Customer Analytics

Whether you are looking to determine new product offerings or develop a personalized marketing campaign, customer segmentation is the principal basis for allocating resources and extracting maximum value from both high and low-profit customers. Our experts use both demographic segmentation data and advanced clustering segmentation techniques to:

• Conduct market segmentation to unveil meaningful and measurable segments or microsegments according to customers needs, behaviors, demographics and social profiles
• Determine the revenue potential of each segment and target segments according to their profit potential and the ability of your company to serve them
• Obtain a complete customer profile to help predict future behavior through a 360° customer view
  Use target market analysis to tailor products, services, marketing and distribution strategies to match the needs of each segment
• Measure performance of each segment and optimize your segmentation approach over time

Understanding the customer life cycle and customer lifetime value offers benefits in budgeting, segmentation and prioritization. CLV ultimately helps you in forecasting and improving the overall health of your company. Key benefits include:

• Customer Acquisition and Retention: CLV gives you a better understanding of what you can spend to acquire customers and profitably retain them.
• Targeted Marketing: One of the major uses of CLV is customer segmentation, which starts with the understanding that not all customers are equally important. CLV-based segmentation model allows the companies to predict the most profitable group of customers, understand those customers’ common characteristics, and focus more on them rather than on less profitable customers.

Companies can identify customers who have a higher propensity of making an additional purchase and target them with innovative and personalized cross selling and up selling strategies. Cross selling and upselling enables you to reduce acquisition costs, increase wallet share and customer lifetime value. Analytical tools and techniques such as Acquisition Pattern Analysis and Collaborative Filtering analyze the patterns in the customer’s past behavior, correlate this information with similar customers, and then identify potential service or product opportunities at each contact with the customer. We can help you do the following:

• Identify and target prospective customers for cross selling
• Determine products or service offerings and optimum price point for each customer
• Build a scorecard to calculate the propensity of the target customers to purchase various products

Using Market Basket Analysis, our experts help you understand which product bundles are being purchased together by your customers, and in what sequence. Understanding the product combinations and the strength of these relationships is valuable information that can be used for making recommendations, cross selling and up selling, and offering coupons and promotions. Just a few years ago, Netflix offered a $10 million prize to improve the efficiency of its recommendation engine. Using our advanced algorithmic techniques, we have the ability to build recommendation algorithms that can outperform the engine Netflix built by 10 times. Here are some of the things we can help you do for your business:

• Assortment Planning and Shelf Storage: CPG companies can plan and create market-based, customer-based, fashion-based, and price-based assortment mixes. Putting co-dependent products close together improves the shopping experience and also allows for cross selling.
• Online media sites and retailers can inform content and product placement in a catalog.
• Build recommendation engines (like Amazon customers who bought this item also bought these items)
• Targeted Marketing: Based on past buying patterns, email customers with product and service offerings that would likely interest them.

We can build your product recommendation engine that understands the preferences and intent of each visitor and shows the most relevant recommendation type and products in real time. You can determine the Next Best Action for each of your customers at any point in time. Driven by models capturing life-event patterns, buying behavior, social media interactions, and other aspects, you learn which customers need to be approached and on which channel, so that you can create the right experience on all connected sales points. Here are our key areas of focus:

• 360° Customer View: A key to determining the next best action is having a complete picture of customers in terms of their profiles, needs and current behaviors.This requires being able to collect data from all channels that customers use to interact with an organization. It is important that this data is merged into a single source and available at the customer touch point to obtain meaningful insights not only to describe customer?s’ past behavior, but also anticipate future behavior.
• Event Marketing: Event marketing is the hallmark of Next Best Action. It identifies customer events that are key milestones to a customer. These key events can take several forms:
  • Major life changes (getting married, having a baby, buying a house etc)
  • Interactions with the retailer (purchase of products, call to express dissatisfaction etc)
  • Environmental and market changes (change in product pricing, competitor product introduction)
  • Analytics enables an organization to mine customer data to identify markers of these events and to send targeted, meaningful communications (for example, sending a special retention offer when a customer is thinking about switching to a competitor).
• Predictive Analytics: With predictive analytics, mine a customer?’s historical and transactional data to identify common behavioral patterns before a certain event, like ?making a purchase, upgrading a service or leaving for a competitor. Based on these patterns, a predictive model can determine if the behavior matches those that would indicate a future purchase. Common applications include predictive scoring for customer value, risk and profitability and market basket analysis to determine which products are often purchased together.
• Coordination of Channels: While next best action is often closely associated with inbound channels, it is also appropriate for outbound channels. Determination of next best action for outbound channels is possible by creating a unified data mart that has access to customer data captured by inbound channels. If the communications via various channels are not coordinated, each could deliver contradictory communications. We make sure that the processes that determine the next best action for each channel take into account the communication by the other channels and maintain consistency by adjusting the next best action as needed.

Given the high costs of customer acquisition in myriad industries, reducing customer churn through an intelligent segmentation of your customer base is essential to business viability. Leverage your customer data to reduce customer churn and reap maximum benefits from a well-segmented and thoroughly analyzed customer database.

