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13 Jun 21:54

Après Apple, la banque Goldman Sachs va collaborer avec Amazon

by Hadrien Augusto

Amazon commercants

La banque d’investissement va opérer auprès des vendeurs Amazon en leur proposer une offre de crédit.
21 Apr 03:52

Engagio Delivers the Demand Unit Waterfall™

by Grant Grigorian
engagio delivers demand unit waterfall

OK, I admit it: it took me a long time to figure out what a “Demand Unit” Waterfall is.

When SiriusDecisions unveiled their latest model roughly 2 years ago, I was scratching my head.

At the time, my mental model was firmly set to care about the previous model they pushed for so long – you know, the one where we counted MQLs, SALs and SQLs – and I wasn’t quite ready for this new way of thinking. I resisted for as long as I could, until I finally had to concede that the new model was, in fact, helpful in pointing out the parts of B2B marketing where there was (and is) a lot of untapped value.

At its simplest the Demand Unit Waterfall™ model says that in B2B, the purchasing decision is made by a group of people who come together to solve a specific business problem. Jon Miller founded Engagio based off of this premise 2 years before the release of the new waterfall. In fact, you can see how closely SiriusDecisions and Engagio are aligned on this core idea in B2B.

Let’s look at simple example: let’s consider the case of a business deciding to buy more cybersecurity software.

And, in this example, let’s say that it’s our job to sell cybersecurity software to businesses.

How can the Demand Unit Waterfall help us sell more?

Targeted Personas, Buying Groups and Product Level Engagement

For one, it says that we should focus our Sales and Marketing efforts on the people who work in that business who will be responsible for making or influencing the purchasing decision (i.e., demand units).

This is a simple and obvious statement to make but difficult to do in practice because it means really knowing our customers (and potential customers) really well.

In our example, the business we’re trying to sell to probably recognized a specific vulnerability that it’s trying to secure. It’s our job to know who in that business cares about that specific vulnerability, and how best to secure it.

  • Should we sell to the Security Analyst? Which one?
  • Would the Chief Security Office care?
  • Is this a technical problem that someone from IT care about?
  • What about the compliance department?

Answering these questions means identifying the right Personas within that business, and how they work as a Buying Group to identify solutions to their problems.

Targeting and tailoring our communication to the right person within the account is a powerful way to stand out among the competition and gain trust in our market.

Executing on this vision with your Sales and Marketing teams requires you to have the following capabilities:

  1. Account Based Foundation: You can’t be account-based when your systems aren’t. Traditional marketing technologies are lead-based, and important information about accounts is spread across disparate systems. This is the foundation that holds everything up under the account.
  2. Visibility into Personas and Buying Groups: ABM requires a different a different way to look at and measure your Sales and Marketing efforts.
    • Do you have the right people in your database? Where are the gaps?
    • Are target accounts and buying groups aware of your company and its different solutions
    • Do the right people and right accounts spend time with you? Where?


Once you know who the right people are in your accounts, we need to be able to understand when is the right time to sell a specific product.

It helps to know what’s top of mind for the buying group in your account: What is the urgent business problem they’re trying to solve, and how can we help them?

Which brings us to the third capability:

3) Product Level Engagement:

  • Which of our products or services are the people in the target account buying group currently looking at?

product level engagement

Configurable Journeys (NEW)

Finally, this brings us to our newest capability: a way to track the Account’s progress by customizing and measuring the buying journey.

Journey analytics define how accounts move through defined stages toward intended outcomes, and give marketers metrics to manage their process with rigor. They service as leading indicators of impact on the way to closed-won revenue.

Traditional lead funnels confuse the transition from individual leads to account-based opportunities.

It’s unclear how to measure “lead to opportunity” conversion since leads are people but opportunities are attached to the account. Furthermore, if an opportunity is created at an account with one lead attached to it, what should happen to the journey for all the other people at the account?

This was one of the key shortcomings of the older SiriusDecisions Waterfalls models – and why the “demand unit” was created!

Account funnels measure customer acquisition, just like traditional demand generation. But they can also track other important stages, too, such as customer success and expansion.

Sales cares about closing accounts, not leads. With account funnels, Marketing does, too.

new configurable funnel

Though account funnel stages vary across different businesses, this simple framework is a starting point.

account funnel framework

We can then iterate from there by adding more advanced stages like Recycled Accounts or Disqualified Accounts.

advanced funnel stages

Different account types move through journeys differently. Some accounts move faster, some slower. Certain types convert better, others worse.

To unlock this insight, drill into journey metrics by account type.

  • Territory and business segment: you need to know how balance and flow vary by territory and business segment, otherwise some sales reps will be “hungry” — for example, what if you need more MQAs in the Northeast?
  • Source: inbound accounts usually convert faster than outbound ones.
  • Company size: large enterprises may convert slower than small companies.
  • Product: if MQAs for specific products convert faster than others, consider investing.
  • Target vs non-target: targets aren’t thinking about you. Non-targets self select. Where do your efforts succeed and stall in each case?
  • Industry: which verticals move best through the funnel?
  • First engagement campaign: often, accounts that respond to inbound channels convert faster than outbound ones.

These insights enhance Marketing’s ability to plan and make investment decisions.

SiriusDecisions developed the Demand Unit Waterfall to move away from a purely leads-focused approach that demand gen offers, in favor of something more sophisticated, strategic, and reflective of the realities on the ground for B2B Sales and Marketing. It’s another manifestation of the move towards effective, personalized, targeted approach to focus on the right set of people and accounts for your business.

The post Engagio Delivers the Demand Unit Waterfall™ appeared first on Engagio.

20 Apr 21:15

See the WiFi Passwords for Every Network You've Connected to With this Android App

by Emily Price

I tend to change gadgets a lot more than most people, which means when I visit friends with a laptop or tablet in-tow it’s more than likely not the same laptop or tablet I had the last time I was there.


19 Apr 15:10

How Augmented Reality Will Create a World of On-Demand Experts

by Aaron Frank

During a recent Lyft ride, I discovered that my driver had never been to San Francisco and had just arrived that morning—I happened to be his first-ever passenger in the city. A San Diego college student visiting a friend, he’d decided to bring his car along so he could get paid driving for Lyft while discovering San Francisco and meeting some locals.

Here was a professional driver being paid to deliver me from one place in my city to another, who had no understanding of the street names, which were the best routes across town, or how traffic might change throughout the day. Yet, of course, he delivered me safely, enjoyably, and promptly to my destination without even a slight setback. He even found a better route around some construction traffic that had built up on the way.

What made it possible for this San Francisco newcomer to perform his job so well? The superpowers of augmented reality in the form of GPS navigation like Google Maps and Waze.

