Category Archives: Know How

WebRTC is a Natural Fit for the Enterprise

Here’s something funny. While most complain that WebRTC isn’t suitable for the enterprise, it is probably the next best thing happening to enterprises. And it is all because we’re in the midst of a digital transformation.

WebRTC is a five-year-old technology, so it is rather new to the scene. At its core, WebRTC enables adding real-time voice and video communications to any website without the need to download a thing. Need to get a customer on a quick support call? Just send him a URL.

The naysayers dismiss WebRTC because it still isn’t available on Safari or Internet Explorer. While that is true, it is changing. Support already exist in the new Microsoft Edge browser with reassuring rumors about Apple and Safari’s plans towards WebRTC. Ubiquitous WebRTC support everywhere is on the horizon.

Which brings me to enterprises.

Enterprises today are going through a digital transformation. In each and every vertical, businesses are being redefined by having the information that runs through the enterprise turned into digital assets that are then used to drive business processes and analytics.

This takes shape in many different ways: enabling customers to use self-service channels instead of using human operated contact centers, using big data and data lake projects to deduce insights and personalize services, streamlining sales processes through marketing automation, etc.

To make this happen, enterprises must integrate the different IT services they employ internally. The ERP system must connect to the e-commerce site, which must be integrated with the contact center, that in turn has to be accessible to the marketer.

Until a few years ago, such projects were only available to the largest of enterprises, relying heavily on protocols such as SOAP and products such as ESBs (Enterprise Service Bus). It takes many man months and lots of dollars to build such integrations, and they oftentimes end up failing due to their size and complexity.

In recent years, though, such integrations have shifted towards the use of REST. A lightweight cousin of SOAP. To explain REST, you need only look at your browser address bar – REST is essentially a URL call, similar to how you load a web page – but used by a program. While REST is rather loosely defined, the number of tools for handling it is growing rapidly and has come to a point where it is ready to replace SOAP.

Almost every new product or service that is being introduced to the market today includes a REST API, enabling integrators or developers to access it programmatically – in ways a lot easier than the older SOAP mechanism.

This change is coupled with the migration of IT towards cloud services. One where certain services are consumed from remote data centers instead of being installed and managed on-premise. This necessitates solid and publicly available APIs to use.

WebRTC fits perfectly in this brave new world.

Up until today, communications took place in a separate logical and often times even physical network. Be it cellular, wireline or VoIP service, these get built in its own private network or virtual LAN within the enterprise. And the interfaces built into these products in one of two ways: communication-based, which is hard to handle (think SIP or Megaco as an API layer for IT developers); or on some proprietary API that is hard to interface and integrate with.

WebRTC changes all that. It not only makes VoIP more accessible as a technology, but it almost forces developers to think with standard web protocols on how to use and deploy it. As an example, it gets your CRM vendor build his own contact center, many times with players such as Twilio who offer their own WebRTC SDK.

It is no wonder that enterprise vendors are adopting WebRTC en masse. Adopters include Oracle, IBM, Cisco, Atlassian, Slack and many others. The enterprise is where the advantages and ease of integration of WebRTC shine.

In a way, WebRTC is the last piece of the enterprise puzzle of migrating to the cloud and going through its digital transformation.

Todoist becomes a work management solution with new features

Doist has released version 800 of the team task management solution, Todoist, effectively moving the tool into the work management category. In particular, Todoist now supports activity ‘logs’ (or ‘streams’), project notes, improved microsyntax for quickly creating tasks, and a reworked notification system user experience.

Screen Shot 2016-06-28 at 9.44.54 AM

Work management is a term that has emerged in recent years as team task management tools were enhanced with various social communication capabilities, principally derived from design motifs that originated in work media (or enterprise social network) tools (like Yammer, IBM Connections, and Jive).

The new activity stream includes recent comments and project notes (although they are named ‘comments’ in the activity stream.

Screen Shot 2016-06-28 at 10.06.40 AM

The new project notes is basically a reuse of the existing model for task comments. This has the benefit of being familiar, but falls short of what I’d like to see since task comments and, now, project notes, are not visible until the icon is clicked, and then they appear in a hover box, covering the task list in the project.

