Marketing research is a critical part of any marketing or brand strategy. Unfortunately, getting started can be difficult and is often prone to mistakes.
And while making mistakes is the best way to learn (or so they say), sometimes you just want to go into a project fully prepared. That's where we come in.
We want to zoom in on some of the biggest challenges marketers face when conducting research, putting some special attention on psychographics.
If you’re keeping up with recent developments in the eCommerce industry, you’ve probably heard a quite a bit about psychographics. At Crobox, often refer to psychographic data as the missing piece of the customer profile puzzle.
Since the numerous benefits of this form of data are already well established, it’s time to go into more detail. Any good customer analysis begins with acquiring the right data. Whether you have the means to do it yourself or you’re thinking of outsourcing, you don’t want to rush into your research project.
Common challenges in psychographic research
In 2017, U.S. companies spent about 10 billion dollars on acquiring third-party data and about the same amount on third-party solutions to support that data.
That’s over $20 billion (!) wasted on buying a bulk of information and consumer insights from outside sources. And the most ironic part of all, the majority of the data these information brokers have on consumers isn’t even correct.
Thankfully, now that Facebook has decided to stop sharing third-party data with partners and stronger online privacy regulations are in action, companies are being forced to look for different solutions.
Don’t get us wrong - there’s nothing wrong with bringing in some help from outside if you don’t have the right resources or experts at your own disposal. However, you want to make sure that the data acquisition part is handled correctly, without investing time, money, and effort into the wrong places.
There are a few pitfalls that many companies overlook when it comes to psychographic marketing research:
- Not selecting the right measurements
- Not saving time by optimizing the process
- Not making sure their research is actually grounded in behavioral science
- Not carrying the research on with repeated testing
To help you overcome these challenges, we’ll recommend a solution for each step of the way.
Challenge 1: Selecting the right measurements
To give you a basic idea of what we’re talking about - or to refresh your memory - psychographic research is mostly involved with uncovering your shopper’s personality, values, activities, interests, and opinions. Unlike demographic, transactional, or behavioral data, psychographics gives us an idea of why a certain customer chose to buy a product.
There are several ways to go about this. For starters, you can ask people for their opinions, interests, or experiences of your product using familiar methods such as surveys, questionnaires, user interviews, or focus groups.
While most marketers love these, they do come with some serious drawbacks. Most notably, attitudinal research methods tend to be untrustworthy, as people are generally quite bad at explaining the (subconscious) motivations for their behavior.
Others tend to obsess over trying to gather as much information as possible, using methods like the Facebook Pixel to keep track of everything their users like, view, or share online. However, looking at just how much dirt companies like Facebook and Google already have on us, it’s not hard to imagine why this path quickly leads to resistance.
It’s a common misconception that data collection needs to be broad and obtrusive to make an impact. In fact, smaller and focused measurements tend to be more effective anyway. By keeping track of anonymized micro-conversions such as clicks, page views, or adds-to-cart you can already tell a lot about your consumer.
Think about it this way. If you had just lost your keys, you’ll most likely start retracing your steps and try to recall the last place you’ve seen them. So when it comes to figuring out why customers (don’t) choose to buy a product, doesn’t it make more sense to focus your investigation on what’s happening on your website?
Challenge 2: Selecting the right tools
The next step is selecting the right tools for your analysis. For now, we’ll stick to micro-conversions, but if you’re looking to add surveys to your research as well - for example, if there’s something more specific you want to ask your audience - there are plenty of tools for that too.
When it comes to measuring on-site behavior, Google Analytics is a good place to start.
While it is one of the more basic tools for this purpose, it has a relatively low learning curve, and more importantly: it’s free to use. For a more in-depth explanation of all the things you can do with Google Analytics, I’d recommend Neil Patel’s walkthrough.
Or, if you’re in a hurry, check these pointers we’ve highlighted below:
- Google Analytics allows you to create detailed customer segments. You can find plenty of demographic statistics under the audience tab, as well some information about the (other) interests of your visitors. Click “add segment” to add any segment you'd like and keep track of..
