Value of Location Analytics Manju Mahishi March 2015 @ArubaNetworks
Agenda Goal: Understand the value of location analytics for enterprises and public venues And how Aruba ALE together with key partner solutions can help with various analytics use cases and drive business value 2 CONFIDENTIAL Copyright 2015. Aruba Networks, Inc. All rights reserved
Understanding Analytics CONFIDENTIAL Copyright 2014. Aruba Networks, Inc. All rights reserved 3
Location Based Services in Enterprises Location / Traffic Pattern Analytics is becoming increasingly important across enterprises and public venues to support various operational and marketing initiatives and mobile engagement with context 4 CONFIDENTIAL Copyright 2015. Aruba Networks, Inc. All rights reserved
Why Location Data Matters Improve User/Customer Engagement Add context to customer purchase patterns Targeted engagement based on location Improve Ad effectiveness by > 2X Improve Operational Efficiencies Staffing Efficiency Don t wait for queues to build Proactively staff based on traffic Workspace Optimization Identify hot zones or lightly utilized spaces to save costs Location as context for access control and security 10% 5% 0% Click Through Rate 10% 7% 0.10% 1.2% 3.5% Source ABI Research 5 CONFIDENTIAL Copyright 2015. Aruba Networks, Inc. All rights reserved
Big Data Analytics: Market Sizing 6 CONFIDENTIAL Copyright 2015. Aruba Networks, Inc. All rights reserved
Location Analytics Across Verticals Retail Hospitality A/B Testing Optimize staffing Understand buying patterns Sentiment analysis Improve customer engagement Real time offers Stadium / Arena Enterprises Improve traffic flow Web analytics Workspace optimization Location based Access Policy management Airports / Malls Optimize traffic flows 7 CONFIDENTIAL Copyright 2015. Aruba Networks, Inc. All rights reserved
Retail Analytics Landscape: Key Trends and Initiatives SHELF SPACE OPTIMIZATION CUSTOMER MARKETING (SEGMENTATION, TARGETING, PERSONALIZATION) FRAUD DETECTION & PREVENTION INTEGRATED / STATISTICAL FORECASTING LOCALIZATION, CLUSTERING (DEMOGRAPHIC DATA) MARKETING MIX MODELING (A/B TESTING) PRICING OPTIMZATION PRODUCT RECOMMENDATION REAL ESTATE OPTIMIZATION SUPPLY CHAIN ANALYTICS; INVENTORY OPTIMIZATION TEST & LEARN WORKFORCE ANALYTICS (STAFF OPTIMIZATION) MULTI-CHANNEL ANALYTICS (ONLINE, OFFLINE) LOCATION ANALYTICS, REAL TIME ENGAGEMENT VIDEO ANALYTICS 8 CONFIDENTIAL Copyright 2015. Aruba Networks, Inc. All rights reserved
Retail Big Data Topology (Source: IDC, 2012) 9 CONFIDENTIAL Copyright 2015. Aruba Networks, Inc. All rights reserved
Decoding Big Data 10 CONFIDENTIAL Copyright 2015. Aruba Networks, Inc. All rights reserved
Analytics: Key Takeaways Analytics is multi-faceted, complex, with many use cases still evolving and several ecosystem players Most real world implementations require integration with other data sources (Sensors, Loyalty databases, POS, etc.) to create more meaningful data May need a SI involvement to put things together Aruba s ALE provides rich mobility context to analytics and Big Data / mining systems.but this becomes truly useful only when combined with multiple data sources to drive business insights and contextually relevant user engagement 11 CONFIDENTIAL Copyright 2015. Aruba Networks, Inc. All rights reserved
An Overview of Aruba Analytics and Location Engine (ALE) CONFIDENTIAL Copyright 2014. Aruba Networks, Inc. All rights reserved 12
Mapping LBS Use Cases to Aruba s Solutions MERIDIAN Indoor Mapping Services Indoor Location Engine ALE (Network) Meridian w/ble MERIDIAN Mobile Engagement App Platform Contextual Engagement: Proximity Notifications MERIDIAN, PARTNERS CLEARPASS Guest Access, Branded Portals LBS Analytics, Data Mining ALE + PARTNERS 13 CONFIDENTIAL Copyright 2015. Aruba Networks, Inc. All rights reserved
