You probably know your best friends pretty well -- their likes, their dislikes, where they shop, what brands they prefer and why. You can probably even predict what they're going to buy before walking into a store. This comes in handy when finding them a birthday gift, but wouldn't it be great you if knew your customers this well, too? While that goal may seem like a reach, conducting a customer behavior analysis is a great place to start.
What Is a Customer Behavior Analysis?
A customer behavior analysis is a qualitative and quantitative observation of how customers interact with your company. Customers are first segmented into buyer personas based on their common characteristics. Then, each group is observed at the stages on your customer journey map to analyze how the personas interact with your company.
A customer behavior analysis provides insight into the different variables that influence an audience. It gives you an idea of the motives, priorities, and decision-making methods being considered during the customer's journey. This analysis helps you understand how customers feel about of your company, as well as if that perception aligns with their core values.
Why should you conduct a customer behavior analysis?
Performing a customer behavior analysis is becoming increasingly important for both B2C and B2B companies. This is because of a growing need for highly-personalized content that's unique to each customer. According to Accenture, 41% of customers switched companies last year due to poor personalization. However, you can't personalize content until you have a complete understanding of your customer's preferences and tendencies.
Another key business need is the ability to predict a customer's overall value. A customer behavior analysis adds efficiency to this process by identifying ideal customer characteristics. By targeting these personas, your business can attract brand-loyal customers before your competitors do.
The data obtained from your customer behavior analysis should help with optimizing your marketing campaigns. Not only can you narrow your focus on the most valuable segment of your customers, but you can also engage them in their preferred channel. Additionally, this analysis can help you be sure content is delivered at the most effective timing. By identifying where roadblocks occur for each persona, you can increase the opportunities for upselling and cross-selling.
While it's important to attract loyal customers, it's just as important to retain them. Accenture reported that 49% of customers expect special recognition when they're a "good customer." Even if they like your company, these people may start to look elsewhere if you don't have a way to acknowledge them. A behavior analysis can help your team reduce this customer churn by identifying good and bad customer traits.
How to Conduct a Customer Behavior Analysis
1. Segment your audience.
The first step in conducting a customer behavior analysis is to categorize your customer base. When doing so, it's important to use a wide range of characteristics. Consider demographic traits such as gender, age, and location, but also be sure to include engagement tendencies like web activity, preferred media channels, and online shopping habits.
You'll want to identify the characteristics of customers who are the most valuable to your business. One way to do this is to perform a RFM analysis which outlines how recent and frequent a customer buys from you. Another way to do this to calculate customer lifetime value. Customer lifetime value considers metrics such as customer lifespan, purchase value, and frequency rate, then determines how much revenue the company can expect from that customer. This information gives you a quantitative picture of how much impact loyal customers have on your business.
2. Identify the key benefit for each group.
Each customer persona will have its own unique reason for choosing your business, and it's imperative to identify it. Look beyond just the product or service, and consider the external factors that influence the customer's buying decision. For example, was the purchase made out of convenience? Or did the customer make a conscious decision to seek out your brand? How urgent is the purchase, and how much does the customer want to spend? Thinking about the context of the customer's needs is a great way to determine where you can improve the customer experience.
3. Allocate quantitative data.
The first two steps help us extract qualitative data, but the next step is to obtain quantifiable information about your customers. While some resources may be more accessible than others, it's important to derive information from both internal and external sources. This ensures you get a complete picture of both micro and macro customer trends.
From within the company, you can pull stats such as blog subscription data, social media insights, and product usage reports. Secondary outlets can offer things like consumer reviews and competitor analytics. Third party data isn't specific to one company, but rather provides general statistics across an entire industry. Through the combination of the three, you'll have a broad scope information to work with when analyzing customer behaviors.
4. Compare your quantitative and qualitative data.
After you've collected your data, the next step is to compare the qualitative data against the quantitative. To do this, go through your customer journey map using the data sets as a reference. Look at which persona bought what product, when they bought it, and where. Did they return for another visit? By comparing the two sets of data against the customer experience, you can develop a detailed understanding of your customers' journey.
Once you compare the data to the customer journey, you should be able to pick out some recurring trends. Look for common roadblocks that seem to pop up at different lifecycle stages, and note any unique behaviors specific to a customer type. Circle back to your high-value customers, and be sure to acknowledge anything that stands out with their buying behaviors.
5. Apply your analysis to a campaign.
Now that you understand your customers' behaviors, it's time to capitalize on it. As we discussed earlier, you can use your findings to optimize your content delivery. Pick the best delivery channel for each persona, and take advantage of opportunities where you can personalize the customer experience. Nurture customers throughout the entire customer journey by responding to roadblocks in a timely manner. The insights you've gained from conducting your customer behavior analysis should give you a good idea of where you can make updates to your marketing campaigns.
Before rolling out your new initiatives, use your analysis to determine what your customers will think about these changes. Customers are habitual creatures, and some will push back on change even if it's for the better. These customers tend to be more loyal to your brand, so it's imperative you don't lose them as a result. Consider different ways you can introduce change to these customers, and remember to be receptive of their feedback.
6. Analyze the results.
Once you've given ample time for testing, you'll probably want to know if your changes worked. Use metrics like conversion rate, acquisition cost, and customer lifetime value to determine the effect of your updated campaigns. It's important to continuously analyze your results as new tech, politics, and events constantly influence customer needs. Revisiting your analysis frequently ensures you're capturing new trends appearing in the customer's journey.
Looking for some help with your conducting your analysis? Check out these platforms which are great for analyzing customer behavior.
As a former HubSpot support rep, I spent the last year working closely with HubSpot's analytics platform. HubSpot's reports and CRM features provide unique insight on both customer characteristics and engagement activity. You can use its reporting tools to view web traffic for contacts, and build lists based on their engagement history. HubSpot even offers an automatic attribution function that applies characteristics or scoring attributes once a contact completes an action.
Trifacta's "Wrangler" features an in-depth analysis of your customer data. The tool creates an automated visual representation to make it easy to identify trends and outliers. It then evaluates the data, and makes predictions and suggestions for where you can improve your customer experience.
Vertica is ideal for processing high-volume data requests coming from a range of resources. The tool takes advantage of underused servers in your data center to create a speedy and cost-effective organization of your data. This lets you upload more data on your customers without sacrificing any time. Vertica can also sync to Google and Microsoft cloud servers to ensure all data is stored in one location.
Price: Starts free; variable for premium tiers as reported by G2 Crowd