Explicato provides business analytics and consulting services to retailers to help them better understand customer behavior and improve strategies. They conduct in-depth market research using unique methods focused on understanding customers' motivations. Explicato also builds data warehouses and business intelligence platforms for retailers that integrate various data sources. This provides retailers operational and analytical reports as well as advanced analytics capabilities.

1. EXPLICATO: PROVIDING
ADDED VALUE FOR THE
www.explicato.com
RETAIL

2. Intro &
Content
This deck is a top-level summary of Explicato’s capabilities and IT research, analytics and development team
and our understanding how to bring value to our retail customers.
02
www.explicato.com
Business model: overview
Research and consulting services
DWH and BI platform: key benefits
01
03
Sample Reports and Analytics 04
Social media analytics 05

3. www.explicato.com
Explicato
Value Added
Proposition
01
We focus on the relations between retailers and customers combining business analytics and IT
technologies
Deep understanding of
customers’ motivational
perceptions, discovering
different consumer
segments by economy and
demographic
characteristics
Precise estimation of the
potential of a business model
measuring customer volumes
by segments, territories and
social groups
Design of the right
strategies based on the
right statistics, analytics
and knowledge about
customers and the
decision drivers that
affect them
External consultancy and
project management
starting from the business
discovery to the UAT phases
ensures that the IT solutions
and implementation will
meet the needs of the
business

4. www.explicato.com
Market
Research
o Unique research methodology
Unlike other research practices, our methodology is focused on the end customer. All
market researches in the FMCG retail field usually aim to analyze the statistics for sales of goods by:
categories, brands, territories and economy environment trends. We provide the missing extra
dimension - the customer. We strongly believe that knowledge of the customer as a person with
his/her motivational drivers, expectations and satisfaction levels is key to retail success.
o All retail industries covered
Our research methods allow for post research analysis to discover consumer behavior
across industries. This approach provides perspective on how the customer spends his/her overall
budget and discovers opportunities for cross-loyalty partner networks.
Supermarkets GAS STATIONS CLOTHES & ACCESSORIES
02

5. o Customers’ motivational perceptions insights
The customer is much more than a statistics unit. Various drivers are affecting his/her
decisions and different approaches can affect customers from one group (e.g. demographic) in a
completely different ways because of uncovered reasons.
www.explicato.com
Base N=1000,
All
respondents
5
4
1
4
5
8
7
7
23
36
3
2
0
2
8
12
2
11
27
32
Current Loyalty…
Future loyalty program
I can control my spends better
Gives me chance to buy the most modern and popular products on the market
Gives me chance to buy the best quality products on the market
Helps me feel I am part of a special group clients
Gives me chance to buy products, which are not available on the general market
Opportunity to gain bonuses which I can spent when I want
Makes me feel more sure when choosing particular items
I can use one and the same loyalty program across different entities
Makes the shopping pleasure last longer
I don’t have any benefits
02
Market
Research

6. Total Participants Non-participants
0
74
67
67
60
56
53
42
40
35
33
30
28
24
23
21
18
13
Quality…
Lower prices
Big variety…
Product…
Good location
Fresh…
Good…
Overall…
Good…
Loyalty…
Long…
Parking lot
Products…
All brands…
Good…
Enough…
0 50 100
Quality…
Lower prices
Big variety…
Product…
Fresh…
Good…
Good…
Loyalty…
Overall…
Good…
Long…
Parking lot
Products…
Good…
All brands…
Enough…
Own brands
www.explicato.com
Own brands
Other
1
68
68
67
53
43
41
41
29
28
24
23
23
20
16
36
55
73
0 50 100
Other
69
63
60
46
38
36
29
29
25
23
19
17
8
5
1
16
35
57
0 50 100
Quality…
Lower prices
Good…
Big variety…
Fresh…
Product…
Overall…
Good…
Long…
Good…
Products…
Parking lot
All brands…
Good…
Enough…
Loyalty…
Own brands
Other
Market
Research
Main drivers affecting the decision “where to go
shopping
02
o Customer drivers research
The drivers that affect customers’ decisions are not predefined constants but variables
that may be influenced through a proactive approach. You can not change the location of a store
easily, but you could make other drivers more important for the customer.

7. Potential
Assessment
Total Already participating
Definitely
not
4%
Definitely
yes
32%
Most
probably
not
7%
Not sure
23%
Most
probably
yes
34%
Definitely
Most
probably
not
3%
Not sure
17%
Plastic card
Casher receipt
Chip-card
Client's profile…
Mobile app
2 www.explicato.com
yes
Most 39%
probably
yes
38%
Definitely
not
3%
12%
8%
5%
0%
23%
Printed materials in shops
92%
Other
Main decision triggers (top 2 boxes)
Main Communication
Channels
Most preferred
technical device
Base N=1008, All respondents
85% 91% 80% 75% 72%
55%
3%
Price
reduction of
particular…
Price
reduction of
all products
Access to
special prize
games and…
Accumulation
of bonus
points for…
Vauchers or
prizes
exchangabl…
Lottary and
prize games
Others
28%
19%
16%
13%
13%
12%
8%
6%
5%
3%
3%
27%
77%
55%
55%
Friends/Relatives
TV ads
Internet
Billboards/Printed ads
Social Networks
Ads in printed media
WEB sites
Radio Ads
Company employees
TV news
Special articles in printed…
Articles in electronic media
Not interested
Radio news
Base N=665,
Would participate in future loyalty program
02
o Drill-down into retailer-specific findings
Based on our research we can extract specific findings for a specific retailer and
determine the segments of customers which are recognized as target groups.

