Unlock Analytics

Data and Analytics Consulting

Data is a precious corporate asset. Shouldn’t you treat it like one? Harness your data to drive business insights, automation, process improvement and innovation.

Your competitors are using data for more than reporting. You can become “data nimble” through cloud, artificial intelligence and modern approaches to data architectures. By pushing beyond the boundaries of traditional business intelligence, you’ll be positioned to transform data into information that accelerates business insight, ensures operational excellence and gives you a competitive advantage.

Our team at UnlockAnalytics is not only conversant with machine learning algorithms but also possess in-depth knowledge of various domains. Our main focus is towards timely delivery with no compromise in quality. Further, we equally emphasize collaboration with our clients and ensure to involve them in every stage of the project. This is one of the things that sets us apart from the crowd.

Irrespective of the industry, it is becoming essential for every organization to make business decisions. This can be easily achieved by data-driven making. That’s where UnlockAnalyticsand Business Intelligence steps in. UnlockAnalyticsis dedicated to assisting its clients in their endeavours using the right blend of analytical technologies and knowledge. 

We follow a very strong yet iterative framework “Anatomy of Statistical model” for solving business problems with ease. We have further divided this framework into 5 stages namely.

Data info-2

TRANSFORM DATA INTO ACTIONABLE ANALYTICS FOR YOUR ORGANIZATION

Numerous organizations have high-quality Hr data dwelling with a multitude such as HRMS, performance management, learning, compensation, study, and so on. With the assistance of Hr analytics, this information is utilized viably to foresee workforce patterns, limit risks and maximize patterns. It empowers HR professionals to settle on information-driven choices to attract, oversee, and retain employees, which enhances Return on investment. Pioneers settle on choices to make better workplaces and maximize worker efficiency with Hr analytics.

Projects Delivered:

  1. Turnover modeling

    Predicting future turnover in business units in specific capacities, geographies by looking at factors, for example, commute time, time since last job change, and performance over time.

  2. Targeted retention

    Discover high risk of churn later on and focus retention exercises around critical few people.

  3. Risk management

    Profiling of candidates with a higher risk of leaving prematurely or those performing below standard.

  4. Talent forecasting

    To predict which new hires, based on their profile, are probably going to be high fliers and after that moving them in to fast track programs.

  5. Predicting Attrition rate

    Attrition, in Human Resource phrasing, refers to the phenomenon of the workers leaving the organization. Attrition in an organization is generally estimated with a metric called attrition rate, which basically measures the no of workers moving out of the organization.

  6. Predictive analytics for renege in recruitment

    A large number of candidates who accepted job offer did not join the organization and drop out. This is called Renege in Recruitment.

The use of Data has far-reaching Implications for retailers. Retail analytics is a contextualized application of using data that comes from retail operations to make decisions that impact profitability. It helps a retailer to target their customers more effectively by campaigns, to improve response time to market changes, to increase employee productivity and to improve customer service at stores.

The goal is to influence short-term sales or to set-up the decision-making infrastructure for long-term success. It addresses all essential retail business functions, including marketing, merchandising, operations, supply chain, and finance.

Projects Delivered:

  1. Customer-centric marketing

    Customer-centric marketing is a standout amongst the most prominent applications of analytics in retail that enables retailers to utilize the accessible information to improve insights about their customers so as to serve them better.

  2. Supply Chain Analytics

    Supply chain analytics enables the retail ventures to comprehend the present condition of their supply chain and recognize the ordinary risks related with the supply regarding purchasing overlaps and costs.

  3. Price optimization

    Price optimization includes utilizing analytics to decide the optimal pricing of products and services through their lifecycles which prompts expanded revenue and benefit.

  4. Market mix modeling

    Market mix modeling enables a retailer to assess the adequacy of their marketing exercises so as to concentrate on the most valuable ones.

  5. Fraud detection

    Fraud detection is a basic issue for retailers determined to avoid or limit misfortunes. Analytics is exceptionally helpful in building successful fraud control methodologies.

  6. Market basket analysis

    Market Basket Analysis is one of the key methods utilized by expansive retailers that intends to discover relationships and build up patterns across purchases. It is connected to different fields of the retail division so as to boost sales and create revenue by distinguishing the necessities of the customers and make purchase recommendations to them.