Screen Shot 2016-06-28 at 9.21.40 AM

It would be much better if display of project and task comments was more like the new activity stream. Imagine that I click the comment icon in either case, and instead of the hover window instead the comments would be displayed below the title in a scrollable list. Here’s a mock-up:

Screen Shot 2016-06-28 at 10.16.19 AM

And I would like to see explicit replies, too. A flat series of notes or comments creates all sorts of headaches.

Bottom Line

The most important takeaway is that Todoist has now moved from team task management to being a true work management tool. While there’s a lot still to do with the new features, Todoist’s traditional strengths — ease of use, flexibility in ordering and nesting of tasks and projects, and smart integration with Gmail — are still in place. But now Todoist is gaining important features for workgroup cooperation and coordination.


Isn’t signing a document just a feature, not a company?

I have to confess that I’ve been surprised by the valuation for DocuSign, which was valued at $3 billion in a funding round last year. I’ve had niddling doubts about the growth possibilities for a company that is basically built around the document signature use case, especially since the idea of ‘electronic signatures’ feels like a skeuomorph crying out for disruption by other approaches to identity verification, most notably fingerprint recognition on smartphones.

Perhaps those questions are being raised by others as well. According to Bloomberg, Rick Osterloh, a former Motorola Mobility exec, had been picked to lead the company forward to an IPO, but just before the announcement he balked and took a job as head of hardware at Alphabet. DocuSign is left with Keith Krach as CEO, who said last fall he wanted to step down.

Basically, verification of identity is now in the hands of the Internet giants, like Google and Apple, and DocuSign is a dinosaur just waiting for the shower of meteorites to come raining down.

So, here’s a small prediction, based on the senior executives that have been bailing out of the company — four out of nine top execs left this year: one of the majors — Google or Microsoft? — will buy DocuSign, and for less than the $3 billion valuation. The company is unwilling to share its financials, and has invested heavily to meet the requirements for eIDAS regulations in the EU, going into effect on July 1.

The Seven Wonders of the Business Tech World

Just over 2000 years ago, Philo of Byzantium sat down and made a list of the seven wonders of the world at that time. Like any such subjective list, it was met with criticism in its own time. The historian Herodotus couldn’t believe the Egyptian Labyrinth was left off and Callimachus argued forcefully for the Ishtar Gate to be included.

At Gigaom Change in September (early adopter pricing still available), we will explore the seven technologies that I think will most affect business in the near future. I would like to list the seven technologies I chose and why I chose them. Would you have picked something different?

Here is my list:

Robots – This one is pretty easy. Even if you make your trade in 1’s and 0’s and never touch an atom, robots will still impact some aspect of your business, even if it is upstream. Additionally, the issue of robots has launched a societal debate about unemployment, minimum wage, basic income, and the role of “working for a living” in the modern world. We have dreamed of robots for eons, feared them for decades, and now we finally get to see what their real effect on humanity will be.

AI – This is also, forgive the pun, a no-brainer. AI is a tricky one though. Some of the smartest people on the planet (Hawking, Gates, Musk) say we should fear it while others, such as the Chief Scientist of Baidu say worrying about AI is like worrying about overpopulation on Mars. Further, the estimates to when we might see an AGI (artificial general intelligence, an AI that can do a wide range of tasks like a human) varies from 5 years to 500 years. Our brains are, arguably, what make us human, and the idea that an artificial brain might be made gets our attention. What effect will this have on the workplace? We will find out.

AR/VR – Although we think of AR/VR as (at first) a consumer technology, the work applications are equally significant. You only have to put on a VR headset for about three minutes to see that some people, maybe a good number, will put this device on and never take it off. But on the work front, it is still an incredibly powerful tool, able to overlay information from the digital world onto the world of atoms. Our brains aren’t quite wired up to imagine this in its full flowering, but we will watch it unfold in the next decade.

Human/Machine Interface – Also bridging the gap between the real world and the virtual one is the whole HMI front. As machines become ever more ubiquitous, our need to seamlessly interface with them grows. HMI is a wide spectrum of technologies: From good UIs to eye-tracking hardware to biological implants, HMI will grow to the point where the place where the human ends and the machine begins will get really blurry.

