The Impact of Business Analytics on Customer Experience

The modern consumer has a lot of expectations. Gone are the days when simply advertising a good product or service was enough. Research by McKinsey shows that 71% of customers expect personalized interactions with the brands they do business with, while 76% of customers are frustrated when this doesn’t happen.¹

The good news is that you have access to vast amounts of customer data from various sources, including social media, website analytics, and customer feedback. Using business analytics, you can analyze this data to understand consumer behavior, needs, and preferences, which will ultimately help you deliver a better customer experience (CX) and surpass customer expectations.

Keep reading to learn more about the impact of business analytics on customer experience.

Business analytics lets you analyze your customers’ past purchases, website behavior, and survey responses.² By doing this, you gain a deeper understanding of their needs and preferences. You can then use this understanding to tailor your offerings to meet your audiences’ needs more effectively. For example, after analyzing your customers’ purchase history, you can use the data to recommend complementary products—milk when someone is buying cookies, for instance, or tech accessories when a customer is browsing new phones. This can not only improve the customer experience but also increase the average order value, which supports business growth.

By using data analytics in customer service, you can identify behavior patterns among your customers.³ For example, you may notice that customers are leaving your website at a specific point in the purchasing journey. In this case, you can use analytics to identify the reason for this behavior and take the necessary measures to rectify the issue and improve the customer service experience.

Using data analytics, your organization can conduct customer segmentation: delineating separate groups of customers who share similar characteristics, preferences, and behavior.³ This allows you to customize product selections, marketing messages, and overall customer experience to align with the specific needs of the people in each segment. This sort of personalized attention can go a long way toward increasing customer satisfaction and loyalty.

By measuring and optimizing for better customer experience, you can increase customer satisfaction and brand loyalty. Develop a successful CX program by tracking these key metrics:^4,5

The NPS measures how loyal customers are to your brand and how likely they are to recommend it to their friends. This metric is measured using one question: “How likely is it that you would recommend our [company/product/service] to a friend or colleague?" The respondents can choose any number on a survey scale of zero to 10, where 10 means “very likely” and zero means “not likely.”

This measures how satisfied customers are with your products or services. Customers are asked to rate their satisfaction on a scale of one to five, where five means “very satisfied” and one means “very unsatisfied.”

Use the CES to measure the effort a customer puts in when interacting with your brand. For example, a CX team can ask, “How much effort did it take to get a resolution from customer support?” You can use a survey scale of one to five to measure this metric.

Business analytics offers a variety of techniques for improving customer experience with data. They include:

This technique uses algorithms to analyze customers’ reviews, social media posts, comments under blog posts, and other forms of communication to gauge their feelings toward your brand and products.⁶ Customer data analytics tools for conducting sentiment analysis include Brandwatch, Lexalytics, and MonkeyLearn.⁷

Sentiment analysis gives you valuable insights into what your customers like and dislike. Using this information, you can then improve your products and services to meet consumer expectations. If multiple customers indicate they have a negative experience with a specific product, for example, that’s a good indicator that an issue with the product needs to be addressed.

Journey mapping involves visualizing the entire customer journey, from initial awareness to post-purchase interactions.⁸ This process helps you understand how customers interact with your brand across different stages and channels. As a result, you can identify their needs, pain points, and expectations and discover new ways to improve your CX.

You don’t have to map out each customer’s journey manually. The various data analytics tools that automate this process include Adobe Experience Cloud, Figma, and Lucidchart.⁹

Your website is often the initial point of contact that your customers have with your company and/or brand. It sets the mood for their entire experience and should be optimized to make a good first impression. Conducting a thorough website analysis involves examining various aspects of it, including heat maps, scroll maps, and SEO performance.¹⁰ It helps you identify potential user experience issues, such as long page-load times or poorly placed buttons on mobile devices.

One of the particularly useful tools for web analysis is Google Analytics. You can use it to capture diverse types of user behavior data on your website, including page views, clicks, time spent on pages, and conversion rates. Analyzing this data helps you understand how users navigate your platform, so you can identify areas of confusion and optimize the user experience for better customer engagement.

CRM software manages customer relationships across different marketing channels, including email campaigns, social media platforms, and phone calls. With a CRM system that has strong reporting features, you can access the performance of each channel against its goals or key performance indicators (KPIs) and then use the insights you gain to improve customer experience across all channels.

Artificial intelligence (AI) and machine learning (ML) are transforming how businesses interact with their customers. You can use these technologies to improve your customer experience strategy:¹¹

AI-powered chatbots allow you to provide 24/7 customer support. Using techniques like ML, these chatbots can interpret intent, understand context, and provide nuanced responses, creating a user-friendly experience for your customers. By 2027, it’s estimated that a quarter of all companies will use chatbots as the primary customer support channel.¹²

AI algorithms can analyze historical data to anticipate customer needs and behaviors. This allows you to address customer issues proactively, before they even arise, and deliver personalized offers that are more likely to resonate with and appeal to each customer.

AI-powered speech and image recognition tools can analyze customer service calls and social media posts to extract sentiment and identify recurring themes. This gives you deeper insights into consumer feedback beyond individual interactions, enabling you to deliver data-driven customer service.

To gain true expertise in business intelligence, you need the Online MS in Business Analytics program from the Leavey School of Business at Santa Clara University. Through the innovative curriculum, you’ll become proficient in the latest industry technologies. Led by seasoned Silicon Valley insiders, this flexible online program provides dedicated faculty mentorship and networking opportunities with industry veterans. You’ll make new connections and unlock valuable career information—all with the freedom to study from anywhere and continue in your current job as you complete your degree.

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