10 Marketing Trends to act on in 2018 (Author: Dave Chaffey)

Source: https://www.smartinsights.com/digital-marketing-strategy/10-marketing-trends/

I feel fortunate to have followed some of the amazing major changes in digital marketing and technology over the last 15 or 20 years. I’m sure you will have enjoyed living through, following and acting on these changes too. Looking back, we’ve seen a phenomenal growth in the importance of organic, then paid search, then social media and more recently, incredible worldwide growth in mobile and particularly smartphone usage.

As well as this article, to help Smart Insights members, we also have a more detailed free download of the marketing megatrends, which are 9 digital marketing and martech megatrends that will help give you an edge in 2017.

Looking forward, in this article, I’m going to review 10 new trends which I believe, based on my experience consulting and training, are relevant for marketers across businesses of a range of sizes. But, first, I’m interested to know what you think will be important to you and your business in 2018.

Which marketing trend will be most important to you and your business in 2018?

We have asked this question over the past few years and it’s been really interesting to see what ‘rocks your digital world’ since there are some common themes amongst the top 3 and some activities surprisingly low. The question we asked was around the most important commercial trends. We had around 850 votes from marketers in different types of business from around the world. Thank you if you voted! Here’s what you thought:

By asking for just one technique from many, this helps shows the top 3, 5 or 10 top-level trends. There are a clear top three techniques, each over 10%, but with a long tail of many other techniques showing the potential for optimising different areas of digital marketing. Let’s take a look at the top three…

It’s no surprise to see content marketing ‘top of the pile’ since this has been in the top three for each of the years we have run this poll. We see content marketing as the ‘engagement’ fuel that powers all digital communications from search to social to email marketing to creating website experiences which convert. Our content marketing toolkit is popular since members want to learn a more planned approach to mapping content against personas across the customer journey.

More of a surprise is that Big Data is in second position. I think this is because marketers are aware of the potential of using data as what we call ‘actionable insight’. To help the decision on which technique to choose, we expanded upon the short labels you see in some polls to help scope the response more carefully. ‘Big Data’ is a nebulous term, but when we expanded the definition to include insight and predictive analytics, it shows the value of the specific marketing techniques for Big Data and this help explains why this is in position number two.

In third position is Artificial Intelligence and Machine Learning. We added this to the poll this year with the interest in it and it’s ‘straight in at number three’! It’s good to see the interest in these techniques which we have been covering a lot on the blog and in our member resources this year. In trend 8 we show how different AI techniques can be mapped against the customer lifecycle.

Here is the full listing of digital marketing techniques:

The ten marketing trends to act on in 2018

If you look at the 14 themes that we covered last year, none of these top-level marketing techniques are especially new, so it’s difficult to describe them as new trends or innovations. However, techniques like Big Data and analytics, Content Marketing and Email/Marketing Automation have continued to grow in importance and will be used by many businesses.

So in my look at the trends this year, I’ll be looking at integration as the theme. In our research on managing digital marketing (another free member download) you can see that only 6% of companies thought their integration process was completely optimised, yet many are actively working on integration.

Integrated marketing communications or IMC isn’t a concept you see written about much on blogs or social media since it’s high-level with everyone getting excited at the latest minor innovations from the frightful 5 – at the time of writing we’re getting excited about the Animojis in iPhone X for example. Fun, but they’re not going to help deliver the most relevant message and offer for an individual, which is the aim of IMC.

So, let’s take a look at the 10 trends. You’ll notice that in a lot of these predictions, I’ll refer to Artificial Intelligence and Machine Learning. It’s what I see as the biggest trend to consider in the year ahead. There has been a lot of hype around it in 2017 and we’re starting to understand the opportunities. In 2018 it will become more about selecting solutions and implementation.

Trend 1. Integrating Marketing Activities Into the Customer Lifecycle

Given the way the complexity of marketing and digital marketing has increased, techniques like customer journey mapping for different personas are increasing in importance to help define the most relevant communications and experiences for different touchpoints in the customer journey.

To support this, the way I like to think about how to improve the effectiveness of digital marketing is to think from the customers’ viewpoint of the communications opportunity available through the customer lifecycle for different types of business.

We define lifecycle marketing as:

Creating a managed communications or contact strategy to prioritise and integrate the full range of marketing communications channels and experiences to support prospects and customers on their path-to-purchase using techniques such as persuasive personalised messaging and re-targeting.

