As customer expectations continue to evolve, brands need to up their game if they want to surprise and delight. It's time for a fresh approach to meet today's demands. 

Marketers want to connect with customers in a way that wows them – real-time updates to their loyalty points, a coupon delivered via text 10 minutes after they abandoned their cart on a desktop, a snow-day closure alert at the local branch of their megastore – but the technology used to accomplish this often gets in the way.

Perhaps not surprisingly, half of the respondents in a recent survey on consumer expectations by MessageGears said that they are annoyed when brands send generic messages, and over 75% said they will unsubscribe from brands that send too many irrelevant messages. Meanwhile, 87% feel that less than half of the brand marketing messages they get are personalized.

We’ve talked about big data, deep analytics, and fancy marketing technology for years. The concept of using data to drive successful marketing strategies and customer experiences is something businesses – and their customers – take for granted as a table-stakes requirement.

Yet, marketers continue to struggle to leverage all (or even most) of the insights that their brand is collecting about customers. So where’s the disconnect?

Here are three key things that we’re seeing the savviest of consumer marketers do for better customer connections – and that other marketing pros should consider as we move into 2024.

Patrick Reynolds AMA: First-party data priorities and business agility
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1. They don’t just use some of their data – they use all of it.

The biggest consumer brands have millions of customers – and a regularly growing number of data points about each one.

Many marketers only work with a portion of their customer data. They likely begin their campaigns by asking their IT team to pull a handful of fields that they think will be relevant for their campaign (like a last purchase or the state the customer lives in) – and that's all that gets synced into their martech platform.

However, the savviest consumer marketers have realized that they can no longer ignore subsets of their data. The most sophisticated consumer brands utilize every data point to craft exceptional customer experiences that generate tangible business value. For example, on top of pulling data fields like last purchase and state, the best brands have context around the time of day the purchase was made, browser history, purchase channel, customer loyalty, and more to get a much fuller picture of customer data.

With direct access to the full data set, marketers can also automatically send messages to customers on their preferred channel at their preferred time. Within a single campaign, an SMS text promoting a seasonal milkshake can be sent to one customer, while another receives an email with a coupon for a free sandwich, and yet another gets an in-store push notification highlighting a festive new cookie. 

This is one of the fundamental reasons so many enterprises are moving to a data warehouse approach, bringing all data sources into a single place. When marketers have access to all of their customer data, it unlocks endless new opportunities for compelling campaigns and experiences in real time. That’s a sharp contrast to only being able to use certain subsets of your data, which may already be outdated or only capture certain aspects of the customer’s behavior and interactions.

2. They’re using powerful, standalone BI tools.

As martech platforms have matured, some have taken a “Swiss Army Knife” approach to features, rolling up as many tools as possible into a single martech platform – rather than focusing on the individual tools that do the work best. And in some cases, that’s a good approach! In-platform analytics is a great example of where this often falls short, though. The need for a separate data analysis tool can be extremely valuable for enterprise marketing teams.

The experts already understand this – and they’re using standalone BI tools for macro and micro data analytics and visualization. 

These tools were built specifically for that purpose and can integrate with their entire martech stack – or better yet, with their data warehouse. BI tools like Looker or Tableau, for example, give you much more powerful analytics, insights, and visualizations than less robust tools built into some marketing platforms. 

This enables far deeper and more creative insights from your data, which in turn leads to richer marketing strategies and customer experiences that would otherwise be missed.

3. They’re taking segmentation to the next level with AI. 

Everyone – literally, it seems – is talking about artificial intelligence these days. And that excitement is well-founded – the possibilities of a maturing AI ecosystem for marketers are virtually limitless at this point.

Savvy marketers are already looking to leverage AI in practical ways today to unlock greater value from their data and their marketing strategies.

While generative AI (think ChatGPT or Bing’s Image Creator) gets most of the attention, predictive AI arguably has the biggest opportunity to impact marketing revenue. By leveraging the historical and real-time data you already have from your customers, you can use predictive AI models to forecast future behavior. You can then create powerful marketing campaigns that specifically target those actions and desired actions. 

Innovative marketers are actively applying predictive intelligence to their data to enhance decision-making within their segmentation, for example. This is where the ability for brands to use all of their data in one central place comes into focus, as a foundation for practical applications of AI-driven insights within marketing strategies.

Here’s an increasingly sought-after use case that illustrates how advanced marketers are already using AI: robust retention campaigns that target high-value customers who appear likely to churn.

These aren’t your run-of-the-mill win-back campaigns. Instead, because savvy marketers are working with their entire data set, they can simultaneously apply multiple different predictive models to optimize campaigns, identifying not only customers who are likely to churn but also segmented by lifetime value – and then delivering a personalized experience to each one on their preferred channel at their optimal day and time.

Similarly, savvy marketers are activating other predictive models too – like driving repeat business and loyalty by identifying when someone is likely to make a second purchase or fueling highly personalized product recommendations based on the customer’s complete data profile.

What’s certain with AI – as with data-driven marketing strategies more broadly – is that the best marketers won’t rest on their laurels. They’re constantly experimenting and optimizing to stay ahead of the competition.

Can AI unlock your brand’s humanity?
Having witnessed firsthand the profound shifts in the industry, I’ve come to realize that while AI holds transformative promise, the heart of marketing still lies in the people, their ideas, and their strategic thinking.

In 2024, leading consumer brands must leverage their comprehensive databases to create exceptional customer experiences. The key lies in utilizing deep insights and predictive intelligence derived from data to drive decision-making. Marketers equipped with a holistic view of customer data will then be able to execute strategies that incorporate true surprise-and-delight moments, emerging as the ones to watch this year.

Effective data collection and usage is going to be even more important in 2024. Make sure you're prepared by tapping into the know-how of a global network of marketing leaders in the CMO Alliance Community Slack channel.

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