"The customer is king." — that's the premise that businesses are built on. Yet, surprisingly a large fraction of companies today are unable to truly understand what their customers want.
They either don't have the means to extract customer insights at scale or don't know how to leverage the right tools to tap into their needs.
Customer experience (CX), regarded as the heartbeat of businesses, includes every customer interaction—from the first point of contact to long-term engagement. But as these interactions grow as they move through the customer lifecycle, managing that data becomes challenging.
This is where CX insights come in. In this article, we’ll discuss the concept, its importance for customer support and CX teams, and how you can tap into these data sources.
What are CX Insights?
Customer Experience (CX) insights refer to the data businesses gather from various sources to understand customers' interactions, preferences, needs, and sentiments throughout the customer journey.
You can get these insights by analyzing qualitative and quantitative data like customer feedback, market research, and audience forums to understand how customers engage with your products, services, and brand. By collecting and analyzing CX data, you uncover trends that shed light on what drives customer satisfaction and loyalty.
Why is it important to measure CX insights?
There are several reasons why CX insights should be a critical part of your internal processes. Some of them include:
Understand customer needs and expectations
Dig into customer data like one-on-one feedback to continuously identify pain points, improvement areas, and unmet needs—not just as a one-time endeavor.
It allows you to tailor products and services to your customers’ needs—not what you’ve assumed they need. Ultimately, it increases customer satisfaction as you meet where they’re at.
Optimizing business processes and efficiencies
It's challenging to find the resources to manually analyze multiple data sources and tie them together with verbatims in a way that tells your customer's story. This is especially true with unstructured data that becomes unusable as you don't have the resources to analyze them at scale or accurately, even if you did have the resources.
When you invest in a CX insights solution, you can prevent this issue altogether. It'll continuously analyze all of your data at scale as long as the data sources are connected.
Increase customer retention and reduce churn
The biggest issue with determining why customers churn is that you have the data—but no means to access the information that’ll tell you why this happens.
For example, you have thousands of tickets detailing every customer concern. Now you have to go through those tickets manually, and also the interpretation of those tickets is up to your team who's analyzing the data. This results in an inaccurate analysis of only what your team can go through.
But with CX insights, this data analysis becomes structured and automated, and you can drill into why certain events are happening. This lets you reduce churn rates and increase the customer lifetime value with added improvements.
Drive revenue growth
Seventy-two percent of business leaders say expanding AI (artificial intelligence) across the customer experience will be a priority over the coming year. And for good reason.
CX teams can tap into unstructured data sources and combine and extract valuable insights using automated systems. And the underlying outcome is a better customer experience that results in consistent revenue growth.
Types of CX insights to understand your customer
Now that we know why these insights are important, let's look at what kinds of CX insights you can gather:
1. Journey insights
Map the customer journey from start to finish by considering all the touch points. Traditionally it has been very difficult to analyze conversations because of their unstructured nature using traditional BI tools.
For example, if your sales team communicates via email and the customer support team communicates via chatbots and ticketing systems, combine that data. This lets you understand the entire customer journey and the customer's experience. If a channel or team has similar issues, you can identify and resolve them to reduce friction. You can also identify which conversations and flows are leading to drop offs and negative experiences.
2. Path insights
Path insights go one step deeper and analyze individual customer touch points.
Traditional CX strategies focus on high-level metrics—but if you exclude qualitative data, it’s hard to determine the actual cause of customer frustration and dissatisfaction.
For example, a customer might give you a 7 of 10 in an NPS survey without additional comments. How do you know what was the underlying reason behind this score? Only when you map their past interactions with your company do you map the individual customer journey.
It lets you uncover the root causes of customer behavior and pinpoint the specific touch points or interactions driving positive or negative experiences.
3. Transformational insights
Transformational insights offer a mix of three metrics: operational (customer interactions), experience (customer feedback), and financial (business performance).
We often hear many CX leaders say they need to combine customer feedback data from surveys or calls with financial data like contact and sales data. Doing so helps them fix the underlying CX issue and easily correlate how repairing it contributes to the financial return.
To achieve that, AI-powered tools that use technologies like sentiment analysis are a must as they dig into the core sentiment around specific issues. When you discover these insights, you can work from the bottom up to transform the CX of your company.
How to extract CX insights that matter?
Here’s a 3-step process you can use to extract valuable CX insights:
1. Consolidate your omni channel data sources
Start with the data you have. Identify your primary customer touch points like websites, social media, and chatbots and bring all those data sources into one place.
If you’re not sure about where to start, here’s a list of data sources you can include based on the type:
Quantitative data sources (Structured data from internal teams):
- Net Promoter Scores (NPS) surveys
- Customer satisfaction (CSAT) scores
- Transactional data
- Website analytics
- User journey tracking
- Third-party review scores
Qualitative data sources (Unstructured data from internal and external sources):
- Customer reviews
- Customer feedback survey data
- Social media comments
- Email tickets
- Chatbot conversations
- Forum conversations
2. Feed them into Dashbot for data analysis
After consolidating the data from various sources, feed it into Dashbot’s centralized data platform for analysis.
The main purpose of this process is to organize unstructured data in a structured manner—creating clean, accurate, and ready for analysis. Dashbot's no-code data tools let you process this data how you want. Use the data exploration tool to group the categories you need—instead of being limited to what a traditional BI or text analytics tool presents to you.
In addition, it pulls out top customer concerns and sentiments around specific topics to show you where you're excelling and lagging at any given time. Slice your data by topics and reasons which go beyond traditional keyword analysis by summarizing multi-turn conversations into concise data points.
3. Find a narrative that speaks to a specific persona
Different customer segments have unique preferences, pain points, and expectations. You can create targeted strategies to address their needs by identifying and understanding these distinct personas.
For example, the insights gathered from data analysis might reveal that a particular customer segment is struggling with a specific product line. You can design a customer service strategy that reduces response times and improves issue resolution for that specific persona.
Crafting a narrative that speaks to a specific persona helps deliver more personalized and relevant customer experiences.
Deeply understand your customer base with Dashbot
Implementing automated CX insights solutions is a benefit companies can't afford to ignore. You can access a granular roadmap of customer interactions—uncovering critical points of failure in your CX strategy.
Plus, you can drill down into what your customers want at any given time, allowing you to predict future trends and personalize your experience. Ultimately, it contributes to better customer satisfaction and revenue growth.
If you’re looking for such a solution, here’s a quick intro to our product:
Like what you see? Book a demo and take the first step in decoding your customers' journey, one interaction at a time.
FAQs:
- What is a CX insight platform?
A CX (Customer Experience) insight platform is a tool or software that helps businesses gather, analyze, and interpret customer feedback. It allows companies to collect feedback through various channels and convert that into readable and actionable insights.
- Why do CX insights matter in business?
CX insights matter as they tell how your customer perceives your company. You can uncover their pain points and preferences without repeatedly reaching out to them. Plus, you can use a data-informed approach to improving CX—resulting in better outcomes.
- What are the main components of CX?
CX includes four components, according to McKinsey: brand, product, price, and service. Here's what that means:
- Brand: Focuses on how customers perceive your company and its reputation.
- Product: Focuses on customer interactions with the company's product or service.
- Price: Focuses on the cost of a product or service relative to the perceived value it offers.
- Service: Refers to the level of customer support and service provided before, during, and after a purchase.
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