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Data analytics
To expand your business

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Financial Companies

Data Driven Decision Making

Data Analytics enables departments to detect oportunities, improve customer experience and   guide the energies to Add Value to products and services provided.

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Analytics and data science end to end

Data Analytics enables departments to detect oportunities, improve customer experience and   guide the energies to Add Value to products and services provided.

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CASE STUDIES

+40%

Contact Effectiveness

+60%

Efficiency in identifying

+40%

Increase in Selling

CUSTOMER
ANALYTICS

PROPENSITY
TO PURCHASE

CROSS
SELLING

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Client's Behavior

Using data on clients" behavior, purchase history, commercial actions, and demographic aspects, we can gain perspective on how they relate to the different product available and how they are likely to behave.

Advanced tailor-made predictive algorithms

Using data on clients" behavior, purchase history, commercial actions, and demographic aspects, we can gain perspective on how they relate to the different product available and how they are likely to behave.

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Demand Forecast for Hotels

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Data Science

Forecast processes, Classification algorithms
and asses available data.

Data Science and Analytics, applied to growth

Integration:

We adapt our inputs to your architecture, analize 
your real data, process them with the more suitable
technology and give you the info you need.

Opportunity:

We deliver considering the best option to let you have
what you need at the right time.

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Demand Forescast for Hotels

Forecast Accuracy converted into bigger Business Margins for Hotels. Forecasting aims at maximizing the revenue by making decisions regarding when to make rooms available for customers and at what price, under the constraint of fixed room capacity.

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CASE STUDIES - HOTEL CHAIN

+15%

Better

2018: 35%

2019: 20%

REVENUE ATRIBUTTED TO DEMAND FORECAST 

+7m

Increment

2018: $145

2019: $152

+2m

Increment

PROFIT ATTRIBUTED
DEMAND FORECAST

2018: $145

2019: $152

FORECAST ERROR
REDUCTION

 

50 hotels in Europe. 6,000 rooms. $150 anual revenue. Avg price per room: $75

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Keys

Tailored predictive algorithms

Avoiding Forecasting Waste

We blended human predictions with machine learning to achieve the best possible results. Beforecaster's algorithms are created under the principle that forecasting accuracy is a means to a business end.

We never take for granted that all forecasters add value to a prediction. We eliminate any prediction elements that return poor results.

Tapping into the right sources

Exploits data from a variety of sources that included historical demand, weather, events, epidemics, or transportation prices.

Permanent updating

Every time new data arrives in the system, Predictions are updated. It warns users whenever it detects changes worth communicating.

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People Analytics

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People Analytics

People Analytics uses data and analytic tools to make better decisions about how we manage people

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CASE STUDIES - HEALTH COMPANY

+8,94%

Differential

Value Added

$1.3m

PERFORMANCE

Differential

+4,33%

Value Added

$1.1m

RETURN OF INVESTMENT

320%

in 2 years

CHURN RATE

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Staff Planning

Work Environment

How many people will we need for the next 2 or 5 years?
How many employees will quit or retire during that period?
How much money will that cost?
What segments will we need?

Wich are the key commitment factor for employees?
What is the e-NPS in my company?
How does employee commitment affect productivity and financial outcomes?
What can we do to improve the work environment?

+ People Analytics: Analysis of causes - Insights of necessary measures

+PA: Segmentation by clustering - Performance Surveys - Employee Net Promoter Score

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Recruiting

Talent Development

Is it possible to automate tasks?

Can I optimize searches?

+PA: Profile Analysis - CV Scoring

Where should we invest to develop my teams?

What are my team's needs?

How can I help my employees to develop their careers?

Loyalty and Attrition

+PA: Profile Analysis - Performance Surveys - Churn Rate improvement

Is any employee thinking about leaving?

What are the main attrition causes?

What impact does attrition have?

What is more effective to stop attrition?

+PA: Analysis of causes - Insights of necessary measures

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