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Analytics Magazine

Personalization: How to close the deal

Why data, analytics and content need to work together to get it right … and the perils of getting it wrong.

Alicia McCartyBy Alicia McCarty

Not long ago, I visited a particular website and was immediately confronted by a confusing message. “Hi, Barak!” it greeted me, before promptly urging me to submit my email to receive some inspiring content.

Why is that confusing? Surely, it’s a clever example of personalized marketing. Well, perhaps it would be … if my name was “Barak.” But it isn’t.

Clearly the mistake had something to do with my company’s IP address (I asked some other people in the office to visit that website, and it promptly addressed them as “Barak” too), but whatever the reason, it was a great illustration of the challenges of personalization – and the perils of failing to get it right.

Who? What? When?

Marketers today know the importance of marketing personalization. According to Marketo’s “State of Engagement” report, 98 percent of marketers understand the need for personalized customer experiences and have implemented strategies aimed at achieving that. The Internet is awash with industry studies demonstrating how personalized content increases engagement. We don’t even need statistics to tell us this. We all know instinctively from our experiences as consumers that personalized content works far better than generic material. We’ve come to expect it, and that expectation has filtered into the B2B market as well.

But for marketers to get it right they need the right data. To be more specific, they need the answers to three crucial questions: who to target, what content to target them with and when to engage.

Step 1: “Who?” – identifying your target audience. Have you ever bought something online, only to be immediately bombarded with ads for the next few days offering you the exact same thing? That’s an example of bad audience targeting. Surely someone who’s literally just bought a specific item online is the last person you should be trying to sell an identical product to?

It’s all about data quality. But “quality” doesn’t just mean accurate versus inaccurate – it’s also about having enough of the right data to see the full picture. To build on the above example, when your ad targeting is simply using cookies to track superficial online activity, that’s what you’ll get – superficial data that simply tells you that a certain IP was at some point interested in product “X.” But that data lacks context (i.e., they were interested, but they’re not anymore because they bought it). “Data” alone isn’t enough; that data needs to provide actionable intelligence for it to be of any practical use. Without that context, well, as the saying goes, “a little bit of knowledge is a dangerous thing.”

For B2B marketers, an emerging market of predictive solutions aim to solve this problem by using historical data to predict which prospects are actually a good fit and would therefore be more likely to buy your product or service.

But the importance of seeing the whole picture is just as important when it comes to analytics and intelligence platforms as it is with raw data. Beware of predictive scoring platforms that operate in a “black box.” If you aren’t sure what data are going in and why, there’s no way to be sure you’ll see long-term value from the predictive model, because: 1) you don’t know how that data will change over time, and 2) even if it is currently “accurate,” that doesn’t mean the right insights are being used to build your predictive model.

Step 2: Understand what content will engage them. In today’s content-saturated world, encouraging anyone to engage with your content is an uphill struggle even if they do genuinely need what you are offering. This is where personalization becomes particularly critical. According to the “State of Engagement,” 34 percent of B2B customers say they are served too much irrelevant content. (That number is considerably higher for B2C customers, at 51 percent, as consumer marketers often have a much wider audience to target.)

Nearly 100 percent of marketers understand the need for personalized customer experiences and have implemented strategies aimed at achieving that.

Nearly 100 percent of marketers understand the need for personalized customer experiences and have implemented strategies aimed at achieving that. Source. ThinkStock

Say you’re marketing a particular piece of technology to a target account. Within that company, you could have two or more individuals you need to convince to buy that product. If it’s a martech tool, for example, you’ll obviously need buy-in from someone in marketing. But IT may need to approve as well. And if it touches on certain shared platforms like CRMs, the sales department might need to be involved in the process too.

How do you target all three stakeholders effectively? It’s highly unlikely that the same kind of content will work for a director of demand generation, a VP of Sales and a director of IT. A truly personalized marketing campaign will tailor each engagement to fit these three different buyer personas: e.g., a technical, data-oriented, factual email with a relevant industry report for the director of IT; a more visual, marketing-focused email with an interesting thought-leadership piece for the director of demand gen; and a relevant case study for the VP Sales, exhibiting how your solution impacts other companies’ bottom lines.

But here’s where many marketing efforts fall short. To carry out this level of personalization, your data needs to drill deep down beyond superficial information like “job title,” to more relevant information like specific job responsibilities, seniority and what technologies they are currently using. For example, if Marketing is already using a competitor, you’ll want to approach them differently. Or if their existing technologies are incompatible with your offering, you might not want to target them at all.

Without that kind of information, marketers are left choosing between playing it “safe” with relatively generic content or relying on a heavy dose of guesswork and leaving themselves vulnerable to getting it wrong.

Think about it: How often do you receive marketing emails clearly targeting you due to your job title or department, but that exhibit a lack of understanding for you or your position and responsibilities within your company, or even the company itself? Those are precisely the kinds of emails we instinctively delete every day – and precisely the kinds of emails you don’t want to send.

Step 3: Strike when the iron’s hot. A prospect can be a perfect fit for your product, and your campaign/content could be precisely tailored to their buyer persona, but if they’re not currently in a buying cycle or are uninterested for another reason, your best efforts could fall on deaf ears. Getting the timing right is an important aspect of effective personalization. That’s why intent data is currently generating a lot of excitement. Intent data is essentially behavioral information collected about a person’s online activity that indicates levels of interests in specific “topics.” Using this information, you can monitor prospects’ levels of interest in your offerings or when they’re moving in or out of a buying cycle.

While intent data is still in its early phases, it’s definitely an exciting, emerging addition to any marketer’s data toolbox. But once again it’s crucial to emphasize that context is everything: intent data alone has limited value if you don’t have a clear picture of who you’re tracking and why they might be acting as they are (e.g., is it a market analyst browsing your website for thought-leadership content, or a potential customer showing interest in and learning about your product?).

Pulling it All Together

Combining these three levels of data and intelligence, B2B marketers can create truly personalized, effective campaigns and content. By prioritizing who to target, understanding what content will interest each buyer’s persona and getting the timing right, marketers can serve experiences that resonate with each of their target audiences and achieve the desired results: better engagement and higher conversion rates.

Alicia McCarty is director of Marketing at Leadspace, a B2B audience management platform delivering business intelligence for sales and marketing.

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