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Customer Analytics: What It Is, How It Works, and How to Use It to Boost Your Business Performance

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Customer Analytics: What It Is and How to Use Them

<p><span style="font-weight: 400;">How well do you know your customer base? In the fast-paced environment of business today, it’s more important than ever to gain an in-depth understanding of your customers, especially if you have multiple customer profiles you are looking to attract. Customer analytics allows you to develop that in-depth understanding to better meet customer needs.</span></p>
<p><span style="font-weight: 400;">To set you up for success with using customer insights to make data-driven decisions in your business, we’ll cover what customer analytics involves, what makes this type of data collection so powerful, and best practices for using data analytics to improve customer experience and business outcomes.</span></p>
<h2><span style="font-weight: 400;">What is customer analytics?</span></h2>
<p><span style="font-weight: 400;">Customer analytics is a specific type of data analysis where valuable insights about customer relationships are obtained from customer data. By tracking and analyzing data sets such as customer behavior, demographics, and experience, businesses can improve how they serve customers.</span></p>
<p><span style="font-weight: 400;">The resulting conclusions can inform a variety of different processes including marketing campaigns, product development, and customer support. This has the power to improve both sales from new customers and customer lifetime value through repeat sales.</span></p>
<p><span style="font-weight: 400;">There are various ways to collect and analyze data about customers depending on what a business wants to learn about and what it wants to achieve.</span></p>
<h2><span style="font-weight: 400;">Customer Analytics Categories </span></h2>
<p><span style="font-weight: 400;">With a variety of different touchpoints for data collection and a variety of intended outcomes of data analysis, it’s important to understand the different customer analytics categories you could include in your data strategy.</span></p>
<h3><span style="font-weight: 400;">Descriptive Analytics</span></h3>
<p><span style="font-weight: 400;">This is data that paints a picture of what has already happened. It uses information from customer interactions to describe past events. So it could be used to explain why a </span><a href="https://www.podium.com/article/marketing-analytics/"><span style="font-weight: 400;">marketing campaign</span></a><span style="font-weight: 400;"> did or didn’t work, for example.</span></p>
<h3><span style="font-weight: 400;">Predictive Analytics</span></h3>
<p><span style="font-weight: 400;">Data science has developed a </span><a href="https://www.podium.com/article/what-is-customer-churn-prediction-how-to-improve-it/"><span style="font-weight: 400;">predictive quality</span></a><span style="font-weight: 400;"> so metrics can be used to foresee future outcomes. To be able to reliably predict future events, past and real-time data is analyzed to identify patterns that can reasonably be relied on to shape the future.</span></p>
<h3><span style="font-weight: 400;">Diagnostic Analytics</span></h3>
<p><span style="font-weight: 400;">In some cases, it’s useful to not just know what happened (descriptive analytics) but why it happened. Otherwise, it’s hard to replicate success or avoid mistakes in the future. Diagnostic analytics uses customer data to get to the root of problems for this purpose.</span></p>
<h3><span style="font-weight: 400;">Prescriptive Analytics</span></h3>
<p><span style="font-weight: 400;">So you know what, why, and a prediction of what’s to come. What should you do with that information? Prescriptive analytics interprets data to suggest the best action to take in a given situation. It can process various factors to produce the best possible decision in any scenario.</span></p>
<h2><span style="font-weight: 400;">4 Types of Customer Analytics </span></h2>
<p><span style="font-weight: 400;">The 4 categories of customer analytics can be applied to customer data specifically to answer questions you might have about customer interactions and how to achieve certain outcomes. When looking at customer analytics, you’ll probably be looking for insights within these 4 types.</span></p>
<h3><span style="font-weight: 400;">1. Customer Experience Analytics</span></h3>
<p><span style="font-weight: 400;">How your customers feel about your business matters. Collecting data about customer interactions gives you valuable insight into their experience of the business and whether it has a positive or negative impact on their perception. </span></p>
<p><span style="font-weight: 400;">For example, you could collect customer data during interactions with the customer support team such as how long it takes for inquiries to be resolved using webchat. You can also directly ask customers how they feel about your business through a customer experience survey like CSAT. This allows you to improve interactions and how highly customers rate their experience with your business. </span></p>