Every business would have silos of business data in its marketing/sales department. Sales and marketing analytics investigation are basic to opening industrially applicable bits of knowledge, expanding revenue and profitability, and enhancing brand recognition. The assistance of the right analytics can reveal new markets, a new gathering of people specialties, zones for future advancement and substantially more.

Sales analytics is utilized in recognizing, demonstrating, understanding and predicting sales patterns and results while supporting sales management in understanding where salesmen can progress.

On the other hand, marketing analytics is the act of gathering, overseeing and manipulating data to give the information expected to marketers to advance their effect.

Projects Delivered:

  1. Unmet need analytics

    Unmet need analytics is the way toward revealing whether there are any neglected needs around a product or service inside the market for the purpose to recognize the gap that exists between what the market needs and what the market presently gives so the new products or product enhancements can close the gap and help a business to improve.

  2. Demand forecasting

    Demand forecasting contains a progression of steps that includes the expectation of demand for an item in the future under both controllable and non-controllable factors.

  3. Pricing analytics

    Pricing analytics use information to comprehend what drives the customers purchasing choices and incorporates this learning to meet company’s evaluating needs. It Optimizes the Trade-Off Between Price, Volume and Profit, Develops High Impact Price Strategies furthermore Increases the Confidence of the Sales Force.

  4. Market trend analytics

    Market trend analytics is the way toward deciding if a market is developing, stale or in decrease and how quick that development is happening.

  5. Market size analytics

    Market size analytics is the way toward working out how huge the market is for your products and services, and whether there is adequate development potential.

  6. Non – customer analytics

    Non-customer analytics is identifying who is not a present customer (and why), which will help the business to expand by including those individuals.

  7. Competitor analytics

    Competitor analytics is important for marketing and strategic planning by identifying the real competitors and understanding their strengths and weaknesses for identifying opportunities to exploit and threats to navigate.

  8. Marketing And Sales Channel Analytics

    Marketing and sales channel analytics permit to assess the distinctive channels that are accessible, and it sets up which are the best for example online or offline channel.

  9. Brand analytics

    Brand analytics, help organizations settle on educated business choices that will strengthen the brand experiences, drive marketing, drive sales, and increment long-term profitability.

The banking, financial services, and insurance industry is one of the biggest adopters of analytic services. Economic turmoil, progressively requesting customer profile, and administrative pressures have made a testing situation for banks. Further, the elevated need of customer focus is driving the interest for analytics arrangements. In the midst of, this condition, banks progressively understand the esteem they can open through advanced analytics capabilities. Likewise, contracting demand, globalization and competition are compelling the businesses to see information, drive analytics and ignite profitable development.

Projects Delivered:

  1. Fraud detection

    Fraud detection helps BFSI to recognize, avert and eliminate with internal and external fraud as well as reduce the related expense.

  2. Risk management 

    BFSI analyzes transaction information to decide risk and exposures dependent on reproduced market behavior, scoring clients and potential customers.

  3. Efficiency optimization

    It causes BFSI to determine issues of customers rapidly by enabling BFSI to foresee customers need ahead of time.

  4. Customer segmentation for optimizing offers

    It gives an approach to comprehend customers needs at a granular dimension so that BFSI can convey focused offers more successfully.

  5. Customer churn analysis

    It helps BFSI to hold their customers by analyzing their conduct and identifying designs that lead to a customer abandonment.

  6. Sentiment analysis

    This tool helps the BFSI to analyze online networking to screen customer sentiment towards a firm, brand or item.

  7. Customer experience analytics

    It can give better knowledge and insights, permitting Bfsi to coordinate offers to a customer’s needs.

HR / People Analytics

Numerous organizations have high-quality Hr data dwelling with a multitude such as HRMS, performance management, learning, compensation, study, and so on. With the assistance of Hr analytics, this information is utilized viably to foresee workforce patterns, limit risks and maximize patterns. It empowers HR professionals to settle on information-driven choices to attract, oversee, and retain employees, which enhances Return on investment. Pioneers settle on choices to make better workplaces and maximize worker efficiency with Hr analytics.

Projects Delivered:

  1. Turnover modeling

    Predicting future turnover in business units in specific capacities, geographies by looking at factors, for example, commute time, time since last job change, and performance over time.

