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How To Use Customer Analytics The Right Way (And Why It Matters)


The most important people to any brand should be the ones they are trying to reach: their customers. Customer analysis tells you who your customers are and what influences their decisions. Key metrics related to your customers can give you critical insight into why your sales figures are in their current state. If you want to improve your bottom line, you need to really understand the customers of today, so you can attract them, retain them and develop them.

Consumers are more informed and far more opinionated than ever, and with endless information available at their fingertips in seconds, they can be easily influenced by one another. If you want to thrive in a competitive world with such knowledgeable customers, you need to have a keen understanding of customer behavior. Customer analytics helps you make informed business decisions that are influenced by the choices your customers make. Everybody ends up happy!

Data from every step of the customer experience can help businesses strategize their marketing and sales efforts and lead generating strategies. Leveraging patterns in customer behavior through analytics can create a business map from a customer journey that is tailored to specific customers.

Benefits of customer analytics

Through predictive analysis drawn from data of interaction and transaction behaviors, customer analytics can help reduce customer churn and increase loyalty. This may sound like a bunch of technical talk but all it means is that studying what your customers have done in the past will help you better serve them in the future!

There are a few other reasons why customer analytics is important, let’s take a look.

Customer retention

Customer acquisition cost is a major financial burden. It’s cheaper to retain customers than acquire new ones. If you are unable to retain your customers, customer analysis can help you understand what caused them to leave. Once you realize the common denominators among lost customers, you can take corrective action. You can also engage proactively with existing customers to prevent further churn.

Increased sales and profitability

Customer service analytics, customer’s location, income, and customer profitability, are all important markers in your data set that you can use to boost conversions. Understanding purchasing decisions is the biggest factor in increasing sales. For example, if there are customers from a certain location who are more profitable than another, it’s beneficial to concentrate your marketing there.

You can shift your focus to high-value customers and interact and communicate with clients who are profitable, but only if you know who these top-notch people are  through customer analytics.

Customer engagement

The last thing you want is your customers or potential customers to leave your website frustrated and unsatisfied! Insights into customer pain points and the challenges they face can equip you to engage with your customers in a more relevant way. Customers will appreciate a customized experience, tailored to their exact needs. To provide a personalized customer experience you need to study customer behavior in detail at every step of the customer journey. Focussing on support queries, call center metrics, and post-sale concerns are of the most value here.

Validating expenses

When you make investments for your business based on data, no one can challenge you. If your customer analytics show that customers are returning orders because of incorrect deliveries, you can invest in inventory management software. It’s a necessity for your business to continue running and you have the data to prove it.

Implementing a customer analytics strategy

Now that you know what you have to learn about your customers, it’s time to put it into action! A robust customer analytics strategy is made up of the following elements:

Walk in the customer’s shoes

If you want to find areas of improvement, you need to walk through the entire customer experience as if you were actually a customer yourself. Interact with your own websites, call centers, and social media pages. Talk to customer-facing employees, judge how they interact with customers and ask them for their “voice of the customer” insights. See if your call center support staff is properly equipped to handle complaints. Do they know how to transfer a call? Can they calm an angry customer? Do you need to improve on customer service?

Walking in the customer’s shoes helps identify touchpoints to collect data from. Every customer interaction has a rich trail of data, from product choices to channel preferences to when and why they want to buy from you, versus the competition. Valuable sources of data include (but are not limited to) mail clicks, in-store visits, online purchases or browsing, and content streaming.

Ask the right questions

Once you know where to collect the data from, make sure the data answers the right questions. The information you have needs to help you gain a competitive advantage and improve your profits. If you have the technology, this can help you zoom in on the most granular level of data to find the right answers and develop the deepest possible understanding regarding your customers.

Validate data

Your data needs proper validation before being accepted for analysis. Ensuring data accuracy is of the utmost importance.

1. Your data operations team needs to have a dedicated resource to validate data.

2. Data needs to be complete.

3. Using a customer data analytics platform, you can collect, organize, and unify customer data to get a 360-degree view of a customer.

Data analysis

Analyzing data can help you match customer choices with customer personas. Especially choices that have a direct relation to your bottom line. It could be how they discovered your business, what they like most about your product, what brings them back, or why they leave. Other than data related to personal choices you also have customer demographics and personal information including job profile, age, gender, location, and income.

You can use artificial intelligence and machine learning to extract useful information and identify underlying patterns from all the data you have. Using these, you can then create a predictive model to forecast your business outcomes. Once the customer analytics framework is in place, you can continue to repeat and use the data to improve the customer experience.

Customer analytics best practices

That was a lot to take in so let’s recap what you’ve learned! Here are a few pointers to make sure you make the best data-backed decisions:

  • Organize your data to have clarity. Build complete unified profiles of customers or segments.
  • Take advantage of AI and machine learning to predict future outcomes more efficiently
  • Data can be sourced from voice-enabled smart devices. Listening to customers unveils a lot more about customer lifestyles and choices
  • Prioritize identifying at-risk customers and taking measures to increase customer retention.
  • Analyze all omnichannel customer interactions
  • Using customer segmentation to provide a personalized customer experience.

Customer analytics can help you a great deal in nurturing your customer relationships. The more you understand your customers, the better you will be able to predict their needs and that naturally means more sales for you. Happy customers = happy brand.

This originally appeared on Smile.io and is made available here to cast a wider net of discovery.
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