The importance of customer analysis

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customer analysis

Customer analysis is the process of examining data and behavior to gain insights into customer preferences, needs, and buying patterns. It involves collecting and analyzing data such as demographics, purchasing history, interactions, and feedback to make informed business decisions.

Discover how customer analysis can revolutionize your business approach.

What common pain points can customer analysis address?

Customer analysis can address several common pain points your business may be facing:

  • Understand customer needs and preferences. Customer analysis provides insights into what your customers want, their preferences, and the features they value most. By understanding these aspects, you can tailor your products or services to better meet customer expectations.
  • Identify customer behavior patterns. By analyzing customer data, you identify trends in customer behavior. This can help you anticipate customer needs and provide personalized experiences.
  • Improve customer retention. Customer analysis can help you identify at-risk customers who are likely to churn. By understanding the reasons behind churn, you can take proactive measures to improve customer satisfaction, enhance loyalty programs, and increase retention rates.
  • Enhance marketing strategies. Customer analysis provides valuable insights for developing targeted marketing campaigns. You can create messages that resonate with different segments by segmenting customers based on characteristics and behavior. This leads to higher engagement and conversion rates.
  • Optimize product development. Customer analysis can guide product development by providing feedback on existing products or services. You can use analysis to identify improvement areas, develop features that align with preferences, and innovate based on needs.

Qualitative vs. quantitative approaches in customer analysis

Qualitative approaches in customer analysis involve gathering non-numerical data such as customer feedback, opinions, and observations to understand customer behavior and preferences. This method provides in-depth insights into customer motivations and feelings but may be subjective and harder to analyze statistically.

  • Ideal for understanding the "why" behind customer behavior.
  • Involves methods like interviews, focus groups, and open-ended surveys.
  • Helps in exploring customer emotions and perceptions.

Quantitative approaches in customer analysis involve collecting numerical data such as sales figures, website traffic, and survey responses to measure customer behavior objectively. This method allows for statistical analysis, trend identification, and comparison across different customer segments.

  • Choose quantitative analysis when you need to measure customer behavior objectively.
  • Suitable for analyzing numerical data and identifying trends across different customer segments.
  • Involves methods like surveys, questionnaires, and data analysis tools.
  • Helps in making data-driven decisions based on statistical analysis.

Deciding between qualitative and quantitative approaches depends on your research objectives, the type of data you need, and the depth of insights required. Combining both methods can provide a comprehensive understanding of customer behavior and preferences.

How can customer analysis improve product development?

Conducting customer analysis during the product development phase helps you gather valuable insights to guide pricing decisions.

Numerous factors contribute to the failure of new products. However, the primary cause of innovation failure is neglecting the customers' willingness to pay during the product design phase. Many businesses delay pricing decisions until after the product has been created. They embark on an expensive and lengthy process of hoping for profitability rather than ensuring it.

By engaging with customers early in the product development process, you guarantee not only the survival of your product but also its success. If you fail to do this, you won't be able to prioritize the features of your product. You cannot determine if you're creating something customers are willing to pay for until it's already on the market.

Feature shock refers to a situation where a product is overloaded with an excessive number of features. For example, you have feature shock if your product is excessively complex, difficult to articulate, and lacks distinctiveness. You've assigned a cost to a product and are optimistically awaiting results.

This typically stems from a genuine attempt to cater to everyone's needs and preferences. But it results in a product that pleases few. Such products are costly to make, over-engineered, and usually overpriced.

Instead of stuffing a product with numerous features, exercise moderation. Resist the urge to satisfy customers by offering excessive value unless they are willing to pay for it. Be cautious when your R&D team proposes a new feature but fails to explain its benefit to the customer.

You can categorize your customers based on their requirements, values, and willingness to pay (WTP). Subsequently, you can customize your products to suit each segment. You should organize features into distinct groups and develop packages or bundles catering to each segment.

Get accustomed to providing only basic quality and service levels to your price-sensitive segment rather than offering them everything. Product development requires the courage to eliminate features.

Consider Microsoft's example. They offer various editions of their Office suite, ensuring that distinct customer groups—such as businesses, households, and educational institutions—can choose options that best meet their requirements.

How does customer analysis help identify potential customers for a new product or service?

Customer analysis helps identify potential customers for a new product or service by analyzing customer data to understand their needs, preferences, and behaviors. By segmenting customers based on characteristics and behavior patterns, you can target specific segments most likely to be interested in your new offering.

Avoid adopting a universal solution. Your customer base is diverse, so your product should reflect that diversity. Instead, develop various versions of your product to cater to your key customer groups.

This concept is even applicable to a basic commodity like water. It's free when it's in a fountain but it costs $2 when bottled. If you add gas, it's $2.50, but if it's in a minibar, it's $5. It's the same water.

Your customers are unique, with varying needs, values, and willingness to pay. The best approach to handling this is to adopt customer segmentation.

Design and bundle different products for specific segments instead of creating a single product for the entire market. For instance:

  • Individuals seeking the top-quality product
  • Individuals who desire immediate possession
  • Individuals who prefer the standard edition
  • Individuals who are highly sensitive to price

Leverage segmentation as a guiding factor, beginning from the R&D phase. Continually investigate customer requirements, values, and willingness to pay.