We designed this mind-tool to help members think through all the potential touchpoints across paid, owned and earned media. Then you can perform a ‘gap analysis’ of the use and effectiveness of lifecycle comms you are using against those you could be using to increase the relevance and response of communications.

Trend 2. Integrating personalization into the user journey / customer experience

To increase relevance and response of comms, website personalization has been widely used within transactional ecommerce sectors like retail, travel and financial services for a long time now.

More recently, lower cost options have become available with different types of solutions. There are many forms of web personalization varying from those integrated into content or commerce management systems; those integrated into analytics solutions or standalone Software as a Service (SaaS) personalization options that integrate with your CMS and analytics. A useful method to review your use of personalization at the top-level is this experience personalization pyramid:

the Personalization Pyramid

The three levels shown in the chart are:

  • 1. Optimization. Structured experiments. AKA AB Testing or Multivariate testing. Google Optimize is an example of one of these services that launched in 2017.
  • 2. Segmentation. Target site visitor groups, each one with specialized content to increase relevance and conversion.
    Each one still requires separate manual rules and creative to be set up. So returns for this approach eventually diminish after the maximum sustainable number of audience segments has been reached.
  • 3. 1-to-1 Personalization. Using Artificial Intelligence (AI) technology to deliver an individualized experience to each customer. 1-to-1 employs some of the same principles as optimization and segmentation, but by offering a solution to their two greatest limitations-delayed results and inability to scale-it represents a fundamentally different approach.

So, the main trend within personalization is increased use of artificial intelligence rather than manual rules. Plus, we can also expect to see Website personalization services being adopted across more sectors than the transactional sectors it has become popular within.

Trend 3. Integrating machine learning into marketing automation

Personalization can also be applied across the lifecycle in email comms.  Yet, our research on email marketing shows that despite the widespread use of email and marketing automation systems, many companies don’t manage to put in place a full lifecycle contact system like that shown in the lifecycle visual above.

We assessed segmentation and targeting of emails based on the number of criteria that are used from none at all up to dynamic content.

The findings from our State of Email marketing report are shocking: Half (50%) don’t use any targeting whatsoever, less than a third (29%) use basic segmentation for targeting and less than 15% use segmentation and personalization rules to reach specific audiences within their database. This means that they may be missing out on opportunities for automated emails with dynamic content for welcome and nurture of prospects and customers.

Although email marketing automation is another technique where artificial intelligence and machine learning is being applied more often. Using machine learning offers opportunities to automate targeting as it does for web personalization. However, personalization is potentially more difficult since emails, by their nature, have more complex creative. This data suggests to me that many businesses aren’t ready for AI and machine learning within email marketing and they need to deploy fundamental triggered automation features first.

Trend 4. Integrating social messaging apps into communications

The increasing use of messaging apps is a trend we have mentioned in previous trends round-ups. According to the latest Ofcom Communications Market research more than half of the total mobile audience used Facebook Messenger (61%) and half used WhatsApp (50%). Both properties are owned by Facebook. The Snapchat mobile app had a reach of 28%, with 10.1 million unique visitors.

We’ve been looking at some early adopters of marketing applications of these social messaging apps on Smart Insights. Examples include using Pizza Hut using Messenger for booking tables and IKEA for customer research.

Trend 5. Integrating video into the customer journey

Video is also increasing in popularity fuelled by social . This breakdown of Google popularity shows the dominance of YouTube. We used to say that YouTube was the second biggest search engine, but this data shows that it is now more popular than Google Search based on number of users in a given month (this research also from the comScore panel via Ofcom).

This visual reminds us of the opportunities to use video marketing through the customer lifecycle from pre-roll ads in YouTube (just one option, Google has 10 Video ad options), explainer ads on site and retargeting through video.

Augmented and Virtual Reality are closely related to video engagement, but although we’ve been tracking these, we have seen fewer examples and case studies this year. So, do let us know of any examples.

Trend 6. Integrating content marketing into the customer journey using a customer engagement strategy

Video is just one type of content, albeit important. In previous polls about the technique that will give the biggest uplift in future, content marketing has been popular, in the top one or two in the list.

The trend I’m seeing here is that businesses are getting serious about treating content as a strategic resource, that means developing a customer engagement strategy using different media as shown in the lifecycle diagrams above, and at a practical level, developing content for different audiences using techniques like Personas and Content mapping. Our research shows that these customer-centric analysis techniques are growing in importance, which has to be a good thing for consumers and businesses!

