XM Knowledge Base
Author: Rosemin Anderson
Subject Matter Expert: Topher Mitchell
What is customer behavior analysis?
Customer behavior analysis is the examination of your customers’ habitual or one-off actions relating to your business. You can use both quantitative and qualitative data to analyze current behavior and make predictions about future trends, allowing you to take action to improve your customer experience.
How customers shop and how often, how they respond to campaigns, what they post on social media about you – all this and more can provide useful data to analyze. When you’ve successfully understood customer behavior and what drives it, you can adapt your strategies for products, sales and marketing and more to better inspire the customer behavior patterns you want to see. When you provide a customer experience that meets your customers’ needs, you’re more likely to drive favorable behavior and therefore sales, while lowering your cost to serve.
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How extensive can customer data analysis be?
Customer behavior analysis can help you to see your customers on an aggregate level and really understand what’s going on. Customers don’t always do what they say they will, so customer behavior analysis can identify what’s really happening when they encounter your brand.
By examining customer-generated data and your own operational data using qualitative and quantitative approaches, you can identify how customers behave at each interaction and understand what drives that behavior. Customer-generated behavior could be data gathered through observation, tracking and analysis of their actions. Operational data could include financial data, customer or employee demographics, product ownership data and more.
You can use a customer behavior analytics tool to help you surface trends and actionable insights from large quantities of customer data.
Why is customer behavior analytics important for businesses?
Understanding how your customers behave and why they do it might sound like a nice-to-have, but why is it fundamental to driving business results and customer satisfaction?
Here are the top reasons why customer behavior analysis is important for businesses:
Identifying patterns helps you make accurate predictions for the future
Getting to grips with customer behavior trends helps you to see the pattern in the way customers shop with you or use your services. Do customers buy seasonally or at certain periods? Are there marketing campaigns – and value propositions – that are more effective in driving customers to purchase? Which stage of the customer journey, or parts of the experience, drives churn and what fix would make them stay?
Salesforce has found that 63% of B2C consumers and 76% of B2B customers expect brands to know and understand their unique needs and expectations. By analyzing patterns of behavior, you can deliver interactions that meet and exceed these expectations and drive business value by giving your audience exactly what they’re hoping to find.
Drilling down on existing customer behavior helps you win over new customers
Completing customer behavioral analysis doesn’t just give you insights into your existing customers – it can help you win over new ones. You can easily and effectively segment your audience by the deeper trends you discover.
According to Invesp, selling to an existing customer has a probability rate of 60-70%, but selling to a new customer is only 5-20%. The more you understand each segment of your current audience, the better you’ll be able to see how each type of customer behaves and what new customers of that type will be likely to do.
Better still, if you identify the behavior of customers who you think will spend the most, you can predict which new customers will follow in that trend and deliver them the optimum customer journey.
Personalizing customer experiences drive sales
You are constantly receiving relevant customer data. Customers are keen to tell you what they want, and when their experiences have not met or have exceeded their expectations. Tailoring your customer experience based on feedback and other customer data can go a long way to shaping customer behavior, rather than just waiting for it to happen naturally.
Our research on global consumer trends has found that two-thirds of customers believe companies should be better at listening to feedback, and 62% of them think brands should care more about them and their preferences. 60% of customers we surveyed indicated that if they felt cared for, they would buy more from a brand.
Personalizing experiences can improve business value. With the right analysis and taking into account behavior and feedback, you can personalize experiences at scale. Bespoke customer journeys that mirror how customers would naturally behave will remove friction and optimize the process, in turn improving the chance of an increase in conversions and business results.
Understanding behavior helps you to increase customer retention
Why do your customers stay loyal to your brand? Are there certain experiences (such as broken links or technical issues) that are driving them away or minimizing usage? What actions will convince them to stay?
Analyzing customer behavior will help you to identify pain points and inform the best solutions. Then, you can optimize the journey based on your customer preferences. This will help you reduce customer churn because you’ll be minimizing frustration and reasons to leave.
