CleverDATA_Afanasev_DigitalEconomy

Digital Economy
Denis Afanasev
CleverDATA

Company Proﬁle
Make your data clever
Digital economy

cleverdata.ru | info@cleverdata.ru
Make your data clever
Business development
on interna?onal
markets
One of top-3 leading
Russian IT companies;
43 branches in Russia and abroad;
7000+ employees.
Marke?ng Data PlaForm
Data collec@on, clients proﬁles
building, data enrichment, extend
clients analy@cs;
Data Marke?ng Cloud
Cloud solu@on for comfortable interac@on
of data suppliers and consumers.

Development and implementa@on of
predic@ve analy@c models and Big Data
processing solu@ons;
In-house centers of development;
Partnership with global leading companies;
Centre of exper?se for Big Data and
Digital Marke@ng technologies.
1DMP

Business solu?ons
Data Management Platforms
Customer base and
experience management
Marketing automation
Building of analy@cal DWs, development of solu@ons for raw data collec@on
based on Hadoop stack and other Big Data technologies, knowledge
extrac@on and auditory segmenta@on.

Building of predic@ve models of data processing for effec@ve retail customer
rela@ons management, churn management, cross-sales, micro-segmenta@on
and client profile 360° and scoring models building.

Implementa@on of global leading vendors’ solu@ons for omni-channel
targeted marke@ng (campaigns, event-based marke@ng, customer web
experience management).

Implementa@on of global leading solu@on Splunk Enterprise for opera@onal
analy@cs in real-@me.
Our target is to make your business more effec?ve with a help of DATA
Operational analytics
4

Our customers
Online ads | Media | Telco
•  Development of DMP plaVorms for targeted adver@sing and new business models
crea@on;
•  Development of solu@ons for traﬃc quality and web-content analysis.

Finance market| Public sector
•  Development of DWs and Big Data DWs;
•  Customers data enrichment with external data;
•  Data management plaVorm development, machine logs real-@me analysis for cri@cal
business process monitoring;
•  Implementa@on of ACRM systems for detailed customer analy@cs, based on Big Data
driven marke@ng and customer experience;
•  Development of models for predic@on of product response and churn management,
scoring models, past-due amounts collec@on;
•  Collec@on and analysis of Internet texts with the use of machine learning algorithms for
media ac@vity monitoring.

Retail
•  Marke@ng automa@on systems implementa@on (Campaign Management);
•  Predic@ve model development for business process op@miza@on.

5

The Fourth Industrial Revolu?on

«Индустрия 4.0», получила свое название от инициативы 2011 года,
возглавляемой бизнесменами, политиками и учеными, которые
определили ее как средство повышения конкурентоспособности
обрабатывающей промышленности Германии через усиленную
интеграцию «киберфизических систем», или CPS, в заводские
процессы.
Производственная сторона, эквивалентная
ориентированному на потребителей «Интернету вещей», в
котором предметы быта, от автомобилей до тостеров, будут
подключены к Интернету.
Слияние технологий и стирание граней между
физическими, цифровыми и биологическими
сферами.

Профессор Шваб видит три причины, по
которым сегодняшние перемены следует считать
не простым продолжением третьей
промышленной революции, а началом четвертой:
•  скорость, с которой происходят
перемены;
•  их размах
•  системный характер последствий.

В первую очередь от очередной
технологической революции должны выиграть
развитые государства, у которых есть задел
в компьютерных исследованиях.
Сингапур
Швейцария
Китай
США
Германия
•  к 2025 году развитие технологий беспилотных автомобилей может
сохранить до 1 млн жизней, сокращение выбросов выхлопных
газов автомобилями — сэкономить до $867 млрд, а общая прибыль
от прогресса составит $100 трлн.
•  развивающиеся страны перестанут быть локомотивами развития,
которыми они были на протяжении последних десятилетий,
поскольку дешевая рабочая сила перестанет считаться конкурентным
преимуществом

•  Новая темпоральность
•  Пространство потоков
•  Глобальная деревня
•  Длинный хвост
(С) Сергей Медведев, профессор ГУ ВШЭ

Hype Cycle for Emerging Technologies 2015
Решайте
практические
задачи!

Exponen?al organiza?on

New business models

Moore's law is the
observa@on that the
number of transistors in
a dense integrated
circuit doubles
approximately every two
years.

Разработка Производство Доставка

Crowdsoursing

Robots/AI

Causality in ?mes of big data
In the past, only half of the customers received a catalog. And it only went to loyal
customers. Taking a look at historical data shows that only 6% of the customers who
didn’t receive a catalog visited the shop, while 30% of those who received one did.
This sounds like a huge marke@ng success... but it isn’t.

But that is precisely the issue that we need to address. Which customers will be
moved to purchase by the catalog?
The result: With only half the budget (25% of all customers), the same adver@sing
eﬀect and the same result were achieved as shipping to 50% of all customers based on
the old selec@on criteria. In other words: with 75% of the budget, customer ac@vity
can be increased by 5%. The circle can now be squared: more sales with fewer costs!

Accurately plan sales
The key ques?on is: Which factors inﬂuence the sale of
seafood?

•  Factor 1 − Seasonality, or the ‘tourism eﬀect’
•  Factor 2 − the weather
•  Factor 3 − loca@on
•  Factor 4 − prices and promo@ons
•  Factor 5 − low stocks
The result: All of this informa@on goes into predic@ve
applica@ons, which turn them into accurate forecasts. This
means the complex materials planning for seafood can be
automated for the supermarket chain’s many stores. You can
imagine the cost savings that result.

Customer buying behavior from their receipt data
•  People buying pharmacy ar@cles will also
− with a high probability − buy other
pharmacy products (plausible).
•  People who buy pharmacy ar@cles will
also − with a high probability − buy
perfume ar@cles (goes together).
•  Interes?ngly, pharmacy ar?cles are also
oven bought together with sta?onery
products (this is not so obvious).

Heatmap of Big Data Business Problems by Industry

3D Prin@ng/Drones

CleverDATA_Afanasev_DigitalEconomy

Recomendados

Recomendados

Más contenido relacionado

La actualidad más candente

La actualidad más candente (20)

Destacado

Destacado (7)

Similar a CleverDATA_Afanasev_DigitalEconomy

Similar a CleverDATA_Afanasev_DigitalEconomy (20)

Más de CleverDATA

Más de CleverDATA (20)

Último

Último (20)

CleverDATA_Afanasev_DigitalEconomy