Recommended resourceContent Marketing Strategy guide

Trend 7. Integrating search marketing into your content marketing activities

If we look at the top digital sales channels, search marketing is dominant. Social media is far behind in most sectors, despite its ongoing popularity with consumers. We now know that in many sectors social media can be a great tool for engaging audiences with a brand and improving favourability and awareness, but it typically doesn’t drive lead volume or sales. So I haven’t given social media it’s own section, although integrating it with other channels like web, search and email marketing remains relevant. See our recap of SMW London for the latest social media trends.

However, within search marketing there is today relatively little innovation that we get to hear about compared to the past. Looking at natural search shows that the Moz algorithm change history has no entries since the non-specific ‘Fred’ update in March, whereas in previous years it would have had 5+ with new updates to Panda and Penguin. This is partly down to Google sharing less, with Matt Cutts no longer actively evangelising, although updates are available from John Mueller in their Search team.

Within organic search, one trend I think marketers should be aware of is the changing face of the SERPs as shown by the Mozcast SERPs features update which shows the types of links within a bundle of top 10k keywords they monitor.

It shows the importance of techniques such as Knowledge Panels (important for brands and local businesses); Related questions; featured / rich snippets / quick answers and reviews. We have found that the way these vary across the top 3 to 5 positions can make a big difference in the volume of visits from informational searches.

Within AdWords, referencing Google’s list of new features shows more innovation. Much of it is around reporting compared to new ad features for mobile in previous years, but there are some new options like with Enhanced CPC (ECPC) bidding and Smart Display campaigns. This is an example of Google deploying different types of machine learning including Automated bidding Using Target CPA as a basis; Automated targeting which means your ads increasingly show where they’ll get you the most business and automated ad creation from the building blocks you provide, like headlines, descriptions, logos and images.

Trend 8. Integrating marketing technology

If you follow applications of marketing technology you have almost certainly seen Scott Brinker’s Martech landscape which has grown to over 5,000 vendors this year.

Our own digital marketing tools wheel seeks to simplify this, but has over 30 categories of insights and automation tools which shows the challenge of integrating marketing technology. The trend here is that there is no let up in tools offering innovative methods to analyse or automate. Our final two categories highlights some of these.

Given the plethora of martech, the most apt definition seems:

‘very large amount of something, especially a larger amount than you need, want, or can deal with

You might expect there would be a trend to increasing use of marketing clouds, but our research suggests there isn’t widespread adoption of these.

As we have mentioned throughout this article, machine learning and AI is one of the biggest trends here, see this article and infographic for AI marketing applications across the lifecycle.

Trend 9. Integrating different data sources

This challenge was highlighted to use recently in our members’ Facebook group where a member asked about tools for integrating insights from different paid media ad serving tools which can give the best results if managed separately, for example, Facebook, Twitter, LinkedIn ads and Google AdWords. Rivery.io is a new option that has launched recently, that should do well. The trend here is new integrated media insights tools other than Google or Adobe, which can help you compare performance of different media.

These services are surprisingly expensive, particularly since they are additional analysis tools. They’re not martech that directly increases leads or sales to the business. For example, I was recently recommended this service (Funnel.io ) that costs a minimum of $200 / month, even if it’s solely used to integrate data from multiple sources into Google Sheets. It’s a lot when to get the value from these tools you have to ringfence time so that the analytics are reviewed and acted on sufficiently.

Trend 10. Integrating digital marketing insights sources

Our digital marketing tools wheel contains many free and paid sources of insight about your digital marketing. Here, I’m talking specifically about services which help you stay up-to-date. We’re avid users of these services since they help us keep readers up-to-date via our own blog, twice weekly newsletters and monthly What’s Hot feature.

In a recent article on keeping marketing teams up-to-date, Mark Kelly explains that we recommend using Feedlyas a way of aggregating primary marketing news sources via RSS. Plus, I recommend taking a look at Zestwhich is a Google Chrome extension, new in 2017, which I and the team at Smart Insights use and is well worth checking out. Its curated content is specifically designed for and updated by marketers. Like Feedly, you can use it to review the most useful content recommended by ‘the crowd’, in this case ‘your tribe’ of marketers.

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How Netflix, Amazon, Hulu Use Big Data to Change TV Watching

Source: How Netflix, Amazon, Hulu Use Big Data to Change TV Watching

 

To radically change TV-watching habits.