Analytics and User / Customer Engagement ALE Contextual Data: User, Device, Application & Location Other Data Sources Sensors CRM ENGAGEMENT Location / User Specific Experiences DATA MINING / ANALYTICS Venue Traffic Patterns, A/B Testing, Demographic Analysis, etc. MARKETING, AD PLATFORMS 14 CONFIDENTIAL Copyright 2015. Aruba Networks, Inc. All rights reserved
Analytics and Location Engine (ALE): Key Functions 1 Unified context for each user (user name, IP, MAC, device type, App visibility, etc.) 3 High performance Northbound APIs (publish/ subscribe, polling) ALE$ 2 4 Real time location engine Seamless, secure connectivity to analytics platforms 15 CONFIDENTIAL Copyright 2015. Aruba Networks, Inc. All rights reserved
ALE System Overview LOCATION$ ANALYTICS$ PLATFORMS$ AirWave Visual RF Analytics Partner Location Services ALE imports Visual RF maps, Decodes AMON, Computes Location, Provides Context APIs ALE Controllers Create AMON Messages MOBILITY CONTROLLERS INSTANT APs AP s Create Virtual Beacon Report (VBR) Probing Clients 16 CONFIDENTIAL Copyright 2015. Aruba Networks, Inc. All rights reserved
ALE Internal Workflow ALE$Virtual$Machine$ Polling$API$ (REST)$ ALE$Processes$ Publish$the$received$data$ using$publish/subscribe$api$ (Google$Protobuf/0MQ)$ Data$from$ Controller$(AMON)$ or$iap$(https)$ Decode$the$ Received$ data$to$ appropriate$ format$ Client$RSSI$data$ North$Bound$API$ Forward$decoded$User,$ Device,$App$data$ Loca6on$ Engine$ Write$the$received/ computed$data$to$ DB$$ Calculate$Device$ Loca6on$(x,y)$ Redis$In: Memory$ Database$ Floor$Maps$ from$visual$rf$ (Airwave)$ 17 CONFIDENTIAL Copyright 2015. Aruba Networks, Inc. All rights reserved
Data Aggregated & Exposed by ALE Presence Feed Indicating a device has been detected in range of WLAN Geofence Events Entering or leaving a zone Device information Model, OS (from DHCP and browser user-agent) User information from network authentication: Type of authentication, username Applications Visibility As detected by monitoring data-plane traffic from the device Destination URLs By monitoring data-plane traffic from the device 18 CONFIDENTIAL Copyright 2015. Aruba Networks, Inc. All rights reserved
ALE Northbound APIs Two types of Northbound APIs: Publish/Subscribe Uses Google Protocol Buffering ( Protobuf ) for encoding and TCP based ØMQ transport External Analytics engines can subscribe to various topics : Location Presence Applications, Destination URLs Campus, building, floor, etc. Polling Based: REST API Supports standard REST queries for various events/objects Example: http://<ip>/api/v1/station will return a list of all stations Return data format is JSON 19 CONFIDENTIAL Copyright 2015. Aruba Networks, Inc. All rights reserved
ALE Software Delivery ALE Product is delivered as a VM only (OVA File) Supported/Tested on VMware ESX/ESXi 5.0 and higher Can be deployed with various different hardware configurations (for CPU, Memory, Hard Disk) based on scale requirements VM has CentOS 6.4 pre-installed with all the needed dependencies ISO Image option is also available ALE licensed on per-ap basis 20 CONFIDENTIAL Copyright 2015. Aruba Networks, Inc. All rights reserved
ALE Server Sizing Guidelines Configuration Number of AP s/ Clients CPU Cores RAM Hard Disk SMALL 500 / 8000 4 16 GB 160 GB MEDIUM 1,000 / 16,000 8 24 GB 320 GB LARGE 2,000 / 32,000 16 48 GB 1 TB Notes on Server Sizing: Maximum number of controllers per ALE instance = 4 Maximum number of AirWave servers per ALE instance = 1 Max number of APs per ALE instance = 2K Maximum number of clients per ALE instance = 32K Client counts includes mix of associated and unassociated devices Recommended Grid Size (Floor Plan in AirWave) = 10 x 10 ft 21 CONFIDENTIAL Copyright 2015. Aruba Networks, Inc. All rights reserved
ALE: Simple Configuration Requirements! Controller Configuration Each controller must be configured to send data to ALE ALE Configuration ALE must know about each controller (this is used to initially pull the current information) ALE must know about the Airwave (AMP) server, so that it can pull in the maps and AP placement data IAP Configuration Each IAP Virtual Controller (VC) needs to be configured to send data to ALE Each IAP (not just VC) needs to be placed on the map also 22 CONFIDENTIAL Copyright 2015. Aruba Networks, Inc. All rights reserved
