The amount of information required to personalize, optimize, and ultimately automate marketing communications is overwhelming. Yet within that enormity lies the granularity to understand the variability that enables personalization for each consumer. Hiring more data scientists who can handle the snowballing data avalanche is an unsustainable arms race.

AI is the key.

Without the support of AI/ML tools, we cannot navigate through this endless pool of data. We interviewed former Fortune 50 CMO, Harvard Business School professor, executive adviser to him, and AI marketing expert David Edelman. Edelman shares the following insights on the most pressing issues for marketers looking to incorporate AI into their digital marketing strategy:

• How marketers navigate the plethora of AI solutions available
• How AI can help brands deliver superior customer experiences
• Why AI can bridge the online and offline data gap and enable attribution

Q: How can brands navigate the plethora of AI solutions available?

David: “Today, AI is being used to bring fragmented channels together by creating a unified picture of the customer journey. Even if you don’t have one, you can create an identity map that can link information about your customers across your systems, and in doing so, AI can help marketers in four key areas.

1. analysis: Simply put, what is going on? AI analytics understand where your customers are on their journeys and what these journeys contain to derive attribution. For example, it helps marketers understand what is driving up costs.
2. automation: Now there is an AI tool from a company called Stanley.ai that allows you to create 100 variations of a particular email you want to send, test these variations, and tag them. Large marketers are starting to use these tools instead of wasting their creative energy on manual work. This is an example of automation. Of course, there are many others.
3. Personalization: What is the best outreach and message for each customer? It’s a matter of constantly testing, experimenting, and finding the right mix of creativity, timing, and channels. Based on these small tests, you can learn and use it to personalize what you send to a wider group. cannot be achieved. For example, a company called OfferFit has tools that can fully set up all test cells, know which personalizations work for whom, and send the right message to the right person at the right time. Offer the right incentives for each person and ride the demand curve in the best way to engage.
4. optimisation: All of these systems learn over time from what is happening continuously about customer behavior. Based on these learnings, they are constantly updating their models.

Consolidation should also be considered. None of these tools are fully functional and can do everything right out of the box. All of these AI tools need to be integrated into the environment. Because these AI tools take data, do something with that data, and often feed the data back to execution or reporting tools. ”

Q: How can brands use AI to manage the customer journey?

David: “Marketers can use AI to compile vast amounts of data into customer journeys and make predictive decisions. An example of a provider that can do this is Pointillist. is used in two ways to provide customer journey analytics.

1. Matchmaking: Filter a company’s channel database to piece together each customer’s journey. It timestamps the data and provides insight into the full longitude of the customer’s journey.
2. Detect patterns and anomalies: Shows the most common trajectories of customer journeys and where variations in journeys occur. For example, suppose a company experiences a spike in calls to its call center. A customer journey analysis found that the user who made the call had just used the Android version of the app within 15 minutes of making the call and was about to pay. This allowed us to see bugs in real time and make changes.

A system like this used upstream and in the customer journey can bring all the information together. Whether it’s an issue that needs to be fixed or a customer needs to be contacted, these AI-based tools allow marketers to manage their customer’s journey on a micro and macro level. ”

Q: How does it help brands personalize post cookies?

David: “Thanks to AI, we are now able to create a better identity graph. You can feel the journey you have made more richly.

For example, if you’re sending a simple email, you’ll need to list a few variables such as photo background, font, font color, word spacing, etc. You need to know when the customer responded, what time did they respond, did they click once, did they click again, and how long were they on screen?

Personalization is all about variation. The more data you can create or match, the more variations you have and the more tags you can tag. You can then model future interactions with your customers. The previous environment of basic cookies did not provide this functionality and data. Now you have more detailed data and much more powerful weapons to personalize. ”

Q: Why is it an important part of the marketing attribution formula?

David: “Marketers have always struggled with finding the data links to close the loop and connect channels (online and offline). There are often, but it’s only relevant to a specific range of industries, and adoption isn’t necessarily high unless you’re handing out money with loyalty cards to get people to use it.

Another thing to consider is the decision timeline. Many steps may be required, especially for high-end products. B2B products, buying cars, buying appliances for kitchen redevelopment. They all take time. So how long should that lag time be in measurement and attribution? What other impacts are there in the process? Longitudinal performance is difficult to understand.

So with all the digital developments of the last 20 years, marketing still has smoke and mirrors. It is not always entirely due. Some techniques can get you closer, but you can’t close the loop completely. AI can help you get closer dramatically. ”

Q: What impact could AI have on marketing in the future?

David: “Looking ahead, the thing that excites me the most is innovation. Marketing is still about the emotional connection. You have to find ways to make that connection, find ways to elicit emotions and come up with new ideas. requires humans to be part of it.

The companies I work with that use these tools are changing the way they think about marketing. Instead of having a standard campaign of running simple A/B tests in stages and pushing one improvement, you can now launch 20 new ideas every two weeks.

An amazing personal example happened when I purchased solar panels for my house. We were contacted by a variety of providers, but one stood out from the rest. I received a physical mailing that was personally addressed to my home address.

It had a personalized URL that took me from Google Earth to a site showing my house and showing what it would look like with the solar panels overlaid on it. They used AI to calculate how many panels I could put on my roof and how much power those panels could generate depending on the angle of my house and its tree cover. Did. Using Zillow, they were able to get data on the square footage of my house and estimate the amount of energy I used. Using these real-time calculations, they told me how much I could save.

This is the future of AI. This empowers marketers to innovate and create more impactful personalization than we can imagine. ”

As CMO, David Edelman, a sought-after advisor on digital transformation and marketing, led Aetna (now part of CVS Health) to grow into a digitally-minded, customer-centric brand. Forbes has repeatedly recognized him as one of the “World’s Most Influential CMOs”, AdWeek has recognized him as one of the “Top 20 Marketing and Technology Executives”, and the LinkedIn blog states that he Has over 1.1 million followers.

David currently teaches marketing at HBS, advising CEOs and CXOs in health and marketing services, with a focus on AI and personalization.