Facebook Messenger: The Future Of Customer Service?

Ian Jacobs

This a guest post by Meredith Cain, a Research Associate on the Application Development & Delivery (AD&D) team.

As Francis Bacon wrote in 1625, “If the mountain will not come to Muhammad, then Muhammad must go to the mountain.” Although he did not write this with Facebook Messenger or customer service in mind, the meaning still applies. If customers will not come to your business, your business must go to the customers. In 2016, customer service application professionals struggle to find common ground where businesses can fulfill as many customers’ needs as possible in a seamless and timely manner. With one out of every nine people on the planet already using Facebook Messenger, businesses should start to capitalize on this consolidation of customers by adopting Messenger, rather than attempting to move the “mountain.”

In our recent report, we argue that customer service application professionals should make plans to incorporate Messenger into their service arsenal. Facebook’s recent announcement of new Messenger tools that include business-friendly innovations, as well as Facebook’s already ubiquitous user base, positions Messenger to serve as the bridge between Muhammad and the mountain. As this metaphorical bridge, Messenger provides customer service pros with:

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Enrich Customer Insights With Unstructured Data

Boris Evelson

Over the past several years, Forrester's research has written extensively about the age of the customer. Forrester believes that only the enterprises that are obsessed with winning, serving, and retaining customers will thrive in this highly competitive, customer-centric economy. But in order to get a full view of customer behavior, sentiment, emotion, and intentions, Information Management professionals must help enterprises leverage all the data at their disposal, not just structured, but also unstructured. Alas, that's still an elusive goal, as most enterprises leverage only 40% of structured data and 31% of unstructured data for business and customer insights and decision-making.

So what do you need to do to start enriching your customer insights with unstructured data ? First, get your yext analysis terminology straight. For Information Management pros, the process of text mining and text analytics should not be a black box, where unstructured text goes in and structured information comes out. But today, there is a lot of market confusion on the terminology and process of text analytics. The market, both vendors and users, often uses the terms text mining and text analytics interchangeably; Forrester makes a distinction and recommends that Information Management pros working on text mining/text analytics initiatives adopt the following terminology:

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Viv.ai and Developers

John Wargo

At the TechCrunch Disrupt event in NY today, Dag Kittlaus delivered the first public demonstration of Viv, his team’s follow-up to the popular Siri service. There’s been a lot of press in advance of the demo and frequent chatter around eBusiness and bots and what Viv means to them. My focus is on Application Development and Delivery (AD&D) professionals, so I thought I’d update you on what all of this means to them.

Viv is attempting to create what they’re calling a Global AI. While I’m not an AI expert, as I understand it AI entities are typically ‘trained’ using either algorithms or by dumping a bunch of data into it and helping it sort through it all. The self-training algorithms are where AI research had stalled until recently, but machine learning and other methods are revitalizing it. The Viv team, however, is taking a different approach. They’ve built the requisite language processing capabilities (through a partnership with Nuance) and coupled that with a code generator (what they call dynamic program generation) that delivers the needed results. What happens in between? Well, that’s the special sauce that will be very interesting for developers.

The knowledge Viv uses to deliver on voice requests is directly driven by direct input from developers. Well, that’s not necessarily true, but you’ll see what I mean in a minute.

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Improving The Reality Of Government: AR And VR Use Cases

Jennifer Belissent, Ph.D.

Since Mobile World Congress, where the reality on the show floor was often either virtual or augmented, I’ve been thinking quite a bit about the practical uses of AR and VR – particularly in government and a smart city context. It’s not just all fun and games, is it?

The example of changing a roller coaster experience with new settings delivered via VR glasses is really cool. Yes, you can imagine repeating the ride to experience catapulting through medieval battle, flying through a tropical jungle, or bobsledding down alpine slopes. But the practical side of us – or at least me – wants to know what else there is. And, fortunately, I have a colleague who has already been thinking of these things.

A few months ago, I had the pleasure of collaborating with JP Gownder on a presentation for Forrester clients in Geneva.  I presented on the ways to derive value from data and opportunities to leverage new insights service providers – clearly something top of mind for many of our clients. But alas JP’s presentation was much cooler, providing examples of how to derive real value from new technologies including AR and VR.  Since then I’ve being thinking about how the two are related.  And, in fact, they are.

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Security Conscious Developers

John Wargo

I’ve been a part of several development organizations, and, for several of those teams, security was an afterthought to the development process. We’d secure databases and even implement field level encryption but we rarely had to consider many attack vectors as we were building internal apps for enterprises and the risks were there, but not as great.

Fast forward to the Mobile First world we live in and that lazy attitude is no longer acceptable. S&R teams have real concerns and actively work to protect their computing environments – both internal-facing and external-facing. Development teams work the other side of that and implement secure code as part of their daily activities (right?). With an appropriate level of trust between the two organizations, many use code scanning utilities to verify delivered code and hunt for vulnerabilities. There are many sources of vulnerabilities; it could come from code written by the company’s developers, code pasted in from Stack Overflow or even added through some third-party or open source library. In my experience, static code scanning tools are effective and can catch a lot of potential vulnerabilities but, from a developer behavior standpoint, what the ultimately do is simply teach developers how to get their code to pass the scans, not actually deliver more secure code.

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For Customer Service Solutions, Bigger Is Not Always Better

Kate Leggett

Years ago, I worked at a large customer service vendor. Our CEO had tasked us to "eat our own dog food" - that is implement our own solutions for our customer service operations which comprised of 40 or so tier 1 and 2 customer service agents. With these marching orders, I put a group of consultants and business analysts together to get this done. And after several months, the project stalled; got restarted; stalled again; then finally died. We limped on with our old systems in place for many more years.