- Google Analytics allows you to analyze your traffic and website flow. The tabs behavior and acquisition are a great place to find out exactly where, when, and how long your visitors are spending time on your website. You can spend some time playing around with it to see what is attracting your audience and keeping them interested - and identify the areas that could improve.
- Google Analytics allows you to set specific goals and test solutions. Once you have a basic idea of the parts of your website that need improvement, you can head over to the conversion tab and create new goals for yourself. There are four categories: destination (visits to a single page), duration (time spent on page), pages/screens per session (click-through rate), and events (specific actions on a page). For a best practice, try matching micro conversion goals to macro conversion goals.
These features combined should be enough to give you a basic understanding of what’s happening on your website, making Google Analytics a great place for newcomers to psychographics. However, if you’re looking to invest in more in-depth analysis, you might try out some alternatives like Mixpanel, Kissmetrics, or Amplitude.
Either way, it’s important to note that while these tools are all perfectly helpful, you can’t expect them to solve to all your (conversion) problems - that’s for you to figure out. To achieve this, you’re going to need a pinch of creativity and just a dash of expertise.
Challenge 3: Supporting your findings with science
This brings us to our next point and perhaps the most important one of all. While psychographics has been receiving a fair share of buzz as of late, there is still one part that most people working with them tend to overlook:
An easy way to make sense of behavior is by making use of the BJ Fogg model. In short, this theory states that promoting desired behavior depends on three factors: motivation, ability, and triggers.
Psychographics and demographics provide us with insight into the first two parts of the equation. If the motivation and ability are both there, a person becomes a potential customer for your product.
However, whether or not they will act on that potential, depends on the presence of the right trigger. Different situations call for different triggers - and behavioral science is what helps us to determine which one is best suited to your customer.
Sure, it’s nice to already know some things about the interests, habits, and opinions of your audience. But your next objective should be to make your strategy both profitable and valid, by taking the following two steps:
- Make your insights actionable by linking back to the psychological theory. Take a deep dive into your dataset. Do you recognize any behavioral patterns? Can you connect them to specific consumer traits? More importantly, can you match those traits and patterns to any relevant persuasion principles? To give you an idea of how this goes in practice, take a look at this article for a good example of a data-driven profiling strategy from the gaming industry.
- Investigate if your assumptions are correct by testing them. Of course, it goes without saying that you can only tell if something works by trying it out. Make adjustments to your website based on your new persuasive action plan and see what sticks. A/B Testing is a possibility - although it will take you quite a while to test every other variation. Alternatively, a more time-efficient option would be to automate your testing process with AI and make your life a little bit easier.
Challenge 4: Perfecting the craft
So, you did your groundwork, tested out a few new strategies on your website, and successfully learned a bit more about your customers. Congratulations! However, the work does not stop here.
While there is plenty of evidence that suggests at least part of our psychological tendencies are hardwired, most of our human behavior is dynamic. The way we think, act, or feel can change over time and across different situations. This variation results in different shopping states, another factor to take into account during your analysis.
The key is to keep testing new variables at various times to build on what you know. Try out different copy variances for different products, and keep striving for even more detailed and dynamic customer segments.
Make use of machine learning to make your predictions more accurate. And of course, staying up-to-date with the scientific field can pay off.
It may seem like a lot of work, but as a wise man once said: practice makes perfect.
As always, we'll wrap these tips in a nicely summarized recap:
- Despite psychographics’ growing popularity, there are still a few common oversights when it comes to the research.
- There are several ways to discover your target group’s interests and opinions, but keep in mind that these are not always the most trustworthy.
- Instead, keep track of micro-conversions to measure the on-site behavior of your visitors with tools like Google Analytics.
- Link back to behavioral science to make your new data findings both actionable and testable.
- Human behavior is dynamic across different times and situations. Continuous testing and machine learning can help to make your customer insights even more accurate.