Showing all posts tagged analytics:

Five Best Practices for Creating Meaningful Mobile Engagement

Engaging customers via their mobile devices is an exciting proposition for many organizations; however, it has to be done with care. These solutions often carry a significant cost and depend on a Return on Investment (ROI) model to make sense.

Achieving this ROI requires walking a fine line between meaningful engagement and being a nuisance. Here are five best practices to help you do that.

5 ways to ensure your mobile strategy works

1. Think big picture

The goal is to create a user experience that provides vast amounts of data to the organization while delivering value to the customer. Accomplishing that means the experience needs to be immersive and omni-channel (e.g., SMS, email, app-based, digital signage, direct mail, etc.).

Too many organizations jump straight to the mobile application without realizing adoption of mobile applications is low and retention of those mobile apps is even lower. A holistic approach that embraces the web (traditional and mobile), mobile apps, digital and physical signage, and some of the emerging areas such as augmented reality (AR) and context-aware chatbots will be far more successful.

Analytics and business intelligence tools must be included because understanding the success of these messages and their impact on the bottom line is a necessity, as engagement attempts that are ill-received may create a negative effect on the business.

2. Establish a baseline

Before rolling out any new engagement solution or even a single targeted campaign, it is important to understand the baseline. What is normal for a specific time of day, day of week, demographic, location, etc.

If there are areas in which these baselines are unknown, the success of an engagement will also likely be unknown. The length of time to determine a credible baseline depends on business and vertical; however, a month of data will provide statistically valuable data for many organizations.

3. Consider your social credibility

Each engagement or touchpoint with the user must be carefully weighed prior to being implemented, as the organization is spending “social credibility" with the customer in issuing these engagements. Determining that a message is hitting the right person at the right time and place is paramount to success.

While the organization may want to drive a specific behavior, it must be done in such a way that it is graciously accepted by the recipient. For less important messages, consider other channels for delivery—email, direct mail and digital signage integrations are options that are less invasive than a targeted push message.

4. Leverage employee engagement

Business should ensure the human component isn’t lost in this digital marketing frenzy.

Consider a scenario in which an employee could be notified when a user has spent more than five minutes in front of a specific retail display or there has been a high density of users in line for a drink at a sports game or concert venue. Rather than trying to ping users to have them go find another bar, consider triggers that have an employee come over with a mobile payment system and perform line-breaking transactions. This human component may still be considered a “digital engagement," but it won’t feel like it to the consumer.

5. Keep it fresh

Digital engagements should always be timely and relevant. Organizations can’t afford to be lazy about managing these platforms because pushing irrelevant messages will drive away customers, cause them to remove their mobile apps, and even consider competitors.

Campaigns should also create a sense of urgency—create a fear of missing out or at least ensure customers understand this immediate deal is good for only the first 100 redemptions.

Gamification is one way to keep things interesting for consumers, and it can drive additional spend as it may promise “bonus" rewards for the additional engagement. The solutions should be simple enough that they can be managed by marketing teams and not IT.

Originally posted here with Network World. Republished with permission as originating author. Also available on my LinkedIn page.

The Spark of Innovation

This week was one of those weeks where I had the opportunity to witness one of the most personally rewarding things in my job and the greatest reason that I do what I do - I saw that spark that lit up my customer's world. We were sharing a narrative of how we could go about providing mobile analytics and business intelligence for our customer. The directors that we were presenting to immediately got what could be accomplished and we were off to the races discussing possible scenarios, story arcs, etc. We were shortly joined by a VP of Operations and the company's Owner who had been asked to join us by their colleagues. Our collective team spent the better part of the next hour and a half hashing out the details of what would make this a successful endeavor. Everyone left the meeting on a natural high sparked by the excitement of innovation and the opportunity to disrupt competition in a major way.

That spark and these moments embody EVOTEK and why I believe so strongly that we are truly bringing something new to our customers. Thank you for everyone in that meeting for creating something truly memorable.

The Rise of the Machine Learning Solutions

Heading into Aruba Atmosphere this year I was most excited to see Aruba’s new Niara solution in action and learn more about this product as it solves a very real need in every network. Inherently any network policy grants some sort of access to the network and users are free to work within the confines of that policy. Even using 802.1X-based authentication and dynamically provisioned VLANs, access roles, downloadable ACLs, etc. isn’t necessarily enough. Niara solves for these issues in an appealing way and lessens the workloads for SecOps teams.