ALE v1.3 Dashboard: New GUI 23 CONFIDENTIAL Copyright 2015. Aruba Networks, Inc. All rights reserved
Choosing Floors to Import from AirWave 24 CONFIDENTIAL Copyright 2015. Aruba Networks, Inc. All rights reserved
Setting Up Secure WebSocket Tunnel to External Analytics Engines 25 CONFIDENTIAL Copyright 2015. Aruba Networks, Inc. All rights reserved
Map - less Support for Small Locations with Instant AP s Assume a small venue deployment with IAP s (coffee shops, small retail stores, etc.) 1-2 AP per location No Maps are needed from Airwave in this scenario (with ALE 1.3) IAP s begin sending data from every location ALE realizes data is being generated from single AP s Switches to Map-less mode and generates events appropriately 26 CONFIDENTIAL Copyright 2015. Aruba Networks, Inc. All rights reserved
Geofencing Support (ALE 1.3) PoC Area Key Highlights Cubicals Draw regions in Airwave Regions equate to Geofences in ALE ALE generates events of ZoneIn and ZoneOut and provides dwell times (through Geofence notify APIs) 27 CONFIDENTIAL Copyright 2015. Aruba Networks, Inc. All rights reserved
Excluding Regions from Location Calculation 1. Draw a region 2. Region Name should begin with underscore Assume a Mall environment Given the openness of area, there is a probability a client gets triangulated in the Atrium To avoid this, ALE does not place clients in any region drawn in Airwave that begins with an _UNDERSCORE 28 CONFIDENTIAL Copyright 2015. Aruba Networks, Inc. All rights reserved
ALE Location Calculation Overview Location is based on RSSI (from Probes, Data Frames) All APs will report RSSI for the probes (Virtual Beacon Report (VBR)) RSSI from Data Frames (for associated clients) is sent via RTLS feeds directly from AP s (or Air Monitors) Location calculation based on Path Loss Models Path Loss = Received signal client transmit power Path Loss = k + 10 n log(d) Where K is the path loss at 1 meter. K is different for 2.4 and 5.0 GHz radios. If we know the path loss, distance can be estimated If we get distance from 3 APs, we can uniquely triangulate With 2 APs, there are 2 points of intersection, so there is ambiguity ALE returns the AP coordinates (x,y) as proxy to client location when fewer than 3 AP s are available for location calculation ( Single AP location feature can be enabled via configuration) In real life RSSI can fluctuate Aruba s location engine uses outlier detection and dampening algorithms 29 CONFIDENTIAL Copyright 2015. Aruba Networks, Inc. All rights reserved
Location Accuracy & Latency (Summary) Factors impacting Accuracy AP density, type, mounting type Higher the AP (and Air Monitor) density, the better the location accuracy Recommended AP / AM density is one every 50 ft (2500 sq ft coverage) Client probing behavior, RSSI Variations, Device type, OS type Factors impacting Latency Client probe frequency (ios vs Android) Network settings: AP/controller timers Impact to Use Cases: In general, Wi-Fi based locationing from ALE lends itself to use cases where traffic trends / patterns can be analyzed over a period of time 30 CONFIDENTIAL Copyright 2015. Aruba Networks, Inc. All rights reserved
Measured RSSI Variation 31 CONFIDENTIAL Copyright 2015. Aruba Networks, Inc. All rights reserved
Design Considerations for Locationing It is imperative to start with a good understanding of business requirements What are the key use cases and true business requirements? Traffic Pattern Analytics inside venues? Self directed museum tours? Push Notifications by Zone (or with more granularity)? Ability to locate specific venue (conference room, restaurant, etc.) within a large venue (statically) or an app that provides turn by turn directions (dynamically)? Knowledge of the use case is key to understanding location accuracy, latency requirements and designing the network to support the use cases For micro-locationing or proximity detection and indoor turn by turn direction use cases, a client based solution (BLE) is recommended 32 CONFIDENTIAL Copyright 2015. Aruba Networks, Inc. All rights reserved