My colleague, Jody Medich, often likes to remind people that GPS navigation is the forgotten but everyday example of augmented reality we use regularly. AR systems like these already give people superpower knowledge (as she describes it) to help them drive to new places.

Soon AR superpowers won’t just be given to drivers using GPS to navigate cities.

Anyone will be able to access the right information to perform the right set of skills, whenever and wherever they need it. We’ll be living in a world of instant and on-demand experts.

“The whole point of augmented reality is that it’s interacting with your real reality. It’s merging virtual worlds and the power of computers with the world around you. It’s also an amazing and intuitive way to deliver information on demand,” said Scott Montgomerie, CEO and co-founder of Scope AR, an enterprise augmented reality company based in San Francisco.

Scope AR is one of several enterprise augmented reality companies making AR software that gives untrained technicians the information they need to perform tasks like equipment assembly, maintenance and repair, or customer support.

Montgomerie explained the company’s approach to me in the context of assembling Ikea furniture. Most people have had the experience of struggling with the paper instructions and confusing line diagrams.

“There is this mental mapping you have to do from the line drawing to the real world which can create errors and misunderstandings. But if you saw a [piece of] Ikea furniture built right in front of you, you probably wouldn’t mess it up,” he said (Note: Someone not affiliated with Ikea built a concept of what this could look like last year).

Montgomerie explained that for many of Scope AR’s clients, if a piece of equipment in a factory goes down, typically an expert who may know how to fix it is somewhere far away. In the past, most companies resolved this by flying that expert out to the location of the problem, but quite often, that problem may need just a simple fix if you know what to do.

With Scope AR, businesses can give the average non-expert employee on-demand knowledge with intuitive AR instructions. One of their products, called Remote AR, gives companies exactly this kind of augmented reality live support.

In one anecdote, Montgomerie described a customer who manufactures fast food kitchen appliances like deep fryers and ovens for clients including Burger King and McDonald’s. If one of their appliances breaks down, there’s not typically someone on site trained to do repairs.

That company relies on general contractors to show up to locate the problem, but often these contractors have never worked with the equipment before. As a result, the first-time diagnosis rate, the rate at which a company can locate the issue on the first try, has been low.

Now, onsite contractors can diagnose the problem with the help of a trained expert. Remote experts can virtually see the problem and explain how to fix the issue quickly and on the first visit.

And the results have been remarkable. According to Montgomerie, they’re now seeing a near 100 percent success rate for first-time diagnoses.

Perhaps the most stunning example of Scope AR’s work is how they’re assisting Lockheed Martin engineers building NASA’s Orion spacecraft, a vehicle designed to travel to Mars.

Lockheed Martin using Scope AR in spacecraft
Lockheed Martin engineers use the HoloLens to assemble the Orion Spacecraft. Image Credit: ScopeAR.
Lockheed Martin using Scope AR in spacecraft
Lockheed Martin engineers use the HoloLens to assemble the Orion Spacecraft. Image Credit: ScopeAR.

“In the old way of doing things, an engineer may start with a 3,000-page binder full of instructions for how to build a specific aspect of the spacecraft. A technician starts by going to the binder, looking up a table, finding the correct fastener, memorizing the torque setting, before then actually going in to tighten the fastener. Then quality assurance needs to come in and verify the work before they can move on,” Montgomerie explains.

That process was relatively tedious, slow, and susceptible to errors.

Now the workflow is designed with hands-free information viewed through a Microsoft HoloLens headset. In three-dimensional space with AR step-by-step instructions, the engineer can see exactly what they need to do, what the torque setting is, and where the fastener goes. They can then take a picture for quality assurance and immediately move on.

By replacing an exhaustive series of detailed paper instructions with AR instructions deployed on the HoloLens, Montgomerie said Lockheed Martin saw an 85 percent reduction in overall time for training. And, he said, Lockheed has replicated those efficiencies across a range of other manufacturing procedures with an average of 42 to 46 percent improvement.

With other major companies including Boeing, Airbus, and GE are also discovering productivity gains from augmented reality instructions, it’s likely many more manufacturing tasks will include some kind of augmented reality assistance in the future.

And for the average person at home, it’s likely not too long before you can get exactly the right information you need, layered on the real world in front of you, when and where you need it.

Before long, we’ll all be instant experts—and assembling Ikea furniture won’t seem so overwhelming.

Image Credit: Scope AR.

05 Apr 18:08

L’intelligence artificielle peut convertir l’activité cérébrale en texte

by Bastien L

Une intelligence artificielle créée par les chercheurs de l’Université de Californie est capable de convertir l’activité cérébrale en texte. Dans un avenir proche, cette IA pourrait s’avérer d’un précieux secours pour les personnes atteintes de mutisme.

La télépathie, à savoir la communication par la pensée, est une capacité que les Hommes cherchent à développer depuis des siècles. Grâce à l’intelligence artificielle, nous pourrions enfin toucher au but.

Joseph Makin et son équipe de chercheurs de l’Université de Californie, située à San Francisco, ont développé une IA capable de convertir l’activité cérébrale en texte. Leurs travaux sont présentés dans le journal Nature Neuroscience.

Le système a été développé en faisant appel à quatre volontaires. Des électrodes ont été implantés dans leurs cerveaux.

Il leur a ensuite été demandé de lire à haute voix 50 phrases à de multiples reprises. Il s’agissait de phrases simples, telles que  » Tina Turner est une chanteuse pop  » ou  » les voleurs ont dérobé 30 bijoux « .

Tandis que les participants lisaient ces phrases, leur activité neuronale était enregistrée par les chercheurs. Par la suite, ces données ont été utilisées pour nourrir un algorithme de Machine Learning capable de convertir les données d’activité cérébrale correspondant à chaque phrase en une série de nombres.

Ces suites de nombres ont ensuite été injectées à un autre algorithme chargé de les convertir en séquences de mots. Au départ, les phrases générées par le système n’avaient pas de sens.

Cependant, en comparant ces séquences de mots avec les phrases lues par les participants à l’expérience, l’IA a peu à peu appris à associer les suites de nombres aux phrases avec plus de précision. Elle a aussi compris quels mots ont tendance à se suivre.

À l’issue de cette phase d’entraînement, les chercheurs ont mis le système à l’épreuve en le laissant générer du texte écrit en se basant uniquement sur l’activité cérébrale durant le discours oral.

L’intelligence artificielle en guise de prothèse phonatoire

En dépit de quelques erreurs et imprécisions, le système s’est révélé bien plus précis que les précédentes approches. Pour l’un des participants, seuls 3% de chaque phrase a eu besoin d’être corrigée en moyenne. En comparaison, le taux d’erreur moyen pour un transcripteur humain atteint 5%.