Traditional television viewership is on the decline, and fewer people are actually going to the movies. Meanwhile, streaming video services like Netflix, Amazon’s Instant Video, and Hulu keep adding subscribers and original programming.

It’s getting harder and harder to deny that digital content providers are dramatically altering the entertainment industry. So, how did they do it—and what will be required for traditional networks and studios to stay in the game?

Michael Smith and Rahul Telang—two professors at Carnegie Mellon University’s Heinz College of Public Policy and Management—explore these questions in their new book, Streaming, Sharing, Stealing: Big Data and the Future of Entertainment, published by MIT Press last month. In an interview with Fortune, Smith discussed the new book, Netflix’s hit, House of Cards, and the future of entertainment.

The following conversation has been edited and condensed for clarity.

Fortune: Your book describes the success of Netflix’sHouse of Cards as a turning point for the entertainment industry and digital content. Why was that such a big deal?

Smith: The making of House of Cards illustrates how a bunch of different changes coming together at the same time can be really disruptive to the traditional industry. The thing that Netflix had that nobody else in the industry had was they didn’t just know that there were a bunch of [fans of the House of Cards‘ lead actor, Kevin Spacey] in the abstract, they knew exactly who those Kevin Spacey fans were and they could use the platform to target them directly. So, Netflix went out and created nine separate trailers for House of Cards and targeted them directly to those users. So, I think part of the story is the power of detailed customer data to help you do a better job of marketing the content.

Has the thinking among traditional media giants—who have frequently downplayed the competition they face from services like Netflix—evolved at all in recent years?

There are a lot of very smart, very capable people, who I respect, saying we’re in a content bubble [and] there’s way too much content being made right now for what’s economically feasible. And, what we’re trying to gently push back in the book is the economics of the large-scale bundled subscription model that Netflix is pursuing, [where what the] economic theory says is you can profitably make things in a bundle that wouldn’t be profitable if you sold them separately. I think it’s just as likely that what we’re seeing is the new economics of what’s possible in a Netflix-style bundle. This isn’t a bubble of content production; this is the new normal of what’s possible.

What’s the biggest reason streaming services have a leg up over traditional media companies?

Netflix, Amazon, and Google all own their own data and they don’t share it with anybody in the entertainment industry.

People have made a big deal about the idea of “binge-watching” as the embodiment of the changing way weconsume media. But, what about the tailored content, based on users’ tracked habits? Which is more important?

Both. It’s understanding at a detailed level how individual consumers are accessing the content, and then using the platform to help them discover and find exactly the right content that’s going to meet their tastes. What the academic literature says is that consumers get an incredible amount of value from being able to find exactly the kind of content that meets their unique tastes—and that consumers’ tastes are incredibly varied, more so than what you can find with traditional broadcast channels.

So, what’s the future of entertainment? What will the industry look like in a decade?

We try not to prognosticate too much in the book. What I do think is true is, because of the nature of the data and consumer behavior, a lot of these channels become winner-take-all or winner-take-most-all kind of markets. I think we’re going to have a small number of very powerful players. Now, we’ve always had a small number of very powerful players—what we’re saying in the book is there’s a very high likelihood that it could be a different set of players if the traditional industry folks don’t move quickly.

Could there be consolidation among some of the big companies operating Hulu?

It’s possible. I honestly think that’s their best strategy, to come up with a separate platform. The separate platforms are certainly a good start. The problem is I have no idea what it CBS content versus ABC content, and even less so for movies. Both for marketing reasons and pure economic reasons, it’s much better to go with a common platform that brings together content from a bunch of different players than to try to go with individual platforms for all the different players.

Comment le Big Data a envahi les hypermarchés, High tech

Source: Comment le Big Data a envahi les hypermarchés, High tech

Les grandes enseignes multiplient les expérimentations entre rachats de start-up et créations d’incubateurs. De nombreuses start-up de la tech se spécialisent dans l’analyse de données pour les hypermarchés.

Carte de fidélité, paiement mobile, chariot connecté… Souriez, vous êtes fichés ! Depuis toujours, les hypermarchés collectent et traitent des données. Mais aujourd’hui, celles qu’ils recueillent sur les consommateurs sont de plus en plus précises et leur analyse devient une arme stratégique majeure pour donner la réplique aux Amazon et autres géants de l’e-commerce dont, on leur annonce tous les jours qu’ils vont leur tailler des croupières.