  2. Targeted retention

    Discover high risk of churn later on and focus retention exercises around critical few people.

  3. Risk management

    Profiling of candidates with a higher risk of leaving prematurely or those performing below standard.

  4. Talent forecasting

    To predict which new hires, based on their profile, are probably going to be high fliers and after that moving them in to fast track programs.

  5. Predicting Attrition rate

    Attrition, in Human Resource phrasing, refers to the phenomenon of the workers leaving the organization. Attrition in an organization is generally estimated with a metric called attrition rate, which basically measures the no of workers moving out of the organization.

  6. Predictive analytics for renege in recruitment

    A large number of candidates who accepted job offer did not join the organization and drop out. This is called Renege in Recruitment.

Retail Analytics

The use of Data has far-reaching Implications for retailers. Retail analytics is a contextualized application of using data that comes from retail operations to make decisions that impact profitability. It helps a retailer to target their customers more effectively by campaigns, to improve response time to market changes, to increase employee productivity and to improve customer service at stores.

The goal is to influence short-term sales or to set-up the decision-making infrastructure for long-term success. It addresses all essential retail business functions, including marketing, merchandising, operations, supply chain, and finance.

Projects Delivered:

  1. Customer-centric marketing

    Customer-centric marketing is a standout amongst the most prominent applications of analytics in retail that enables retailers to utilize the accessible information to improve insights about their customers so as to serve them better.

  2. Supply Chain Analytics

    Supply chain analytics enables the retail ventures to comprehend the present condition of their supply chain and recognize the ordinary risks related with the supply regarding purchasing overlaps and costs.

  3. Price optimization

    Price optimization includes utilizing analytics to decide the optimal pricing of products and services through their lifecycles which prompts expanded revenue and benefit.

  4. Market mix modeling

    Market mix modeling enables a retailer to assess the adequacy of their marketing exercises so as to concentrate on the most valuable ones.

  5. Fraud detection

    Fraud detection is a basic issue for retailers determined to avoid or limit misfortunes. Analytics is exceptionally helpful in building successful fraud control methodologies.

  6. Market basket analysis

    Market Basket Analysis is one of the key methods utilized by expansive retailers that intends to discover relationships and build up patterns across purchases. It is connected to different fields of the retail division so as to boost sales and create revenue by distinguishing the necessities of the customers and make purchase recommendations to them.

Marketing and sales analytics

Every business would have silos of business data in its marketing/sales department. Sales and marketing analytics investigation are basic to opening industrially applicable bits of knowledge, expanding revenue and profitability, and enhancing brand recognition. The assistance of the right analytics can reveal new markets, a new gathering of people specialties, zones for future advancement and substantially more.

Sales analytics is utilized in recognizing, demonstrating, understanding and predicting sales patterns and results while supporting sales management in understanding where salesmen can progress.

On the other hand, marketing analytics is the act of gathering, overseeing and manipulating data to give the information expected to marketers to advance their effect.

Projects Delivered:

  1. Unmet need analytics

    Unmet need analytics is the way toward revealing whether there are any neglected needs around a product or service inside the market for the purpose to recognize the gap that exists between what the market needs and what the market presently gives so the new products or product enhancements can close the gap and help a business to improve.

  2. Demand forecasting

    Demand forecasting contains a progression of steps that includes the expectation of demand for an item in the future under both controllable and non-controllable factors.

  3. Pricing analytics

    Pricing analytics use information to comprehend what drives the customers purchasing choices and incorporates this learning to meet company’s evaluating needs. It Optimizes the Trade-Off Between Price, Volume and Profit, Develops High Impact Price Strategies furthermore Increases the Confidence of the Sales Force.

  4. Market trend analytics

    Market trend analytics is the way toward deciding if a market is developing, stale or in decrease and how quick that development is happening.

  5. Market size analytics

    Market size analytics is the way toward working out how huge the market is for your products and services, and whether there is adequate development potential.

  6. Non – customer analytics

    Non-customer analytics is identifying who is not a present customer (and why), which will help the business to expand by including those individuals.

  7. Competitor analytics

    Competitor analytics is important for marketing and strategic planning by identifying the real competitors and understanding their strengths and weaknesses for identifying opportunities to exploit and threats to navigate.