For example, GPS device manufacturer Garmin has developed various products tailored for drivers, golfers, runners, hikers, and cyclists. Drivers receive traffic updates on their devices. Golfers receive information on their proximity to the hole and advice on avoiding sand traps and water hazards.

  • Start with data on customer willingness to pay. Group individuals based on their WTP, value, and needs information. This will help you identify your segments.
  • Don't be enslaved by statistics. The most statistically significant result may not necessarily yield a practical segmentation strategy. Look for distinct boundaries between segments — features one segment strongly desires, but others do not. The ultimate test is to ask your sales team if they can categorize their customers into the segments you identify.
  • Less is more. Begin with 3-4 segments, then slowly increase until you find the ideal number. Adding each new segment significantly increases the complexity of sales, marketing, and other departments.
  • Don't attempt to cater to every segment. Use market sizing to ensure a segment will generate enough revenue to justify it. Calculate how many customers you can attract and retain and at what price points. Then, distinguish the profitable segments from those that aren't financially viable. Remember: you're not required to cater to every potential customer. The products and services you create should align with your company's overall financial and business objectives.
  • Define the segments for effective targeting. Ensure every segment has clear guidelines for customizing your sales and marketing communications. This is crucial. When crafting TV ads, online banner ads, or any other marketing and sales communications, you must describe your target segments as accurately as possible.

How can international automotive companies convince potential customers to consider their brands? Check out our article on the importance of understanding target consumers.

Discover how we identified market priorities for a secure communications technology provider. Read the case study here.

How does customer analysis help attract and retain customers?

Customer analysis can help you identify at-risk customers likely to churn, enabling you to take proactive measures to improve customer satisfaction and loyalty. Here's an example of how this can work:

Identify the triggers for churn and quantify risk

Which customers am I about to lose? How can I recognize these signs? More importantly, how can I prevent them from leaving?

The solutions form the crux of successful customer base management. Knowledge is crucial in this context – you require organized and pertinent customer data as a groundwork. But how can you cultivate such a data repository?

Our customer base management platform, MyBase, amalgamates and harmonizes existing data sources, authenticates the enclosed data, and employs data analytics and machine learning algorithms to produce impactful insights.

Find out the exact value of your customers.

Let’s be honest: If one of your most profitable customers moves on to a competitor, it hurts much more than with a smaller, less profitable customer. To manage your customer base efficiently, it's crucial to determine your customers' lifetime value (CLV).

CLV serves as a unique element in your customer segmentation. It allocates a churn risk and a value to each customer and classifies them into a particular segment. This can also be paired with current segmentation, for instance, high-risk young professionals versus high-risk families. The resulting segment then becomes the defining factor for your churn prevention measures.

Use measures to reduce churn.

Retaining customers is much cheaper than acquiring new ones, so it’s vital to design a powerful customer retention strategy. Understanding your client's lifetime value, their propensity to churn, and the elements that instigate churn during their journey empowers you to formulate proactive retention tactics that foster loyalty among your most prized customers.

The churn triggers will direct you to the strategies to implement. Segmenting customers based on their lifetime value and churn likelihood will help you identify the customers on whom to focus these strategies.

Uncover new avenues for cross-selling, upselling, and deep selling

Reducing churn and enhancing customer retention are not the only crucial aspects of effective customer base management. High customer loyalty and future opportunities for upselling, cross-selling, and deep selling also significantly contribute to low customer turnover.

The likelihood of a customer churning decreases as they utilize more products or services. Recognizing the most appealing customers aids in directing your sales group and marketing initiatives efficiently. This way, you can goal-win users with high CLV and loyalty.

How to use customer analysis to address the needs of existing customers?

Customer analysis helps you understand what your customers want and value the most. You can tailor products or services to better meet customer expectations by identifying these preferences. For example, if customer analysis reveals a high demand for eco-friendly products, you may develop a new line of sustainable offerings to cater to this need.

It can also help you identify trends in customer behavior. By understanding patterns, you can anticipate future customer needs and preferences. For instance, if customer analysis shows a growing interest in online shopping, you can invest in developing a user-friendly e-commerce platform to meet this demand.

Growing customer expectations for effective digital solutions are creating challenges for many companies. Find out how our customer data analysis helped an international imaging company create effective segmentation to meet its customers’ complex needs. Read the case study here.

How Simon-Kucher can help

At Simon-Kucher, we support your customer analysis by leveraging our proprietary research methods and analytics tools.

  • Market research & segmentation analysis. Understand the needs and preferences of your target customers and segments.
  • Customer profiles and buyer personas. Understand how customers interact with your business. We create buyer personas and profiles based on demographic, psychographic, and behavioral data.
  • Marketing strategy. Increase ROI for your marketing efforts. We develop tailored marketing strategies that attract and retain customers effectively.
  • Customer journey map. We enhance the overall customer experience by identifying pain points in the customer journey and pinpointing areas for improvement.
  • Product development. We gather insights on product or service preferences to guide our product development efforts. We ensure that your offerings align with customer needs and expectations.
  • Customer retention. Maximize the lifetime value of existing customers. We analyze your existing customer base to identify cross-selling, up-selling, and retention opportunities.

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