UNIDATA Consulting is a team of the experts with more than 10 years of experience in Data Science, Machine Learning and Analytics. In our assets tens of successfully completed projects. We never rest on the laurels and constantly expand for you range of services and improve our tools.

1. UNIDATA
consulting
Professional analytics
for effective business
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2. UNIDATA Consulting is a team of the experts with
more than 10 years of experience in Data Science,
Machine Learning and Analytics.
In our assets tens of successfully completed projects.
We never rest on the laurels and constantly expand
for you range of services and improve our tools.
Kiev
ABOUT COMPANY
Our mission is to do Big Data useful for your
business.
Our purpose is to unlock yours business untapped
potential and to force it work for its growth.

3. ACTIVITIES
Our expertise
Building predictive models
Data collection, analysis and transformation
Showcases and dashboards building
Expertise in leading-edge analytical tools
(open source, packaged solutions)
Our main activities
Market Analysis
Staff development
Customer Relationship Management

4. COLLABORATION
FMСG companies E-commerce Logistic
companies
Publishers
Tourist
agencies
Banks and insurance
companies
IT-communications and
telecommunications
Pharmacy
and 100 more

5. MODELINGPredictive Modeling
Understandingtheprospects
Predictivemodelsbuilding
Analysis

6. Predictive Modeling is our main activity.
By identifying and using patterns in the Big Data, we successfully find any unknown in the equation of
your business.
Predictive Modeling Services
Predictive system building
MODELING
Predictive Modeling
Predictive model building
Customer segmentation
Cross- и up-selling‘s model building
Analytics reports building
Construction of fraud detection models
Retention model building

7. DATA MININGWorking with large
data volumes
Database enrichment
Database validation
Perfect
Database

8. DATA MINING
Working with large
data volumes
We are working with any volumes of information.
We will help you to structure your database and use this information effectively for growing your business
Data Mining Services
Database structuring
Database cleaning
Formation of the proposals on the base of Data Mining
Database validation
Database verification
Database enrichment
Database segmentation
Analysis of any database volumes

9. CRMCustomers relationship
management
Database analysis
and segmentation
Forming of the unique
proposals
Profit growth

10. Automation and standardization of customer relationship management is an essential tool for effective marketing
interaction with the end user.
We offer you a range of services that will ensure an effective dialogue with your customers.
CRM services
Integrated development of the CRM solutions
CRM
Customers relationship
management
CRM strategy development
Increasing work efficiency of commercial and technological personnel
Database segmentation
LTV and lifetime value analysis
RFM analysis
Development of the recommendations on dealing with each segment
Improving the efficiency of marketing and sales processes
Reporting

11. TRAININGSTraining and staff
development
Achievementofresults
Studying
Task

12. It is important for us a successfully implementation of our recommendations to lead yours business to
the desired result. That is why we are happy to share with yours experts our knowledge and tools.
We will teach them to perform highly specialized reports on a regular basis.
Staff development services
Introduction to the methodology of the knowledge area and acquaintance with tools
TRAININGS
Training and staff
development
Support in specified areas of responsibility on an ongoing basis
Clarification of the causality problems
Studying to prepare highly specialized reports

13. RECOMMENDATION
ENGINE
Whatinterests
dotheyhave?
Whoyour
Clientsare?
Suggest them what
They really need

14. Recommendation Platform is an analytic system that predicts which objects (movies, music, books, news, products,
services, websites ) will be interesting to the end user, on the base of the information about his behavior.
This is one of the most effective way to increase turnover and maximize profits in any industry.
RECOMMENDATION
ENGINE

15. Our advantages
Parameterization: flexible definition sets of properties possessed by the user, object, and event in history
RECOMMENDATION
ENGINE
Self-learning: a model takes as input a feedback on the results of prediction and improves the
quality of prediction
Universal: the model is trained to recommend the preferred objects to users regardless of the subject area
Scalable solutions
Adaptability by phase of the life cycle
Solved the problem of "cold start"
Using open source tools
Масштабируемые решения
A breakdown of the implementation process on the short phrases with tangible results
Recommendation Platform is an analytic system that predicts which objects (movies, music, books, news, products,
services, websites ) will be interesting to the end user, on the base of the information about his behavior.
This is one of the most effective way to increase turnover and maximize profits in any industry.

