Gone are the days when customer experiences (CX) were limited to in-person stores. With CX being spread across multiple channels—a website, social media accounts, or customer support, it's hard to offer a consistently high-quality experience.
And with customer needs changing with the seasons, you can't keep track of all this information—at least, not manually. The sheer resources that go into monitoring each channel are far too much, and the cost increases over time.
The answer to these issues? Customers experience analytics.
In this article, we'll review how this works, its benefits, and popular use cases for this solution.
What is Customer Experience Analytics?
Customer experience analytics (CXA) refers to a solution that collects and analyzes customer data from different channels. The goal is to determine whether your current customer success strategy is working. You can also use it to decide whether you can meet customers at every step of their journey—whether that's the awareness or post-purchase stage.
On the TECHtonic show, Emma Sopadjieva, head of customer experience analytics at ServiceNow, said, “The role of analytics is critical to simplifying the customer experience. And it's not only about building a simpler product. I think a lot of companies focus solely on that. Like, how can we simplify the product? But it is about building a simpler customer journey, which needs to be frictionless, delightful, and valuable to customers. And that involves the work of every department, not just product, marketing, sales support, customer success, finance, even like the back office departments and beyond.”
And CX analytics enables you to prioritize the improvisation and simplification efforts across that journey.
Why is it important to measure customer experience analytics?
Here are a few benefits of investing in CX analytics solutions:
Dial into your customers' needs and wants
Customer needs and expectations change regularly. And it's challenging to monitor this through manual data analysis. So invest in CXA solutions that allow you to gain deep insights into their customers' needs, preferences, and pain points.
By understanding customers at a granular level, you can tailor your products, services, and interactions to meet and exceed customer expectations—ultimately driving customer satisfaction and loyalty.
Provide personalized experiences
CXA also enables companies to segment their customer base and create personalized experiences based on individual preferences. This level of segmentation allows you to create targeted marketing campaigns, tailored sales and customer support, and personalized recommendations. It builds stronger customer connections, enhances satisfaction, and increases the likelihood of repeat purchases.
Let's say you segment customers by location and analyze their behavior across email, SMS, and website. Your marketing team will know what kind of offers to send their way based on their browsing and purchase behavior.
Increase customer retention rates
It also helps identify the factors that drive customer loyalty. For instance, you can use tools like Dashbot to pinpoint the main themes of customer requests or topics leading to high churn rates.
This helps you understand the entire customer journey, proactively address pain points, streamline processes, and provide a seamless experience on all channels. This, in turn, boosts customer satisfaction and loyalty, reducing customer churn and increasing customer retention rates. By visualizing the user journeys, you can see where your customers are having the best and worst experiences with your brand.
Improve customer renewal rates
A Gartner report found that 82% of customers stay with a company if they get significant value enhancement throughout the engagement. But you can only know where these delightful experiences are happening by analyzing customer data across every channel.
This is where a CXA solution can help. It uncovers insights into customer behavior patterns that lead to goals or KPIs you’ve set such as order completions, renewals, and even bad experiences such as drop offs, negative sentiment conversations, and cancellations. By leveraging customer experience analytics, you will identify opportunities to cross-sell and upsell your product/service and understand where to allocate resources to reduce negative interactions.
Improves your bottom line
A recent Zendesk report found that 77% of business leaders who invested in CX solutions have seen it pay off. It shows that such investment directly impacts your financial performance.
Many companies need help unifying CX as they can't stitch the data from multiple channels. Over time, they'll be the ones that lag behind those who invest in such solutions. Only using a single channel analysis, such as reviewing survey data, is no longer enough in today’s competitive business landscape.
Ultimately, it drives customer satisfaction, loyalty, and advocacy—all of which lets you stay ahead of your competitors. And as customer acquisition costs rise, you reduce your organization’s costs by reducing churn rates over time.
Customer experience data: How to capture the full picture
Here’s a step-by-process on how you can compile and analyze data from multiple channels:
1. Identify what you need from the data
First, work out what you need from the data at hand, as that'll decide which datasets you'll go after and which channels you can get them from.
For instance, if you want to understand how post-purchase onboarding is going, you'll want to look at customer surveys and metrics like NPS scores, time to first value, and customer satisfaction rates.
You need to look inwards and run through existing data sources before analyzing external sources. This’ll also let you determine what gaps exist in your systems. Here are a few sources you can look at:
- Customer feedback surveys (qualitative and quantitative)
- Social media feedback
- Website interactions
- Chatbot transcripts
- Mobile app usage
- Desktop app usage
- SMS and MMS data
- Email support
- 1:1 call data
2. Choose the channels based on your goals
Choose platforms and customer touch points where you interact with customers. These include websites, mobile apps, social media platforms, email campaigns, CRM systems, point-of-sale systems, call center logs, and other relevant data sources.