Traffic Pattern Analytics Enabled by ALE! Presence (Inside Venues / Conference Rooms)! Capture Rates (Inside versus Walk-Bys)! Dwell Times by Geofence! Repeat versus New Visitors! User Classification (Employees versus Guests) 33 CONFIDENTIAL Copyright 2015. Aruba Networks, Inc. All rights reserved
Key Location Analytics Enabled by ALE Traffic Patterns, Engagement in Public Venues Enterprise: Workspace Optimization Location Based Security Policies SDN Enablement (Context APIs) Smart Energy Management Integration with Machine Data Systems 34 CONFIDENTIAL Copyright 2015. Aruba Networks, Inc. All rights reserved
ALE In Action: A Few Case Studies Analytics Partners CONFIDENTIAL Copyright 2014. Aruba Networks, Inc. All rights reserved 35
Analytics Example Hospitality (ALE Integration with APAMA) 36 CONFIDENTIAL Copyright 2015. Aruba Networks, Inc. All rights reserved
Geofence Analytics Example Hospitality (ALE Integration with APAMA) 37 CONFIDENTIAL Copyright 2015. Aruba Networks, Inc. All rights reserved
Retail Traffic Analytics Reporting (Sample) ShopperTrak Sample Report (Generated for a Retail Store in Spain; integrating with ALE) 38 CONFIDENTIAL Copyright 2015. Aruba Networks, Inc. All rights reserved
Retail Traffic Analytics Reporting in Shopping Mall (AisleLabs Flow Analytics Sample) 39 CONFIDENTIAL Copyright 2015. Aruba Networks, Inc. All rights reserved
Traffic Pattern Analysis (AisleLabs Sample Data) $ Operations $ Information can assist with $ planning day-to-day shopping center management operations, such as staffing$ $ Is$a$specific$markeHng$ campaign$effechve$ A$daily$review$of$peak$6mes$will$ help$evaluate$and$measure$the$ results$of$promo6onal$ campaigns$and$event$programs$ Peak$hours$remain$stable$ between$$$$10:00$am$o$2:00$pm$$ Compared to the rest of the Saturdays, guest numbers climbed at 10:00 AM for week #3 and for 6:00 PM for week #4 perhaps due to promotional campaigns. 2014 Aislelabs 40 CONFIDENTIAL Copyright 2015. Aruba Networks, Inc. All rights reserved
Correlation with Point of Sale Information (AisleLabs Sample) 41 CONFIDENTIAL Copyright 2015. Aruba Networks, Inc. All rights reserved
SkyFii Analytics (ALE Integration Example) 42 CONFIDENTIAL Copyright 2015. Aruba Networks, Inc. All rights reserved
Location as Context for Access Policies (Roadmap) X Restrict resources by location for compliance Restrict guest access to inside Geo-fence Finger Print Aruba WLAN (Access Policy Enforcement based on Location) Dynamic Policy Update/ Enforcement (CoA) ALE Device Location Update / Gepfence Event XML API ClearPass Policy Mgr Location as Policy Definition 43 CONFIDENTIAL Copyright 2015. Aruba Networks, Inc. All rights reserved
Machine(Data(Analytics( ALE$ $Splunk$Integration( Splunk Forwarder Devices Devices Devices ALE Applications SDK splunk> Streaming data Log Files Development Kit: - Interact with the data in Splunk - Control, manage, script - SDK support for Perl, Python, Ruby etc. - Develop custom applications - 1000s of applications already available Splunk Engine: - No RDMS(stored natively) - Parse/Index/Store the data - Runs scripts, queries, dashboards - Cluster & Cloud enabled - Hunk for Hadoop - Splunk can be hierarchical (allows distributed searches) Data Feed: - Files & Directories (remote) - TCP/UDP unstructured data feed - Forwarders (Universal/Light/Heavy) - Gather data from network - Forward (un-indexed) to Splunk Engine - Compression, SSL, Configurable Buffering - Feedback from the engine 44 CONFIDENTIAL Copyright 2015. Aruba Networks, Inc. All rights reserved
Splunk App Application Visibility Dashboard 45 CONFIDENTIAL Copyright 2015. Aruba Networks, Inc. All rights reserved