<h3><span style="font-weight: 400;">2. Customer Journey Analytics</span></h3>
<p><span style="font-weight: 400;">How do your customers go from not knowing your business exists to becoming loyal customers? By mapping the customer journey, you can better identify buying behaviors and therefore warm leads as well as opportunities for optimization to improve customer acquisition and retention. </span></p>
<p><span style="font-weight: 400;">To learn about the customer journey, collect data from key touchpoints such as your website. Track the sources of website traffic, the length of time spent on the website before buying, and what pages they looked at. This will highlight where leads are dropping off so you know where to focus your efforts.</span></p>
<h3><span style="font-weight: 400;">3. Customer Loyalty and Retention Analytics</span></h3>
<p><span style="font-weight: 400;">Your work doesn&#8217;t end after the first sale. Successful businesses foster a base of loyal customers who repeatedly purchase from the business. So as well as tracking how new customers convert, and track customer behavior after purchasing. </span></p>
<p><span style="font-weight: 400;">Monitor your customer churn rate (the period after which customer tends to drop off) to gain insights on how you can lengthen that time to improve </span><a href="https://www.podium.com/article/customer-retention-kpis/"><span style="font-weight: 400;">customer retention</span></a><span style="font-weight: 400;"> through measures such as elevating onboarding. With all the effort you put into acquiring new customers, you want to keep them as a customer for as long as possible. </span></p>
<h3><span style="font-weight: 400;">5. Customer Lifetime Analytics</span></h3>
<p><span style="font-weight: 400;">It’s also useful to know your Customer Lifetime Value which measures the total revenue gained from a single customer over the whole relationship. This puts things into perspective as it indicates the outcome of customer experience efforts and what can be reasonably spent on measures to keep customers. </span></p>
<p><span style="font-weight: 400;">This can vary by customer segment, highlighting which types of customers need extra attention. It also shows the type of customer that is most profitable to the business, suggesting resources should be focused on acquiring more of that segment of your customer base. </span></p>
<h2><span style="font-weight: 400;">Why Customer Analytics is Important for Businesses</span></h2>
<p><span style="font-weight: 400;">Businesses need to keep track of what matters to their customers in real-time to be able to forge a competitive advantage while operating in a highly competitive atmosphere. Trends come and go. New technology is always emerging. Customer needs, preferences, and behavior are inconsistent. It requires constant effort to stay ahead. Tracking relevant customer analytics can lead to tangibly better outcomes for businesses such as the following.</span></p>
<h3><span style="font-weight: 400;">1. Improved customer experience.</span></h3>
<p><span style="font-weight: 400;">With a better understanding of what it’s like for customers to interact with the business through customer metrics, the customer experience can be elevated to iron out any issues and make it even more convenient. This will ease the flow through the customer journey.</span></p>
<h3><span style="font-weight: 400;">2. Higher ROI.</span></h3>
<p><span style="font-weight: 400;">In a data-driven business world, businesses don’t have to resort to trial and error. They can track the impact of every initiative and campaign they run to ensure it’s achieving the intended results. Utilizing customer data prevents businesses from wasting money on strategies that just don’t work.</span></p>
<h3><span style="font-weight: 400;">3. Better business decision-making.</span></h3>
<p><span style="font-weight: 400;">When business leaders know what is going on in a business in real-time, they can make informed decisions to better serve their customers while still ensuring financial success. This is made even easier by combining customer analytics with AI and machine learning technology because a lot of the interpretation of data and decision-making can be automated.</span></p>
<h3><span style="font-weight: 400;">4. Increased customer loyalty.</span></h3>
<p><span style="font-weight: 400;">By implementing a customer analytics strategy, you’ll see key metrics improve such as customer loyalty, customer engagement, and customer satisfaction. That’s because the business is more in-tune with what customers want and what they are struggling with. It can meet and anticipate customer needs.</span></p>
<h2><span style="font-weight: 400;">Best Practices for Implementing Customer Analytics</span></h2>
<p><span style="font-weight: 400;">You will only gain results from implementing customer analytics such as acquiring and retaining more customers if the data collected is used effectively. The data collection itself doesn’t make a difference. It’s all about how the data is used. Here are some best practices to keep in mind when introducing your customer analytics strategy.</span></p>