C’est évident : l’avenir des hypers passe par le Big Data (mégadonnées). « Amazon vient concurrencer Auchan et Carrefour avec de nouvelles armes, comme le traitement des données, que ces enseignes traditionnelles doivent s’approprier », clame Yves Marin, directeur chez Wavestone.

Campagnes publicitaires plus efficaces

La route est longue. Un seul chiffre : l’américain Walmart, numéro un mondial de la distribution, a généré l’an dernier un chiffre d’affaires de 13,7 milliards de dollars sur Internet, contre… 107 milliards pour Amazon, dont l’un des points forts réside aussi dans son système de recommandation. Ce n’est pas pour rien que Walmart a annoncé mardi mettre 3 milliards de dollars sur la table pour racheter Jet.com , un concurrent de la firme de Jeff Bezos.

La grande distribution a commencé à se mettre au pas. Les expérimentations se multiplient : rachats de start-up, créations d’incubateurs ou investissements en matériels et logiciels… Walmart s’est ainsi offert la société Kosmix pour monter sa propre infrastructure d’étude en temps réel des données.

Auchan Retail Data, l’entité du français Auchan qui gère les données, a quadruplé ses effectifs en un an (40 personnes). « La nouveauté avec le Big Data, c’est que l’on peut personnaliser la relation client à une très grande échelle. Avant, on s’adressait à un segment de clientèle. On est aujourd’hui dans une relation de one-to-one grâce aux capacités de calcul », affirme Olivier Girard, son directeur. Ainsi les bons de réduction susceptibles de vous faire craquer arrivent par miracle sur votre page de navigation et dans votre boîte aux lettres ou mails. Les campagnes publicitaires deviennent plus efficaces. « On constate jusqu’à 40 % d’augmentation des ventes avec notre régie Imédiacenter », note-t-il.

Un terrain fertile pour les start-up

Certains, comme Leclerc font appel à des « data scientists », très en vogue chez les géants du Web. L’enseigne fait aussi appel aux start-up, sans forcément les racheter. « Il suffit qu’un acteur de type Amazon sorte une innovation pour que des technologies qui ont à peine quelques mois deviennent obsolètes. Dans ce cadre, investir ses propres billes à long terme est une prise de risques beaucoup trop importante ! » justifiait l’an dernier Michel-Edouard Leclerc, patron du groupe, dans « L’Usine digitale ».

Des jeunes pousses ont ainsi fleuri dans des domaines très pointus. « Il n’y avait aucun moyen de mettre en relation les données d’une personne à la fois cliente en magasin et en ligne. Notre société est capable de les associer pour améliorer les interactions avec les clients », explique Vihan Sharma, directeur général de Liveramp, une entreprise américaine qui a Carrefour pour client et qui s’est lancée dans l’Hexagone il y a un an. Elle traite 20 milliards de profils par mois environ en France, au Royaume-Uni et aux Etats-Unis.

« Le temps, c’est de l’argent »

A terme se profile la possibilité de monétiser les données aux clients : c’est déjà une source essentielle de revenus chez Cdiscount. C’est un enjeu pour les grandes surfaces. Pour l’heure, elles cherchent surtout à affiner le data. « Auchan commence à utiliser des données issues de l’open data, c’est-à-dire celles ouvertes et accessibles à tous sur Internet comme la météo et le trafic routier », pointe Olivier Girard. Quant aux données des réseaux sociaux : « Nous les utilisons peu par peur de se disperser. Ce n’est pas notre priorité aujourd’hui. » Le temps, c’est de l’argent.

« La clef est de nous adapter au gros volume de données qui va nous arriver. Il faut être sûr que ce ne soit pas une source de perte de temps et d’inintelligence, expliquait récemment Georges Plassat, PDG de Carrefour, au Salon Viva Technology. « Nous évoluons vers une manière plus prédictive de servir le consommateur mais honnêtement si nos clients ont besoin, dans le futur, d’un indicateur sur leur réfrigérateur indiquant qu’ils ont besoin de lait, il faut que l’on s’inquiète. »
En savoir plus sur http://www.lesechos.fr/tech-medias/hightech/0211205079169-comment-le-big-data-a-envahi-les-hypermarches-2020715.php?ve2ZCphffSmulXAh.99#xtor=EPR-12-%5Btech_medias%5D-20160816-%5BProv_%5D-2159277%402

Big Data: How Valuable Is Your Marketing Data?

