Council Post: How to Really Deliver AI Marketing Initiatives

CMO PwC American and innovative executives at the crossroads of marketing, media and technology.

There’s a big thing I’ve learned about artificial intelligence (AI) in marketing. You need to take a “top-level” approach. What I mean is that AI can generally help marketers in three ways: improving decisions, systems, and broader transformations. But marketers only do one or two things at a time. AI can really pay off when it does all three at once. It can be difficult (AI is difficult) but the results can be great.

AI in Marketing

As a CMO working hard to keep up with the latest MarTech developments, I see three main ways to use AI: The first is to make better decisions. Are you trying to decide on a channel? How much will you invest in your campaign? What demographics will you target? AI collects relevant data and then generates predictions and analytics to help you make the right choices.

The second way is to enable AI to simplify or better perform routine tasks. Tired of your team writing reports? Let your data AI pipeline take action with real-time results and analytics. Is your creative spending time searching for information or figuring out what to do next? Let AI compose your workflows and desktops.

The third way is to enable digital transformation. Do you want a future marketing function that continuously iterates through campaigns as data comes in, forming, distributing and restructuring as challenges arise? You need AI (cloud and data-enabled) to do this.

Each of these goals is ambitious. But if you only do one at a time, you’ll miss it.

what works

Recently survey The biggest implication for active leaders in AI is that companies that work concurrently with AI in three dimensions (improved decision-making, system modernization, and business transformation) are far more likely to achieve valuable business outcomes.

Typically, marketers do not do this. It is common to use AI to modernize marketing systems, such as AI-based marketing systems. online recommendation And chatbot. lately survey We also found that marketers expect the use of AI or machine learning for prediction and measurement (which supports better decisions) to triple over the next three years. But it’s rare to put them all together. among digital marketing leaders. 17% We are using AI throughout our functions.

how you can

One reason all of the above approaches work so well is their scale and synergy. For example, if you have an AI-powered chatbot and online recommendations, other AI models generate consumer data that can be used to make decisions. Another reason is that all of the above approaches require the technical team to work together. you. do not misunderstand. I love our technicians. However, collaboration is essential to ensure that tools are valuable and understandable.

Your CEO probably won’t call you for AI advice. But in reality, as a marketer, there are many things you can do to get the leadership you need and help your organization as a whole.

1. Start with the results. Don’t start with identifying great AI tools, thinking you’ll know how to use them later. Instead, start with the desired outcome (such as more ability to predict and measure the impact of your campaigns) and then evaluate how AI and other MarTech can help. This approach will help you and IT explore all the ways AI can help deliver goods.

2. Connect. As a marketer, you are used to dealing with a diverse audience. We guide those talents inward as we strive to align business and IT around the project. When management sees the value of a project (and more likely if it supports better decision-making, modernized systems, and digital transformation), the chances of success increase.

3. Skill Enhancement and Engagement. Too many initiatives fail due to lack of adoption. New AI-powered data analytics can only lead to better decision-making and data-driven marketing capabilities if people actually learn and use it. Emphasis is placed on teaching as well as ways to make teaching and use attractive.

4. Take responsibility. As a marketer, you are stewards of the brand. opinion evaluation process AI models for explainability, robustness, bias, fairness and transparency. There is no point in having AI if it doesn’t produce accurate results or leads to bias issues or privacy breaches.

AI isn’t easy, but if you take the right approach, one of the biggest investments a marketing department can make can increase your chances of great success.

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