Splunk App Station Dashboard 46 CONFIDENTIAL Copyright 2015. Aruba Networks, Inc. All rights reserved
Key 3 rd Party Location Analytics Partners - 1 Partner Details Expertise: Real time / streaming data analytics Focus on Finance industry; new to retail location analytics Highly customizable; Integration with other data sources; High cost Suitable for large enterprises (e.g. Hyatt Resorts & Hotels) Retail foot traffic analytics Integration with video camera feeds; other data sources (POS, Loyalty databases, etc.) Customizable reports, alerts; predictive analytics Omni-channel KPIs Presence Analytics Mainly operate in APJ, LATAM, SA Standard KPIs: Dwell time, People counts, First Time vs Repeat Visitors, etc. Retail and Casual Restaurants (e.g. Westfield Malls) Small startup, based in Spain Solution focus: Retail Presence Analytics Standard Retail Traffic Analytics KPIs: Visitor frequency, Dwell time by zones Integration with video feeds End to end platform for shopping mall marketing and analytics Customizable analytics of shopper behavior Social Wi-Fi Engagement solutions (with BLE / SDKs) 47 CONFIDENTIAL Copyright 2015. Aruba Networks, Inc. All rights reserved
Key 3 rd Party Location Analytics Partners - 2 Partner Details Well know for retail analytics (global list of customers). 20 Year experience Started with stereoscopic methods for foot traffic counting; new to Wi-Fi integration with other data sources: POS, etc. Highly consultative sales / engagement process Cloud-based Retail / QSR traffic analytics Basic KPIs; some integration with other data sources (POS, etc.) Customizable reports including benchmarking, A/B Testing Low cost of entry Retail traffic analytics; Based in Finland Standard KPIs: Engagement; dwell times; identifying loyal customers, etc. APIs to external marketing software, Google Analytics, etc. Recently acquired by Brickstream Started with Wi-Fi only solution (Like Eulid).now have Beacons for Engagement, and integration with video feeds for people counting Similar store analytics KPIs as others (dwell times, paths, etc.) Business intelligence for workspace optimization Can integrate multiple data sources (Wi-Fi, secure card readers, other sensors) Predictive analytics 48 CONFIDENTIAL Copyright 2015. Aruba Networks, Inc. All rights reserved
SUMMARY CONFIDENTIAL Copyright 2014. Aruba Networks, Inc. All rights reserved 49
Summary: Analytics A Journey Identify Key Use Cases, Business Value Proposition 1 POC 2 to 3 months Evaluate couple of solutions Refine Use Cases 3 2 4 Tune Network, Identify Key Partners for POC, Design Use Cases Develop ALE Adaptor (API Programming) Build Internal Processes to consume and act on the data. Refine Use Cases 50 CONFIDENTIAL Copyright 2015. Aruba Networks, Inc. All rights reserved
Summary: Key Purpose of ALE Context Aggregation and Export User, Role, Device, Location, Application Meta Data: [URL, Session] Real Time Traffic Flows.To Drive key business use cases: Traffic Pattern Analytics in Retail and other enterprises (Presence, Dwell Times by zones, etc.) Network / IT Analytics Location context for access / security policy management ALE is NOT An indoor Navigation / Blue Dot solution A solution for proximity engagement requiring less than 5 m accuracy A.L.E 51 CONFIDENTIAL Copyright 2015. Aruba Networks, Inc. All rights reserved
ALE: Key Resources Detailed ALE API Document Sample Feed Reader Code (0MQ) in C and Java Source Code for ALE Demonstrator App (Android) on GitHub Shows how to consume both REST and 0MQ APIs Help with API programming Secure link to streaming Data from ALE server (Sunnyvale LAB) for Adapter development Help with Splunk / ElasticSearch + Logstash (ELK) integration Help with POCs Whatever help you need, we are available! ALE Demonstrator App (Android) 52 CONFIDENTIAL Copyright 2015. Aruba Networks, Inc. All rights reserved
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