Why did this project fail? It was because of a mismatch between the complexities of the solution that we were trying to implement, and the company's business needs. The customer service company that I worked for made enterprise software solutions, suitable for large organizations, which was typically implemented in call centers of many hundreds, if not thousands of call center agents. These solutions offered robust case management, with very customizable workflows, queuing and routing rules. These solutions also offered complex knowledge management, email and chat engines that could support millions of interactions a month. Implementation tended to span many months, where professional services consultants dove into the business processes that agents followed, and then reproduced them in these enterprise solutions.

Yet these solutions - as powerful as there are - were too complex for our simple needs. There were no simple "out of the box" best practice process flows. There were no rapid deployment options to get a company up and running quickly. There were no simple ways of setting up FAQs or simple knowledge, or creating simple email and chat routing rules for a moderate volume of digital interactions. What we needed was a highly usable solution, with a quick time-to-value, which contained just the most common functions of the enterprise solution.

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Search Can Build The Foundation For Cognitive Experiences In The Enterprise

Rowan Curran

Knowledge is power. And in a time where insights drive business differentiation, knowledge is also the origin of power. In our daily routines as consumers, search is probably the most common application we use to find knowledge, and it forms the basis of our personal systems of insight. But at long last, search in the enterprise is catching up. A new wave of search-based applications and search-driven experiences are now being delivered by companies who understand the need to empower their employees and customers with immediate, contextual knowledge in an easily-consumable format.

These applications are not for mere search and results, but also for knowledge discovery. And increasingly, they are a foundational component of cognitive application experiences. Building cognitive experiences can seem arcane and mysterious, but by taking advantage of familiar search technologies at the foundation, enterprise developers can start on the cognitive journey.

In our new research, Mike Gualtieri and I look at how the emerging landscape of cognitive search experiences are incorporating advanced analytics, natural language processing (NLP), and machine learning to enable organizations to see across wide arrays of enterprise data and stitch together insights hidden among them.

Cognitive Search Is Ready To Rev Up Your Enterprise's IQ

It's 10 O'Clock! Do You Know If Your BI Supports Actual Verifiable Facts?

Boris Evelson

Delivering broad access to data and analytics to a diverse base of users is an intimidating task, yet it is an essential foundation to becoming an insights-driven organization. To win and keep customers in an increasingly competitive world, firms need to take advantage of the huge swaths of data available and put it into the hands of more users. To do this, business intelligence (BI) pros must evolve disjointed and convoluted data and analytics practices into well-orchestrated systems of insight that deliver actionable information. But implementing digital insights is just the first step with these systems — and few hit the bull's eye the first time. Continuously learning from previous insights and their results makes future efforts more efficient and effective. This is a key capability for the next-generation BI, what Forrester calls systems of insight.

"It's 10 o'clock! Do you know if your insights support actual verifiable facts?" This is a real challenge, as measuring report and dashboard effectiveness today involves mostly discipline and processes, not technology. For example, if a data mining analysis predicted a certain number of fraudulent transactions, do you have the discipline and processes to go back and verify whether the prediction came true? Or if a metrics dashboard was flashing red, telling you that inventory levels were too low for the current business environment, and the signal caused you to order more widgets, do you verify if this was a good or a bad decision? Did you make or lose money on the extra inventory you ordered? Organizations are still struggling with this ultimate measure of BI effectiveness. Only 8% of Forrester clients report robust capabilities for such continuous improvement, and 39% report just a few basic capabilities.

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Launch Your OTT App Faster

Nick Barber

When was the last time you watched OTT programming? If you’re a millennial there’s an overwhelming chance (89%) that you watched it in the last week. Amazon’s vice president of video wants to capture 100% of OTT services in the US and integrate them onto the Fire platform. That means Application Development & Delivery Professionals need to respond to and support this trend.


Amazon's Michael Paull speaking at NAB 2016. 

OTT or over-the-top lets you watch video (repurposed television programming or otherwise) through an app or device like a Google Chromecast, Amazon Fire or game console. They’re big with cord cutters, cord nevers and cord shavers as a way to reduce cost and increase selection. At the National Association of Broadcasters (NAB) conference in Las Vegas, Michael Paull the vice president of digital video at Amazon discussed discussed an OTT push for the company, where he revealed his goal of signing up 100% of SVOD (subscription video on demand) services in the US.

As an AD&D pro you cannot ignore the implications of OTT. You need to answer these questions:

  • Will you partner? Amazon made it clear that it’s making a big push to consolidate OTT players. It has 30 US SVOD services on its Fire TV platform and it’s hoping to grow. Partnering can mean growing your audience, but splitting your revenue; surrendering about 30% is standard. 
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Mobile App Functional Testing, Device Labs, and Open Source

John Wargo
In the latter half of last year, I started researching mobile application testing tools. My research focused, so far, on functional testing, primarily around mobile app front-end testing. As I began the research, it became clear that the automation capabilities testers needed to validate app UIs was there, but application development and delivery teams felt that device labs were too expensive to be practical. During the research for the Vendor Landscape: Front-End Mobile Testing Tools report, we expected that device labs would be a differentiator among products only to discover that most of the major mobile testing solutions provide them in one way or another. There are differences between vendors when it comes to the flexibility, configurability, and management of their device lab offerings, but if you’re delivering customer-facing mobile apps you can do much of your testing on physical devices (our recommended method).
 
In earlier reports, we recommended that, because of the cost of on-device testing, development organizations focused their testing efforts on the most important aspect of their apps, letting users find issues in less popular areas of the app for them. With most of the major mobile testing vendors offering device labs plus Amazon and Google’s entry into the device cloud space, competition will drive down cost and make on-device testing the more common option for mobile app testing. Microsoft’s acquisition of Xamarin now gives Microsoft a robust and capable device lab, stuffed with a variety of Android and iOS devices, which adds to the competition in this space as well.
 
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