With 65% of your business likely to come from your existing customer base, you can’t afford to ignore customer behavior insights.
See how understanding customer behavior can improve the experience in real time
How do you perform a customer behavior analysis?
You understand why it’s useful to identify customer actions, but how do you go about finding and analyzing them?
Here’s our step by step guide to help you out.
1. Set out your segments
You’ll likely already have your buyer personas for your customer audiences, but it’s worth reviewing your customer segments in advance of starting your consumer behavior analysis.
You should understand customers’:
- Demographics: Age, gender, income, location, family status, annual Income, education level
- Personal background: Hobbies, interests
- Professional information: Industry, job title, company size.
- Values and goals: Beliefs, aspirations both personal and professional
- Challenges: Personal pain points, worries, needs, problems to solve
- Use of your product/service: how your brand is relied upon in their life
- Identifying information: social media use, potential for being an influencer in their online or offline communities, communication preferences
- Objections or barriers to purchase: external factors influencing their likelihood of buying, or company-generated issues that are preventing them from taking that step (such as a high price point)
It’s important to note that demographics aren’t the most useful for predicting customer behavior, though it is still valuable to track this data to see if patterns do emerge.
Ideally, you’re identifying the features of your ideal, highest revenue-generating customer – after all, you’re hoping to replicate this customer when finding new ones. Factors to consider include:
- Customer satisfaction: Who are your most satisfied customers? What do they identify as key to satisfying their needs?
- Customer lifetime value: Which customers/customer segment has the best overall value for customer retention?
Segmenting by customer lifetime value can be a very helpful way of separating out your audience and determining which customers to aim for in future.
2. Gather qualitative and quantitative data on customer behavior
Once you’ve identified who your customers are – particularly your revenue-generating customers – in segments, you’re able to start evaluating their data for patterns.
This information will fall into two types: quantitative data and qualitative data.
Quantitative data will include information such as:
- Purchase history (and product/service popularity)
- Website visits and views
- Social media engagement
- Conversion reports for marketing/sales activity
- How many customer service tickets they’ve raised and whether their issues were resolved quickly
Quantitative data will describe what is happening when customers take action.
Qualitative data will cover information such as:
- Direct customer feedback (collected through surveys)
- Conversation analytics data (such as emotion, intent and effort)
This type of data can give you the “why” behind customer actions (or lack of, in some cases) in their own words.
You can gather this information from a variety of sources: their online shopping habits and the data that generates with your company, focus groups, social media insights, user surveys and more. Gathering data can help you to build larger data sets to draw insights from, giving you a greater chance of understanding user behavior and purchasing decisions.
Ideally, you’ll have a consumer behavior analysis tool that allows you to automatically track and monitor each digital session, detecting frustration behavior, refining patterns and discovering the drivers of actions. You should be able not just to find data in text form, but also use session replay videos, mouse movement tracking and more to build a fuller picture of what’s happening.
3. Evaluate your data for behavior insights
Looking at the data you’ve gathered, you can start evaluating your information for behavioral insights. Ideally, you will use a customer behavior analytics tool to help you – you might have large quantities of data to parse.
Customer behavior: types and approaches
Consumer actions can fall into several types, and there are a few theories why a customer might behave the way they do. Your data might be reflected in some of the types of customer buying behavior and theories outlined below.
What are the 4 types of customer buying behavior?
- Extended Decision-Making: What research does a customer do and how much time do they invest before deciding to buy a product? This could include asking family and friends for references, reading reviews, looking at comparison sites and browsing a brand site for further information.
- Limited Decision-Making: Customers might be limited in what they buy due to availability. Are they buying a product because it’s the only option on the market?
- Habitual Buying Behavior: What do customers regularly seek out and buy? How does this differ from segment to segment?
