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Effective and Efficient Customer Behavior Analysis

June 19, 2017

How well do you know your customers? It’s a seemingly simple question that becomes increasingly difficult to answer as you dig into the nuances of customer preferences and habits in correlation with demographics such as age, gender, location, etc. But it’s worth the effort. Answering this question is the key to improving products, gaining new customers, increasing upsell or cross-sell opportunities with current customers, and reducing customer churn. 

What is customer behavior analysis?

Customer behavior analysis is the main strategy that marketing and sales teams employ to gain knowledge about their customers’ behavior—and not just in broad strokes, but the fine details. Customer behavior analysis can consist of questions such as: 

  • How often do my customers buy or use my product(s)? 
  • What influences my customers’ decision to buy or use my product(s)? 
  • Do my customers find my special offers/promotions valuable? 
  • Do my customers resonate with my brand? Why or why not? 
  • In what locations, times of day, etc. do I see spikes in product purchases or usage?

Steps to conducting a customer behavior analysis

There are a number of ways to conduct customer behavior analysis. Some studies might be more qualitative in nature, using in-depth customer interviews as the basis of research, while others are more quantitative, tracking numbers like purchases, clicks, sign-ups, etc. At some point or another, most companies will use both qualitative and quantitative methods as the basis of their customer behavior analysis. 

In either case, there are a few general guidelines to get started with your customer behavior analysis: 

  • Understand the specific questions you want to answer.
    It isn’t enough to perform customer behavior analysis because you want to “gather insights” about your customer. Hone in on a specific objective that corresponds with your business objectives.
  • Source the appropriate data.
    Understand how the data is generated and will be collected. For example, an organization could collect in-store sensor data to understand how customers move about the store. Or, they could look into purchase trends during a holiday season or sale. Or, they could interview their most loyal customers to better understand how and why they have remained loyal to the brand. Either way, it’s important to understand how the data will help answer the question at hand.
  • Select variables in your analysis to examine.
    Selecting variables can be tricky—too many, and the analysis will be clouded; too little, and the analysis won’t be complete enough. In a study around nationwide Black Friday sales, for example, it may be most important to assess particular demographics (age and gender, for example) in relation with the product categories they purchase to determine how the two are correlated on that particular shopping day. However, another customer behavior analysis example may be looking more closely at geographic data to understand how a particular product has performed yearwide in different areas of the country. 

Benefits of customer behavior analysis

The end result of successfully-run customer behavior analysis can yield tremendous results for a company, such as: 

  • Increased upsell opportunities.
    By analyzing what customers purchase, you can enhance your customer service representatives’ ability to provide your current customers with additional products they may need.
  • Personalized service.
    Strong customer behavior analysis will give you the data needed to personalize customer service experiences. Determine if your customers get better service using email, chat systems, or by phone.
  • Customer segmentation.
    You don’t serve just one customer. More nuanced segments of your customer base will allow you to more accurately target your customers, which will improve ROI while increasing overall customer satisfaction with your products and services.
  • Preventing churn.
    Targeting the wrong customer is a costly endeavor. By analyzing customer behavior, you will know exactly who you are targeting, and most importantly, what resources are needed to ensure that they stay with you.
  • Customer retention tactics.
    Here, experimentation is the key to success. Access and manipulate data from multiple points in order to measure the success of new tactics that are meant to gain, retain, or upsell customers.

Data fuels customer behavior analysis 

To be truly effective, customer behavior analysis shouldn’t be considered a one-time project, but must be done routinely and quickly. The good news? Companies have more data than ever to use as the foundation for customer behavior analysis. From the moment a customer even considers a purchase on a digital platform, a firm will have data about that person and their interactions with a product. This applies to B2C companies, of course, but increasingly to B2B sales, as well. Nearly 50 percent of customers will use social media, smartphones, and other digital platforms for their B2B purchases according to McKinsey & Company. These digital platforms give enterprises an ocean of data for marketers and salespeople to sift through.

But how does one plow through layer upon layer of structured and unstructured data to glean insights from customers? It certainly requires a more thoughtful data strategy than pieced-together Excel sheets. However, for many industries, connecting large, disparate data silos—much less putting that data to use—can feel like an insurmountable challenge.

Data preparation platforms help close the gap between businesses and their customers

To more thoroughly and intelligently prepare huge volumes of data for customer behavior analysis, many companies are adopting data preparation platforms like Trifacta. 

Trifacta offers a visual interface powered by machine learning that allows anyone to wrangle huge quantities of complex data themselves, rather than shipping out their work to IT departments. What’s more, data preparation jobs can be scheduled to be run as new data of the same kind comes in, allowing users to analyze ever-changing data like website activity or store sensor data faster than ever. And, since Trifacta can connect and manipulate data in a variety of formats, no customer touchpoint—whether in sales, customer support, or product usage after purchase—will go unnoticed.

The time saved preparing data can be used to reexamine and refocus the customer experience on a company-wide scale. Without Trifacta, preparing data for customer behavior analysis can be a burdensome task that is often done begrudgingly with haphazard accuracy. With Trifacta, users can get the most out of their data quicker and easier. 

Learn more about how Trifacta can improve your customer behavior analysis today.