Le résultat est donc plutôt impressionnant. Cependant, les chercheurs soulignent le fait que cet algorithme n’est pour l’instant capable de prendre en charge qu’un faible nombre de phrases. En dehors de ces 50 phrases, ses performances s’estompent fortement.

Pour cause, le système repose sur l’apprentissage de phrases spécifiques, l’identification de mots à partir de l’activité cérébrale, et la reconnaissance de patterns générales en langue anglaise.

Toutefois, l’équipe s’est aperçue qu’en entraînant l’algorithme sur les données d’un participant, moins de données d’entraînement seront nécessaires pour l’utilisateur final. L’entraînement sera donc moins coûteux pour l’utilisateur final.

À terme, cette IA pourrait permettre aux patients atteints de mutisme, ou incapables de taper sur un clavier à cause d’un handicap, de communiquer par la pensée. Selon le Dr Joseph Makin, il pourrait donc s’agir d’un premier pas vers une prothèse phonatoire…

Cet article L’intelligence artificielle peut convertir l’activité cérébrale en texte a été publié sur

01 Apr 21:34

"Why Do So Many of My Salespeople Fail to Perform as Expected?"

by Tony Cole

Why do so many of my salespeople fail to perform as expected?  It's a loaded question.  Or, is it?  In our corporate sales training experience, we've seen that evaluating underperforming salespeople in the pre-hire sales assessment is crucial for success in your business.

29 Mar 16:50

This AI Clones Your Voice After Listening for 5 Seconds 🤐

by Two Minute Papers

❤️ Check out Weights & Biases here and sign up for a free demo:

The shown blog post is available here:

📝 The paper "Transfer Learning from Speaker Verification to Multispeaker Text-To-Speech Synthesis" and audio samples are available here:

An unofficial implementation of this paper is available here. Note that this was not made by the authors of the original paper and may contain deviations from the described technique - please judge its results accordingly!

🙏 We would like to thank our generous Patreon supporters who make Two Minute Papers possible:
Alex Haro, Anastasia Marchenkova, Andrew Melnychuk, Angelos Evripiotis, Anthony Vdovitchenko, Benji Rabhan, Brian Gilman, Bryan Learn, Christian Ahlin, Claudio Fernandes, Daniel Hasegan, Dennis Abts, Eric Haddad, Eric Martel, Evan Breznyik, Geronimo Moralez, James Watt, Javier Bustamante, John De Witt, Kaiesh Vohra, Kasia Hayden, Kjartan Olason, Levente Szabo, Lorin Atzberger, Lukas Biewald, Marcin Dukaczewski, Marten Rauschenberg, Matthias Jost, Maurits van Mastrigt, Michael Albrecht, Michael Jensen, Nader Shakerin, Owen Campbell-Moore, Owen Skarpness, Raul Araújo da Silva, Rob Rowe, Robin Graham, Ryan Monsurate, Shawn Azman, Steef, Steve Messina, Sunil Kim, Taras Bobrovytsky, Thomas Krcmar, Torsten Reil.

Splash screen/thumbnail design: Felícia Fehér -

Károly Zsolnai-Fehér's links:

27 Mar 23:21

2 Months Ago, Andreas Antonopoulos Explained Why Bitcoin Would Crash

by Cointelegraph By William Suberg

Bitcoin is bound to see a massive sell-off if the danger of recession looms, Andreas Antonopoulos correctly warned in January

27 Mar 22:23

Psycho et NeuroMarketing - La manipulation douce : Table des matières

by HK

Table des matières de Psycho et NeuroMarketing- La table des matières

Préface de François Momboisse Président de la FEVAD
Préambule d’Henri Kaufman Président du CMD


    • Collecter les informations pour prendre une décision 
    • Chacun dans sa bulle sensorielle 
    • La collecte d’informations 


  • Le cerveau et le processus « Bottom Up » 
    • Combien de sens avons-nous réellement ? 
    • Les sens, la décision et la consommation 
    • La vue : notre super champion 
    • 1 Anecdotes et expériences 
    • 2 Principes théoriques 
    • 3 Applications pour convaincre un consommateur 
    • Le nez : un grand sensible 
    • Le goût très influençable 
    • L’ouïe, le sens de l’équilibre 
    • L’ouïe et la voix humaine 
    • Le toucher : un grand pudique 
  • Les hormones et la consommation 
    • Le fonctionnement des hormones 
    • L’influence des hormones sur le cerveau 
    • La plasticité du cerveau s’exonère des gènes 
    • Le marketing a-t-il un sexe ? 
    • Hormones et relations clientèle 
    • Comment le marketing a déjà tiré parti des hormones 
    • Le marketing a-t-il un sexe ? Testostérone contre œstrogènes dans les rayons 
    • Testostérone et yaourt 
    • Hormones et anatomie : du marketing au design « genré » 


  • La mémorisation 
    • Mémoire sensorielle, mémoire à court terme et mémoire à long terme 
    • Différents types des mémoires long terme 
    • La mémoire et l’amorçage 
    • Amorçage sensoriel et comportemental 
    • Le cas de la e-publicité et la mémoire implicite 
    • La mémoire en héritage 
    • Le bien-fondé de la recherche de mémorisation 
  • Les émotions 
    • Définir l’émotion 
    • Le désiromètre imaginaire ou la difficulté de la mesure des émotions 
    • L’analyse des expressions faciales 
    • Marketing et émotions 
    • Emotions et impact visuel : le cas de la couleur sur les sites marchands


  • Finalement : qui commande ? 
    • Les neurosciences : observer le cerveau, oui… mais lequel ? 
    • Intestin = In testa (dans la tête) 
    • Le cœur a ses raisons… 
    • Le troisieme cerveau 
    • Le marketing omnicanal 

V- Douceur manipulatoire

  • La manipulation douce 

VI- Le cerveau et les prolongements de soi

  • Soi et le prolongement de soi : le marketing de soi 
    • le marketing de soi 
    • Du produit à l’objet : émotions et mémoire 
    • De la marque à l’objet : Le storytelling, c’est le client qui écrit l’histoire 
    • Le cerveau des objets : les objets connectés 
    • Les lieux habités : le prolongement de soi 
    • Les lieux sont aussi des objets, mais pas comme les autres 


  • L’automobile : les hormones dans tous leurs états 
  • Le tourisme 
  • La banque 
  • Marque de lieux, territoires : les espaces habités et le marketing
27 Mar 09:56

Affinity’s AI-powered relationship intelligence platform is transforming CRM

by Jacqueline Dooley

30-second summary:

  • Affinity is an AI-powered relationship intelligence platform with patented technology that structures and analyzes over a billion data points across emails, calendars, and third-party sources.
  • The Affinity platform helps users manage relationships across 30 million people and 7 million organizations.
  • Affinity’s platform harnesses the data from business communication resources like email and calendars, that people generate on a regular basis, and merges it with data pulled from sources they’ve partnered with to create a very clear view of an individual or organization’s network.
  • Affinity’s platform enables users to spend much more time building meaningful human relationships because they’re liberated from having to think about maintaining their CRM database.
  • Affinity’s patented technology structures and analyzes over a billion data points across emails, calendars, and third-party sources. The platform offers users a range of tools focused on helping them automatically manage their most valuable professional relationships, prioritize important connections, and discover untapped opportunities.