3D Printing – We call this part of Gigaom Change “3D Printing” but we mean it to include all the new ways we make stuff today. But there isn’t a single term that encapsulates that, so 3D Printing will have to suffice. While most of our first-hand experience with 3D printing is single-color plastic demo pieces, there is an entire industry working on 3D printing new hearts and livers, as well as more mundane items like clothing and food (“Earl Grey, hot”). From a business standpoint, the idea that quantity one has the same unit price as quantity one-thousand is powerful and is something we will see play out sooner than later.

Nanotechnology – I get the most pushback from nano because it seems so far out there. But it really isn’t. By one estimate, there are two thousand nanotech products on the market today. Nano, building things with dimensions of between 1 and 100 nanometers, is already a multi-billion dollar industry. On the consumer side, we will see nano robots that swim around in your blood cleaning up what ails you. But on the business side, we will see a re-thinking of all of the material sciences. The very substances we deal with will change, and we may even be said to be not in the iron nor stone age, but the nano age, where we make materials that were literally impossible to create just a few years ago.

Cybersecurity – This may seem to be the one item that is least like all of the others, for it isn’t a specific technology per se. I included it though because as more of our businesses depend on the technologies that we use, the more our businesses are susceptible to attacks by technology. How do we build in safeguards in a world where most of us don’t really even understand the technologies themselves, let alone, subtle ways that they can be exploited?

Those are my seven technologies that will most effect business. I hope you can come to Austin Sept 21-23 to explore them all with us at the Gigaom Change Leader’s Summit.

Byron Reese

Slack moves past slash commands to message buttons

Slack has announced a new mechanism for third party apps to better integrate with its work chat platform. Rather than relying on so-called ‘slash commands’ — like /trello add Taco Drone Delivery — and then sending subsequent messages to assign values to the metadata of that task, third party apps can be configured to present a UI much more like that in a native app, including buttons that can be pressed to assign values.

Here’s a animated gif for the new Trello integration with message buttons:


Note that the buttons can cascade, as when the user selects ‘due date’ and then various options for the due date are presented. Also note that ‘attach conversation’ will attach a link to the Trello card pointing back to the chat context where the task was created.

This is a serious advance for Slack integration, and specifically, the cognitive dissonance problem with a /slash command-style integration like the one with Trello. I wrote about this recently in Slack ‘Spots’, not just Bots, where I suggested that Slack was probably working on something like this. And yes, they were.

The Analytics of Language, Behavior, and Personality

Computational linguists and computer scientists, among them University of Texas professor Jason Baldridge, have been working for over fifty years toward algorithmic understanding of human language. They’re not there yet. They are, however, doing a pretty good job with important tasks such as entity recognition, relation extraction, topic modeling, and summarization. These tasks are accomplished via natural language processing (NLP) technologies, implementing linguistic, statistical, and machine learning methods.

Computational linguist Jason Baldridge, co-founder and chief scientist of start-up People Pattern

Computational linguist Jason Baldridge, co-founder and chief scientist of start-up People Pattern

NLP touches our daily lives, in many ways. Voice response and personal assistants — Siri, Google Now, Microsoft Cortana, Amazon Alexa — rely on NLP to interpret requests and formulate appropriate responses. Search and recommendation engines apply NLP, as do applications ranging from pharmaceutical drug discovery to national security counter-terrorism systems.

NLP, part of text and speech analytics solutions, is widely applied for market research, consumer insights, and customer experience management. The more consumer-facing systems know about people — individuals and groups — their profiles, preferences, habits, and needs — the more accurate, personalized, and timely their responses. That form of understanding — pulling clues from social postings, behaviors, and connections — is the business Jason’s company, People Pattern, is in.

I think all this is cool stuff so I asked two favors of Jason. #1 was to speak at a conference I organize, the up-coming Sentiment Analysis Symposium. He agreed. #2 was to respond to a series of questions — responses relayed in this article — exploring approaches to —

The Analytics of Language, Behavior, and Personality

Seth Grimes> People Pattern seeks to infer human characteristics via language and behavioral analyses, generating profiles that can be used to predict consumer responses. What are the most telling, the most revealing sorts of thing people say or do that, for business purposes, tells you who they are?

