Customer Data Analysis Done Right: Recommendations & Best Practices

Due to the growing market competition, getting your message across to your target audience is becoming more challenging. Many businesses fail to find the right touchpoints with their customers due to the lack of knowledge about whom they need to target. One thing that stands between you and your customers is data analytics.

Customer data analytics in marketing affect sales and customer relations. Making the right picture of your client helps to understand their behavior patterns and brings useful insights on how to improve customer experience. For this, businesses use customer analytics tools developed to monitor consumer hot spots and make data-driven decisions. In the following sections, we discuss why data analysis is important and how it helps your company grow.

What is Customer Analytics?

Customer data analytics is a technology for examining customer behavior that provides organizations with valuable data for promoting their products and services. In other words, this is a set of tools, including statistical analysis, market predictions, data visualization, sales optimization, targeting, and segmentation, to help businesses understand the main triggers that drive customers' behavior.

Analytics is primarily used to identify the target audience, attract and retain customers. You can apply various models like churn, look-alike, and LTV to assess customers' status and revenue regularly.

Why Customer Data Analysis is a Must

Customer choices are based on particular beliefs, needs, or preconceptions. All details about when, where, and primarily why they are willing to purchase are essential for forming an accurate customer portrait. Successful businesses are focused on collecting this information to improve customers' interaction with a brand and achieve higher traffic monetization. Knowing your target audience is key to unlocking your customers' loyalty and building a robust relationship with them.

The significance of brand-customer relationships has constantly been rising, and many companies are shifting to a customer retention strategy. According to McKinsey surveys, the majority of businesses aim at existing customers, particularly fostering their loyalty and boosting sales to them. A money-oriented mindset is gradually fading into the background while customer satisfaction analytics is gaining more value.

Another regard for customer analytics platforms being an indispensable tool for customer attraction is highlighted in Forbes 2018 research. As much as 83% of respondents are convinced that data analysis contributed to a better customer experience, and 54% see an increase in sales and marketing efficiency.

Different Types of Customer Analytics

Customer Journey Analytics

The prime focus of customer journey analytics is monitoring users' interactions with a brand throughout the wholesales funnel. It begins with the first search query and finishes with the actual purchase and general service satisfaction. By analyzing customer data, you can see what’s happening at each stage of customer interaction analytics and use this information to your advantage.

Behavioral Analytics

When developing an effective marketing strategy, you cannot do it without customer behavior analytics. It is also necessary for your business to take proactive actions according to behavioral data obtained from multiple channels. For instance, companies can build a customer analysis to isolate friction points within certain conversion funnels. Analytics for customer engagement provides businesses with actionable data that helps them respond to user needs quickly and eventually increase sales.

Loyalty Analytics

If you want your business to thrive, you should focus not only on attracting new customers but also on retaining existing ones. Your ultimate goal is to understand the motivations behind your consumers' loyalty. To do this, you will have to gather a lot of information from various sources. Analytics can help you tailor your services to meet customers' expectations by identifying how they can be improved.

Retention Analytics

Compared to loyalty, retention analytics helps to make predictions better. In contrast, loyalty analytics measures satisfaction and the likelihood that users will recommend your product. Keeping customers loyal leads to growth, and keeping them on board prevents churn. Gaining knowledge on how to sustain actionable client data by raising retention and new user acquisition rates requires retention analysis.

CLTV Analytics

Customer Lifetime Value is one of the most crucial metrics in today's customer-centric corporate environment. Let's say you own a shoe business, and a customer has recently purchased a pair of boots from you. They could buy yet another pair of boots, sneakers, or any other thing in the future. How much you should contribute to keeping the relationship going should ultimately be determined by CLTV.

Feedback Analytics

Customer comments are used to enhance service and general company performance, as well as lower churn. Even if you were the market leader, client feedback might help you identify the ideal conditions for expanding and implementing innovations. The idea of gathering and analyzing customer feedback is also ingrained in the process of empowering consumers to speak out and have their voices heard.

How to Collect and Analyze Customer Data the Right Way

Collecting:

Web Tracking

Having a website is a great advantage since you can collect virtually all kinds of customer analytics data. Numerous useful pieces of information are left behind every time a consumer visits your website. Those may come in handy for your website's further promotion. For instance:

• What brought your clients here?
• How many pages did they browse after entering the page?
• For how long did they stay?
• Have they subscribed to your email list?

Transactional Data

You get transactional data after each purchase a consumer makes. The platform you choose to run your point-of-sale system will often automatically track a customer's past transactions like purchases, refunds, and other payments. Additionally, you may gather information on the search terms clients used to discover the product they finally decided to browse choices and the usage of coupons.

Surveys

Who, if not your customers, can tell what can be improved about your products and services? Conducting surveys is a good way to get constructive feedback and see if anything can be done to enhance the experience. You may do this through SMS, email link, or phone call. However, there is no assurance that clients will answer surveys, which is a drawback. Still, if you choose the appropriate time for doing surveys, you can get some helpful feedback.

Analyzing:

Defining your data analysis strategy

Asking questions and knowing more about your goals is the first step in using analytics for customer experience. Data analytics has to have well-defined objectives to be an effective business tool.

Collecting the data

The next stage is determining what kind of facts you must use to answer your queries. It is preferable to look into various sources, so you can get a different perspective. You will need to actively participate in doing consumer data analytics if you want to enhance the CSI and other important metrics.

Optimizing the collected data

You cannot draw inferences from the information you have acquired right away. The data is probably in its raw form, which will inevitably lead to misconceptions, distorted conclusions, etc. Data optimization, sometimes referred to as data cleaning, aims to rectify or eliminate unnecessary and inaccurate data and ensure that the gathered information is consistent and aggregated.

