By now, you’re probably very familiar with how we feel about the B2B buy cycle today: It’s completely buyer-led, and the majority of their journeys take place without a lot of guidance from us.
That’s not to say we as marketers have no influence over the buyer journey. In fact, the opposite is true. The time today’s B2B customers spend not talking to us—which amounts to about 68% of their whole journeys—is time spent on educating themselves about a problem they’re facing or compiling information to help figure out the best way to solve said problem.
How well your brand is represented along each stage of the buyer journey is critical. But you’re not here to show up, you’re here to win. And getting to that last 32% of the journey, where a customer actually talks to you, is a function of two things:
And, according to a recent study by Walker Information, the vast majority of B2B brands aren’t even close to giving their customers the brand experiences they’re expecting—by 2020, 88% of customers will be expecting a user experience personalized to them and their needs.
By comparison, just 9% of B2B CX professionals said they were very effective at this.
Success is all about knowing how to put the right highly relevant, highly personalized content in front of the right buyer at the right time, in the right place and across the right channels, all at the right stage of the buy cycle.
The key to knowing who the “right” customers are and targeting them?
To giving those customers the content they need, when they need it?
To knowing what they’re looking for, sometimes even before they do?
That rests in how you use your company’s data.
Providing the kind of personalized experience your customers are coming to expect from a “digitally mature” organization depends on your ability to combine all the different data sources available to you—web traffic, sales data, etc.—into a single data view. That’s the only way to achieve the kind of cohesive, frictionless experience we're talking about, and it’s how we bring B2B brand and demand together on an organizational level.
Digital maturity can be summed up in three points:
Data management and acquisition is treated like "a cost of doing business," but data is the most valuable thing, in some cases, that a company owns. In fact, data has the potential to be the most valuable capital that any company can own.
Think of it this way. The potential your data has to irrevocably impact the success of your business is such that, if they can collect and leverage customer data better than you, a complete newcomer to your industry with a lesser-quality product offering could potentially eat your lunch. There isn't a single non–high tech sector that you couldn't go into with a me-too product and your identity data management (IDM) done right—where you can target the right buyer, right from the start—and take over the whole market.
This is the “big data marketing" that Kotler and Drucker have been talking about since the ’80s. But the technology didn't exist to implement it. And the closer we get to having that technology, the further away we seem, because we encounter new problems we could not have anticipated earlier.
Heck, DoubleClick had their eyes on using data to customize their message and sequence of messaging per user back in 1998, and we still aren't there.
But it’s important that we start the journey. So, how do you actually do that? And how can you tell where your organization is—and where it should be going?
Our model contextualizes a marketer’s ability to deliver highly personalized content and brand experiences—the kind that lead to higher conversions down the line—to clients based on their ability to target, from “can’t target” to “can target in real time across all channels,” and it consists of five organizational steps:
Here, you’re where everyone was in 2005: no ability to target anyone due to the lack of actionable customer data. Your website hasn’t been configured to record what is being interacted with, when it’s being interacted with or how often.
Here, you have the ability to know if two separate interactions were performed by one user or by two different users. Otherwise, all you’re really doing is counting. Adobe Experience Manager, Salesforce and Oracle are all examples of companies with tools that can access the data you need.
This step is enabled by using tracking cookies to see what users are doing when and for how long. And with what’s called “single-tag user support” through an analytics platform (Google Analytics, Eloqua, Pardot, etc.), you can react to those actions effectively through marketing automation. You just can’t do it in real time.
Here, you are utilizing a DMP tool like Adobe Analytics to pull user data and compile it into one main database. Very few companies are at this stage of the spectrum but the companies that have managed it are using AI to connect external data streams (and the software creating them and the databases that store them) to their DMP tools.
The combination of AI and DMP will eventually lead to the breakthrough that will allow us to implement full identity data management, where you can recognize individual activities within your data streams in real time and react automatically to those behaviors. And by that point, we’ll all live in the future with our flying cars and our monogrammed dog-friendly jetpacks.
The Digital Maturity Spectrum may look a little scary. But just as Rand McNally’s road atlas looks intimidating at first glance, it offers expert directions to anyone with enough patience and dedication to stick with it. Here’s what we suggest if you’re a little confused about how to start your journey toward the intersection of brand and demand in the digital marketing promised land:
Where are you today? The end goal of this exercise will be the creation of a data-based predictor of future customer actions, so familiarize yourself with the data you do collect and try to see what it can tell you. Does your data tell you anything useful? Can you use what you have to discern anything about your customers or how they interact with your organization? If not, think about the steps your organization will need to take with data collection to realize that goal.
If there are gaps in your data, start filling them. Form hypotheses. Run some tests. Sign up with Google Analytics or another free analytics tool and see what it’s telling you, then determine what needs to happen to progress to further incorporate customer data into how you inform your digital strategy.
Being able to answer a question as big as, “How do customers interact with your organization?” depends on having data from all across your company. Try to achieve a unified view of your customer somewhere, whether that means starting new by dumping everything you have into Salesforce or bringing untapped databases into your current analytics suite.
And if anything we said above seems impossible, just remember: This is a necessary journey, but it’s also an iterative one. Don’t get discouraged by the road ahead. And, if you need a little help with finding your way, we’re just a click away.