Jason Baldridge> People explicitly declare a portion of their interests in topics like sports, music, and politics in their bios and posts. This is part of their outward presentation of their selves: how they wish to be perceived by others and which content they believe will be of greatest interest to their audience. Other aspects are less immediately obvious, such as interests revealed through the social graph. This includes not just which accounts they follow, but the interests of the people they are most highly connected to (which may have been expressed in their posts and their own graph connections).

A person’s social activity can also reveal many other aspects, including demographics (e.g. gender, age, racial identity, location, and income) and psychographics (e.g. personality and status). Demographics are a core set of attributes used by most marketers. The ability to predict these (rather than using explicit declarations or surveys) enables many standard market research questions to be answered quickly and at a scale previously unattainable.

Seth> And what can one learn from these analyses?

People Pattern Audience Page

People Pattern Audience Page

Personas and associated language use.

As a whole, this kind of analysis allows us to standardize large populations (e.g. millions of people) on a common set of demographic variables and interests (possibly derived from people speaking different languages) and then support exploratory data analysis via unsupervised learning algorithms. For example, we use sparse factor analysis to find the correlated interests in an audience and furthermore group the individuals who are best fits for those factors. We call these discovered personas because they reveal clusters of individuals with related interests that distinguish them from other groups in the audience, and they have associated aggregate demographics—the usual things that go into building a persona segment by hand.

We can then show the words, phrases, entities, and accounts that the individuals in each persona discuss with respect to each of the interests. For example, one segment might discuss Christian themes with respect to religion, while others might discuss Muslim or New Age ones. Marketers can then use these to create tailored content for ads that are delivered directly to the individuals in a given persona, using our audience dashboard. There are of course other uses, such as social science questions. I’ve personally used it to look into audiences related to Black Lives Matter and understand how different groups of people talk about politics

Our audience dashboard is backed by Elastic Search, so you can also use search terms to find segments via self-declared allegiances for such polarizing topics.

A shout-out —

Personality and status are generally revealed through subtle linguistic indicators that my University of Texas Austin colleague James Pennebaker has studied for the past three decades and is now commercializing with his start-up company Receptiviti. These include detecting and counting different types of words, such as function words (e.g. determiners and prepositions) or cognitive terms (such as “because” and “therefore”), and seeing how a given individual’s rates of use of those word classes compares to known profiles of the different personality types.

So personas, language use, topics. How do behavioral analyses contribute to overall understanding?

Many behaviors reveal important aspects about an account that a human would struggle to infer. For example, the times at which an account regularly posts is a strong indicator of whether they are a person, organization or spam account. Organization accounts often automate their sharing, and they tend to post at regular intervals or common times, usually on the hour or half hour. Spam accounts often post at a regular frequency — perhaps every 8 minutes, plus or minus one minute. An actual person posts in accordance with sleep, work, and play activities, with greater variance — including sporadic bursts of activity and long periods of inactivity.

Any other elements?

Graph connections are especially useful for bespoke, super-specific interests and questions. For example, we used graph connections to build a pro-life/pro-choice classifier for one client to rank over 200,000 individuals in greater Texas on a scale from most likely to be pro-life to most-likely to be pro-choice. By using known pro-life and pro-choice accounts, it was straightforward to gather examples of individuals with a strong affiliation to one side or the other and learn a classifier based on their graph connections that was then applied to the graph connections of individuals who follow none of those accounts.

Could you say a bit about how People Pattern identifies salient data and makes sense of it, the algorithms?

The starting point is to identify an audience. Often this is simply the people who follow a brand and/or its competitors, or who comment on their products or use certain hashtags. We can also connect the individuals in a CRM to their corresponding social accounts. This process, which we refer to as stitching, uses identity resolution algorithms that make predictions based on names, locations, email addresses and how well they match corresponding fields in the social profiles. After identifying high confidence matches, we can then append their profile analysis to their CRM data. This can inform an email campaign, or be the start for lead generation, and more.