Performing the data analysis process

At this stage, you directly start analyzing the sorted data to understand specific behavioral patterns and develop new insights. Data analysis tools may help, especially if you have to deal with huge pieces of information.

Visualizing your results and putting them to use

After analyzing data and driving conclusions, it is vital to visualize your findings and make them easy to understand. The material must be comprehensible enough and aesthetically appealing, inspiring those who utilize it to make practical use of the facts.

How to increase sales with CDP: business case

You can do customer analytics with CDP Yespo. This omnichannel platform provides pre-made tools and actionable strategies for medium-sized online businesses. It allows marketers to integrate product feeds, select omnichannel campaigns, or configure their segments and workflows without much effort. This tool is a great solution for automizing many analytics processes and making quality marketing decisions based on analyzed customer data.

There are numerous successful cases when Yespo helped companies boost their sales by increasing customer retention. One of the customer insights examples is the Ukrainian pharmacy chain ANC. It has long been one of the most recognizable pharmacies in the offline space, but the digital one was its biggest weakness. They had a relatively poor customer service system, and since the pandemic ushered in a new era of artificial intelligence and online services, they decided to reapproach their communication with customers. The business has always benefited from digitization, and automation, so they turned to Yespo to see if it works for them. They made e-commerce their main priority, which allowed to increase their sales by 87% through rich messaging and by 34% via personalized mailing.

User Behavior is a Key to Higher Retention

Segment customers

When it comes to dealing with customers, a one-size-fits-all approach is proven to be ineffective. Different customers require different approaches. That is when segmentation comes in handy. It enables you to discover more about your consumers and make them want to buy from you. With this knowledge, you can modify your material to meet the specific requirements and difficulties of each group.

Set Behavioral Triggers

The trigger is an incentive, a signal that subconsciously encourages you to take a certain action. One of the most frequently used schemes is product shortage bias. It makes customers make faster decisions under the pressure of a limited quantity. Another trigger implies customers’ fears. Customers become vulnerable when you touch their deepest fears, so it gets easier to influence their feelings and actions.

Customer Data Analysis Best Practices

Specify the desired outcome

The first thing you should do before engaging in actual client data management is to determine an objective your company hopes to accomplish. Defining your goal correctly is 50% of plan compilation because you set your prime focus on what matters.

Prioritize

You may get overwhelmed with data without knowing how to make good use of it. If you try to include everything in your deep customer analytics, you might overlook essential discoveries and waste time. Consider cutting out everything that brings you minimum output.

Conclude

Once you know more about your customer, it is time to work on the big picture. You can gain a deeper understanding of your customer by generalizing without getting into details. Mining various data sources for insights is time-consuming and ineffective. What you need for your business is a real, unified customer data management platform that makes it simple to comprehend clients on an individual level and allows for quick, informed decision-making.

Implement

When your research is finally completed, you can move to the next stage — implementation. You can make smarter business decisions based on the results of the analyzed customer data, not your pure predictions.

Tools for Perfect Customer Data Analysis

Google Analytics

Google Analytics provides insight into online interactions by tracking user behavior and website traffic. It does not necessitate engineers to create data pipelines, unlike other alternatives. Instead, it extracts customers' information from the firm's website, using JavaScript to analyze user data activity. Moreover, it allows user-created segments to separate people based on characteristics or behaviors, highlighting their differences.

Google Data Studio

This is a web-based application for data visualization with embedded analytics capabilities that enables users to create personalized dashboards and clear reports. It helps in displaying patterns, comparing performances over time, and measuring traffic and important KPIs for clients.

Talkwalker

Create a detailed picture of your potential customer with Talkwalker. Whether you want to optimize your customer experience analytics, develop more targeted content, or just understand your audience better, Talkwalker's capabilities will get the job done. Quick search is among the useful features that sorts trending content depending on its relevance. One more cool thing about it is sentiment analysis, which can tell a lot about customer satisfaction with the services you offer.

Hotjar

Hotjar's website is truly a find for those who struggle with stats but want to be on the same page with their customers. Where most predictive customer analytics solutions provide you with a breakdown of traffic statistics, Hotjar tells you what visitors are doing on your website. It has Heatmaps with a visually appealing depiction of user activity on your website, which lets you know what captures visitors’ attention.

Brand24

Do not underestimate the importance of online reputation. The more people share and suggest your brand, the higher your brand awareness is. Brand24 knows that and helps you track reviews and brand mentions. Using Mentions Feed, you can speed up your intersection time significantly.

Yespo

Yespo is a customer data platform for your highest business efficiency. It concentrates on building strong relationships with customers through online linkers like emails, SMSs, product recommendations, and other means of communication. Knowing your customer contributes to their loyalty and retention, and also raises your brand value.

Woopra

Not knowing what your clients are doing is the most common challenge for numerous companies. Woopra gives you the ability to explore different types of customer data, so you can comprehend people from every viewpoint. They aid in the real-time development of thoroughly customized profiles for each customer.

Final Thoughts

Customer analysis is only one part of the whole marketing process, but quite a major one. It may sometimes be daunting and mundane, but its significance cannot be underrated. It offers a wide range of advantages that can lead to lasting success. Make sure you get the appropriate tools for the work.

FAQ

Why do I need customer data analysis?

Using customer data analytics is necessary if you want to find touchpoints with your customers and retain them in the long run.

Why choose Yespo?

Yespo platform is easy to work with, and it has a good reputation among other customer analytics tools with many success cases.

How do I select the right package?

You just need to go to Yespo and find the right package for your business that will meet your goals.

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