Turn network and customer data into actionable insight Whether you are a wireless, wireline, or cable network operator, the customer is king. From retaining existing customers to acquiring new subscribers from your competitors, competitive advantage in the fast-moving communications market is all about customer satisfaction and network modernization. Alteryx Strategic Analytics allows you to combine massive volumes of business and engineering data from your Business Support Systems (BSS) and Operational Support Systems (OSS) with third-party demographic, firmagraphic, and industry-specific data in single, integrated environment. Powerful analytics transform disparate data into actionable insight with geographic significance, so you can make strategic decisions about network expansion, customer acquisition and retention, proactive maintenance, and other critical improvements. Plus, results can be easily shared across your company to enable agile decisions that improve network performance, increase customer satisfaction, and drive new revenue opportunities.

1. Alteryx
Sample Use Cases
Telco

2. © 2012 Alteryx, Inc. 2
Table of Contents
Reducing Backhaul Expenses........................................................................... 3
Populations in a Coverage.............................................................................. 7
Identifying Signal Strength Issues .................................................................... 11
Smoothing Coverage Graphics ........................................................................ 15
Match Customer Profiles to Devices ................................................................. 17

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Reducing Backhaul Expenses
Business Question
How can my company reduce its backhaul expenses?
Background Information
A significant portion (35%) of a wireless carrier’s operating expenses is tied up in
backhaul.
Traffic from cell towers is transmitted via a multitude of circuit types (DS-1, DS-3,
and OC-3) depending on how much traffic a particular cell site experiences. There are
certain thresholds that are put in place when you switch from one circuit type to
another. For example, when you have a concentration of approximately 8 DS-1's (each
one is 1.5 megabits per second), then it normally makes fiscal sense to switch to a
DS-3 (45 mbps). There are also the same types of calculations moving to an OC-3 (155
mbps), but that office has to have the network equipment to support that
connectivity since those data streams are transmitted by fiber optics.
Answer Provided
This analytic app can be used by engineers to make sure that they have the most
efficient backhaul chosen for the cell tower locations.
It defines where that circuit is honing back into a Wire Center, and whether it crosses
a Wire Center boundary. If backhaul does cross a boundary, that is a more expensive
proposition for the carrier. The types of transport that defines this are inter-office
transport, or intra-office transport. Inter is more expensive, and the ILEC will gladly
provision these types of circuits since it represents more revenue for them.
Actionable Results
• As engineers or planners identify areas where circuits are incorrectly honed back
into a Wire Center, they can ensure the provisioning organizations are made aware
of these anomalies in order to implement less expensive alternatives.
• As indicated by the output below, the central office that is the shortest distance
away from the tower is not always the optimal office to backhaul to. If the
engineering or provisioning teams have incorrectly applied this methodology, they
will be crossing Wire Center boundary lines and incurring additional network costs.
This information can provide the basis for better provisioning.

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Output
The engineer will see both a visual map output, as well as the choice of
XLSX/CSV/TXT outputs for the tower locations and information relating to the Wire
Centers.
The following pages are a representative sample of the report output provided by the
analytic application.
Analysis of the Overall Footprint for the Area

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Representation of a Sample of an Individual Tower
Alteryx Data Utilized
The data from GeoResults can be used for this analysis to accurately describe the
Wire Center boundary areas.
• National Wire Center Boundaries
• National Central Office Buildings
• TomTom Map Layers

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Customer Data Utilized
The typical source of data for this analysis comes from the OSS (Operational Support
System) which can exist in any variety of storage methodologies.
Key Alteryx Tools Utilized
• Spatial Match
• Spatial Info
How it works
You will need to input the following in the Cell Tower Analysis application.
Cell Tower Location - This will include the following core components:
• Tower Name
• Tower Latitude
• Tower Longitude
Central Office Locations - This includes the Wire Center polygons which define where
that central office (where the backhaul circuit terminates to) is located.
Example of Input Format used by Analyst