Making sense of data — let’s look at three aspects — demographics, interests, and location —

Our demographics classifiers are based on supervised training from millions of annotated examples. We use logistic regression for attributes like gender, race, and account type. For age, we use linear regression techniques that allow us characterize the model’s confidence in its predictions — this allows us to provide more accurate aggregate estimates for arbitrary sets of social profiles. This is especially important for alcohol brands that need to ensure they are engaging with age-appropriate audiences. All of these classifiers are backed by rules that detect self-declared information when it is available (e.g. many people state their age in their bio).

We capture explicit interests with text classifiers. We use a proprietary semi-supervised algorithm for building classifiers from small amounts of human supervision and large amounts of unlabeled texts. Importantly, this allows us to support new languages quickly and at lower cost, compared to fully supervised models. We can also use classifiers built this way to generate features for other tasks. For example, we are able to learn classifiers that identify language associated with people of different age groups, and this produces an array of features used by our age classifiers. They are also great inputs for deep learning for NLP and they are different from the usual unsupervised word vectors people commonly use.

For location, we use our internally developed adaptation of spatial label propagation. With this technique, you start with a set of accounts that have explicitly declared their location (in their bio or through geo tags), and then these locations are spread through graph connections to infer locations for accounts that have not stated their location explicitly. This method can resolve over half of individuals to within 10 kilometers of their true location. Determining this information is important for many marketing questions (e.g. how does my audience in Dallas differ from my audience in Seattle?) It obviously also brings up privacy concerns. We use these determinations for aggregate analyses but don’t show them at the individual profile level. However, people should be aware that variations of these algorithms are published and there are open source implementations, so leaving their location field blank is by no means sufficient to ensure your home location isn’t discoverable by others.

My impression is that People Pattern, with an interplay of multiple algorithms and data types and multi-stage analysis processes, is a level more complex than most new-to-the-market systems. How do you excel while avoiding over-engineering that leads to a brittle solution?

It’s on ongoing process, with plenty of bumps and bruises along the way. I’m very fortunate that my co-founder, Ken Cho, has deep experience in enterprise social media applications. Ken co-founded Spredfast [an enterprise social media marketing platform]. He has strong intuitions on what kind of data will be useful to marketers, and we work together to figure out whether it is possible to extract and/or predict the data.

We’ve struck on a number of things that work really well, such as predicting core demographics and interests and doing clustering based on those. Other things have worked well, but didn’t provide enough value or were too confusing to users. For example, we used to support both interest-level keyword analysis (which words does this audience use with respect to “music”) and topic modeling, which produces clusters of semantically related words given all the posts by people in the audience, in (almost) real-time. The topics were interesting because they showed groupings of interests that weren’t captured by our interest hierarchy (such as music events), but it was expensive to support topic model analysis given our RESTful architecture and we chose to deprecate that capability. We have since reworked our infrastructure so that we can support some of those analyses in batch (rather than streaming) mode for deeper audience analyses. This is also important for supporting multiple influence scores computed with respect to a fixed audience rather than generic overall influence scores.

Ultimately, I’ve learned to think about approaching a new kind of analysis not just with respect to the modeling, but as importantly to consider whether we can get the data needed at the time that the user wants the analysis, how costly the infrastructure to support it will be, and how valuable it is likely to be. We’ve done some post-hoc reconsiderations along these lines, which has led to streamlining capabilities.

Other factors?

Another key part of this is having the right engineering team to plan and implement the necessary infrastructure. Steve Blackmon joined us a year ago, and his deep experience in big data and machine learning problems has allowed us to build our people database in a scalable, repeatable manner. This means we now have 200+ million profiles that have demographics, interests and more already pre-computed. More importantly, we now have recipes and infrastructure for developing further classifiers and analyses. This allows us to get them into our product more quickly. Another important recent hire was our product manager Omid Sedaghatian. Omid is doing a fantastic job of figuring out what aspects of our application are excelling, which aren’t delivering expected value, and how we can streamline and simplify everything we do.

Excuse the flattery, but it’s clear your enthusiasm and your willingness to share your knowledge are huge assets for People Pattern. Not coincidentally, your other job is teaching. Regarding teaching — to conclude this interview — Sentiment Analysis Symposium in New York, and pre-conference you’ll present a tutorial, Computing Sentiment, Emotion, and Personality. Could you give us the gist of the material you’ll be covering?

