Customer analytics is an important part of any business's operational and marketing strategies. The insights you gather from customers can be incredibly beneficial and help you make improvements to your business.
With the wealth of data the average business accumulates in its day-to-day operations, it's important to have a clear strategy for collecting, sorting, filtering and analyzing the right customer data for your specific goals and needs. You can use this data to refine your business processes, improve the customer journey and engage in predictive analytics, but only if you identify the specific data you need.
"Customer data comes at you from many different directions, and it's not going to organize itself," said Spencer Fry, founder and CEO of Podia. "You can never consume all of the data your business collects, because it's like drinking from a fire hose. Being clear about exactly what data is actually useful to you, and being efficient about collecting only that data, will help you get real insights and action from your data, rather than simply collecting it."
Here's what you need to know about collecting the most useful customer data, analyzing it and implementing it effectively in your business.
What is customer analytics?
When your business tracks customer data and uses it to make informed business decisions, you're leveraging customer analytics. Insight into customers' behaviors can help you make changes to your sales, marketing, and product development strategies to boost customer acquisition, improve customer satisfaction, and continue growing your business. You can collect this data through various means, including software, online forms and AI-powered systems.
If your business is struggling in sales or can't figure out why a new product isn't connecting with customers, analyzing customer behavior and communications is an important first step in solving these problems. You can see what has worked with your customers (and, perhaps more importantly, what hasn't) and make informed decisions on what to do next.
Why does customer analytics matter in business?
In the digital age of constant customer connectivity, your business must be accessible consistently through desktop, mobile and social media platforms. Your customers expect a quick and seamless experience when buying products or searching for services. With consumers having less attention to spare these days, you have to make sure your business is targeting your potential clients.
This is where customer data analytics comes in. By knowing how your customers react to different tactics, you can improve your products and user experience to create a smoother experience for them. You'll grow your sales not with a big marketing campaign, but with relatively minor tweaks that cater to your audience.
Think of customer data analytics as a business cheat code for connecting with your target audience. It gives you direct insight into your customers' patterns and behaviors, enabling you to deliver communications, content and solutions that meet their precise needs better than your competitors can.
As global management consulting firm McKinsey & Company notes, companies that use customer data analytics comprehensively are twice as likely to outpace their competitors' profits as companies that don't. In other words, by investing in customer analytics, you put yourself ahead of the curve.
Buying, installing, and implementing the analytics software that can collect and organize your customers' data have costs. But the expenses to start using customer data analytics are well worth it: According to McKinsey's data, businesses that extensively use customer analytics see a 115% increase in return on investment.
Who uses customer analytics?
Marketing analytics is no longer solely the domain of tech companies: Any business can and should be using customer data analytics.
While you can apply it across all facets of your business, many companies find marketing analytics most useful in customer service, marketing and product development. Here are a few hypothetical examples of how small businesses can improve by properly leveraging customer data:
A brick-and-mortar clothing boutique saw great in-store success before the pandemic, but those sales numbers haven't carried over to its new e-commerce platform. The business decides to collect and measure customer feedback to learn more about the online shopper experience. This is called customer experience analytics.
Users share that it took too long to get a response from the customer service contact form when they had a product question, which discouraged them from completing their purchases. When the boutique owner combines this direct feedback from customers with the metrics they're seeing on their website – high bounce rates, low conversions and frequent cart abandonment – they discover an opportunity to build a better, more streamlined experience that could boost customer loyalty. The boutique installs a customer service chatbot and new helpdesk software to create a more intuitive, seamless experience, which directly leads to an increase in sales.
A once-popular pizzeria has noticed a decline in sales. The owner doesn't know why and decides to send out a survey to customers who have recently placed online orders. Through the survey, the owner learns that customers would prefer to see a wider variety of items on the menu, including healthier options.
The pizzeria adds a few new salads and wraps to the menu and sends an email blast to all customers who received the original survey link. The owner also runs local social media and search engine ads promoting the new healthier menu items. Because the pizzeria's customers feel heard, they begin to order from there more frequently, and sales pick up over the next month. This move increases the pizzeria's customer lifetime value by encouraging customer retention and driving repeat orders.
To take advantage of the COVID-inspired demand for cleaners and sanitizers, a cleaning supply company wants to bring a new multipurpose cleaner to market. The product development team invites a group of loyal customers to try out the new formula and asks for honest feedback through a simple online survey.
The beta group's biggest complaint is that the new product leaves streaks on glass. The company takes the product back into development and adjusts the formula to combat streaks. The beta group retests and approves of the new product, and the company enjoys a successful product launch.
How to implement a customer analytics strategy
With the right tools, every business has the ability to collect all types of customer data, but you may not know which is the most helpful for your business. Having a surplus of information can actually do you a disservice in the beginning if you don't know how you're going to use it and what your company's long-term goals are.
Rather than looking at all of your customer data and trying to make sense of it, Fry recommends segmenting your data and looking only at information about your ideal customers first.
"[Look at] those who have been happy, repeat buyers with high account value," he said. "This gives you a goal to work backward from: What does the data show about these customers in particular? Where do they come from? What actions do they take on your website? Often, this data differs greatly from your broader customer data set."
As you create and implement your customer analytics strategy, keep these four key factors in mind:
1. Know your customers.
Mapping your customers' journey helps you determine who they are, where they prefer to buy from, their preferred mode of purchase and how they communicate. Once you know who your customers are, you can build your strategy.
Do your customers have a high rate of opening your emails? Send more emails. Do they prefer Apple Pay over credit cards? Install more mobile payment options. When you know your customers' preferences, you'll better understand how to proceed.
2. Define your desired outcomes.
Before you start collecting data, it's important to know what you're looking to achieve. What problems with your company or sales are you trying to solve? These goals will define your analysis process and how you turn the data you collect into actionable insights.
3. Collect relevant data.
Strategize with your team on which data to collect and how you want to generate and process it. Whether you gather it from email surveys, online forms, helpdesk tickets, in-store visits, website browsing or blog comments, synthesize it and organize it all together in a single dashboard to look at the data patterns holistically.
4. Prioritize data security.
As a business, you have a responsibility to ensure your customers' data is safe and only used in appropriate ways. If you cut corners and don't prioritize security, it can open you and your customers up to fraud and identity theft. A data breach will also damage your reputation and your customers' trust in you, which will reflect negatively in your profits.
Kristian N. Thøgersen, president of the North America division at ViaBill, believes a business's No. 1 priority should be keeping its customers secure, especially if they are subject to regulations like the California Consumer Privacy Act and Europe's GDPR.
"Customers are protective of their data, and rightfully so," Thøgersen said. "Most customers will only agree to engage with your product or service if they trust you with their data – even more so if it's financial data."
Thøgersen advised businesses to be exceptionally organized when collecting and storing user data, ensuring the data is secure and never accidentally misused or exposed.
"Providing peace of mind to customers that their data is protected creates a sense of security," he said. "A track record of keeping data safe earns a brand loyal customers over time, too."