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Populations in a Coverage
Business Questions
How much of the population of an area is covered by our network? What market areas
are being missed by our network coverage? Are we missing population centers that we
could cover?
Background Information
Wireless carriers need to determine how many people are covered by their network.
This information is important as it is a crucial requirement in reporting to the FCC and
financial markets. Valuations are based on the types of customers the carriers can
obtain, and those populations under their coverage layers. Being able to provide this
information rapidly and accurately allows the carriers to meet analyst needs
effectively, and make strategic decisions on where capital expenditures should occur.
Marketing is also able to use the data driven through this analysis to show their
coverage of populations in their network. This data can also be compared to existing
competitors to help gauge necessary improvements. Understanding the Demographic
and Behavioral profile of the customers within covered networks can assist in
identifying the most effective promotional campaign strategies.
Companies also need to find the population density within a wireless carrier’s
coverage area based on the quality of coverage. Identifying the varying decibel drop
ranges (e.g., Best Coverage at 50db to -60db, Better Coverage at -61db to -80db) that
will define coverage contours is significant. From this information engineering
managers are able to determine where networks need bolstering or where problems
may lay in current coverage.
Answers Provided
• Reports required for regulatory and financial purposes can be generated.
• Strategic decisions can be made with the resulting data to assist in identifying areas
for network expansion.
• Marketing departments can utilize this information to help compare coverage
populations with competitors.
• Network engineers can be provided with information that can be used to plan for
network upgrade.
Actionable Results
• Management will be able to suggest reallocation of capital expenditures based on
population shifts or shifts with customer profiles.

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• Management will be able to meet reporting needs in the financial markets more
accurately and efficiently.
Output
The map shows signal strength in the covered area.
The report includes population demographics for covered area.

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Alteryx Data Utilized
• A demographic data set is required to report out population values
Customer Data Utilized
Raw grd/grc data from native propagation analysis tools such as Atoll and Planet EV
are required.
Key Alteryx Tools Utilized
• Allocate Input
• Input
How it works
You will need to perform the following actions in the Population Analysis application.
1. Choose the grd/grc file that you will be reading and performing the Population analysis, as
well as the output location.
Sample first tab of application

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2. Select the demographic variables that you would like to calculate within the coverage
area.
Sample 2nd tab of application

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Identifying Signal Strength Issues
Business Question
How can we determine where we have signal strength issues within our network?
Background Information
Wireless carriers are continually monitoring their coverage areas to maintain an
understanding of where they may have poor signal strength or poor signal quality.
Poor signal strength or quality results in dropped calls for the customer which
negatively impacts customer retention.
They also want to know how their coverage area compares to that of their projected
coverage and to the strength of their competitors' coverage areas. To analyze their
coverage areas, wireless carriers often 'drive test' roads to measure the coverage,
capacity and quality of services of their radio network. Drive testing is a method of
measuring and assessing the coverage, capacity and Quality of Service (QoS) of a
mobile radio network.
The technique consists of using a motor vehicle containing mobile radio network air
interface measurement equipment that can detect and record a wide variety of the
physical and virtual parameters of mobile cellular service in a given geographical
area.
Drive testing collects an enormous amount of data and when using traditional tools,
network engineers have experienced difficulty with processing the vast amounts data
and analyzing the results in a timely manner using traditional tools such as GIS.
Answer Provided
Utilizing this application with the accumulated data will easily identify the actual
strength of signal in a given area within the network.
Actionable Results
• Identification of areas where actual signal strength varies from the propagation models
built with Planet EV or Atoll will allow for "tuning" of those models.
• Drive time feeds can be readily used by Marketing and Product teams to assure that the
coverage to support their campaigns and devices are in place. It will determine the types
of services that can be offered and the expected customer experience.

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Output
The following are sample outputs from this analysis:
The first is a map that shows the signal strength in the defined area by the grid sizes
(miles) as set by the user.
Defined signal strength by chosen Grid size
The second show the population densities in the corresponding grid areas.
Defined population densities within grid areas

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Alteryx Data Utilized
Map datasets and the demographic variables.
Customer Data Utilized
The included file would need to have signal strength, as well as the latitude and
longitude of the drive test readings.
Key Alteryx Tools Utilized
• Spatial Match
• Spatial Info
• Trade Area
• Allocate Append
How it works
The analyst uploads the data file from the Drive Test process and identifies the
corresponding fields in the file to
• Field identifying signal strength (-db drops)
• Fields identifying latitude and longitude of reading location
The analyst then inputs:
• Desired size of the grids for analysis and mapping (in miles)
• Name of the area for the title of the map
Example of Input Format used by Analyst

