As a customer insight leader, you’re constantly looking for key behavior drivers behind your organization’s CX scores. Understanding what motivates customers is essential for knowing how to improve their experience and ultimately drive revenue.
Uncovering deep and meaningful customer insights is easier said than done!
Physical motivators are easy to spot, such as the kind of products your customers like and when and where they buy them. Customer insights teams however must dig deep to uncover the psychological drivers behind customer decisions and preferences.
But why do your customers behave the way they do?
To unlock deep and meaningful customer insights, you need to use available resources at your disposal. Beyond using standard survey forms, your customer insights team should combine qualitative and quantitative data to gain a holistic understanding of the ‘why’ behind customer feedback.
Doing this can help your organization develop a pointed business strategy, high-impact marketing campaigns, and a stronger sales funnel all of which drives revenue.
Let’s look at how you can utilize qualitative feedback data from multiple sources for deeper customer insights.
Qualitative vs. Quantitative Research
Qualitative and quantitative research are two terms you’ll see a lot when collecting customer data. While there are obvious practical differences between the way you gather qualitative vs. quantitative data, the biggest contrast lies in the type of insights you’ll get from each.
On one hand, quantitative studies answer the “what, where, when, and who” of decision making. On the other hand, qualitative research answers the “why and how”. Although you should use them in tandem, qualitative feedback is what really reveals the motives behind customer purchases.
This means that qualitative data helps customer insights teams understand behavior drivers in ways quantitative data cannot.
You can use these deeper psychological insights as a human-centric guide for improving customer experiences across the spectrum.
This goes from their first touchpoint with the organization through to what happens post-purchase).
Let’s take a look at some of the different sources of qualitative customer data , as well as how you can combine these to generate the most valuable consumer insights possible.
8 sources of qualitative customer data
There are many ways to gather qualitative customer data. And you don’t need to choose just one - spreading your resources across many platforms and methods allows you to get a more comprehensive view of customer sentiment and behaviour drivers.
Here is a list of some of the most effective sources of qualitative customer feedback:
One-on-one conversations with customers are a straightforward way of gathering qualitative feedback. You can ask a series of questions (and follow-up ones) to find out why they buy your products or services, how they use them, and what they think could be improved. The challenge with this approach is going to be scale. Datasets with thousands of individual verbatims are always going to increase the chance of finding repeatable patterns of behavior than a handful of individual responses.
An advantage of grouping interviewees together into focus groups is that they can bounce ideas and opinions off each other, something which often leads to better insights. They also allow you to gather more qualitative data in a shorter period of time, when compared to individual customer interviews. This is particularly beneficial if you want to test out products or campaigns on a particular audience before a launch. For customer insights teams, talk to your product team to see if they have this type of qualitative data available to share.
Customer feedback surveys
NPS or CSAT surveys which ask open ended questions in addition to a score value.
Social media comments are a great source of qualitative customer data. Two considerations to keep in mind. Firstly, this is more effective when you have lots of comments to look at in your dataset. Second, like any external source of data you’ll have to scrape for this data (even if you own the social media channel). There are third parties which provide this service or you could bring this job in-house.
Moreover, social media research can improve cost-efficiency versus traditional research methods, especially with online tools like Kapiche that help customer insights teams make sense of their qualitative customer data (including from social media).
Studies show that nearly all (91%) of 18 to 34 year olds trust online reviews as much as they do personal recommendations. Even more (93%) say that online product reviews have influenced their purchase decisions, because they reveal what previous customers experienced with the product. For customer insights teams, user-generated reviews also offer a direct glimpse into how and why their products satisfied customers - information which can be used to improve products in the future. This is a great way to rally the Product/Operations/Frontline Service Delivery departments in your organization around the role of customer insights.
Call Transcripts and Support Tickets
Customer service teams often use call recording software to keep track of all customer calls. While they typically use this to improve their customer service performance, customer insight teams can also use the calls to understand why customers buy their products by analyzing the types of questions they ask most frequently. Gathering qualitative data from call transcripts therefore helps organizations achieve long term growth from customer success. If you can glean useful insights along the way you might as well leverage the data you already have in-house.