Affinity uses artificial intelligence to analyze relationship strength and illuminate the best paths to warm introductions. The platform also offers a holistic view of users’ networks in a centralized, automatically updated database without any manual upkeep. ClickZ spoke with Affinity Co-Founder and CEO, Ray Zhou, to get a better understanding of the company’s technology and Affinity’s role in a changing, technology-driven CRM landscape.

Making relationships easier to manage

Founded in 2014, Affinity is headquartered in San Francisco and is used by over one thousand financial firms globally. They’ve also seen incredible traction in commercial real estate, investment banks and other professional services. In addition to their large portfolio of asset management firms, Affinity’s clients include top tier brands like LinkedIn and Twilio.

The Affinity platform helps users manage relationships across 30 million people and 7 million organizations. Pricing for the platform starts at $125 per user per month for small teams, with various pricing packages for enterprise customers.

Back in 2014, Affinity’s founders saw a need for businesses, large and small, to leverage their existing networks more efficiently. Ray Zhou, Affinity’s co-founder and CEO, is an engineer who dropped out of Stanford after developing Affinity’s core technology..

Says Zhou, “I, along with fellow Affinity co-founders, Shubham Goel and Joe Lonsdale, spoke with people across a variety of industries. We realized that the way companies were managing their networks and relationships was incredibly suboptimal. Data science and artificial intelligence had advanced to a tipping point in terms of changing the CRM paradigm and that’s what inspired us to start the company.”

Affinity’s founders recognized a need for streamlining how companies managed their relationships. Their goal, from the start, was to build a technology that enabled professionals and businesses to fully harness their networks.

“It’s a vision of democratization,” explains Zhou. “We want to bring the technology we created to every industry and every individual professional in the world.”

Tapping the source of business connections

Affinity was created on the premise that it’s impossible to tell who really knows who from standard sources such as LinkedIn, social media, and personal email.

“The real source of truth about people’s networks is inside their business communications,” says Zhou. “Everyone uses the same tools—emails, calendars, and phone calls to talk to each other. At Affinity, we view these tools as more than just ways for us to communicate. They’re also data sources.”

The raw data gleaned from these common tools paints a powerful picture of what business networks look like. Affinity’s platform harnesses the data from business communication resources that people generate on a regular basis and merges it with data pulled from sources they’ve partnered with to create a very clear view of an individual or organization’s network.

One of Affinity’s patented technologies is a user interface that visually demonstrates the strength of the relationship between two people. The tool does this using historical interaction data which analyzes the data then visually displays it by showing the strength of the relationship.

Affinity CRMAffinity’s interface enables users to visualize the strength of people’s connections

Automating the CRM process

There are two key problems that Affinity solves for its customers—automating the manual process of maintaining relationships (e.g., removing data entry tasks required by CRM tools) and helping people make better decisions about how they allocate time to their network.

Says Zhou, “Our entire thesis around the problems that Affinity solves is that the meaning for CRM has been lost over time. Today we think of CRM as a database of contacts that puts the onus of keeping the data up to date on the user. The onus of figuring out what insights to be derived from that data is also on the user. Everyone assumes they need to maintain this database to drive any value from it, but it’s important to remember that CRM is a means to an end.”

Affinity’s platform, in the most ideal sense, enables a world where people are spending much more time building meaningful human relationships because they’re liberated from having to think about a database at all.

“In an ideal world, there is no database at all,” explains Zhou, “Technology is capable of understanding and capturing the activity around our relationships by harnessing the natural data streams we’re already creating through various communication sources like email. In the ideal end state, the user doesn’t need to think about a database because it’s automating itself, constructing the background for the user.”

Onboarding with Affinity

It takes like less than a week to get fully set up with Affinity. The platform integrates with a variety of different protocols that enable users to sync their email, calendar, and other accounts with a one-click login. From there, Affinity constructs and automates the user’s network.

“When you log into Affinity, you see your entire network of connections fully mapped out,” says Zhou. “I can say with pretty high confidence that there’s no other platform on the market that achieves this with Affinity’s degree of automation.”

Affinity CRMSource: Affinity

Affinity maintains a relentless focus on usability and design. They aim to create a positive user experience that allows users to focus on the strengths of their relationships and how to leverage those relationships.

In this way, Affinity is unique from other popular relationship management and sales tools such as Salesforce, but there are also many Affinity customers who integrate Affinity with Salesforce to get a more complete view of their customer relationships.

Says Zhou, “On the relationship intelligence side, we truly believe that we have a differentiator in how we are handling the insights that we are surfacing.”

Visualizing the future of CRM

Affinity recently announced the acquisition of, a relationship product specifically aimed at sales teams in a B2B landscape.

Per the release, “Nudge is a relationship intelligence platform designed to help sales professionals access new accounts, analyze deal risk, measure account health and more. Tens of thousands of B2B sales representatives rely on Nudge to find and nurture relationships in order to generate and accelerate their pipeline.”

For Affinity, the future of CRM is about reducing the many hours of time people spend each week entering information by hand into a spreadsheet, CRM system, or contact book. “All of this can be automated away,” says Zhou. “It can be done 24/7 in the background by the AI that Affinity has built.”

Affinity gives teams instant visibility into all the different paths of introduction that are available to users. It’s an alternative to all the guesswork involved in platforms like LinkedIn, enabling you to answer questions about your network—in real time—involving relationships and connections.

Affinity CRMAffinity’s team

Says Zhou, “The reality is your team might have a relationship with the individual that you’re trying to reach out to, but you might not know this. The old school way was to send a message to everyone, e.g., ‘Does anyone know John Doe over at Goldman Sachs?’ With Affinity, you can see that Jane in Accounting has a 92% relationship score with John Doe, so you can ask Jane for an introduction instead of sending John a cold email.”