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Where to find the analytic app
Drive Test Data Analysis
http://www.alteryx.com/module-exchange-details/103

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Smoothing Coverage Graphics
Business Questions
How can we make our RF coverage data files more user-friendly with our other
systems?
Background Information
Often times when producing RF coverage files, they are too exact and are not very
palatable for applying them to Marketing and customer facing applications. Polygons
constructed from this data tend to be more complex than needed and can result in
slowing down the processes running against them. When these represented polygons
go through a ‘smoothing’ process, it makes the polygons less complex, and allows for
other internal teams to use those shapes for publishing covered areas on company
websites, etc.
Industry tools that create coverage polygons from these grd/grc files do not usually
take smoothing into consideration when generating from those files, leaving analysts
with data that is difficult to utilize. Having less complex polygons to represent those
coverage areas, while at the same time remaining as lossless as possible, helps to
introduce efficiencies when utilizing those files. This can save time for downstream
organizations and processes.
Answer Provided
This process creates less complex polygon objects that still accurately represent
coverage areas.
Actionable Results
• Better coverage graphics are available for Marketing departments
• More efficient use of the polygons by downstream organizations that may not be utilizing
Alteryx
• Smaller polygon file sizes to increase processing, and reduce memory consumption needs
Output
The actual output would be the spatial objects created after the smoothing effect.
As an example, the images below show the original coverage on the left and the
smoothed coverage on the right.

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Comparison of data files before/after 'smoothing'
Alteryx Data utilized
There are no Alteryx datasets necessary for this processing.
Customer Data utilized
Native grd/grc data from propagation analysis tools such as Atoll and Planet EV.
Key Alteryx Tools Utilized
• Generalize
• Smooth
• Polygon Split
• Spatial Process
How it works
Choose a sample coverage file that represents a raw output type. These would include
grd/grc file types that are from source propagation tools.
As shown in the module below that is downloadable, the points in the data file are
‘generalized’ and ‘smoothed’ multiple times depending on the amount of smoothing
desired.
Where to find the analytic app
Smoothing Examples
http://www.alteryx.com/module-exchange-details/646

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Match Customer Profiles to Devices
Business Question
What kind of customer uses a specific device?
Background Information
The usage of devices on a carrier network will vary greatly by the type of consumer
using that device. The Handset Profile analytic app looks at specific areas that are
user defined, and will then return core demographics of the user base in that area.
Being able to identify customer types in a given area, and then matching them to
devices allows for penetration analysis. For example, when the Marketing team runs
campaigns to for particular devices, the Engineering team can be assured that
capacity in the area can support sales of the device - given the populations of those
"appeal to" demographics in the area.
Answer Provided
Demographic and behavioral profiles can be attached to groups of users of specific
devices.
Actionable Results
• Marketing departments can tailor promotions in areas with predominant demographic
profiles to specific customer groups.
• Finance teams can verify that the pricing models for the plans that have been created are
profitable for varying customer types based on their usage patterns.
• Engineering teams can validate that capacity in given regions is supporting network
growth based on the customer type populations in a given area.

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Output
The output file includes information about the device (note: these will have to be a
chosen set of key points describing the particular handset model). It also includes
summary demographic information about the customer types based on the addresses
from the inputted customer file.
Alteryx Data Utilized
Demographic data is used to form the basis of National Averages.
Customer Data Utilized
Data will need to be used from BSS/OSS systems that include information on device
usage. Minutes of Use (MOU), Data Utilized, and SMS/MMS (Short Messaging Services

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and Multimedia Messaging Services) reporting needs to be included. Additionally, the
demographic data associated with either the Account or Device holder needs to be
included. This will determine whether we are describing the demographic variables of
either the Household or the individual Subscriber of the device.
Key Alteryx Tools Utilized
• Allocate Append
How it works
You will need to input the following in the Handset Profile module.
• Customer Input File – Includes address information for the customer segmented by the
device type to be analyzed.
• Device Type - The Input file customer file will need to reflect the device that is to be
analyzed.