- Variety-Seeking Buying Behavior: Sometimes, there’s several very similar options on the market. Customers might be driven to buy and try several of the same product over time to see what the differences are. Are your customers comparing you to others in your market offering the same thing?
What are the five consumer behavior approaches?
- The economic man approach: The theory that customers always choose the lowest price product when offered a range of similar products at varying prices. Customers are believed to be driven by making the “rational” decision when reconciling their need and the limited money they have to meet that need.
- The cognitive approach: The theory that consumers act with a particular mental process in mind. This includes recognizing they have a need, searching for information, evaluating their choices, making a purchase and then evaluating whether that purchase was a good one.
- The psychodynamic approach: Based largely on Sigmund Freud’s theories, this theory suggests that consumers are motivated to reduce conflict between what they want and what they should do. Consumers are believed to search for the maximum amount of gratification they can find while also doing what they “should” be doing according to society.
- The behaviorist approaches: This theory suggests that consumers’ behavior is shaped by stimuli and past experience. Negative and positive experiences serve as lessons to either avoid or do the same action again.
- The humanistic approach: This theory posits that consumers are all individuals, with their own subjective reasons for taking action. They’re always self-interested and their purchases will demonstrate their individuality in some way.
Identify patterns
Across your segments, what patterns can you see? For example, you might want to answer the following questions:
- How does a customer access your brand? Is it through online searches for products, social media posts, marketing emails?
- When are they most likely to purchase a product in terms of day, week, month, season?
- What stops them from completing a purchase? Is it a broken payment system or a price point?
- Alternatively, what drives usage? Is it ensuring payment details are added within the first hour of downloading a new taxi app?
- What functionality and design features of your website or purchase platform were a problem for your customers?
- What marketing or sales campaigns worked on them?
- What encouraged them to make multiple purchases?
- What did customers feel that made them make a purchase?
- Why were customers driven to make a purchase in the first place?
- How hard was it to make a purchase for these customers?
Again, using a customer behavior analytics tool will help you to identify patterns, as it can automatically surface trends and predict future behavior. Then, you have the tools to go and act on that insight.
Discover the truth of customer experience
What customers tell you and what you actually see happening can often differ. For example, your ideal customer might tell you in a feedback survey that they prefer to use Twitter to engage with your brand – but you might see that actually, your regular update email sent by your marketing team encourages more of them to buy your products.
When identifying patterns with consumer behavior analysis, discover the truth that lies between what customers say is happening and what is actually occurring. This information is the most useful for creating an optimum journey.
4. Adjust your customer journey and experience for better customer lifetime value
Once you’ve analyzed your data for customer behavior analysis insights, you can more accurately see what the optimized experience is for your customers and how to deliver on it. You can start to take steps to minimize behavior that you don’t want to see – cart abandonment, high bounce rates, failure to add payment details – and maximize the behavior you do want to see.
However, this might mean tweaking your customer experience and buyer journey to better encourage this behavior. For example, if customers often buy two products together, bundling them together and advertising this new bundle might sell more because you anticipate customers’ needs and reduce the effort of having to search for both products. Or perhaps sending a reminder email to ensure your new customer who has just downloaded your taxi app adds their card details so they can start using the app.
Optimizing your customer experience to better reflect customer behavior
Customer behavior analysis can greatly aid you in understanding customer behavior and then improving the entire customer journey, from initial research on a product and first interactions to the post-purchase sharing of feedback. Understanding behavior and implementing appropriate changes helps you to deliver an improved experience, with the end goal being increased customer loyalty and decreased cost to serve.
Qualtrics® XM for Customer Frontlines® can help you to not only help with customer behavior analysis, but to shape customers’ actions in future.From adding further detail to your customer journey map to building hyper-specific marketing campaigns, you’re able to predict behavior in an ongoing process that becomes more accurate over time.
Give customers the journey that exceeds their expectations and meets every need, based on the customer behavior analysis insights you generate.
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