How To Support Data with Real-Life Interviews – Whiteboard Friday

Posted by rcancino

With all the data that today’s marketers can access, there’s often still no substitute for the quality of information you can get from interviewing real people. In today’s Whiteboard Friday, we welcome Rebekah Cancino — a partner at Phoenix-based Onward and #MozCon 2016 speaker — to teach us the whys and hows of great interviews.

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Video Transcription

Hi, Moz fans. I’m Rebekah Cancino. I’m a partner at Onward, and I lead content strategy and user experience design. Today I’m here to talk to you about how to support the data you have, your keyword data, data around search intent, analytics with real life user interviews.

So recently, Rand has been talking a little more about the relationship between user experience design and SEO, whether it’s managing the tensions between the two or the importance of understanding the path to customer purchase. He said that in order to understand that path, we have to talk to real people. We have to do interviews, whether that’s talking to actual users or maybe just people inside your company that have an understanding of the psychographics and the demographics of your target audience, so people like sales folks or customer service reps.

Now, maybe you’re a super data-driven marketer and you haven’t felt the need to talk to real people and do interviews in the past, or maybe you have done user interviews and you found that you got a bunch of obvious insights and it was a huge waste of time and money.

I’m here to tell you that coupling your data with real interviews is always going to give you better results. But having interviews that are useful can be a little bit tricky. The interviews that you do are only as good as the questions you ask and the approach that you take. So I want to make sure that you’re all set and prepared to have really good user interviews. All it takes is a little practice and preparation.

It’s helpful to think of it like this. So the data is kind of telling us what happened. It can tell us about online behaviors, things like keywords, keyword volume, search intent. We can use tools, like or Ubersuggest or even Moz’s Keyword Explorer, to start to understand that.

We can look at our analytics, entry and exit pages, bounces, pages that get a lot of views, all of that stuff really important and we can learn a lot from it. But with our interviews, what we’re learning about is the why.

This is the stuff that online data just can’t tell us. This is about those offline behaviors, the emotions, beliefs, attitudes that drive the behaviors and ultimately the purchase decisions. So these two things working together can help us get a really great picture of the whole story and make smarter decisions.

So say, for example, you have an online retailer. They sell mainly chocolate-dipped berries. They’ve done their homework. They’ve seen that most of the keywords people are using tend to be something like “chocolate dipped strawberries gifts” or “chocolate dipped strawberries delivered.” And they’ve done the work to make sure that they’ve done their on-page optimization and doing a lot of other smart things too using that.

But then they also noticed that their Mother’s Day packages and their graduation gifts are not doing so well. They’re starting to see a lot of drop-offs around that product description page and a higher cart abandonment rate than usual.

Now, given the data they had, they might make decisions like, “Well, let’s see if we can do a little more on-page keyword optimization to reflect what’s special about the graduation and Mother’s Day gifts, or maybe we can refine the user experience of the checkout process. But if they talk to some real users — which they did, this is a real story — they might learn that people who send food gift items, they worry about: Is the person I’m sending the gift to, are they going to be home when this gift arrives? Because this is a perishable item, like chocolate-dipped berries, will it melt?

Now, this company, they do a lot of work to protect the berries. The box that they arrive in is super insulated. It’s like its own cooler. They have really great content that tells that story. The problem is that content is buried in the FAQs instead of on the pages in places it matters most — the product detail, the checkout flow.

So you can see here how there’s an opportunity to use the data and the interview insights together to make smarter decisions. You can get to insights like that for your organization too. Let’s talk about some tips that are going to help you make smarter interview decisions.

So the first one is to talk to a spectrum of users who represent your ideal audience. Maybe, like with this berry example, their ideal customer tends to skew slightly female. You would want that group of people, that you’re talking to, to skew that way too. Perhaps they have a little more disposable income. That should be reflected in the group of people that you’re interviewing and so forth. You get it.

The next one is to ask day-in-the-life, open-ended questions. This is really important. If you ask typical marketing questions like, “How likely are you to do this or that?” or, “Tell me on a scale of 1 to 10 how great this was,” you’ll get typical marketing answers. What we want is real nuanced answers that tell us about someone’s real experience.

So I’ll ask questions like, “Tell me about the last time you bought a food gift online? What was that like?” We’re trying to get that person to walk us through their journey from the minute they’re considering something to how they vet the solutions to actually making that purchase decision.