16. OUR CLIENTS

17. CASESFew of our projects
Detailed acquaintance with each briefcase
Analysis of all the factors
Successful results

18. 1. CRM Development (campaign creator)
2. Campaigns reports development
3. Building a model of customers acquisition
4. Deposit customers acquisition via external databases
5. E-commerce customers acquisition via external databases
6. Conducting predictive modeling training sessions for employees
7. Database cleaning, identification, verification and enrichment
8. Building a response prediction model for loans offers
9. Building RFM(D) classification
10. Risk analysis for the mobile internet banking project implementation
11. Customer lifecycle model development. Calculation cost of customer acquisition (CAC)
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OUR PROJECTS

19. Project 1. CRM Development (campaign creator)
Client: Bank
Field of activity: finance business
Problem: loss of clients
Results:
Our team developed a system of customer segmentation
It was worked out personalized offer for each client on a
regular basis
The quantity of the marketing campaigns was increased from 2
to 12 per month
An average quantity of purchased products per client increased
from 1,1 to 2,3 items
Response rate increased by 3,5 times
OUR PROJECTS

20. Project 2. Campaigns reports development
Client: Bank
Field of activity: finance business
Problem: lack of the analysis tools
Results:
Regular campaigns reporting in the context of the proposals
and communication channels
Reports on customers` outflow & retention
Reporting on Data Relevance & Quality
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Category 1 Category 2 Category 3 Category 4
OUR PROJECTS

21. Project 3. Building a model of customers acquisition
Client: Bank
Field of activity: finance business
Problem: low response, high client acquisition price
Results:
Based on the model for each customer is determining the
probability of his response to the proposal
The probability model is taken into consideration by taking
decision on communication necessity and choosing
communication channel
63% of customer acquisition costs was saved due to proposed
customer acquisition model
Response rate increased on 40%
OUR PROJECTS

22. Project 4. Deposit customers acquisition via external databases
Client: Bank
Field of activity: finance business
Problem: low efficiency in co-working with partners databases
Results:
Our team developed a model of external sources development
It was calculated the potential of the external database with a
given level of response
Cost of new customer acquisition reduced on 45%
Response rate increased on 190%
OUR PROJECTS

23. Project 5. E-commerce customers acquisition
via external databases
Client: Internet shop
Field of activity: e-commerce, remote sales
Problem: not effective work in area clients attraction
Results:
Marketing-analytical hypothesis development
Pilot mailing via Viber
Pilot mailing via e-mail
Calculation and implementation the model of the predictive
response on the basis of pilots
Acquisition of cheaper clients (savings up to 50%) and more
effective clients (1.34 response increase up to 35%)
OUR PROJECTS

24. Project 6. Conducting predictive modeling training sessions
for employees
Client: Bank
Field of activity: finance business
Problem: lack of knowledge among staff
Results:
Specialists trained by this method using predictive modeling
in their daily work
First built model Result - the Model for predicting the issuance
and activation of the credit card has increased the level of
activation cards issued on 20% for the first month of Model
implementation.
OUR PROJECTS

25. Project 7. Database cleaning, identification,
verification and enrichment
Client: Bank
Field of activity: finance business
Problem: working with not actualized database
Results:
Cleaning, recognition, verification, parsing (the layout of the fields)
and the enrichment of clients’ database
As a result: Recognized: 94%
Parsed: 89%
Cleaned: 78%
Enriched by personal and contact data: 25,4%
OUR PROJECTS

26. Project 8. Building a response prediction model
for loans offers
Client: Bank
Field of activity: finance business
Problem: not effective clients acquisition
Results:
OUR PROJECTS
Our team developed model for external databases
It was calculated the external database’s potential with a given
response level
Client’s acquisition costs were reduced by 1,5 times
Response increased by 2,2 times

27. Project 9. Building RFM(D) classification
Client: E-commerce Group
Field of activity: e-commerce, industrial machinery and equipment
Problem: not effective marketing
Results:
RFM-report is considered on a regular monthly basis
Developing a system of recommendations for the retention
and customer segments’ development
Developing and implementation an individual reports for each
site of e-commence group
Our team worked out the following reports: lifecycle, LTV, the
cost of acquisition and retaining customers
OUR PROJECTS

28. Project 10. Risk analysis for the mobile internet banking
project implementation
Client: Bank
Field of activity: finance business
Problem: unstudied risks
Results:
According to bank’s experts evaluation the prepared analysis
will spare from 9% to 15 % of the projects’ budget, even if the
risks will be partially implemented
OUR PROJECTS

29. Project 11. Customer lifecycle model development.
Calculation cost of customer acquisition
Client: The network of retail food stores in the luxury segment
Field of activity: FMCG
Problem: false business analytics
Results:
Reduction of the customer acquisition cost (CAC) on 20%
Customer lifetime value calculation
Increasing average revenue per user (ARPU) on 91,3 $ due to
correct communication tools formed on the base of current
clients lifetime phase
OUR PROJECTS

30. CONTACTS
WE WILL BE GLAD TO COLLABORATE WITH YOU
www.unidata.biz.ua info@unidata.biz.ua +38 097 332 51 60 unidata.ua /unidata.biz.ua