Actually, I just did. Well, almost.

I’ll start the tutorial with a natural language processing overview and then cover sentiment analysis basics — rules, annotation, machine learning, and evaluation. Then I’ll get into author modeling, which seeks to understand demographic and psychographic attributes based on what someone says and how they say it. This is in the tutorial description: We’ll look at additional information that might be determined from non-explicit components of linguistic expression, as well as non-textual aspects of the input, such as geography, social networks, and images, things I’ve described in this interview. But with an extended, live session you get depth and interaction, and an opportunity to explore.

Thanks Jason. I’m looking forward to your session.

People Pattern uses data science methodologies to bring clarity to the vast amounts of social data available and helps you discover quality customers and create innovative people-based datasets.

Missive is social email with tasks

I have been using a new app for the past week or so, called Missive ( When I first looked at the tool it was just a social email client, by which I mean a client for email that also support social communications extrinsic to email, but possibly about email. However, at that time I found that I could use a Google exention to integrate it with Todoist (see Missive looks like a MVP ‘Social Email’ tool). But now, they’ve released their own task implementation.

Here’s a screenshot to reprise the basics of Missive:


Above, on the left you see an email being edited — a reply to an email from Carlos Kelly — but on the right is a chat among Rafael and others working at a company called Conference Badge. They can share docs — like the PDF quote — and talk about the email thread. The email becomes shared, as are the chat comments and attachments.

missive chat

Missive also supports group chats not explicitly linked to specific emails, as shown above.

But what is most exciting — and what I have been waiting for — is the addition of tasks to Missive. These have been implemented as a special version of the basic comment feature in chats, except the user selects the task option:

Screen Shot 2016-06-20 at 11.05.54 AM

Above you see a comment being created, and as you see they can be assigned to one of various users.

Screen Shot 2016-06-20 at 11.05.29 AM

And above, you can see that tasks have a status box so that someone can check off the task as done. (Personally, I favor a three state model — created, in process, completed — but I will wait to convince them of that.)


All open tasks are visible in the ‘tasks’ section of the client, which shows all chats with tasks and provides a count — like 1 of three — to indicate how many tasks are contained and completed.

Missive builds on Gmail, and allows users to file emails in gmail labels. These will be for personal, private use.

I’ve been told that this simple organization technique — I’ve been bumping my head on it for just a week or so, painfully — will be extended in the very near term with tags. As a result, I will be able to pull into a single list all the tasks that are tagged ‘#projectXYZ’ or ‘#finance’ no matter what chat they were originally created in.

Tags, unlike labels, will be shared and available to those in your Missive ‘organizations’ or teams. I am eagerly awaiting the release of tags in Missive, to make it a richer experience and one that is much more manageable. I am also awaiting due dates, and other metadata for tasks, but tags are the most important, I think.

The Bottom Line

Missive is an example of content-based work management — where the tasks are embedded in chats associated with specific email threads or chat contexts — based on a social email foundation. I believe this is one of the few models of work management that will attract a large user base following the decline of web 2.0 era work media tools (like Yammer, Jive, IBM Connections, and so on). Yes, Slack and its work chat direct competitors are getting a great deal of the buzz at present, but email is here to stay, and the emergence of social email — like Missive and its competitors — will be giving email another decade or more of life.

FixMe.IT Delivers Fast and Flexible Remote Support Tool

I’ve recently been talking to Danila Kukarsky of Techinline Ltd., the developer of the FixMe.IT remote support service, about changes in the market for remote support technologies.

Delivering end user support services has long been the exclusive domain of the Service Desk. Either delivered in-house or increasingly via outsourced service providers, it can be a deeply frustrating experience for client and support staff alike: Visualize the client’s inevitably imperfect description of their issue, identify a likely solution, and then laboriously walk the client through the steps to address whatever problem is at hand. It’s a process that can be painfully slow, and overrun with errors and missteps. The obvious way to eradicate this torture is through an endpoint management system which as well as providing configuration management, usually offer virtual deskside support services to deliver remote viewing and remote desktop control. These tools enable the Service Desk to see their client’s problem first-hand, shortening time to repair, and eliminating the frustrations of telephone support.