Case #1: Stolen Credentials
A known valid user can operate within their policy, but what happens if they are compromised either through social engineering, weak passwords, poor password management, etc.? Niara builds a profile of what is typical behavior of a specific user, if their patterns change this will be identified by the system. Perhaps the user starts attempting to access new areas or is visiting new websites—by a change in behavior, it is possible to identify a need for a change in policy, alert the SecOps team, or eventually automate remediation or lockdown of the user. Comparing to a baseline as well as other similar users gives Niara a frame of reference for the user under evaluation.

Case #2: Malware and Viruses
Both malware and viruses are capable of changing the behavior of network attached clients, while numerous tools already exist to help combat these Niara could serve as a welcome tool to identify and isolate infected clients or in a perfect world learn about how a Day Zero Attack might attempt to compromise the network and automatically harden the network in anticipation of this attack. The combination of these capabilities along with Aruba’s open APIs using Aruba’s Exchange offers some very interesting possibilities by enabling the collection of data from ecosystem partners with a greater speciality in the malware and virus arena. Imagine a world in which your firewall vendor has detected a new type of malware, shares that data with Aruba ClearPass and Niara via APIs, syslog, SIEM, or other similar routes and then the network automatically reacts to prevent the spread of that malware at the same time you are being notified.

Case #3: Software Bugs/Anomalous Behavior
If an application is updated and begins to operate differently on the network, Niara can identify this and enable teams to understand the new behavior. New behaviors deemed as risky can be mitigated against and feedback can be provided to the company’s development team. A specific example of this was provided at the conference in a popular file share company who’s update generated unwanted traffic on the network. Niara’s machine learning was able to identify and allow this undesirable behavior to be stopped.

Aruba, a Hewlett Packard Enterprise Company opens the door to a world of possibilities with the addition of machine learning and extends those capabilities elegantly through their open architecture in Aruba Exchange. I would anticipate that this field of machine learning is going to explode in the networking world as IT teams are facing increasingly difficult security challenges and are being asked to do more with less people and less resources. Automation of detection and defense should be able to solve 75-80% of the issues out there, enabling IT to focus on the most challenging and highest value problems out there.

Building a Contextually Aware Network: Geolocation (Part 2 of 4)


Geolocation is defined as the process of physically locating or the actual location of an object on Earth. In defining contextually aware networks, it is no longer enough to know whether someone is on-net or off-net. Where they are "off network" is important as well and can offer additional insights and opportunities for engagement.

Geolocation Technical Details

Geolocation primarily leverages a Smartphone's built in Global Positioning System (GPS) and uses the installed application and either Wi-Fi or cellular backhaul to report current location for users that have opted in to this offering. This enables the operator of a contextually aware application to engage with the customer outside the "four walls" of the organization. At this macro scale, location is typically measured in meters however results vary wildly depending on the type of location being deployed.

Assisted GPS (A-GPS)

Assisted GPS uses a secondary system to increase the accuracy of the GPS satellite reporting. In the case of Smartphones the cellular network is responsible for assisting. This enables the phone to download information about the GPS satellites in order to quickly determine its position and provide updates at an interval frequent enough to be useful for engagement purposes. The newest smartphones are able to use both the US Department of Defense GPS system and the Russian GLONASS system to further increase accuracy. These solutions are limited in scope from an engagement perspective as they require clear visibility to the sky, so they tend to not function in large downtown areas. Recent testing has shown that A-GPS offers approximately an 8 meter accuracy range, which is typically accurate enough for any of the geolocation use cases. IT is important to note that accuracy in dense urban centers may still be challenged at times.


One of the most important aspects of constructing a contextually aware network is the concept of geofencing. A geofence is a virtual construct that overlays a logical "fence" on the world map and allows decisions to be made as a device crosses the geofence or is inside or outside that geofence. A virtually unlimited number of geofences can be constructed, but it is important to know when engaging with the customer is meaningful and wanted. Since the geofence is virtual, no equipment is required at any location defined by a geofence.

