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Analytics

Behavioral Segmentation

Behavioral segmentation has recently regained its ebbing popularity thanks mainly due to the resurgence of behavioral targeting in digital marketing. Web marketers have banked on the quick and easy availability of the behavioral information in web marketing to anticipate and fulfill customer choices.

Psycho-Demographic profiling is important but they tend to be incomplete because they do not leverage knowledge, attitudes, interests and actions of the customer, which in turn determine, how customers respond to actual products/services or their attributes. With the recent advances in technology, this critical information which was once difficult to acquire, is now easy to obtain. Behavioral segmentation, relying on past customer behavioral data, is used in identifying homogeneous groups of customers that reveal similar behavioral patterns in the future.

Behavioral segmentation divides the customer base into groups based on the way they respond to promotions, price changes, channels they use to communicate, etc.

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Scorecard Development

Loyalty Square provides comprehensive predictive modeling solutions using state-of-the-art technologies. The approach includes a combination of statistical techniques and machine learning algorithms to provide incremental lift. We develop

  • Response Models
  • Activation Models
  • Incremental Sales Models
  • Churn and Prepayment Models
  • Forecasting Models

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Market Basket Analysis

Market Basket Analysis (MBA), also known as affinity analysis, is a technique to identify items likely to be purchased together. The introduction of electronic point of sale systems have led to collection of large amount of data. Simple, yet powerful - MBA is an inexpensive technique to identify cross-sell opportunities. A classic example is toothpaste and tuna. It seems that people who eat tuna are more prone to brush their teeth right after finishing their meal. So, why it is important for retailers to get a good grasp of the product affinities? This information is critical to appropriately plan for promotions because reducing the price on some items may cause a spike on related high-affinity items without the need to further promote these related items.

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Personalization: The Key to Success in the Online Era

Most people are looking for a way to add a personal touch to their gifts; most customer service companies are planning to provide unique customer interaction; most banks providing customized products (e.g. loans, cards) and investment plans; and most retailers are recommending products that are close to customer’s preference.

In the last few years, the companies that have grown and dominated the market place have also been the early adopters of personalization. Dell, Amazon, Netflix, etc. are just a few names that come high on the mind. For example, Amazon would recommend books, apparels, electronic items, etc. based on your past purchases, clickstream data, etc.

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Churn Management

The biggest challenge facing marketers is getting the timing of the attrition right and reaching out to the customer in time to incentivize them to stay. Companies often make significant investments to get back lost customers with win-back programs and re-acquisition efforts. These efforts are quite often wasted since they are too late in their intervention.

A logical approach to churn management might include the following steps:

  • identification of factors influencing customer defection
  • determining the factors that influence when the customers are likely to attrite
  • assessing the effectiveness of available customer retention tools
  • selecting the optimal retention channel for a given customer profile and churn risk level

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Text Mining

In a CRM environment, customer’s comments, complaints or requests are captured by call center agents that could be mined to get valuable insights. This information can be utilized in numerous ways as mentioned below:

  • Analyze call center transcripts to identify customer concerns. Use this information back to understand customer actions and segments
  • Improve customer retention by determining which customer complaints are most likely to result in attrition, and take proactive action
  • Discover what drives customers to your customer service call center and identify trends in product defects or areas for service improvement
  • Identify common customer complaints from online customers by analyzing customer e-mail and instant message transcripts. Use this information to identify areas of your site that need improvement

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Campaign Management

Campaign Management is the critical and final customer touching activity of Database Marketing. Though it sounds simple, the entire process needs rigor to successfully to run it. A number of IT/database constraints pose additional challenges.

Loyalty Square uses Six Sigma rigor to provide end-to-end support from program design, campaign execution to campaign tracking. We deploy Analytic tools to analyze the effectiveness of a marketing or promotion campaigns. The analysis is also aimed at identifying the factors affecting the turnover from the campaigns and identifying potential improvements required for the campaigns. The team has considerable expertise in designing the campaign experiments aimed at achieving the optimal mix of marketing strings.

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Social Network Analysis

The process of mapping or measuring links and relationships, which exist between organisations and individuals, who are engaged in various networking or collaborative activities is known as Social Network Analysis. This visual and mathematical analysis seeks to explore specific expertise or influences, which exist in groups. It aids in the computation of indices, which measure characteristics of the network, such as, measures of centrality. It also seeks to determine the structural importance of a “node” (example, people) in graphs.

The term, 'social network analysis' was coined by Professor J A Barnes in the 1950’s. He studied social ties in a Norwegian fishing village and concluded that social life is ‘a set of points, some of which are joined by lines’, and it forms a ‘total network’ of relations.

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Net Promoter Score

The growth of a company is highly dependent on its satisfied customers. Net Promoter Score is a simple yet powerful method to measure customer loyalty. The approach was devised by Bain consultant Fred Reichheld. The method involves asking a simple question to customers - How likely is it that you would recommend [the company] to a friend or colleague? The customer then responds on an 11 point scale - from 0 (not at all likely) to 10 (extremely likely) depending upon customer's satisfaction level with the concerned company. 

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