<h3><span style="font-weight: 400;">1. Establishing clear goals and objectives.</span></h3>
<p><span style="font-weight: 400;">The type of customer analytics you collect and how you use the retrieved data all depends on what you want to achieve. So set clear goals and objectives to inform the whole data collection process. For example, collecting customer loyalty data is only going to be useful if you are working on improving customer retention. It’s not the most relevant to customer acquisition.</span></p>
<h3><span style="font-weight: 400;">2. Measure the right analytics.</span></h3>
<p><span style="font-weight: 400;">Choose carefully the specific analytics that will help you to meet your goals. Consider the categories (descriptive, predictive, diagnostic, and prescriptive) and the types (customer experience, customer journey, customer loyalty, and customer lifetime value) that best suit your purpose. Collecting a mix of qualitative and quantitative data allows you to get a full picture of the customer relationship because while numbers are easier to track, words give clarity to the reason behind the numbers. </span></p>
<h3><span style="font-weight: 400;">3. Choosing the right tools and technologies.</span></h3>
<p><span style="font-weight: 400;">Investing in customer analytics tools for the processing and interpretation of various data sources gives businesses the upper hand. All the customer data collected can be turned into easy-to-understand interpretations through data visualization. This makes the insights much easier to apply in the decision-making process.</span></p>
<h3><span style="font-weight: 400;">4. Building a skilled analytics team.</span></h3>
<p><span style="font-weight: 400;">With the rise of big data, there is a high volume of data spanning various formats. Therefore, customer analytics are best managed by a skilled analytics team who have a better understanding of how to glean results from such data sets. Getting the right talent eases the implementation of customer analytics.</span></p>
<h3><span style="font-weight: 400;">5. Ensuring data quality and accuracy.</span></h3>
<p><span style="font-weight: 400;">Any old data won’t cut it. The data you use to understand your customers and inform business decisions should be validated for quality and accuracy. This is standard practice for analytics processing. Your system should have multiple checks to ensure data is input and stored correctly.</span></p>
<h3><span style="font-weight: 400;">6. Monitoring and adjusting strategies based on results.</span></h3>
<p><span style="font-weight: 400;">Data analysis is a complex process. It can take time to get it right and for your business to be able to gain valuable insights about your customers and take action to improve your relationship with them. So monitor your customer analytics strategy and adjust as necessary to ensure you’re getting useful data insights that can inform improved action.</span></p>
<h2><span style="font-weight: 400;">Unlock the Power of Customer Analytics with Podium</span></h2>
<p><span style="font-weight: 400;">As an all-in-one marketing and communications solution, Podium is the hub of customer data essential to collecting, monitoring, and acting upon customer analytics. The </span><a href="https://www.podium.com/inbox/"><span style="font-weight: 400;">omnichannel inbox</span></a><span style="font-weight: 400;"> collates in a customer contacts </span><a href="https://www.podium.com/contacts/"><span style="font-weight: 400;">CRM</span></a><span style="font-weight: 400;">, tracking customer interactions throughout the customer journey.</span></p>
<p><span style="font-weight: 400;">You can expect improved customer engagement and loyalty as you can contact your customers over their preferred form of communication, whether social media messaging, </span><a href="https://www.podium.com/text-marketing/"><span style="font-weight: 400;">text messaging</span></a><span style="font-weight: 400;">, </span><a href="https://www.podium.com/phones/"><span style="font-weight: 400;">phone</span></a><span style="font-weight: 400;">, or </span><a href="https://www.podium.com/webchat/"><span style="font-weight: 400;">webchat</span></a><span style="font-weight: 400;">. Customer communication is well organized so it can be analyzed for better insights into needs and preferences. As the customer experience is elevated, you’ll receive more positive online reviews which you can track through our </span><a href="https://www.podium.com/reviews/"><span style="font-weight: 400;">review management</span></a><span style="font-weight: 400;"> tool. </span></p>
<p><span style="font-weight: 400;">These capabilities have resulted in increased revenue and profits for our clients. Find out for yourself with</span><a href="https://www.podium.com/free-trial/"> <span style="font-weight: 400;">our free trial</span></a><span style="font-weight: 400;">.</span></p>


Customer Analytics: What It Is, How It Works, and How to Use It to Boost Your Business Performance

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