One of Affinity’s main goals is to get people to realize that the most valuable information about their business relationships is something that they already own. It’s data that every company and every team has accrued through utilizing email, calendars and other communication tools.

“As we look ahead into where we take Affinity in the longer term, we’re focused on helping other markets and industries understand the paradigm shift that technology is creating in CRM. We’re we’re trying to get people to realize that relationships are what drive the world’s most critical industries. The most powerful information that you need in order drive relationships across these verticals is something that everyone already owns. They don’t think about it as a data source. That’s the seminal challenge that we’re trying to solve.”

The post Affinity’s AI-powered relationship intelligence platform is transforming CRM appeared first on ClickZ.

27 Mar 09:54

Prospection commerciale : les 4 techniques clés à connaître !

by Team
Tout est dans l’Art de maîtriser la Force !

Dans cet article, vous apprendrez les fondations nécessaires pour devenir un Top Performer en Vente ! A votre sabre laser, que la Force soit avec vous…Luttez contre l’Empire !

Technique n°1

27 Mar 09:53

Record with Friends 2.0 — Easy remote podcasting for a distributed world, by Anchor

by Mike Mignano

“ Hi PH community - hope you’re all staying safe, healthy, and optimistic in this difficult time. Today, Anchor is releasing an all new version of our remote podcasting tool, Record with Friends, now in beta. Like all of you, the team at Anchor is adjusting to ever evolving constraints and circumstances right now. Given the distributed world we’re now living in, we’re also hearing from our users that there’s an increased need for tools that can adapt to the current situation. So today, after working quickly over the past few weeks to expand Record with Friends’ functionality, we’re making it a little bit easier to record with others, even from a distance. Now up to 4 people can join your podcast recording from any device, on desktop or mobile, with or without an Anchor account. And on mobile, your guests don’t need to download the Anchor app - they can record directly through their mobile web browser. This means it’s incredibly easy for anyone to join your podcast, whether that’s a friend, family member, or expert you want to have a quick conversation with for your podcast. Like Anchor’s other features, it’s available globally and 100% free to use. We hope today’s release will make it a little bit easier for us all to talk with each other, share stories, and capture conversations to share with the world through podcasting. Let me know if you have any questions, and stay safe! ”
– Mike Mignano

Discussion | Link

27 Mar 01:40

5S Methodology | What Is 5S Methodology? | 5S Methodology Explanation | Simplilearn

by Simplilearn

This video on 5S Methodology will take you through everything you need to know about the workplace oganization method, 5S. This video also covers a number of different topics like the basics of the 5S methodology, its benefits and the process of 5S, like Sort, Set in order, Shine, Standardize, and Sustain. So now, let's jump in and learn about the 5S methodology.

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#5sMethodology #5sMethodologyExplanation #WhatIs5sMethodology #SixSigma #SixSigmaGreenBeltTraining #SixSigmaExplained #SixSigmaCourse #Simplilearn

Learn to develop your organizational projects with the Lean Six Sigma Green Belt certification online program. Aligned to the IASSC exam, this online six sigma certification integrates lean and the DMAIC methodology with case studies to provide you the skills required for an organization's growth.

About Simplilearn SIx Sigma green belt course:
This Lean Six Sigma Green Belt course provides an overview of Six Sigma and the DMAIC methodology and is aligned to the leading Green Belt certifications at ASQ and IASSC. In this Lean Six Sigma Green Belt course, you will learn how to measure current performance to identify process issues and how to formulate solutions.

Six Sigma Green Belt Training Key Features:
- 56 hours of high-quality blended learning
- 33 PDUs offered
- 4 simulation test papers, 4 real-life projects
- Aligned to ASQ and IASSC

Lean Six Sigma professionals are in high demand due to their ability to use problem-solving techniques to reach business solutions and assuring quality control throughout the process. The Lean Six Sigma Green Belt certification is ideal for Quality system managers, Quality engineers, Quality supervisors, Quality analysts and managers, Quality auditors, and any individual wishing to improve quality and process within an organization.

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27 Mar 01:31

Helping Sales Managers Lead In A Crisis

by David Brock

We are facing a global health and economic crisis few have ever experienced before. It’s clear the only way we will deal with this is by working together, helping each other.

Over the past few weeks, I’ve had hundreds of calls and emails from sales managers struggling to figure things out. I have thought a lot about how I can best help sales managers step up their game in these difficult times.

As a result, I’ve decided to make the Kindle version of Sales Manager Survival Guide available as close to free as possible (If I can figure it out, I will make it available for free). I’ve marked it down to $0.99. I will keep it at this price until at least April 30, 2020.

I wrote Sales Manager Survival Guide as a pragmatic desk guide to help managers think about how to help their people perform at the highest levels possible. This is more critical now than ever before.

Even at $0.99, Amazon insists on paying me a $0.35 royalty. Through April 30, 100% of the royalties I receive for both the Kindle and hardcopy versions will be donated. My good friend, Jill Konrath, helped me think about how to get the best leverage out of these contributions. I will be buying gift cards from local small businesses in my community to help support them. I will donate those gift cards to Laura’s House, a fantastic organization helping battered women.

I hope Sales Manager Survival Guide is a useful resource as you and your teams think about how you best help your customers and achieve your own goals. We will only get through this by working together for our common interests.

27 Mar 00:52

How we must respond to the coronavirus pandemic | Bill Gates

by TED

Visit to get our entire library of TED Talks, transcripts, translations, personalized talk recommendations and more.

Philanthropist and Microsoft cofounder Bill Gates offers insights into the COVID-19 pandemic, discussing why testing and self-isolation are essential, which medical advancements show promise and what it will take for the world to endure this crisis. (This virtual conversation is part of the TED Connects series, hosted by head of TED Chris Anderson and current affairs curator Whitney Pennington Rodgers. Recorded March 24, 2020)

The TED Talks channel features the best talks and performances from the TED Conference, where the world's leading thinkers and doers give the talk of their lives in 18 minutes (or less). Look for talks on Technology, Entertainment and Design -- plus science, business, global issues, the arts and more. You're welcome to link to or embed these videos, forward them to others and share these ideas with people you know. For more information on using TED for commercial purposes (e.g. employee learning, in a film or online course), submit a Media Request here:

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21 Mar 21:47

17 Intent Data Terms Every B2B Sales or Marketing Leader Should Know

by (David Crane)
To help provide some clarity in a noisy field, here are 17 terms and definitions to help those B2B marketers new to intent data.
21 Mar 14:45

Email Verification in Google Sheets v2 — Verify up to 230K email addresses directly in Google Sheets

by Chris Messina
12 Mar 22:37

Interview: The Structure of Prospecting Teams With Josh Roth

by Morgan J. Ingram

What’s going to happen to SDRs and prospecting teams in the future? The sales development function is always changing. We spoke to Josh Roth to hear how he thinks prospecting teams and the role of an SDR is going to change. Here’s a hint, it’s an exciting time to be an SDR right now. Below is a quick summary of the conversation, but listen to the full interview via the YouTube video below.