Select the channels that provide the data points you require to understand the customer journey and experience comprehensively.
3. Consolidate data from these channels
Consolidating data involves aggregating and integrating customer data from various sources into a unified database or analytics platform. This step can be achieved through various methods, including:
- Data integration tools: Connect to different data sources, extract the relevant data, transform it into a standardized format, and load it into a central database.
- Application programming interfaces (APIs): Automate collecting data from different platforms and pull it into a central repository using the platform's API, like Dashbot’s API.
- Data cleansing and normalization: Cleanse the data by removing duplicates and errors. Normalize the data structure and format to ensure consistency across all data points.
- Data analytics and visualization: Perform data analysis, apply statistical models, and generate reports or CX dashboards that comprehensively view the customer journey and experience.
Alternatively, you can use tools like Dashbot that automate the entire data unification process. All you have to do is connect the data source(s) and begin to analyze the data. Dashbot uses proprietary language learning models (LLMs) and Machine Learning (ML) to extract customer insights from unstructured data, giving you a complete overview of your customers' needs that goes beyond traditional singular metrics.
Use cases of customer experience analytics
Here are a few ways in which you can use CXA solutions in your organization:
Unify customer data from different platforms
By unifying this data, you gain a holistic view of your customer's needs and the most pressing issues they face. This lets you understand their behavior, preferences, and needs across different touch points. Ultimately, it empowers you to create personalized experiences, make data-driven decisions, and enhance customer satisfaction.
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Map customer user journeys accurately
CXA solutions provide insights into how customers navigate digital interfaces and engage with different touchpoints. These tools allow businesses to map customer journeys accurately, visualizing the paths customers take, their actions, and the drop-off points in their journey.
By understanding the customer journey, you can identify areas for improvement, optimize user flows, and enhance conversion rates—ultimately improving the overall digital customer experience.
Understand the Voice of the Customer (VoC)
Understanding VoC goes beyond processing data from one channel. Most CX leaders struggle with getting a complete picture because they're unable to process multiple data sources. If you want to expand your VoC coverage, you need a solution that helps you do that—like CXA.
CXA solutions like Dashbot ingest as many sources as needed and automate the entire process. This makes it simpler for you to analyze the shortcomings in your CX program.
Train support agents with hard-hitting data
CXA data can also be used to train support agents effectively. Businesses can identify common issues, recurring questions, and areas where support agents may need additional training or resources by analyzing customer support interactions.
Armed with the data, support agents can provide more efficient and tailored assistance, improving customer satisfaction and faster issue resolution.
Reduce support costs through automation
It also becomes easier to identify repetitive and low-value support queries. Run your data through Dashbot and pinpoint which queries can be automated or resolved using self-serve options. Ideally, 30% of your work can be automated. Why not streamline these processes and let support agents focus on high-value interactions?
For instance, you can feed your unstructured customer data into Dashbot’s Conversational Data Cloud, which transforms that data into actionable insights—without input from your end. This type of CX automation reduces the volume of routine inquiries, frees up support resources, and lowers support costs. You can allocate their support teams to more complex and value-added tasks, improving efficiency and overall customer experience.
Improve your CX program with customer experience analytics
Your CX program is only as strong as the insights you have in hand. And when you’re dealing with omnichannel data, stitching it up to give you a complete picture of your customer’s expectations is a massive challenge. But with customer experience analytics tools, you can fill this gaping hole in your CX strategy.
Solutions like Dashbot can help you make data-driven decisions to optimize your CX operations, from unifying customer data across platforms to mapping customer journeys accurately. Ultimately, this results in improved customer satisfaction, brand perception, and revenue growth.
Interested in learning how Dashbot can help you analyze your customer experience across the board? Book a demo with us today.
FAQs for Customer Experience Analytics:
- What is CX analytics?
Customer experience analytics (CXA) is a solution that collects and analyzes data from various customer interactions with a business. This data can include website usage, social media engagement, customer service interactions, and more. CXA aims to gain insights into how customers interact with a business and use that information to improve the overall customer experience.
- How do you analyze customer experience data?
You can analyze customer experience data in three steps:
- Identifying what you need from your data sources
- Choosing the channels where you’ll source the data
- Consolidating the data and feeding it into a CXA solution
- Why are CX analytics important?
CX analytics are essential because they provide valuable insights into how customers interact with your business. You can identify pain points and areas for improvement and use this data to make data-driven decisions and implement changes that will ultimately lead to higher customer satisfaction and loyalty.
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