Also called “shop-alongs,” in-person observation research is when you pay attention to how your consumers interact with your product in-store. Since this kind of observation happens in real life and without the knowledge of the customer, there should be fewer inaccuracies due to survey respondents giving canned responses (or trying to spare your feelings). As with individual reviews and focus groups, scale can be an issue but this is also a low hanging fruit opportunity for insights teams wanting some quick wins or adding variety to their datasets. Combining multiple datasets (both quantitative and qualitative is something you can quite easily do inside Kapiche provided the datasets are in a csv or xlsv format.
Public Competitor Data
Competitor insights analysis won’t be comprehensive compared to an analysis of your own customers. They do however help cast some light on the behavior drivers impacting your competitors. . This all helps with positioning and identifying opportunities in the market where your organization has a competitive advantage. At the end of the day, if your insights team can report not only what drives your own customer behavior but also competitors executives develop strategies that win and you’ll look like a hero.
All of these qualitative feedback sources can provide you with incredibly valuable data about your customers.
But after you gather this information, how should you analyze it? More importantly, how can you dig deeper into the results to produce actionable customer insights?
Combining Multiple Qualitative Sources for Deeper Insights
While each of the feedback sources above offers useful insights when used independently, combining them is the key to becoming more in-depth and targeted with your customer insight strategy.
Since the goal is to reveal the why behind consumer behaviours, insights teams should look beyond surveys as the only source of qualitative customer data, utilizing other sources simultaneously to get a holistic understanding of the customer journey. Throw in columns for quantitative data such as NPS score, revenue, number of days since first transaction and all the usual demographic data such as country, state, gender, age etc and you have the beginning of an amazing analysis. This video shows you how to quickly (and I mean within minutes) build dashboard ready reports at this level of depth.
Here are some ways you can combine multiple qualitative sources for deeper insights:
For qualitative research, the case study method includes gathering in-depth analysis from multiple qualitative data sets to draw conclusions about why customers act the way they do, and what a positive experience means to them.
Say, for example, you want to know why a particular customer prefers your products over competitors’. You can take insights collected from multiple sources, like:
- Individual interviews, where you ask questions such as "Why do you buy our products? What do you like most about them? What made you choose us over a competitor?”
- Social media and product reviews, where you look closely at customer sentiment and conversations surrounding your brand
- Public competitor data, where you compare the things people are saying about your competition to your own customer feedback
Once you’ve gathered this information, you can develop case studies that trace real-life customer journeys and explore what worked (and what didn’t) when it came to producing conversions. Executives love it when they can relate to real human experiences.
This research method is similar to going to the library for more references. If you've been collecting qualitative feedback for some time already, you can use historical data to validate or polish the new insights you've gleaned from more recent research.
One example is to use social media as a “library” of existing information, since social platforms generate customer information without much intervention. You can use software to backtrack and analyze how your customers experience your brand and pit them against newer surveys and interviews to understand your customer base on a deeper level, as well as discern trends in customer satisfaction levels over time. Where you log this is up to you but ideally you want a platform that can visually show trends over time (particularly useful for reporting to executives).
Trended Data Collection
Also called longitudinal studies, this refers to repeatedly performing the same qualitative feedback method over an extended period. The idea is to analyze a theme against past data but from the same qualitative source. Doing so will help you find emerging themes. Best practice is to work toward automating the discovery of emerging themes from existing datasets. Discovery being the operative word here. Customer insights is much easier when you let technology solutions give you the answers rather than relying on tools that just automate what humans already do.
Using the social media example again, you can conduct the same online surveys multiple times over five years. By the end of the fifth year, you'll have trend data showing the evolution of your customers' purchase reasons, providing deep and meaningful insights into how things like new competitors or changing market trends impact your relationship with your customers.
Single source collection won’t give you the full picture behind why your customers interact with your brand the way they do.
Instead, you should approach and analyze qualitative research from multiple angles.
That way, you’ll have a fuller understanding of your customer base that can help you make better short and long-term business decisions.
Complete Understanding of Your Customers with Kapiche
With the rise of social media and online review sites, customers are now more able and willing than ever to tell businesses what they want and need. That means that businesses like yours can listen and learn from your customers to gain insight into how you can better serve them in the future.
By collecting and analyzing qualitative feedback from multiple sources, your customer insights team can harness the power of customer data to achieve actionable business insights.
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