Here’s how the structure of prospecting teams is going to change…

Prospecting Teams Using Marketing Skills

Morgan: You mentioned marketing. Have you had any thoughts of going back? And what are some things that you studied while you were in marketing that help you and your SDR leadership role and as an NSS sales rep?

Josh: When I started as a sales rep, I think you were still able to sell with a phone and Google. We were still at the point where if you would call a company maybe headcount is 5000, you still might be able to get the decision-maker on the phone just by saying, “Hey, I’m looking to speak to this person”. So we had a little bit more success there.

Now with all of the different gatekeepers, administrative assistants, phone systems, that can kind of block your way, the model is really shifted. What I learned was to create. You really need to create in sales development. But I would argue with sales as a whole, you have to create. You can’t just sell with a phone and Google anymore. One out of every 18 calls to a decision-maker will get answered. That statistic was as of two years ago. So I think it’s probably closer to one out of every 22 or even 25 calls now.

You’ve got to create posts on LinkedIn, do podcasts like you’re doing, really be sure to create valuable content. Don’t just repurpose stuff. I mean if you go on LinkedIn, I can’t tell you how many people are just repurposing Gary V or Grant Cardone content. Go in and create your own, talk about your own experiences, do a debate, do awards, anything that can get people saying like, “This person has experience that he or she knows what they’re talking about”. That’s what I learned in marketing that is so applicable to sales dev today. Create. Do what you got to do, but create.

The Future of Prospecting Teams

Morgan: Now let’s go into the topic of where do you see the SDR role going? Where do you see the model going? What are prospecting teams going to be like?

Josh: You know, I think that you’re gonna end up seeing reps starting to build careers as top of funnel SDRs, you’re going to see compensation that’s going to become equal to what building a career is worth as opposed to having three month ramps, six, nine, twelve month timelines as SDRs, I think you’re going to start seeing it being a two to three year career as an SDR and filtering into either account executive work or actual SDR leadership where you’re going to jump into like a BDM for example. I see from an organizational structure standpoint, where it could go.

I think the other way it could go is cycling into full-cycle reps as opposed to SDR and BDR where you have a similar title. Where an SDR and account executive, similar title, similar roles, everyone is full cycle, but typically the account executives will have a larger book of business accounts may be reassigned, whereas SDRs are going to be more up that kind of initial outreach. I think you’ll see the life cycle of SDRs just be elongated a little bit instead of kind of these 12-15 month roles, I think you’ll see them instead about two to three years.

Compensation Plans

Morgan: Are you going to see where people are going to be compensated more on pipeline that they source that’s getting close? Are people just going to stick with meeting was just scheduled and completed? That’s how they’re going comp. Do you feel like that’s going to change in the model?

Josh: I think realistically what I would like to do is kind of similar to the account executive lane. If you’re self prospecting, if your bringing in leads (I’m assuming this isn’t an outbound function) I would rather you get compensated at a higher rate than if you were just bringing in, for example, a demo request or interest level call that is through demand gen function. If you’re bringing someone that’s brand new, I want you to be compensated more. More than if someone that’s already exhibited interest or clicked through on an email. I just want to structure that a little differently from a comp standpoint.

That’s a wrap. Join us next time

If you made it this far, you’re the best. Thanks for reading and listening to this interview. We hope you gained a ton from it and will listen in next time. Don’t forget to check out our recent podcast episode highlights too.

If you have some feedback for us, connect on LinkedIn. And don’t forget to share the podcast on social media.

The post Interview: The Structure of Prospecting Teams With Josh Roth appeared first on JBarrows.

25 Feb 21:25

Coronavirus : comment l’IA et le Big Data aident à lutter contre le Covid-19

by Bastien L

Dans la lutte contre le coronavirus SARS-CoV-2, apparu à Wuhan fin 2019, l’intelligence artificielle et le Big Data pourraient être les meilleurs atouts de l’humanité. Découvrez comment ces technologies sont utilisées pour endiguer l’épidémie.

Les autorités chinoises sont actuellement lancées dans une course pour endiguer la propagation du coronavirus SARS-CoV-2 à l’échelle mondiale. Alors que la maladie COVID-19 a déjà infecté plus de 70 000 personnes et réclamé 1775 vies à l’échelle mondiale, les chercheurs du monde entier mettent tout en oeuvre pour éviter la pandémie.

Dans cette bataille contre le nouveau coronavirus apparu à Wuhan, le Big Data et l’intelligence artificielle se révèlent d’un précieux secours. Ces technologies avaient déjà permis à l’entreprise canadienne BlueDot de prédire l’épidémie, mais elles peuvent aussi aider à la contenir.

Dans un communiqué, la National Health Commission (NHC) chinoise recommande aux gouvernements locaux d’utiliser  » le Big Data pour suivre et détecter les cas, et prévoir le développement de l’épidémie en temps réel « .

Ainsi, les autorités sont appelées à  » renforcer le lien d’informations entre la sécurité publique, le transport et les autres départements « . Elles sont notamment invitées à partager les données médicales, de communication, et celles des transports tels que les trains et les avions.

Le Big Data pour retrouver les voyageurs de Wuhan

Alors que la ville de Wuhan est en quarantaine depuis le 23 janvier 2020, plus de 5 millions de voyageurs ont quitté la ville durant le festival du Nouvel An Lunaire selon le maire. L’une des urgences est donc de retrouver ces personnes avant qu’elles ne propagent le virus dans toute la Chine et au-delà.

Afin d’y parvenir, les autorités s’appuient sur les données. Dans certains quartiers de Pékin, les résidents sont sommés de scanner un code QR pour renseigner leurs informations personnelles : numéro de téléphone, adresse postale, plaque d’immatriculation, récents voyages et mode de transport…

Il leur est aussi demandé s’ils ont  » récemment  » visité la province du Hubei, dont Wuhan est la capitale. Les citoyens doivent aussi préciser s’ils ont eu un contact avec une personne de cette région.

Récemment, un homme qui avait voyagé à Wuhan s’était mis en quarantaine autonome dans sa résidence située à Nanjing dans la province du Jiangsu. Il n’avait parlé de son voyage à personne, mais les autorités locales ont pu l’identifier en analysant les données de voyage depuis la ville. A sa grande surprise, des officiers ont ainsi été envoyés à son domicile afin de vérifier sa température.

