How to Conduct Effective Customer Analysis

When it comes to retail and ecommerce, it’s all about the numbers — not just revenue and profit, but data that gives you insight into how your customers interact with your company, what drives their purchasing decisions and what keeps them coming back.

In other words, customer analysis. Customer analysis helps you identify your target customers, anticipate their purchasing needs, and then use both qualitative and quantitative data to ensure that your product satisfies those needs – leading to happier customers who are likely to buy from you again, increasing your lifetime value.

It’s a way to understand the “who” and “how” as it relates to your customers and your company. And according to a KPMG survey, 92% of C-level executives are using data and analytics to gather marketing insights, and 81% use those analytics to learn more about and understand their customers.

Here, we’ll explore the benefits of customer analysis, how to conduct it, and why it’s so important for your business.

What is customer analysis?

Customer analysis is a method of using the data you have about your customers – from their demographics to their purchasing behavior – to understand more about their habits, preferences, needs and decision-making. The goal of customer analysis is to get to the root of what your customers are looking for when they shop for the products you sell – and how you can position your business to better meet those needs, from your marketing campaigns to your online or in-store shopping experience to what happens post-purchase.

Customer analysis can tell you:

  • Who your customers are and what they have in common – or what makes them unique
  • What their needs are
  • What influences their decision-making
  • How long their decision-making process is
  • How much they’re willing to spend
  • Whether and how often they’re likely to make repeat purchases
  • What content, products and campaigns resonate best

Together, these insights can help you understand who’s purchasing your products, and what you can do to better position your business to acquire and retain those customers.

Benefits of customer analysis

Why should you do customer analysis? There are myriad reasons — namely once you know your customer and their pain points, you’re in a better position to meet their needs — but other benefits of customer analysis include:

Personalized content

When you have a better understanding of your customers’ preferences and the “why” in how they shop, you can better tailor your content to meet their needs. This is important, because 80% of shoppers are more likely to buy from an ecommerce business that offers personalization, and 59% of customers reported that personalization influences their decision to buy.

Optimized marketing campaigns

When you have more accurate data from customer analysis, you can use that information to optimize your marketing campaigns. This allows you to narrow your focus and engage customers in their preferred channel, with an impactful message, at the right time.

Customer retention

By knowing what your customers prefer, you’re in a better place to attract — and retain — loyal customers. It’s important to acknowledge your loyal customers, as 49% report that they expect special recognition for their loyalty, and a 5% boost in customer retention can increase profits 25% to 95%.

What data do you need to perform customer analysis?

Now that you know the benefits, it’s time to move on to the data that will help you perform your customer analysis. While there is a lot that goes into a customer’s journey with your business, here are some of the metrics that can help you shape your customer analysis — most of it easily available in Glew.

  • Demographic data like name, gender, age, revenue, geographic location and lifestyle
  • Most frequent sales channel — ecommerce, brick and mortar, or both
  • The email, social media, and advertising campaigns they’ve interacted with successfully
  • The amount that they’ve spent with your company/customer lifetime value
  • Their average order value – how much they tend to spend with you per purchase
  • How they originally found your business
  • Order information — products purchased, dates, how often they purchased and when they most recently purchased
  • Cart abandonment information — total number of products and value abandoned
  • Information about reward/loyalty program, such as when they enrolled and if/when/how they redeemed their rewards
  • Whether they use discount codes frequently or only shop full-price items
  • Whether they return items frequently or not

These data points can come from a number of different sources – your ecommerce cart, your retail locations, your marketing channels, your customer loyalty and support platforms and more – so having all of that data, easily accessible in one place, is key.

Get better insight into your customers with Glew

Glew’s advanced customer analytics and segmentation help you understand your buyers and their purchasing behavior, for smarter and more profitable customer acquisition and retention. Start a free trial to get powerful insights about your customers today:

Start a Free Trial

How to conduct customer analysis effectively

There are a number of ways to conduct a customer analysis — everything from automated reporting tools and Google Analytics to good old fashioned spreadsheets. Your needs will depend on your business’s preferences, but the key is to get enough data to analyze every aspect of your customers’ interactions with your business. Here are the first basic steps you should take.