  8. Marketing And Sales Channel Analytics

    Marketing and sales channel analytics permit to assess the distinctive channels that are accessible, and it sets up which are the best for example online or offline channel.

  9. Brand analytics

    Brand analytics, help organizations settle on educated business choices that will strengthen the brand experiences, drive marketing, drive sales, and increment long-term profitability.

BFSI Industry

The banking, financial services, and insurance industry is one of the biggest adopters of analytic services. Economic turmoil, progressively requesting customer profile, and administrative pressures have made a testing situation for banks. Further, the elevated need of customer focus is driving the interest for analytics arrangements. In the midst of, this condition, banks progressively understand the esteem they can open through advanced analytics capabilities. Likewise, contracting demand, globalization and competition are compelling the businesses to see information, drive analytics and ignite profitable development.

Projects Delivered:

  1. Fraud detection

    Fraud detection helps BFSI to recognize, avert and eliminate with internal and external fraud as well as reduce the related expense.

  2. Risk management 

    BFSI analyzes transaction information to decide risk and exposures dependent on reproduced market behavior, scoring clients and potential customers.

  3. Efficiency optimization

    It causes BFSI to determine issues of customers rapidly by enabling BFSI to foresee customers need ahead of time.

  4. Customer segmentation for optimizing offers

    It gives an approach to comprehend customers needs at a granular dimension so that BFSI can convey focused offers more successfully.

  5. Customer churn analysis

    It helps BFSI to hold their customers by analyzing their conduct and identifying designs that lead to a customer abandonment.

  6. Sentiment analysis

    This tool helps the BFSI to analyze online networking to screen customer sentiment towards a firm, brand or item.

  7. Customer experience analytics

    It can give better knowledge and insights, permitting Bfsi to coordinate offers to a customer’s needs.

HR / People Analytics

Numerous organizations have high-quality Hr data dwelling with a multitude such as HRMS, performance management, learning, compensation, study, and so on. With the assistance of Hr analytics, this information is utilized viably to foresee workforce patterns, limit risks and maximize patterns. It empowers HR professionals to settle on information-driven choices to attract, oversee, and retain employees, which enhances Return on investment. Pioneers settle on choices to make better workplaces and maximize worker efficiency with Hr analytics. Projects Delivered:
  1. Turnover modeling

    Predicting future turnover in business units in specific capacities, geographies by looking at factors, for example, commute time, time since last job change, and performance over time.

  2. Targeted retention

    Discover high risk of churn later on and focus retention exercises around critical few people.

  3. Risk management

    Profiling of candidates with a higher risk of leaving prematurely or those performing below standard.

  4. Talent forecasting

    To predict which new hires, based on their profile, are probably going to be high fliers and after that moving them in to fast track programs.

  5. Predicting Attrition rate

    Attrition, in Human Resource phrasing, refers to the phenomenon of the workers leaving the organization. Attrition in an organization is generally estimated with a metric called attrition rate, which basically measures the no of workers moving out of the organization.

  6. Predictive analytics for renege in recruitment

    A large number of candidates who accepted job offer did not join the organization and drop out. This is called Renege in Recruitment.

Retail Analytics

The use of Data has far-reaching Implications for retailers. Retail analytics is a contextualized application of using data that comes from retail operations to make decisions that impact profitability. It helps a retailer to target their customers more effectively by campaigns, to improve response time to market changes, to increase employee productivity and to improve customer service at stores. The goal is to influence short-term sales or to set-up the decision-making infrastructure for long-term success. It addresses all essential retail business functions, including marketing, merchandising, operations, supply chain, and finance. Projects Delivered:
  1. Customer-centric marketing

    Customer-centric marketing is a standout amongst the most prominent applications of analytics in retail that enables retailers to utilize the accessible information to improve insights about their customers so as to serve them better.

  2. Supply Chain Analytics

    Supply chain analytics enables the retail ventures to comprehend the present condition of their supply chain and recognize the ordinary risks related with the supply regarding purchasing overlaps and costs.

  3. Price optimization

    Price optimization includes utilizing analytics to decide the optimal pricing of products and services through their lifecycles which prompts expanded revenue and benefit.