As good as today’s enterprise endpoint management systems are, there are an increasing number of situations where they cannot be used. The rapid growth of the consumerization of IT over the last five years has seen individual employees and departments bypass centralized IT services in favor of SaaS providers to plug the gaps in the enterprise supported application portfolio. Getting effective support for SaaS apps takes a little more work. Lacking any onsite presence, If SaaS venders want to provide virtual deskside support they can’t rely on their customer’s remote support systems, nor are they able to install large footprint endpoint management tools of their own. Instead they have to use lighter, small or zero footprint remote support apps, that can be run on demand without prior installation and without needing elevated privileges.

FixMe.IT straddles the boundary between being a lightweight web-based remote support app ideal for SaaS providers, and a not quite enterprise-class product. Its lightweight client makes it a good fit for SaaS providers, but at the same time it’s far more than just a remote control app and has enough advanced features to make of interest to SME customers looking for a richer remote support tool. As well as being able to either shadow or control the client’s desktop, support staff get both a virtual laser pointer and pen to annotate the remote display, tools that can be very helpful when it comes to supporting busy apps with complex user interfaces. There’s a well thought out admin console that enables support staff to manage multiple concurrent support sessions as well as a basic logging tool to keep track of time spent on support sessions. Support staff also have the option of recording support sessions for audit or training purposes, and can also share their own desktop with the customer, useful for one on one training, or for customer’s whose data security concerns make them unwilling to share their own desktop while still looking to benefit from visual hand holding. While admins might find FixMe.IT’s rich remote support features provide the biggest benefit from their customers’ perspective, it also provides great value as a flexible, easy to use alternative to Microsoft’s Remote Desktop Connection tool. Admins can create a list of remote physical or virtual systems authorized for unattended access. Once created, the FixMe.IT admin console makes it simple to switch between a client’s desktop and any remote systems needed to troubleshoot and resolve issues. And knowing that FixMe.IT is always available for ad hoc connections can bring peace of mind to those who need remote access to their workstations on the go.

1 - FixMeIT-session-admin

FixMe.IT is offered as service; customers can choose either to buy a fixed number of support sessions, that can be consumed any way they wish, or buy a flexible use license limited only by the number of concurrent users on the service desk – there’s no license cost for the client-side component. And it’s well priced, at less than $1 per day for the subscription license, it’s the kind of product that is worth having around even if you only use it once or twice a month.

2 - FixMeIT-unattended-client-list

I particularly like how FixMe.IT maintains remote support sessions through client reboots. Making it possible for support personnel to install updates, reboot and reconnect without the customer having to do anything to reinstate the connection. It’s not a unique feature by any means, but it’s the kind of detail that is essential for anyone with an eye of good user experience. This persistence can also be maintained when restarting in Safe Mode and when switching user accounts. The one thing I didn’t like, was the lack of any obvious tell-tale to remind the client that their desktop was being shadowed, controlled, or recorded. The app does provide the client with a log showing that their desktop is being shadowed or controlled, but visible tell-tale in the foreground would be preferable. As it is, this won’t be to be an issue for much longer, Techinline already has plans to incorporate this in a future release.

3 - FixMeIT-remote-control

What FixMe.IT doesn’t have today is support for Apple OS X or Chrome OS. With PC sales in steady global decline, the only growth markets today are for Chromebooks and iMacs, especially in K-12 education where Chromebook sales have exploded in the last 18 months. This is a deficit that Techinline is working to address. Kukarsky tells me that support for both OS X and Chrome are in the pipeline for delivery in 2017 but isn’t yet ready to share exactly when they will be available.

Adrien Sommier and Amplement

I recently learned about Amplement, an intriguing tool for professionals to communicate and interact, with a clean and minimal design with features drawn from work chat, video chat, and professional networks. I had a chance to ask some questions of the founder, and I’m even more intrigued afterward.

About Adrien Sommier

adrien sommer

Adrien Sommer

Adrien founded France-based Amplement in 2010, and leads the company as CEO. Previously, he worked in web strategy and communications for several large companies in France. Amplement has grown to 15 staff members, and has over 500,000 users.