Plusieurs entreprises chinoises ont aussi développé des applications permettant aux utilisateurs de vérifier s’ils ont pris le même avion ou le même train que des personnes infectées. Ces applis se basent sur des données tirées de listes publiées par les médias officiels.

L’intelligence artificielle pour détecter la fièvre

détection fièvre baidu

La fièvre est l’un des principaux symptômes du COVID-19. De fait, détecter la fièvre est une priorité pour les autorités chinoises afin d’identifier les infectés potentiels.

Dans la plupart des quartiers, ce sont des thermomètres traditionnels qui sont utilisés à cet effet. Cependant, les hubs de transports publics essayent également des systèmes reposant sur l’intelligence artificielle et les caméras infrarouges.

A Pékin, un système développé par Baidu (le Google chinois) scanne les voyageurs de la gare Qinghe en combinant l’infrarouge et la reconnaissance faciale. Si la température d’une personne dépasse 37,3 degrés, une alarme se déclenche et le personnel de la station effectue un deuxième test.

Selon Baidu, le système peut vérifier plus de 200 personnes par minute. Cette méthode est donc bien plus rapide que les scanners thermiques utilisés dans les aéroports.

L’entreprise chinoise Megvii spécialisée dans l’IA a elle aussi développé un système similaire. Celui-ci est utilisé dans une station de métro de Pékin. Pour créer cette technologie, plus de 100 personnes ont dû collaborer depuis leur domicile pendant les vacances du Nouvel An Lunaire.

La Chine améliore sa reconnaissance faciale face aux masques de protection

Comme évoqué auparavant, la reconnaissance faciale est utilisée par la Chine pour détecter la fièvre chez les potentiels infectés. Cependant, cette technologie se révèle inefficace durant la crise puisque les citoyens chinois portent des masques pour se protéger du virus.

Pour remédier au problème, le South China Morning Post révèle que le gouvernement chinois a décidé d’améliorer sa technologie de reconnaissance faciale. Désormais, le système est en mesure de reconnaître les masques médicaux, mais aussi les autres obstructions telles que les barbes, les écharpes, les masques de purification d’air etc…

Pour ce faire, la Chine s’est tourné vers les travaux du chercheur Amarjot Singh de l’université de Stanford. A l’aide de son équipe, ce dernier a créé un algorithme conçu pour reconnaître les visages même s’ils sont couverts par des masques, des lunettes ou même des chapeaux.

Cet algorithme examine 14 points du visage et les connecte entre eux pour effectuer une identification. Une version de cette technologie est à présent déployée en Chine, et aide les résidences à reconnaître leurs habitants et à refuser les visiteurs même s’ils sont équipés de masques.

Lorsque l’épidémie sera terminée, l’utilisation de cette version améliorée du système de reconnaissance faciale se poursuivra en Chine. Les entreprises et les résidences pourront ainsi profiter d’une sécurité accrue.

Prédire la propagation du virus grâce aux données

Après l’épidémie de SARS au début des années 2000, ayant causé le décès de 774 personnes dans le monde, l’équipe de John Brownstein, Chief Innovation Officer au Boston Children’s Hospital et professeur à la Harvard Medical School, a développé l’outil Healthmap.

Grâce au Machine Learning, Cet outil agrège des informations sur les épidémies à partir d’articles d’actualité du monde entier, de réseaux sociaux, de discussions en ligne et plus encore. Le programme cherche notamment des publications mentionnant des symptômes spécifiques du virus, en provenance de zones géographiques où les médecins ont rapporté de nouveaux cas potentiels.

Le traitement naturel du langage est utilisé pour analyser les textes postés sur les réseaux sociaux et distinguer une personne commentant l’actualité d’une personne se plaignant de son état. Ces données sont ensuite organisées automatiquement et des visualisations sont générées pour démontrer la manière dont la maladie se propage.

A l’époque du SARS, les experts de la santé n’avaient pas encore accès à de tels volumes de données issues du web ou des réseaux sociaux pour suivre les épidémies. Il s’agit donc d’un atout dans la lutte contre le SARS-CoV-2.

Toutefois, même pour l’IA, il peut être difficile de faire le tri entre les données fiables et les spéculations, rumeurs, fake news et publications au sujet de symptômes d’une simple grippe. Les modèles de Machine Learning doivent être entraînés à déceler cette nuance subtile pour être réellement efficaces.

Malgré tout, cette approche s’est d’ores et déjà révélée efficace pour détecter le coronavirus. Dès le 30 décembre 2019, les données en provenance des réseaux sociaux et médias chinois ont permis de détecter un cluster de rapports sur une épidémie comparable à la grippe. L’information a été partagée à l’OMS, mais il a fallu un peu plus de temps pour confirmer la gravité de la situation.

Ainsi, Healthmap vient compléter les techniques d’agrégation de données plus traditionnelles utilisées par les organisations telles que le CDC américain ou l’OMS. Des médecins, des chercheurs et des gouvernements s’appuient sur ces données.

Désormais, Healthmap est même utilisé par le projet Early Alerting and Reporting, visant à détecter rapidement les menaces biologiques. Il s’agit d’un projet coopératif international entre les institutions de santé publique, auquel participe notamment le CDC. De même, l’initiative Epidemic Intelligence from Open Sources de l’OMS utilise aussi cet outil.

En plus de permettre d’identifier de nouveaux cas, cette technique pourrait aider les experts à décrypter le comportement du virus plus rapidement qu’en se basant sur les sources médicales traditionnelles. Il est par exemple possible de déterminer l’âge, le genre et l’emplacement géographique des personnes les plus à risque.

De même, l’entreprise canadienne BlueDot, basée à Toronto, collecte des données en provenance de multiples les sources en ligne. Cette startup fondée en 2014 était parvenue à prédire l’épidémie plusieurs jours à l’avance.

À présent, elle utilise les informations des compagnies aériennes pour prédire où le virus risque de se répandre. Un précieux recours pour les compagnies aériennes et pour le personnel des services d’urgences risquant d’être les premiers à interagir avec des patients infectés.

Identifier les infectés grâce à l’IA

alibaba damo academy virus

L’institut de recherche Damo Academy, fondé par le géant chinois de la tech et du e-commerce Alibaba, a développé un algorithme d’intelligence artificielle capable de diagnostiquer le coronavirus avec une précision de 96% à partir de tomographies.

Les chercheurs ont entraîné un modèle d’IA à partir d’échantillons de données issues de plus de 5000 cas confirmés. Désormais, cette IA peut distinguer les patients infectés par le SARS-CoV-2 de ceux atteints d’une pneumonie virale ordinaire.

