What is a customer behaviour analysis?
Customers’ habits, such as how much they post on social media, when they look at your products and what drives them to buy, is all encompassed by the term “customer behaviour”.
It describes how customers shop, from how often they make a purchase to how they respond to your marketing campaigns.
Understanding this behaviour will help you make predictions about what comes next and adapt your strategies for – from product to sales and marketing – to better reflect your customer’s behaviour patterns. When you provide a customer experience that meets your customers’ needs, you’re more likely to drive sales and maximise your ROI.
Customer behaviour analysis, as this process of understanding is called, can go to a granular level of detail on your customers. Customers don’t always do what they say they will, so customer behaviour 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 behaviour. You can use a customer behaviour analytics tool to help you surface trends and actionable insights from large quantities of customer data.
When you take this consumer behaviour analysis and action on it to improve your customer experience you can drive customer retention and increase your revenue.
Why is customer behaviour 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 ROI and customer satisfaction
Here are the top reasons why customer behaviour analysis is important for businesses:
Identifying patterns helps you make accurate predictions for the future
Getting to grips with customer behaviour 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 analysing patterns of behaviour, you can deliver interactions that meet and exceed these expectations and drive profit by giving your audience exactly what they’re hoping to find.
Drilling down on existing customer behaviour helps you win over new customers
Completing customer behaviour analysis doesn’t just give you insights into your existing customers – it can help you win over new ones.
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 behaviour 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.
Personalising 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 behaviour, 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.
Personalising experiences can drive ROI. With the right analysis and taking into account behaviour and feedback, you can offer experiences that customers will love. Bespoke customer journeys that mirror how customers would naturally behave will remove friction and optimise the process, in turn increasing the likelihood of an increase in conversions and revenue.
Understanding behaviour helps you to retain customers for longer
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 minimising usage? What actions will convince them to stay?
Analysing customer behaviour will help you to identify pain points and inform the best solutions. Then, you can optimise the journey based on your customer preferences. This will help you reduce customer churn because you’ll be minimising frustration and reasons to leave.
With 65% of your business likely to come from existing customers, you can’t afford to ignore customer behaviour insights.
How do you perform a customer behaviour analysis?
You understand why it’s useful to identify customer behaviour, but how do you go about finding and analysing it?
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 behaviour 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: factors that might affect their choice to buy
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?
2. Gather qualitative and quantitative data on customer behaviour
Once you’ve identified who your customers are – particularly your revenue-generating customers – in segments, you’re able to start evaluating their data for customer behavior 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)
Qualitative data can give you the “why” behind customer actions (or lack of, in some cases)in their own words.
3. Evaluate your data for behaviour insights
Looking at the data you’ve gathered, you can start evaluating your information for behavioural insights. Ideally, you will use a customer behaviour analytics tool to help you – you might have large quantities of data to parse.
Customer behaviour: types and approaches
Consumer behaviour 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 behaviour and theories outlined below.
What are the 4 types of customer buying behaviour?
- 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 Behaviour: What do customers regularly seek out and buy? How does this differ from segment to segment?
- Variety-Seeking Buying Behaviour: 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 behaviour 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 recognising 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 behaviourist approaches: This theory suggests that consumers’ behaviour 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.
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 behaviour analytics tool will help you to identify patterns, as it can automatically surface trends and predict future behaviour. 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 customer behaviour analytics, 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 analysed your data for customer behaviour analysis insights, you can more accurately see what the optimised experience is for your customers and how to deliver on it. You can start to take steps to minimise behaviour that you don’t want to see – cart abandonment, high bounce rates, failure to add payment details – and maximise the behaviour you do want to see.
However, this might mean tweaking your customer experience and buyer journey to better encourage this behaviour. 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.
Optimising your customer experience to better reflect customer behaviour
Customer behaviour analysis can help you to improve the entire customer journey, from initial research on a product and first interactions to the post-purchase sharing of feedback. Understanding behaviour and implementing appropriate changes helps you to deliver an improved experience, with the end goal being increased customer satisfaction and loyalty.
Qualtrics CustomerXM can help you to not only complete customer behaviour analysis, but to shape customers’ actions in future. Give customers the journey that exceeds their expectations and meets every need, based on the customer behaviour analysis insights you generate.
Shape your customer behaviour and drive your ROI.