Source: Big Data: How Valuable Is Your Marketing Data?

Research from Dun & Bradstreet’s B2B Marketing Data Report 2016 has revealed gaping holes in B2B marketing databases. In a study of 695 million records in B2B companies’ databases, inaccuracies were found in over 70% of the records.

  • 87% lacked revenue information
  • 86% had no employee information
  • 82% had no website information
  • 77% were missing industry information
  • 62% did not contain phone numbers
  • 45% were missing contacts job titles

The following are some of the primary reasons that you should prioritise clean data over big data to optimise the value of your sales leads.

Focus on Selling

So much time is wasted in organisations looking for the right data.

When your sales reps are equipped with thorough, clean data, they can focus their time on converting prospects into buyers. In contrast, it takes time to work through the issues created by bad data.

The same can be said for marketing departments when they are trying to guide customers down the sales path, or creating customer loyalty programs.

Imagine a rep opening a contact profile in a database and realising that a digit is missing on the phone number or an important line is missing on an address.

These missing items impede the rep’s ability to optimise his workflow and begin the selling process. The distraction also takes away from your team member’s focus on optimising presentation and closing stages.

58% of Chief Marketing Officers (CMOs) say email marketing, search engine optimisation (SEO), search engine marketing (SEM), and mobile are the main areas that big data is having the largest impact on their marketing programs.

image: http://cdn2.business2community.com/wp-content/uploads/2016/08/Big-Data-Impact-for-a-CMO.jpg.jpg

big-data-marketing

Source: Big Data and the CMO: What’s Changing for Marketing Leadership?

More Targeted Appointment Setting

Clean data is more useful in landing appointments with high-potential buyers. It is difficult for a person to make targeted prospecting calls when profiles are incomplete or inaccurate. A smaller amount of high-quality sales leads improves targeting capabilities.

With quality data, reps can better detect which contacts offer the right opportunities to sell the right solutions. Having in-depth information on B2B buyers is especially important, as your reps need the ability to tailor messages to specific interests.

In another study of 50,000 US and international marketing, sales and business professionals Ascend2 discovered that:

“35 percent of those surveyed said the biggest barrier to lead generation success is the lack of quality data.”

Save Time and Money

The efficiency with which reps can connect with top decision makers and sell is much lower with bad data. Instead of investing the majority of time preparing and delivering sales messages, reps are taking the time to sort through problematic prospect details.

With clean data, you eliminate wasted steps that cost your organisation significantly.

image: http://cdn2.business2community.com/wp-content/uploads/2016/08/sales-leads2.jpg.jpg

Sales leads

Better Results and Financial Performance

Most importantly, clean data gives your team the best opportunities to optimise conversion rates, selling cycle times and average deal sizes.

Think of this scenario as similar to a doctor going into a waiting room after reviewing a patient’s file. The more thorough and accurate the nurse’s notes, the greater the doctor’s ability to effectively and efficiently detect and resolve a patient’s health problem.

Better sales results drive optimised financial performance as well. It is easier to forecast sales accurately, which enables you to better align budgets with revenue projections.

Conclusion

Big data doesn’t do much good if all you have is a cesspool of problems. However, ample data that is clean and useful is of tremendous value to your team. Internal Results has expertise in data acquisition.

We maintain accurate data on over 61 million decision makers in more than 20 countries. Over 500,000 records are updated every month to ensure they are clean and accurate.

Whether you are looking at entering new markets, or geographical territories, contact us today to discuss why our expertise in clean data is a perfect match for the sales skills of your organisation.
Read more at http://www.business2community.com/brandviews/internal-results/big-data-valuable-marketing-data-01621555#u4gesLukXskfSDQW.99

Ce que fait Axa pour ne pas être “ubérisés” (Source: BFM)

Anticiper l’inévitable disruption à venir dans l’assurance – Axa investit 100 millions d’euros dans Kamet, un véhicule inédit à ce jour dans l’industrie. Mais ce n’est pas la seule initiative de la compagnie. Explications.

Source: Voilà ce que nous faisons chez Axa pour ne pas être “ubérisés”

Comme de très nombreuses industries, l’assurance est à l’aube d’une révolution majeure, probablement la plus importante depuis son origine. L’explosion des objets connectés liée au développement exponentiel des technologies mobiles, l’évolution des modes de consommation (économie du partage, économie du “on-demand”,…), mais aussi les opportunités offertes par le “Big Data” en termes d’analyse du risque et d’anticipation des comportements et des événements, ouvrent d’immenses opportunités en matière de prévention et de gestion des risques.

