Many organizations struggle with issues that stem from their lack of customer insights. How do your customers behave? What needs do they have? Which tasks do they have to complete in order to make a purchase, or acquire a service from your company?
Gathering insights on customer behavior is just the start however. Predicting and acting on your customer’s next move is equally important. In this article we will deep-dive into the importance of gathering these insights, and how to best act on them.
These customer insights allow companies to make the best possible decisions, based on real data instead of assumptions. Let’s use an example to illustrate.
Imagine you are the CMO of a B2C Automotive company, called QCC Sports Cars. You have the right metrics in place to track the performance of the sales of a certain sports car model in the Benelux. QCC has multiple dealerships, across multiple regions in various countries. When analyzing last month’s results, a drop in sales and customer satisfaction becomes evident at a local dealership in a particular region. You see the drop in turnover, but you have no idea what triggered this decline. You make a few calls to the dealership, the sales reps, and some mechanics, but to no avail.
You have the right metrics in place to follow and act upon the operational data, but the insight behind the change is missing. A small example of how information isn’t always necessarily insightful. We see this happen at many companies, and leads to decisions made on assumptions.
The question how you can gather these insights still remains.
Our example illustrates just one use-case where customer insights are unavailable, but we can think of many enterprises that have to deal with this issue and would benefit greatly from having the correct customer insights.
With these insights you can project where customers will move next and stay ahead of your competitors, by using bespoke messaging crafted by your marketing team that directly addresses the customer’s wants and needs. This also allows you to build stronger relationships with your customers, as your conversations will always be relevant to them.
Having the proper data in place ensures you’re making decisions based on facts instead of assumptions, with immediate effect. This is particularly valuable when rolling out a new digital platform based on a specific strategy and roadmap.
Digging deeper and getting all the information needed to acquire essential customer insights is more than worth the effort.
O-data refers to operational data; all the information related to the day-to-day operation of your business. These are hard numbers, such as costs, accounting and sales.
O-data does provides some insights on how the business is performing. It tells you what is happening on a day-to-day basis. However, it does not tell you why it is happening. That’s where X-data comes in, but we’ll get into that in a bit.
Operational data is of vital importance when running your business, as this tells you all about customer behavior. How they place orders, how much they order, how much each customer spends, and so on.
Examples of operational data:
To understand why things happen, you need to understand the thoughts and emotions of the people (customers) involved. We call that information Experience Data (X-data).
Now here comes the tricky part. How do we successfully collect data that captures a customer’s emotions and thoughts about a brand, service or experience? It all comes down to following three steps, and having the right tools in place to listen to and impact your customer:
You need to be able to listen to your customers. This can be done using call centers or sales reps. A common issue here is that there’s a lot of customer feedback information available throughout an organization, but usually this data is scattered and incomplete.
To structure the way data is gathered, it’s possible to setup a feedback program containing email NPS cycles, a feedback strategy, and so on. This can be done by using tools such as Qualtrics. Read more about Qualtrics here.
By doing this, you provide your organization with the tools to truly understand your customers, and the challenges they face when interacting with your company, or using your products and services.
The last step is closing the feedback loop, by acting upon the information you’ve gathered in the first two steps. For instance, if you see customers (step 1 & 2) struggle with making online appointments at a specific dealer due to a poorly designed website, you can act upon this by improving the experience on the website, specifically the scheduling tool.
When looking at the data and deciding on what to improve, the answer could range from design and content, to better supporting the devices your customers use to access your digital platform, and everything in between.
It empowers your company to have insights into what drives your customers. How do they rate your products and brand? Do they experience issues while engaging with your services? The information collected provides insights into the all-important ‘why’.
Examples of experience data:
Having both the O-data and X-data in place is a great achievement, but to reap the full benefits this data has to be combined, as this leads ato the most valuable customer insights. The challenge is finding the best way to combine this information. So how exactly do you combine this data and come to the actionable insights we have been chasing all along?
Let’s have another look at our QCC Sports Cars example from before, where the O-data is already in place. This is captured and measured in systems such as the digital (e-commerce) platform, and CRM & ERP solutions.
Now we find the X-data is also in place, after implementing an experience management solution that captures customer feedback using an online feedback dialog on their website.
With both the O-data and X-data available, QCC Sports Cars is now facing the daunting task of combining them. To do so, they’re using predictive analytics via a dashboard tool that integrates both data streams, resulting in a statistical analysis.
Using the resulting analysis QCC Sports Cars has gained an in-depth look at what types of products and service interactions lead to promoters and detractors. They can also use this data to predict the NPS for large segments of their customer base. This includes customers that never even responded to a survey. This in turn creates the opportunity to engage with these customers within the appropriate context.
By collecting experience data at every meaningful customer touchpoint, you can analyze and understand customer experience gaps, and determine what to do about them. This leads to real customer insights that you can immediately act upon. The predictive customer insights are used to further serve their needs in the near future.
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