Customer Analytics For Dummies
Jeff Sauro
- English
- ePUB (apto para móviles)
- Disponible en iOS y Android
Customer Analytics For Dummies
Jeff Sauro
Información del libro
The easy way to grasp customer analytics
Ensuring your customers are having positive experiences with your company at all levels, including initial brand awareness and loyalty, is crucial to the success of your business. Customer Analytics For Dummies shows you how to measure each stage of the customer journey and use the right analytics to understand customer behavior and make key business decisions.
Customer Analytics For Dummies gets you up to speed on what you should be testing. You'll also find current information on how to leverage A/B testing, social media's role in the post-purchasing analytics, usability metrics, prediction and statistics, and much more to effectively manage the customer experience. Written by a highly visible expert in the area of customer analytics, this guide will have you up and running on putting customer analytics into practice at your own business in no time.
- Shows you what to measure, how to measure, and ways to interpret the data
- Provides real-world customer analytics examples from companies such as Wikipedia, PayPal, and Walmart
- Explains how to use customer analytics to make smarter business decisions that generate more loyal customers
- Offers easy-to-digest information on understanding each stage of the customer journey
Whether you're part of a Customer Engagement team or a product, marketing, or design professional looking to get a leg up, Customer Analytics For Dummies has you covered.
Preguntas frecuentes
Información
Getting Started with Customer Analytics
- Discover exactly what customer analytics is.
- Accurately measure with quantitative and qualitative data.
- Collect descriptive, behavioral, interaction, and attitudinal data from customers.
- Choose the right metrics, methods, and tools.
- Visit www.dummies.com for great Dummies content online.
Introducing Customer Analytics
Defining Customer Analytics
- Gathering data: Pull together customer purchase records, transactional data, surveys, and observational data at all phases of a customer’s journey.
- Using mathematical models to detect patterns: There are many number crunching, statistical analysis, and advanced modeling techniques that help turn raw data into more meaningful chunks.
- Finding the insight: From the patterns of the data come insights into causes of customer behavior.
- Supporting decisions: Understanding past behavior helps predict future customer behavior from data instead of relying on intuition.
- Optimizing the customer experience: Detect problems with features, purchases, and the product or service experience.
- Mapping the customer journey: From considering, purchasing, and engaging with products and services, mapping the touchpoints and pain points helps identify opportunities for improvement.
- Customer focused: The first word in customer analytics is customer. This means that the metrics collected need to come from customer actions or attitudes, or are derived in some way that’s connected to customers.
- At the individual customer level: You need access to the lowest level of customer transaction data, not data rolled up at the product or company level.
- Longitudinal: Customer analytics involves looking at customer behavior over time.
- Behavioral and attitudinal: You need a mix of what customers do and what customers think. Although customer actions (purchasing, recommending) are ultimately what you care about, attitudes affect actions — so measuring and understanding customer attitudes helps to predict future behavior.
The benefits of customer analytics
- Streamlined campaigns: You can target your marketing efforts, thus reduce costs.
- Competitive pricing: You can price your products according to demand and by what customers expect.
- Customization: Customers can select from a combination of features or service that meets their needs.
- Reduced waste: Manage your inventory better by anticipating customer demands.
- Faster delivery: Knowing what products will sell when and where allows manufacturing efforts to anticipate demand and prevent a loss of sales.
- Higher profitability: More competitive prices, reduced costs, and higher sales are results of targeted marketing efforts.
- Loyal customers: Delivering the right features at the right price increases customer satisfaction and leads to loyal customers, which are essential for long-term growth
Multidisciplinary
- Marketing: This encompasses the messaging, advertising, and the customer demographics and segments.
- Information Technology (IT): The IT department usually has access to the databases of customer transactions and data.
- Sales: Front-line contact with customers, knowledge of pricing, revenue, transactions, and reasons for lost customers are included here.
- Product development: This includes product features, functions, and usability.
Multimetric
- Revenue: Simple enough, this is your top line and you’re probably tracking this for your accountant already.
- Transactions: How many transactions are you completing in a given time frame? Digging deeper into the data, transactions become important for finding patterns.
- Customer Lifetime Revenue: The total top line revenue a customer generates over some “lifetime,” which can be days, months or years (see Chapter 6).
- Future intent: Will your existing customers buy from you again (see Chapter 11 and Chapter 12)?
- Likelihood to recommend: How likely will customers recommend your company and products (see Chapter 12)?
- Product usage: Which features are your customers actually using (see Chapters 10 and 13)?
- Website visits: Are potential customers finding your website and doing what you expect — finding information or buying a product (see Chapter 10)?
- Return rates: How many products are being returned due to dissatisfaction (see Chapter 11)?
- Abandonment rates: Did a customer start a transaction and then quit before completing (see Chapter 10)?
- Conversion rates: How many potential customers do you convert into actual customers (Chapter 10)?
- Satisfaction: Are customers satisfied with your product, company, and service (Chapter 9)?
- Usability: Do customers have problems using your products (see Chapter 15)?
- Findability: Can customers find the features they’re looking for in your products, or find what they’re looking for in your website? I discuss findability in Chapter 15.
Multimethod
- Surveys analysis: This involves collecting, analyzing, and ...