How to make AI marketing initiatives really deliver

CMO in PwC US and an innovative executive at the crossroads of marketing, media and technology.

When it comes to artificial intelligence (AI) in marketing, there’s one big thing I’ve learned: you need to take an “all above” approach. What I mean is that AI can typically help marketers in three ways: improving decision making, systems, and broader transformation. But marketers only address one or two at a time. It’s when you do all three at once that AI can really pay off. This can be difficult (AI It’s difficult), but the results can be magnificent

AI in Marketing

As a CMO who works hard to keep up with the latest developments at MarTech, I see three main ways to use AI. The first is to make better decisions. Trying to decide on channels? How much to invest in a campaign? What demographics to target? AI can ingest the relevant data and produce predictions and analysis to help you make the right choice.

The second way is to let the AI ​​simplify your daily tasks for you or help you do them better. Is your team tired of putting together reports? Let a data AI pipeline do the work, with real-time results and analytics. Are creatives spending time looking for information or just figuring out what they need to do next? Let AI organize your workflow and desktop.

The third way is to bring digital transformation to life. Do you want a marketing function of the future that constantly iterates campaigns as data comes in, forming, dispersing and reforming as challenges arise? You will need AI (backed by cloud and data) to make this happen.

Each of these goals is ambitious. But if you only do one at a time, you will likely lose.

What works

In a recent survey of leaders who are actively working on AI, the biggest conclusion was that companies working on AI in three dimensions at the same time (improved decision making, systems modernization and business transformation) are much more likely to get results. of valuable business.

Typically, marketers don’t do this. It is common to use AI to modernize marketing systems such as online recommendations and AI-powered chatbots. A recent survey also found that marketers expect the use of AI or machine learning for prediction and measurement (which would support better decisions) to triple in the next three years. But putting it all together is rare. Even among digital marketing leaders, only 17% are using AI across the board.

How can you do that

One of the reasons an all of the above approach works well is scale and synergy. If you have AI chatbots and online recommendations, for example, they will produce consumer data that another AI model could use to help you make decisions. Another reason is that an all of the above approach forces technology teams to work with you. Don’t get me wrong, I love my firm’s technicians. But collaboration is essential to confirm that the tools are valuable and understandable.

Your CEO probably doesn’t call you for AI advice. But actually, there’s a lot you can do as a marketer to get the lead they need and help the entire organization.

1. Start with the results. Don’t start by identifying a great AI tool thinking you’ll figure out how to use it later. Instead, start with the outcome you want – say, more power to predict and measure the impact of a campaign – and then assess how AI and other MarTech technologies can help. This approach will help you and IT look at all the ways AI can help deliver the goods.

2. Make connections. As a marketer, you are used to approaching different audiences. Drive that talent inward, working to align business and IT around your project. If your executives see the value of your project (which they will likely see if it supports better decision making, modernized systems, and digital transformation), your chances of success increase.

3. Improve skills and get involved. Many initiatives fail for lack of adoption. New AI-powered data analytics can lead to better decisions and a data-driven marketing function only if people actually learn and use them. Emphasize not only training, but ways to make training and use attractive.

4. Uphold accountability. As a marketer, you are a brand steward. Insist on processes for evaluating AI models for explainability, robustness, bias, fairness, and transparency. There’s no point in having AI if it doesn’t produce accurate results – or if it leads to bias issues or privacy violations.

AI isn’t easy, but if you take the right approach, you can increase the odds that one of the biggest investments the marketing function can make will be a resounding success.


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