Dans 10 ans, l’assurance aura un visage très différent de celui d’aujourd’hui. Les besoins et attentes de protection des individus et des entreprises ne disparaitront pas du jour au lendemain. Bien au contraire, le monde qui nous entoure fera plus que jamais courir des risques. Mais la façon de répondre à ces besoins, notamment par les sociétés d’assurance, va fortement évoluer. Il est probable également que de nombreux acteurs non “assureurs”, existants ou nouveaux, imagineront et développeront des produits et services concurrents, voire radicalement différents, de ceux offerts aujourd’hui par les acteurs établis.

Nous avons compris très tôt que digital et big data allaient profondément changer ses métiers (assurance des biens, assurance des personnes, assurance de la santé, épargne et gestion d’actifs). Depuis plusieurs années, un plan massif de transformation a ainsi été engagé sur l’ensemble des métiers et régions couverts par Axa.

60 spécialistes analysent les données

Nous avons développé plusieurs initiatives globales visant à aider et accélérer les efforts des équipes opérationnelles. Un “Data Innovation Lab” (DIL) a été créé à Suresnes et rassemble une soixantaine de data scientists qui travaillent avec les entités opérationnelles sur la mise en place d’initiatives autour du big data. Le DIL double de taille chaque année et vient d’étendre ses équipes à Singapour afin d’être encore plus proche de nos entités asiatiques. Deux “Axa Lab” ont également été créé, l’un à San Francisco et l’autre plus récemment à Shanghai. Véritables têtes chercheuses, ces équipes sont au plus près des écosystèmes d’innovation, identifient des nouveaux modèles et mettent en relation start-up innovantes et équipes opérationnelles d’Axa à travers le monde.

Nous avons également créé un fonds d’investissement, Axa Strategic Ventures, doté de 200 millions d’euros et dédié aux start-up de l’InsureTech. Il leur apporte des financements via des prises de participation minoritaires, soit très tôt dans leur cycle de vie (early stage/seed), soit plus tard afin de financer leur croissance et internationalisation (growth stage). Ce fonds a déjà effectué une douzaine d’investissements et est maintenant en mesure d’opérer sur la majeure partie du globe.

Financer les start-ups pour découvrir les Uber et AirBnB de l’assurance

Toutes ces initiatives visent à permettre aux différents métiers d’Axa de se moderniser en utilisant au mieux ce que les technologies permettent de réaliser afin de mieux servir clients, distributeurs, partenaires et collaborateurs.

En complément des nombreuses initiatives mentionnées ci-dessus, il est progressivement devenu clair que des modèles encore plus “disruptifs”, à l’image de ce que Uber ou Blablacar ont rendu possible sur la mobilité, AirBnB sur le logement et l’hébergement, Lending Club sur le prêt à la consommation, allaient immanquablement voir le jour dans le monde de l’assurance. Et il y a fort à parier que ces nouveaux modèles seront en grande majorité imaginés par des start-up.

Axa a donc décidé de financer – dans une logique industrielle (et non financière ou d’investissement) – une plateforme qui aura pour mission de développer des modèles disruptifs d’assurance. Ce concept, parfois appelé “Start-up Studio”, vise à créer un écosystème d’entrepreneurs en résidence, un vivier de savoir-faire technologiques afin d’initier des idées, les prototyper et en faire des sociétés qui seront co-dirigées par Kamet et l’équipe de fondateurs.

Kamet pourra construire des modèles concurrents des modèles d’affaires existants du Groupe Axa, car l’objectif est bien de ne pas laisser à d’autres le soin de nous devancer ou “disrupter”. Cette structure sera indépendante d’Axa et fonctionnera comme une start-up tout en ayant la capacité soit de s’appuyer sur les savoir-faire des équipes internes, soit de s’allier stratégiquement avec des partenaires externes pour mettre au point des modèles innovants. La mission est ambitieuse. Bien exécutée, elle devrait nous permettre de réussir notre transformation numérique et conserver notre place de marque leader dans le secteur de l’assurance.