1. Segment your customers

No two customers are alike, and they all interact with your brand in unique ways. The first step is to get a breakdown of your customers, which will allow you to target them with the most appropriate content and offers.

To categorize your customer base and develop buyer personas, use a wide variety of characteristics, such as demographic traits, online shopping habits, and other engagement tendencies like customer lifetime value. An ecommerce-focused analytics tool can help by automating this process – Glew provides 25+ pre-built customer segments, as well as the ability to easily filter data to create your own customer segments, including:

  • X months since last purchase
  • Recent purchasers
  • Active, at-risk and lost customers
  • Paying customers
  • Recently refunded customers
  • High AOV
  • Low AOV
  • Full price customers
  • Value shoppers
  • Repeat customers
  • First purchase customers
  • VIP customers
  • Big spenders
  • Big ticket shoppers
  • Small ticket shoppers
  • Refunders
  • Most active customers
  • Never purchased
  • Abandoned carts

2. Identify their needs

Now that you have buyer personas, it’s time to figure out why they chose your business and the pain point you’re solving for them. Did they purchase out of convenience? How much were they willing to spend? Did they consciously seek your brand out? Are they likely to purchase from you again – and when? Perform this exercise for each of the buyer personas you identified in step 1. Once you think about the context of your buyers’ needs, you’ll be in a better position to gear your outputs towards meeting those needs — which is the next step.

3. Determine how your brand meets those needs

The initial research is done: you have your buyer personas, and you know what their main goals are. The next step is to determine how your business specifically can solve your customers’ problems. The goal is to make their purchasing experience as seamless and easy as possible, so now is the time to focus your efforts on the data-driven insights you’ve gained. Think about what experience each buyer persona might prefer – what products and price points they might be most attracted to, what marketing channels and strategies will work best on them, and how you can create a purchase and post-purchase experience that promotes repeat visits and customer loyalty.

4. Apply your analysis

Finally, capitalize on all of this data you’ve collected by optimizing the way you connect with your customers and prospective customers. Each persona will respond differently to different channels and types of content, so use it to personalize the buying experience. With the insights you’ve gained from conducting your customer analysis, you’re in a better position to optimize your marketing campaigns, driving key metrics like total sales, average order value, lifetime value and repeat purchase rate.

Focus your efforts by thinking about what your goals are here – are you trying to acquire more new customers in a certain customer demographic, or retain more of your existing high-value customers? Are you trying to boost lifetime value over time or get each of your customers to spend more with you on a single purchase?

How to use customer analysis for your business

So — what does all of this mean for your business? By conducting a thorough customer analysis, you’ll gain insight into your customers’ behavior that allow you to focus your marketing efforts better. The data you’ve collected can help you steer more potential customers your way, provide them with a more streamlined and personalized experience, and ultimately increase brand loyalty and customer retention. That means greater efficiency in your marketing efforts, and added revenue for your bottom line.

Your customer data will also help you identify which advertising campaigns are most effective and predict future consumer behavior, which is more important than ever given the competitive ecommerce market — a market that’s estimated to have 2.05 billion global digital buyers in 2020. Companies that pay attention to their customers’ behavior and preferences will have the most success — now and in the future.

Don’t forget these key takeaways:

  • Customer analysis helps you identify your target customers, anticipate their needs, and then use data to ensure that your products and services satisfies those needs
  • Customer analysis allows you to provide personalized content and marketing campaigns for your customers, which leads to stronger customer acquisition and retention, as well as increased brand loyalty
  • Data points needed for customer analysis can come from your ecommerce cart, retail locations, marketing channels, CRM, customer loyalty and support platforms and more – and can include things like demographic data, purchase behavior, marketing campaign interactions, spending habits and more
  • Effective customer analysis includes segmenting your customers, identifying their needs, determining how your brand meets those needs, and applying that data to your business practices in order to optimize your experience for your customers

Smarter customer analysis with Glew

Glew makes customer analysis easy, with all your data sources and all your customer information in one place. View customer profiles, build customer segments, analyze purchasing behavior, and access data from marketing campaigns, loyalty platforms, customer support and more.  Start a free trial today:

Start a Free Trial