b2b applied AI GEO platform for RETAIL

Alexander Kiryanov, CEObestplace.aiakiryanov@bestplace.pro

Every single mistake in site

selection costs Starbucks

$500,000

Arthur Rubinfeld, Chief Creative Officer at Starbucks Corporation

”“

250+ unique

datasets

20+ models for

goods and services

State of the art algorithms

16 ready-to-use

solutions for retail

Applied AI GEO platform

2

Model of Demand

3

Machine Learning

Valid Data

1

Client Proposal

4

Valid and Valuable Data

Machine Learning

1. Social demographic

85 – 95%

Analysis Speed

of forecast quality improvement we get from valid data sources

39%2. Income

3. Traffic

4. Number of cars

7. Places of Interest

9. Shopping malls

5. Location Popularity

10. Business centers

vs

6. Competitors

8. Social Networks

200+ more

Forecast Accuracy 20% EBITDA growth 50% less closures

85% speed increase in decision-making process

58 times >In 2 years

platform has already analyzed

35 000+ locations

Expert can analyze only 600 locations in 2 years

Customer Proposal Inditex

▹ Machine Learning Predictive Model▹ Scenario Scoring▹ Malls Potential▹ Whitespace Analysis

Site Selection

▹ Existing Store Assessment▹ Territory Optimisation▹ Customer Acquisition

Portfolio Audit

Collect data using app

Designa request

Make decision

Opennew store

1 2 3 4

BestPlace helps you to reduce 85% costs on staff operations

Mobile & Web For Staff Operations

32%Growth in improving forecast accuracy

CASE STUDY: RIVE GAUCHE

✓ Average bill and target

audience evaluation for

shopping mall✓ Model creation for a new retail

format (1000 m)

✓ Daily store openings and

closures tracker

СФЕРА

РАЗМЕР СЕТИ

ТЕРРИТОРИЯ РАЗВИТИЯ

КЛЮЧЕВЫЕ ЛОКАЦИИ

ПОЛЬЗОВАТЕЛЬ СИСТЕМЫ

Мелкооптовая торговля

86 гипермаркетов

Европа, Азия, Россия

На автомобильных магистралях

Маркетолог

НАЧАЛО СОТРУДНИЧЕСТВА

Май 2017

ЧЕМ ПОЛЬЗОВАЛИСЬ РАНЕЕ

Ручные исследования, Росстат,

МОДЕЛЬ БИЗНЕСА

Собственная сеть50%Growth in improving forecast accuracy

✓ Evaluating B2B customers

potential: 110 000 traders и 49

000 HoReCa✓ Modeling of store area

✓ Distant (150 km) assessment of

potential demand

CASE STUDY: METRO C&C

CASE STUDY: PAPA JOHN’S

28%Growth in improving forecast accuracy

✓ Delivery zone assessment for new

franchisees

✓ Transportation and competition

forecasting

✓ Monitoring of competitors’

marketing campaigns and

creating similar campaigns for

the client

▹ We customise machine learning to your business model

▹ We measure the final meta-metric and 10 sub metrics

▹ We provide exclusive data sources in Middle East, Asia and CIS

▹ We re-learn the clients models every week to be actual

▹ We digitize the client experts’ market knowledge

Competitive Advantages