How Geofencing Works

Let's assume for a moment that you are headed out on a gambling vacation to "The Vegas Hotel" on the south end of the Las Vegas strip and have installed their mobile concierge app. Upon landing at McCarran airport and taking your phone out of airplane mode, it is able to recognize its GPS coordinates via A-GPS and the concierge app wakes up. Once awake, the app prompts you to meet your hotel shuttle outside baggage claim #2. Once you meet your shuttle and arrive at the hotel, you could also cross a geofence. This hotel side geofence lets the hotel know that you have arrived on their property. A property geofence allows for analytics around when customers are on or off property, insights into the shuttle service travel times, etc.


Geoconquesting is the ability to leverage geolocation and fencing to pursue those who are patronizing a competitor's location. This information may be used for direct customer engagement via their installed application or indirectly by providing information that can tailor how future marketing is done to sway the customer's future decisions as to where they spend their money and/or time. Let's assume that the "Vegas Hotel" highlighted above is running a strategic marketing campaign to capture more business on the south end of the strip. Geofences could be established around competitors properties for analytics purposes to help an organization better understand how much time their customers are spending on property versus at a competing site. Typically this can then be used to entice users to come back to their establishment.

Closing Thoughts

Geofencing is a very powerful component of context aware networking, however the engagements need to be used sparingly as there are many users who feel this type of engagement could be an invasion of privacy if they weren't expecting to receive messages. There are many use cases for the back end analytics enabled by geofencing from location enabled work flow automation for a mobile fleet to targeted interactions with customers to predicting whether or a patient might arrive for a doctors appointment or not and early adopters of this technology have a distinct competitive advantage versus those who do not have the same capabilities.

Quick Links

Part III: Building a Contextually Aware Network: Analytics (TBD-Mid Jan)
Part IV: Building a Contextually Aware Network: The Big Picture (TBD-Late Jan)

An Intro to the Contextually Aware Networking Blog Series

This blog series has been the impetus for me to get back into blogging and sharing my thoughts openly with the world. This topic of contextually aware networks is one that I have been discussing with my inner circle of techie friends for quite some time and it is finally getting to a place where it is relevant for us a technologists and consumers and for our customers. I hope to foster some of the same excitement that I share in those who are new to the space and elicit some good discussion from my colleagues, partners and customers out there. The first three parts will be building blocks for a final post that pulls the it all together.

What is a Contextually Aware Network?

A contextually aware network is one that is capable of delivering the right messages to the appropriate people based upon user defined preferences and do so at the right time and place. To accomplish this the system must be able to determine what is relevant to the user through opt-ins, installed Smartphone applications, etc. It is important to understand that for now, the Smartphone is a required ingredient of this solution as it is something that is personal to each of us. With time it is inevitable that there will be further integration with wearables that may offer further context and interaction.

Contextually Aware Network Scenario

You have booked a vacation at a tropical resort with your favorite people and are headed out to the airport. At the prompting of the hotel you have gone ahead and installed their application on your phone, enabling it to be your personal concierge for your trip. Upon arrival in this city your resort's app on your phone wakes up and pops up a message "Welcome to ______, John/Jane Doe. Please meet your shuttle outside the Terminal 1 baggage claim." After a ride to the hotel, you walk in and are prompted by your phone again "Welcome to Hotel _______. Would you like to use our e-check in?" Upon selecting yes, your phone checks you in based on your ID and credit card information on file with the hotel. The app then prompts you "You are in Room 135, can I get you directions?" Selecting yes here will provide you with turn-by-turn directions to your room from your current location. Your phone also notifies you that hotel management has installed smart locks in all of its rooms and the phone can be your room key if so desired. Upon entering your room, the phone is able to ask if everything meets your standards and allows for immediate delivery of anything that is missing or desired. Throughout the stay, your phone is able to notify you of anything you are interested in such as happy hours, shows, gym hours, etc. Down at the swimming pool, you are able to relax knowing that your valuables and cash are locked up in the hotel room safe and that your app can be used for checking out towels and paying for beverages or cabana rentals. Out on the golf course, you and your friends are able to order snacks and beverages from your Smartphones and have it delivered to you on the next tee. The shopping area notifies you of a free appetizer at dinner with a purchase from one of the stores. Upon checkout your receipt and bill summary can be delivered via app and a link to review your stay may be provided to you.

This blog series will explore how the systems supporting this scenario are built at a very high level and shed some light on some of the key components that make a context aware network tick.

Quick Links

Part III: Building a Contextually Aware Network: Analytics (TBD)
Part IV: Building a Contextually Aware Network: The Big Picture (TBD)