The Interview

Gigaom: Amplement seems like a modern and minimal competitor to Linkedin and Xing, where professionals can interact in private and public groups, and also find job offers that match their profiles. Those interactions are a lot like chat in Slack, it seems. Is that a motivation?

Adrien Sommier: Amplement is a web application which enables users to collaborate and discuss in real time with other professionals around the world. We aren’t like Linkedin or Xing because we aren’t a social network.

Before Amplement, professionals couldn’t use a single website for business interaction. They were forced to use many tools: Slack for collaboration, Linkedin to find profiles of other professionals, and Skype to conduct real time discussions or video calls.

Amplement is the only web application which brings together — on a single platform — all the tools professionals need. It’s a single page application.

So, to answer your question precisely, we are a little competitor for Slack, for Yammer, for LinkedIn, for Skype. You see?

G: An all-in-one tool for professional communication. I see. But the challenge for you is this: will people that are already using Slack, Skype, Yammer, and so on switch to using Amplement?

AS: There’s basically nobody in the professional world who doesn’t already use one of those tools. That tells me that most, if not all, of the 700 new users we get each day are open to trying alternatives.

The thing that keeps people from adopting new platforms is hesitation to add “yet another app” to their workflow. We don’t face that issue because we’re condensing their workflow, not bloating it. That and we have an extremely short learning curve, so those who can’t yet replace their use of Skype, Slack, etc. entirely don’t have anything to lose with us.

G: Is job search the primary use case, or just a way to monetize the professional network?

AS: No, in fact the job search isn’t hasn’t yet launched in the U.S. Unlike LinkedIn, our job search feature isn’t there for monetization, but instead because it’s an important feature for our members. On a professional platform, people want to manage their professional careers.

G: Which means connecting with others and sharing profiles? Is that the model?

AS: That’s right. And since you use the same profile for your career development and your daily work, employers can import the same profiles they used to hire someone directly into their work channels. They’ll be all ready to work before their first day in the office!

G: I’ve read that Amplement has over 400,000 members, and over 100,000 job offers have been made since the 2013 launch. What are the user expectations when they join?

AS: We have a half a million active users. Users join Amplement because it’s the fastest app for finding other professionals, communicating with them, and doing both quickly.

G: Amplement does not offer file sharing or integrations with Google Drive or Dropbox, at least not yet. Is that on the roadmap? What other features can we expect in the future? Bots?

AS: We plan to support file sharing soon. Users will be able to work with their teams on Amplement like other tools, such as Slack. We have not developed the integrations, but that’s underway.

G: What about LinkedIn’s approach to support posting, updates, and so on? Will we be seeing that in Amplement?

AS: Staying up-to-date with your network is a key part of your career, so absolutely. Many of those features are already finished.

The recent acquisition of Linkedin by Microsoft shows that the integration of professional networks and the tools that people use to get their work done makes sense. Amplement’s founder, Adrien Sommier, may have seen that future fusion coming earlier than others.

This post was sponsored by Amplement, but the content has been created by Gigaom.

Zenefits makes more cuts; Twitter Selfies; Dropbox profitable*

Zenefits, the online HR platform that ousted its founding CEO recently as a part of a regulatory investigation regarding insurance sales (where the company makes its money), has announced more layoffs, an additional 9% of the company’s workforce, around 100 people. 250 were cut in February, as part of a revamp of sales and operations, following David Sacks — the former CEO of Yammer — assuming the helm as CEO. The company was valued at $4.5 billion in a raise of capital last year, and has disrupted the market for HR tools. Sacks has also jumped on the Zappos’ model of offering money for employees to leave in this reduction of force, he calls this ‘the Offer’. Sacks say he is making a new version of Zenefits: Z2. He spoke with William Alden of Buzzfeed, saying

The company isn’t making The Offer because we don’t want you. We do want you, but we want the best of you.

Twitter now allows self-retweeting, or what I want to call Twitter selfies:

Screen Shot 2016-06-15 at 10.38.00 AM

Dropbox CEO Drew Houston says that the company has achieved a milestone that investors will like: the company is free cash flow positive, meaning operating cash minus capital expenditures. This will set the stage for an easier IPO, which is anticipated.