L’outil a été utilisé pour la première fois au Qiboshan Hospital de Zhengzhou, dans la province de Henan. Il sera prochainement adopté par plus de 100 hôpitaux dans les provinces de Hubei, Guangdong et Anhui.

Cet algorithme pourrait permettre de réduire la pression pesant sur les hôpitaux, puisqu’il permet d’effectuer le diagnostic en seulement 20 secondes. D’ordinaire, un médecin humain a besoin de 5 à 15 minutes pour analyser la tomographie d’un cas suspect et livrer son diagnostic.

Auparavant, les chercheurs de la Damo Academy ont également développé un outil de santé publique basé sur l’IA. Celui-ci délivre des informations sur le virus, et a été déployé dès le 27 janvier 2020 par le gouvernement de la province Zhejiang. De cette façon, les citoyens peuvent obtenir des informations sur l’épidémie via une application officielle.

L’IA pour trouver un remède au COVID-2019

L’entreprise Insilico Medicine, basée à Hong-Kong, a utilisé l’IA pour créer une base de données de composés de médicaments. Afin de trouver rapidement comment guérir le COVID-2019, la firme vient d’ouvrir partiellement sa database et permet aux entreprises pharmaceutiques du monde entier de l’utiliser.

La semaine dernière, Insilico a publié sur son site la structure moléculaire de centaines de composés chimiques conçus en quatre jours pour vaincre le coronavirus. En utilisant les méthodes traditionnelles, il aurait fallu beaucoup plus longtemps.

Pour parvenir à cette prouesse, les 85 Data Scientists de l’entreprise ont exploité la puissance du Cloud Amazon et ses propres Data Centers basés aux Etats-Unis et à Taiwan. La firme demande à présent les retours de médecins chimistes et compte synthétiser et tester une centaine de composés avec ses partenaires.

Elle prévoit aussi de tester et de synthétiser entre cinq et dix composés par ses propres soins. Toutefois, pour chaque composé, l’opération requiert au bas mot 12 000 dollars et ce montant peut atteindre plusieurs dizaines de milliers de dollars. C’est la raison pour laquelle Insilico demande l’aide de partenaires industriels et d’instituts de recherche…

Empêcher les futures épidémies grâce à l’IA

Grâce à l’intelligence artificielle, les futures épidémies de coronavirus pourraient être évitées. Plusieurs entreprises travaillent à entraîner des IA pour découvrir de nouveaux médicaments.

Parmi elles, on compte la startup Exscientia Ltd basée à Oxford. Selon son CEO, Andrew Hopkins, de nouveaux traitements pourraient aller de la conception au test clinique en seulement 18 à 24 mois au cours de la prochaine décennie grâce à l’IA.

Ainsi, la startup elle-même a conçu un nouveau composé pour le traitement des troubles obsessionnels compulsifs qui est déjà prêt à être testé en laboratoire moins d’un an après la phase de recherche initiale. C’est presque 5 fois plus rapide que la moyenne.

De même, la startup Healx, basée à Cambridge, utilise le Machine Learning pour trouver de nouveaux cas d’usage aux médicaments existants. Ces deux entreprises nourrissent leurs algorithmes à l’aide d’informations en provenance de sources telles que des journaux, des bases de données biomédicales et des essais cliniques. En se basant sur ces données, les algorithmes peuvent suggérer de nouveaux traitements pour les maladies.

Selon Neil Thompson, le CSO de Healx, cette technique pourrait très bien être déployée contre une future épidémie similaire à celle du SARS-CoV-2 à condition de disposer de suffisamment de données sur la nouvelle maladie. La semaine dernière, le MIT a annoncé avoir découvert un nouveau composé antibiotique capable de tuer les superbactéries grâce à l’IA.

Malheureusement, même si l’intelligence artificielle permet de découvrir un médicament rapidement ou de trouver un nouveau cas d’usage à un médicament existant, il est nécessaire de le tester cliniquement avant de pouvoir le prescrire. Ceci peut prendre plusieurs années avant que le remède soit enfin commercialisé

Cet article Coronavirus : comment l’IA et le Big Data aident à lutter contre le Covid-19 a été publié sur

24 Feb 06:53

Quand la police utilise une assistante virtuelle pour enregistrer les dépôts de plainte

by Jean-Yves Alric

IA police

Les forces de l'ordre néo-zélandaises veulent se rendre plus accessibles au public.
24 Feb 06:52

Un sondage révèle l’inquiétante montée en puissance des stalkerwares aux États-Unis

by Jean-Yves Alric

Utiliser un logiciel espion pour espionner un proche ou un conjoint devient presque monnaie courante.
24 Feb 06:08

USA : Ford propose une remise sur ses assurances en échange des données des conducteurs

by Eric

Ford Explorer

Ford lance aux USA un programme de tarifs modulés d'assurances en échange des données de conduite.
22 Feb 07:21

How to hack your morning routine to get things done

by Laurie Clarke
Forget celebrity routines. If you want to have a truly productive day, follow these tips
22 Feb 07:20

Airbnb has devoured London – and here’s the data that proves it

by James Temperton
More than 10,000 Airbnb listings in London are seemingly in breach of the city’s 90-day limit on short-term rentals, according to new research
22 Feb 07:18

Heston Blumenthal wants robots to make your boring lunch

by Amit Katwala
The experimental chef has joined the board of Karakuri, a startup trying to automate the mass customisation of sandwiches and salads
22 Feb 07:18

How Citymapper deals with the chaos of the world's cities

by Victoria Turk
Rolling out in new countries isn't just a matter of translation, says Citymapper founder Azmat Yusuf
22 Feb 07:18

As electric car sales soar, the industry faces a cobalt crisis

by Nicole Kobie
First it was lithium, now it's cobalt. Electric vehicles need them for batteries, but supply issues will only worsen as demand rises
22 Feb 07:17

Who will really benefit from the EU's big data plan?

by Gian Volpicelli
Europe wants to force companies to pool their industrial data. It's unclear what the end game is
22 Feb 07:16

Shopify décide de rejoindre le projet de crypto-monnaie Libra

by Hadrien Augusto

Libra cryptomonnaie Facebook

Shopify rejoint le projet de monnaie virtuelle de Facebook, pour « construire un réseau de paiement qui facilite l’accès à l’argent ».
22 Feb 07:16

Lancement imminent pour cette plateforme de streaming soutenue par 2 milliardaires

by Arthur Vera


Tremble Netflix, ce petit nouveau compte frapper fort dès le début et dispose de soutien de taille.