Challenges and Opportunities

Customer attrition or churn is a rate that measures the number of clients whose business is lost over a particular timeframe. In highly competitive industries where substitute products or services are readily available and the cost of retaining an existing customer is significantly lower than the cost of acquiring a new one, reducing customer churn is the key to long-term profitability. Customer segmentation—dividing a customer base into geographic, demographic, behavioral, and income categories so as to more effectively target products and services—is the key to reducing customer churn. The better segmented your customer data, the more efficiently you can invest scarce resources in those consumers who are most likely to respond to your offerings and the more able you will be to iteratively refine your products and services so as to retain their loyalty.

The challenge for many businesses is that the data required to reduce customer churn is:

• Not gathered from across the organization using the best data mining techniques
• Not analyzed using the most sophisticated and innovative algorithms
• Not stored securely in line with the latest data security practices

Experfy can help you to diagnose and overcome your customer data challenges and develop a program of action to harness that data to reduce customer churn in your specific industry.

Our Solution

Experfy has deep expertise in customer lifetime value modeling and the measurement of ROI in marketing. The foundation of our approach is to analyze how your organization gathers data about its customers and what data gaps you must address. Our mission is to enhance your capacity to mine customer data or capitalize on existing data which is both a technological and a business structure issue. Who are your customers? How do they behave? What data should be collected about them? How should we be gathering information about them? How do we place that data in the hands of those who can best use it? What technologies and business practices facilitate this?

Once that fundamental challenge is addressed, our consultants can help you to harness sophisticated Big Data techniques such as machine learning and predictive analytics to calculate and analyze your churn rate—percentage of customers whose business is lost per quarter or year; anticipated profit potential and lifetime revenue per customer by income, geography, demographics, etc.; discount rate—the cost of capital used to discount future revenue from a customer; retention cost—the amount of money required to retain a customer per quarter or year; and other metrics that may be important to your specific business. Having acquired and analyzed the data, we will make a strategic recommendation as to how best to harness it. Specifically, we can help you to design strong and highly personalized loyalty programs by identifying those services, support, and promotional offers that your most valued customer segments require to remain in good standing or increase their spending with your company. We can also help you to identify the customers that you don’t want because their risk profile is too high or their contribution to your bottom line is too minimal to warrant the investment.

Finally, we will help to train your personnel in how to secure customer data. This latter point should not be underestimated as the personal information and deep consumer insights that makes effective customer targeting possible also makes that data attractive to thieves. The battle to secure customer data is an iterative and ongoing one that requires ever-increasing sophistication. Failure in this struggle can have profoundly negative consequences for your brand as Yahoo! and Target have unfortunately learned. Experfy can help you to determine the weaknesses in your approach to data security and how to best protect one of your most valuable assets: your customer data.

We will be your partners in delivering actionable recommendations to reduce customer churn.

Tell Us About Your Specific Project

To assist our consultants and data scientists in developing a customized solution for you, please provide the following information:

Business Context

• What products and services do you sell?
• Who are your target customers within your industry?

Corporate Strategy

• What is the problem you are looking for assistance with?
• How is your marketing operation organized?

Data Assets

• Describe the systems that are utilized to hold your customer data.
• How much data do you have?

Data Analytics

• What data techniques do you currently use to analyze your customers?
• Do you use a marketing platform and if so, which one?

Data Security

• What technologies and security protocols do you use to protect your data?
• Have you experienced any data breaches?

Project Framework & Pricing

Depending upon the size of your organization, the state of your data and the volume of information to be analyzed, we can complete our consulting engagement in 3-4 weeks at a cost starting at $10,000, depending on the deliverables selected.

Step 1: Analysis of Data Operations

Assessment of business operations and technologies utilized to mine customer data. Identification of customers and their behaviors.

Deliverables

Documentation including recommendations on how to mine and deploy customer data to maximize its utility in your organization.

Step 2: Analysis of Customer Data

Use Big Data techniques to analyze and forecast key customer data metrics such as churn rate, segment customer data, and calculate lifetime value of customers.

Deliverables

• Recommendations on how to best design customer loyalty programs, reduce customer churn and increase lifetime value of customers.
• Identification of most valuable and riskiest customers.
• Formal presentation and high level documentation supporting how to best implement recommendations.
• Creation of dashboard to display key data inputs and model outputs.

Data Security Assessment

Investigation of the weaknesses in your customer data security.

Deliverables

Formal presentation and documentation including recommendations of the best practices and technologies required to address identified data security challenges.
Data Security Training

Combining machine learning and artificial intelligence, we help you understand the tonality of conversations (positive, negative or neutral) through text mining and analytics. You can analyze the unstructured customer feedback through any communication channel (email, call center, surveys, social media) and manage their experience in all of their contact points with the company. Our experts can use opinion mining of your fans and followers on social media to get the picture of what people talk about and how they perceive your brand.