've only begun to scratch the surface of what AI will mean for business and society as a whole. However, it is clear that today's marketers have the toolset to ensure that they are leading the way in building the AI-driven organisations of the future.