8. data model Points
Retailer IT
infrastructure
Incremental data loads
following own designed
www.explicato.com
Loyalty
Strategy Design
Retailer’s
sales data
Customer basket
analysis
DEDICATED CAMPAIGNS
POS System Loyalty System Other Systems
Transactional sales
and loyalty data
Earn & burn
Discounts
Promo
Information
Privilege
02
o Discovery and establishment of value chains
between retailers and customers
Loyalty results from establishing strong value chains between retailers and customers.
For the customer 'value' means much more than discounts, bonuses and vouchers - it also means
access to special offers designed with deep understanding for their particular needs, information,
and privilege attitudes.

9. www.explicato.com
Explicato
DWH & BI 03
o Predefined database models of retail specifics
Our deep knowledge in retail and IT environment helped us develop a uniform
database model giving ready-to-use solutions to retailers from the start and a platform for
development of advanced analytic tools following the specifics of a particular organization. The
predefined database model can reduce time and costs for BI integration up to 90%.
o Cloud based solution
No need for big investments in servers, storage, software licenses and administration.
Practically no risk of data loss along with the highest standards for data security.
o ETL that is easy to adapt to rough data sources
The ETL extracting data from retail systems is designed to cover various retail system
standards like POS, BOS, HOIS, Loyalty, etc. Our goal is to have a pre-developed ETL for the most
common systems in a given market to reduce the integration time and cost to the minimum.
o Advanced analytics
Our goal is not just to provide the next-in-row reporting solution but real value for the
business by advanced analytics. We believe that Big Data should not be seen as the purpose, but as
a tool to reach deep understanding of the retail business.
o Fully web-based front end panel
We offer practically unlimited ways to access the BI front end using your laptop, tablet
or smart phone. No licenses for desktop applications, no requirements for devices, no additional
costs for support and maintenance. All this, with access fully secured by SSL certificates.

10. Sales by Store and Product Sales of Promoted Items
Sample Dashboard for the Store Manager Activity by Cardholder
www.explicato.com
Explicato
DWH & BI 04
o Operational report samples I
Operational reports cover sales and loyalty activities and build on the reports of
existing systems like POS, while avoiding full duplication.

11. Store performance by visits, sales and average
purchase
www.explicato.com
Store performance by hour of the day
(filter by weekday and period)
Cashier performance
Activity by Cardhoder
At-glance store status for the store manager
( to be included in the dashboard)
Customers Total Sales, Th Average Purchase Points Issued Points Burnt Points Balance
862 937,795 1,088 15,500 22,000 523,465
8% 2% -5% 3% 47% 0%
04
o Operational report samples II
The reports are designed to provide management with a full view of operations and
their efficiency.
Explicato
DWH & BI

12. o Analytical report samples
Analytical reports aim at providing the right tool for actionable insight covering the mix
of sales, loyalty and promotional activities.
Analysis of promotional activity – sales before,
during and after a promo
Effect of promotion on age group by average weekly
purchase
Targeting a promo campaign to specific customers Bonus points earned and burnt by age group for a
time period
www.explicato.com
04
Explicato
DWH & BI

13. Coverage and Technology
www.explicato.com
Social media
Analytics 05
o Integrated social media and analysis tools
Explicato and its development team can currently integrate the following social media and analytical tools:
Facebook;
Adform;
Gemius;
Google (Adwords and Analytics);
Sklik.
o How it works
Detailed data is collected from a specific social media page, e.g. Carrefour’s Facebook profile and not from the
Internet in general. The connection is established through configurable connectors (via APIs). The company provides
credentials for their profile to be used by the connector and a data collection engine is set to run on a specified time
interval (hours, days, etc.). The data is initially stored in its original form and then aggregated in accordance to the
requirements of the client. Data grouping and transformation is addressed in a flexible and customized way so new data
elements can be added without additional development effort as well as to meet changes in user requirements for the data
aggregation. The processed data is stored in a database for convenient use and further analysis.

14. www.explicato.com
Social media
Analytics 05
Data and Analytics Potential
o Type of collected data
The engine collects data for:
- Page likes;
- Post likes;
- Number and content of post comments;
- User data aggregated by age group, geographical factors, gender;
Note that specific user data such as login name is not provided by social media sites.
o Data usability
All dimensions of collected social data could be crossed in any possible way to produce valuable insight for the
specific needs of a customer. The data could be analyzed on its own or in conjunction with sales and loyalty data for deeper
and broader actionable insight. Example of such analyses include.
- Popularity of the company profile and its dynamics over time;
- Brand awareness;
- Website user profile by demographics and locations;
- Activity of web-site user groups in terms of visits, likes and comments for specific time intervals or posts;
- Targeting of promotional campaigns;
- Promotional campaign analytics - effectiveness and success;
- Text analytics to explore the user reaction to a post (promotional message, product review, etc.);
- Introduction of new products or product bundles;
- Test success of a retail activity through analysis of the comments.
Combining data for sales, loyalty and activity on the social media page could produce a universe or possibilities for an
analytical-minded organization and many options to explore for the less analysis-savvy ones.

15. www.explicato.com
Value
Chain