Next is don’t influence the answers. You don’t want to bias someone’s response by introducing an idea. So I wouldn’t say something like, “Tell me about the last time you bought a food gift online. Were you worried that it would spoil?” Now I’ve set them on a path that maybe they wouldn’t have gone on to begin with. It’s much better to let that story unfold naturally.

Moving on, dig deeper. Uncover the why, really important. Maybe when you’re talking to people you realize that they like to cook and by sharing a food item gift with someone who’s far away, they can feel closer to them. Maybe they like gifts to reflect how thoughtful they are or what good tastes they have. You always want to uncover the underlying motives behind the actions people are taking.

So don’t be too rushed in skipping to the next question. If you hear something that’s a little bit vague or maybe you see a point that’s interesting, follow up with some probes. Ask things like, “Tell me more about that,” or, “Why is that? What did you like about it?” and so on.

Next, listen more than you talk. You have maybe 30 to 45 minutes max with each one of these interviews. You don’t want to waste time by inserting yourself into their story. If that happens, it’s cool, totally natural. Just find a way to back yourself out of that and bring the focus back to the person you’re interviewing as quickly and naturally as possible.

Take note of phrases and words that they use. Do they say things like “dipped berries” instead of “chocolate-dipped strawberries?” You want to pay attention to the different ways and phrases that they use. Are there regional differences? What kinds of words do they use to describe your product or service or experience? Are the berries fun, decadent, luxurious? By learning what kind of language and vocabulary people use, you can have copy, meta descriptions, emails that take that into account and reflect that.

Find the friction. So in every experience that we have, there’s always something that’s kind of challenging. We want to get to the bottom of that with our users so we can find ways to mitigate that point of friction earlier on in the journey. So I might ask someone a question like, “What’s the most challenging thing about the last time you bought a food gift?”

If that doesn’t kind of spark an idea with them, I might say something even a little more broad, like, “Tell me about a time you were really disappointed in a gift that you bought or a food gift that you bought,” and see where that takes them.

Be prepared. Great interviews don’t happen by accident. Coming up with all these questions takes time and preparation. You want to put a lot of thought into them. By asking questions that tell me about the nature of the whole journey, you want to be clear about your priorities. Know which questions are most important to you and know which ones are must have pieces of information. That way you can use your time wisely while you still let the conversation flow where it takes you.

Finally, relax and breathe. The people you’re interviewing are only going to be as relaxed as you are. If you’re stiff or overly formal or treating this like it’s a chore and you’re bored, they’re going to pick up on that energy and they’re probably not going to feel comfortable sharing their thoughts with you, or there won’t be space for that to happen.

Make sure you let them know ahead of time, like, “Hey, feel free to be honest. These answers aren’t going to be shared in a way that can be attributed directly to you, just an aggregate.”

And have fun with it. Be genuinely curious and excited about what you’re going to learn. They’ll appreciate that too.

So once you’ve kind of finished and you’ve wrapped up those interviews, take a step back. Don’t get too focused or caught up on just one of the results. You want to kind of look at the data in aggregate, the qualitative data and let it talk to you.

What stories are there? Are you seeing any patterns or themes that you can take note of, kind of like the theme around people being worried about the berries melting? Then you can organize those findings and make sure you summarize it and synthesize it in a way that the people who have to use those insights that you’ve gotten can make sense of.

Make sure that you tell real stories and humanize this information. Maybe you recorded the interviews, which is always a really good idea. You can go back and pull out little sound bites or clips of the people saying these really impactful things and use that when you’re presenting the data.

So going back to that berry example, if you recall, we had that data around: Hey, we’re seeing a lot of drop-offs on the product description page. We’re seeing a higher cart abandonment rate. But maybe during the user interviews, we noticed a theme of people talking about how they obsessively click the tracking link on the packages, or they wait for those gift recipients to send them a text message to say, “Hey, I got this present.” As you kind of unraveled why, you noticed that it had to do with the fact that these berries might melt and they’re worried about that.

Well, now you can elevate the content that you have around how those berries are protected in a little cooler-like box on the pages and the places it matters most. So maybe there’s a video or an animated GIF that shows people how the berries are protected, right there in the checkout flow.

I hope that this encourages you to get out there and talk to real users, find out about their context and use that information to really elevate your search data. It’s not about having a big sample size or a huge survey. It’s much more about getting to real life experiences around your product or service that adds depth to the data that you have. In doing that, hopefully you’ll be able to increase some conversions and maybe even improve behavioral metrics, so those UX metrics that, I don’t know, theoretically could lead to higher organic visibility anyway.

That’s all for now. Thanks so much. Take care.

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