It’s easy to assume you have all the data you could possibly need. But assumptions are dangerous.
The availability bias — the idea that the data you have available is also the best data available — leads to misconceptions about your marketing efforts, causing more trouble than it’s worth.
Let’s take a lesson from our friends Han Solo and Luke Skywalker. In A New Hope, Han and Luke are trying to evade some malicious pursuers quickly closing in on their ship. Luke decides this is all the data he needs and immediately wants to jump to lightspeed. Luke has an availability bias because he assumes he has all the data needed to make the decision. Han knows better. So it unfolds:
Han: “It’ll take a few moments to get the coordinates from the navi-computer.”
Luke: “Are you kidding? At the rate they're gaining —”
Han: “Traveling through hyperspace ain’t like dusting crops boy! Without precise calculations we’d fly right through a star or bounce too close to a supernova and that’d end your trip real quick, wouldn’t it?
As you can see, Han feels strongly about having the right data and warns against making decisions without it. Even though you’ll probably never have to worry about things literally happening at light speed (despite how things often figuratively feel in marketing), you should still set yourself up for success by gaining access to the right data.
The Right Data on Healthcare IT Content Marketing Personas
Now that you're a little more aware of availability bias issues, do you feel a bit lost in space? Think of it this way: does your data primarily involve information on an end user’s demographics and role? Sure, this is good data to have, but it’s not enough. The idea that demographic data is sufficient poses problems, because it doesn’t contain the information that lets you know what leads directly to a purchase.
Let's say a CTO leaves his business card in a prize raffle bowl at your event. The demographics are gold, but behaviorally, you don't know if he just wants the prize — and is ready to ignore follow-up outreach — or if he's actually interested in your brand and the prize is merely a bonus. How should you follow up with this CTO? Should you simply guess at his intentions? Or should you try to cultivate more data? By following up with trackable content and extracting behavioral data you're adding to the overall picture and strengthening your understanding. Demographic and behavioral data are both valuable pieces of information, but too often the behavioral element is left out. The reality is that when these two data sets are used in tandem you're empowering yourself in ways that neither of them can do alone. But if you have an availability bias you'll simply stick with the demographics and assume he's interested in your brand. This of course creates data gaps and puts you in danger of putting too much weight behind titles while missing the behavioral element.
If you don’t have behavioral data, you’re operating on a range of wide assumptions instead of having a directly connected variable. So, the right data is a combination of the demographics and the behavioral. Without that combination, you're essentially flying at lightspeed blind. With it, you see the full picture and can understand what actually drives outcomes.
Imagine you're having an in-person conversation with someone, but all you're processing is their name, title and company. How well would you actually know them? Would you understand their decisions and interests? Would you be prepared to have a conversation with them on those topics? Without processing their behavior, such as body language, facial expressions, eye contact and tone in person (as you would content consumption and engagement behaviors digitally) you're missing all the information that leads to personal understanding. And let's face it, that would lead to some awkward conversations. That’s why ensuring you have a complete picture of your buyer is so vital to success.
But how do you know you have the right data? Let’s have a look.
4 Indications You Are Working With the Right Data
You should always be operating with a set of benchmarks that are inline with your industry that can serve as an objective baseline for any given effort. Performance quality — whether high or low — should never be subjective, but based on a degree of variance from the baseline.
Benchmarks give you a baseline to understand and judge your own performance. In fact, that's where internal benchmarks really come in handy. Internal benchmarks are great for understanding your baseline, letting you know how you're doing and what to expect in the future. Over time they'll help you achieve consistent performance. From there you can set your sights on plotting a path to best-in-class industry standards to see where you stand in relation to the standard industry performance.
Consistent results within benchmark ranges — not relying on massive swings or one-off successes — are strong indications you’re using the right data. Of course, overperformance is a bonus, but not necessarily a new formula for success. At least not until that overperformance becomes consistently attainable and not merely a streak of "good luck."
2. Genuine Human Interaction
Not everything is about numbers. Sometimes it’s about those intangible tangibles. Genuine human interaction consists of those moments on social media, at trade shows or through customer feedback when real people tell you: they connected with your content, you understood them, you reached them and you solved their challenges. Anecdotal reactions — insight into the relevance of your material and efforts — happen when you're in tune with more than just your buyer’s demographics, such as their behaviors and needs. Of course there are still ways to track some of these. One way is by keeping track of the frequency of these types of reactions. A simple spreadsheet tallying comments or reactions and the date of the occurance will likely suffice. Early on, any reaction may be a win and should be documented, but as you grow in effectiveness these reactions should increase in frequency.
3. Refinement and Standardization
Another indication you’re collecting the right data is that you’re able to further refine your content marketing personas or market-facing categorizations through standardization to better target them. For instance, on your forms — or other materials — most users are selecting one of your pre-defined dropdown options for industry, job function, worksite, etc. instead of selecting “other.” These are the types of indications that tell you your buyers are seeing themselves in your choices and feel accurately represented. The data is right because you’ve successfully zeroed in on your most relevant groupings and aligned your offers and communications appropriately. If you only receive "other" answers, it's likely you don't have all of the data you need to form strong targets or categories.
With personas and groupings you want your categorizations to match how your audience would identify themselves. With the right data you can see, understand and present offers in a way that fits how that particular group identifies. By leveraging these groups you can scale more effectively while still maintaining relevent and even personalized communications. Not to mention, the target members of these groups will feel more comfortable by seeing themselves accurately represented in your standardized options. In other words, the structures you've put in place for structured data actually hold up.
4. Data Confidence
Data confidence is a unique feeling founded on objective, empirical, repeatable evidence. It's the idea that as long as anyone follows the same process, works with the same data sample, or otherwise does the same things you did without injecting any new variables, you can confidently expect them to get the same result. Emphasis, of course, on "same." When data indicates that something may have gone wrong in your marketing efforts, data confidence means you don't doubt the data. Whether it's a desired result or an undesired result, data confidence means the result is still right. Your data is always a source of clarity and insight, not a wildcard defense mechanism for placing blame or pivoting the narrative. It’s the idea that you’ve seen the data and you know it’s right, as opposed to trying to convince others — and yourself — that it’s right. And that’s a powerful place to be because when you've seen the numbers, done the math and confirmed the findings, there's no longer a need for second guessing.
So take a look at the data you currently have. Is it the right data on your buyers? Is it demographic and behavioral data, or are you suffering an availability bias? The right data makes all the difference!
Remember, there's danger in assuming. So be Han Solo, not Luke Skywalker.
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