  4. Market mix modeling

    Market mix modeling enables a retailer to assess the adequacy of their marketing exercises so as to concentrate on the most valuable ones.

  5. Fraud detection

    Fraud detection is a basic issue for retailers determined to avoid or limit misfortunes. Analytics is exceptionally helpful in building successful fraud control methodologies.

  6. Market basket analysis

    Market Basket Analysis is one of the key methods utilized by expansive retailers that intends to discover relationships and build up patterns across purchases. It is connected to different fields of the retail division so as to boost sales and create revenue by distinguishing the necessities of the customers and make purchase recommendations to them.

Marketing and sales analytics

Every business would have silos of business data in its marketing/sales department. Sales and marketing analytics investigation are basic to opening industrially applicable bits of knowledge, expanding revenue and profitability, and enhancing brand recognition. The assistance of the right analytics can reveal new markets, a new gathering of people specialties, zones for future advancement and substantially more. Sales analytics is utilized in recognizing, demonstrating, understanding and predicting sales patterns and results while supporting sales management in understanding where salesmen can progress. On the other hand, marketing analytics is the act of gathering, overseeing and manipulating data to give the information expected to marketers to advance their effect. Projects Delivered:
  1. Unmet need analytics

    Unmet need analytics is the way toward revealing whether there are any neglected needs around a product or service inside the market for the purpose to recognize the gap that exists between what the market needs and what the market presently gives so the new products or product enhancements can close the gap and help a business to improve.

  2. Demand forecasting

    Demand forecasting contains a progression of steps that includes the expectation of demand for an item in the future under both controllable and non-controllable factors.

  3. Pricing analytics

    Pricing analytics use information to comprehend what drives the customers purchasing choices and incorporates this learning to meet company’s evaluating needs. It Optimizes the Trade-Off Between Price, Volume and Profit, Develops High Impact Price Strategies furthermore Increases the Confidence of the Sales Force.

  4. Market trend analytics

    Market trend analytics is the way toward deciding if a market is developing, stale or in decrease and how quick that development is happening.

  5. Market size analytics

    Market size analytics is the way toward working out how huge the market is for your products and services, and whether there is adequate development potential.

  6. Non – customer analytics

    Non-customer analytics is identifying who is not a present customer (and why), which will help the business to expand by including those individuals.

  7. Competitor analytics

    Competitor analytics is important for marketing and strategic planning by identifying the real competitors and understanding their strengths and weaknesses for identifying opportunities to exploit and threats to navigate.

  8. Marketing And Sales Channel Analytics

    Marketing and sales channel analytics permit to assess the distinctive channels that are accessible, and it sets up which are the best for example online or offline channel.

  9. Brand analytics

    Brand analytics, help organizations settle on educated business choices that will strengthen the brand experiences, drive marketing, drive sales, and increment long-term profitability.

BFSI Industry

The banking, financial services, and insurance industry is one of the biggest adopters of analytic services. Economic turmoil, progressively requesting customer profile, and administrative pressures have made a testing situation for banks. Further, the elevated need of customer focus is driving the interest for analytics arrangements. In the midst of, this condition, banks progressively understand the esteem they can open through advanced analytics capabilities. Likewise, contracting demand, globalization and competition are compelling the businesses to see information, drive analytics and ignite profitable development. Projects Delivered:
  1. Fraud detection

    Fraud detection helps BFSI to recognize, avert and eliminate with internal and external fraud as well as reduce the related expense.

  2. Risk management 

    BFSI analyzes transaction information to decide risk and exposures dependent on reproduced market behavior, scoring clients and potential customers.

  3. Efficiency optimization

    It causes BFSI to determine issues of customers rapidly by enabling BFSI to foresee customers need ahead of time.

  4. Customer segmentation for optimizing offers

    It gives an approach to comprehend customers needs at a granular dimension so that BFSI can convey focused offers more successfully.

  5. Customer churn analysis

    It helps BFSI to hold their customers by analyzing their conduct and identifying designs that lead to a customer abandonment.

  6. Sentiment analysis

    This tool helps the BFSI to analyze online networking to screen customer sentiment towards a firm, brand or item.

  7. Customer experience analytics

    It can give better knowledge and insights, permitting Bfsi to coordinate offers to a customer’s needs.

Get started instantly!