Learn how many useful KPIs and features we can provide vs. traditional cameras and wifi-bluetooth mac tracking

1. 1
Learn how many useful KPIs and features can we provide over
traditional cameras and wifi-bluetooth mac tracking?
Seeketing provides in depth analysis and insights about visitors behavior to improve the location
performance. You can now attract more visitors, send them personalized notifications, and measure how
effective your offline and online strategies are with regards to attracting new visitors to the point of interest
Seeketing technology is able to collect and manage phygital and digital behaviour person by person
as a single and continuous process
www.seeketing.com (+34) 676482952 contact@seeketing.com
Shopping
opportunities
increase
35%
Promo
Conversion: 23%
New visitors: 342
Recurrent visitors:
43

2. Tickets
+
Footfall
Dwell Time
Opportunities
Unique Visitors
Proximity
response
Recurrence
Personal Data
Flows
Phygital
Response
1.1.Aggregate or extrapolated data
Heat Maps
1.2.Visitor by visitor measurement
ratios and their evolution
1.3. Optimization
Customer knowledge
2.1. Employees in the store
2.2. Employees
by zone
2.3.Employees by
client’s behavior
3.1. Performance Rate
(tickets/footfall)
3.2. Conversion rate
by category
3.3. Evolution by type
of client and
recommendations
Colored Map
- Performance Map and Flows
2. Use case: Employees
1. Data value
- Aggregated / extrapolated
- The layout sets the maps
- Visitor by visitor
- Zone by zone
- Segments and profiles
Seeketing integrated
Traditional Cameras
+ Wifi tracking
Seeketing integrated
3. Use Case : Clients

3. Proximity marketing
(Seeketing)
Web behavior Store behavior
Seeketing Omnichannel ID
App behavior
Seeketing can link CRM user’s data with store and Web/App navigation behavior
CRM
Marketing Funnel
Registered users
Visits
Sales
Outdoor Campaigns
Phygital behavior segmentation
In-Store Campaigns
Omnichannel response and visibility
Client by client optimization
Outdoor Campaigns
Basic segmentation.
(Gender/Age)
No data in physical stores
The user must identify the
campaigns origin
Seeketing integrated
Traditional CRM
1%
0,15%
8%
4%
25% 20%

4. The appropriate ratio to value is
the performance per zone
Zone ABC
Footfall= 28?
3.000 Euros
Zone B. 980 Euros
Performance = 245
Zone A. 1000 Euros
Performace = 45
Zone ABC
OUT IN
Sales of each category/products/services in each area may be similar. Transaction and footfall data are not
enough to optimize the space. We must know how many people are interested in each product/service and their
time spent to really know which one works best (performance). Zones B and C have an excellent performance,
while sub-zone A has many potential for improvement.
Zone C. 1020 Euros
Performance = 340

5. 1 minute
It takes a person a minute to go back and forth or come and go multiple times in the same minute. Also, a person
can be at the door for a minute talking on the phone. In these cases, the footfall (camera) cannot give any
precision in people counting, specially in areas with wide doors or without doors.
Opportunities = 1
Unique visitors = 1
Persons= 1
Presence time= 10 seconds
Window Opportunity= 60 seconds
Footfall (camera) = 2
Hourly data
Opportunities = 1
Unique visitors= 1
Persons= 1
Presence time= 1 seconds
Window Opportunity= 60 seconds
Footfall (camera) = 10
Hourly data
OUT IN
The opportunities and unique visitors
are the indicators to value.

6. The number of people entering an area/building may be lower. However, it represents a better performance since
1 in 3 people enter. Seeketing technology measures how many people who pass by finally enter. We can’t
optimize knowing only the number of steps, without knowing how many people could have entered and have not.
Conversions = 16%
Persons= 1 of each 4
Footfall (camera) = 6
Daily data
Conversions = 33%
Footfall (camera) = 2
Daily data
OUT IN
Conversion= 15%
Conversions= 33%
Persons= 1 of each 3
Conversions are the
appropriate ratio to value.

7. ABC Footfall= 40?
ABC Opportunities = 32
ABC Unique visitors= 32
ABC Persons= 34
Flow= 30%
Flow= 50%
Zone B
Zone A
Zone C
Flow= 15%
Zone ABC
The destination and origin flows
indicate the percentage of the total
opportunities that are detected first
in one are and then in another.
Seeketing allows to know 80% of the
movements and behavior. Footfall
data are not enough to know
people’s behavior.
Flows between zones are the
appropriate ratio to value.

8. Persons= 36
Footfall= 36
Opportunities = 36
Unique visitors= 6
Persons= 6
Recurrency = 3 times by month
Time between visits = 80% every week,
20% every 15 day
Hourly data
In the situation that fewer and fewer people visit us, but those who visit us increase their frequency of visits, with
a count of steps we won’t be able to anticipate solving the people. Once the sales drop, it will be late.
Persons= 6 Hourly data
The ickets / footfall ratio doesn’t add any value
Footfall= 36
The appropriate indicator to value is
recurrence.

9. Each person waits a certain time to be attended to in the waiting area. The average waiting time and the total
time when a person enters the area until that person leaves, allows us to measure waiting times, attention and
distinguish people by their behavior. For example, employees who spend more than 5 hours in an area are not
mistaken for costumers.
Employees presence time= 5 hours
Queue time= 12 minutes
Zona A. Dwell time= 2 minutes
In each area people spend more or less time. Some of these areas are passageways and others aren’t. We
cannot compare the performance of each zone, or the interest people have on each zone with footfall data.
Zona B. Dwell time= 21 minutes
Footfall (camera) = 13 Footfall (camera) = 7
The presence time of each person is
the appropriate indicator to value.

10. Door of ABC zone
Footfall= 28?
Zone B. Social distance > 2 meters
Zone A. Social Distance <1 m
Zone ABC
OUT IN
Cameras provide an uncertain capacity value. However, social distancing is not respected, almost all people crowd
in certain areas.
Zone C. Social distance > 2 meters
Social distance by area is the
appropriate indicator to value.

11. We went from just having gender and age data, to adding person-to-person behavior data, and knowing their
response to proximity messages and having their data from web visits and a specific physical area person-to-
person.
Gender data = 50% M 50% Female
Age data: 18-25 = 20%, 26-35= 80%
Recurrency = 3 times by month
Visited Zones = A, B, C
Monthly data
Web Visitors = 10%
Proximity messages received = 10
Purchases by week = 4
Surveys = tastes, children, incomes, colors
Interest in sports = 80%
Tourist= 10%
Phygital behavior is the appropriate
indicator to value.

12. +34 915024409 / +34 670463223
contact@seeketing.com
Skype: Seeketing
www.seeketing.com
Seeketing develops Marketing Intelligence solutions for:
§ Malls Operators
§ Retailers
§ Airports and other Transportation Hubs
§ Hotels and hospitals
§ Leisure and Attraction Parks,
§ Cultural Sites such as museums
§ Digital Signage
§ Municipalities for infrastructure investment
Seek ID: 760382
Visits Year: 38
Visit Frequency: High
Freq. Visit: 13:00-14:30
Total Stores Visited: 3
Avg. Dwell: 34 mins
Visits Week: 2
Seek ID: 153704
Visit Frequency: Low
Total Stores Visited: 12
Visit Peak Times: 19:00-20:30
Average Dwell: 18 mins
Visit / Week: 4
Visits Year: 38
*Key Categories: Sports -
Apparel
*Conversion: 68%
*Average Spend: €28.54
*Trend €: ↑ 4%
*Age: 33
*Combination CRM, Web, App,