Data est digital et digital est data. Le chaînon manquant dans « la maladie de l’Europe » de Guy Verhofstadt (Ivan Vandermeersch, Secrétaire général BDMA)

Par Ivan Vandermeersch, Secrétaire général BDMA

“Cher Monsieur Verhofstadt,
Cher Guy,

Il faut bien le dire, la salle Henri Lebœuf était comble aux Bozar et comme toujours tu passionnais ton audience. Avec ferveur et assertif comme toujours. Le visionnaire des grands jours. Quelque part tu as décidé que l’Europe doit changer et va changer. Ce n’est pas la première fois dans ta vie que tu te mets à abattre des murs avec tes poings nus. Puis vint la cession de signatures. Et bon, soit, à un moment où la file n’est pas encore trop longue je fais signer mon exemplaire. Dans notre relation qui oscille depuis 40 ans entre la sympathie et le bougon et qui n’est jamais neutre tu poses la question : « Pour Ivan ? C’est bon ? ». Je te réponds : « fais comme tu veux ». Après avoir constaté que tu écris encore toujours mon nom avec un « Y » au lieu d’un « I » je te dis avant de te quitter : « je commence à lire le chapitre qui commence à la page 117 ». Et je l’ai fait. Et me voilà en plein désert digital.

C’est vrai, il faut un cadre juridique unique avec un régulateur unique au lieu d’un tissu disparate de 28 unités. Qu’on est dans une constellation de 28 pays ont leur mot à dire. Et c’est vrai que là se trouve différence avec les États-Unis qui fonctionne sur base d’une réglementation pour couvrir tous ses Etats. Effectivement, pas étonnant que des 25 grandes sociétés d’Internet 15 qui ont leur siège aux États-Unis et seulement une seule en Europe. Et que tout ce que tu cites dans ce passage peux impacter 900.000 emplois en Europe. Que le morcellement européen tue l’innovation.

Mais il y a plus. Quand on prononce le mot digital automatiquement le concept « données » s’y attache. Big Data. 90% des données mondiales ont été créées pendant ces deux dernières années. Depuis que la première version de la proposition de régulation sur la protection des données a été émise par la Commission Européenne le 25 janvier 2012. Avec les pouvoirs publics, les entreprises et les citoyens comme utilisateurs de données. La quantité de données croît de façon exponentielle, venant de partout. Nous les créons surtout nous-mêmes par nos interactions avec l’Internet. Ces données contiennent des informations très détaillées sur nos intérêts, réseaux, habitudes et comportements individuels. Il s’agit d’un flux rapide et continu générant de grandes quantités de données. En temps réel, pour ainsi dire.

Cela permet aux entreprises d’amorcer la production de produits hautement personnalisés et le consommateur prend part au processus de production en spécifiant ses exigences de conception. A travers des sites e-commerce, via les centres d’appels. Un nouveau canal de production a vu le jour. Et demain tu pourras virer ton fidèle chauffeur Gaétan. Ce sera en «voiture Google », sans chauffeur, que tu feras tes trajets commandé par ton téléphone mobile. « Data driven ». Littéralement. L’économie se repose donc de plus en plus sur les données. On ne peut plus évoluer à contresens.

Il y a un enjeu majeur pour les entreprises en ce qui concerne la transparence dans la relation avec le consommateur ainsi que pour les gouvernements celui de respecter les droits fondamentaux et les libertés des citoyens. Le développement économique allant de pair avec les intérêts des consommateurs. La politique devant être la garante des libertés civiles.

La protection de la vie privée n’est plus uniquement une question de protéger, mais devient également un défi en termes d’offrir des opportunités. Parce que notre économie est aujourd’hui une de ces données. Et effectivement, sur base d’une législation harmonisée applicable de la même façon dans tous les pays européens. Ou l’on trouve le juste équilibre entre autoriser et interdire. Comme Angela Merkel le disait au congrès digital de la CDU en septembre dernier : « Les données sont la matière première de l’avenir… Dans l’avenir, la valeur ajoutée ne sera plus principalement générée par la fabrication d’un produit, mais surtout grâce à l’utilisation des données des clients… Si nous ne permettons pas d’établir des relations avec des consommateurs correctement, une partie substantielle de la valeur ajoutée sera perdue »

La proposition de Règlement Général sur la Protection des Données qui est en discussion au trialogue contient 23 « delegated acts », mais surtout, il y a sur la table des négociations bon nombre de provisions dont l’application serait laissée à l’appréciation de chaque Etats Membres. Ceci va totalement à l’encontre de ton souhait d’harmonisation de notre vieux continent qu’on appelle l’Europe et ne va pas donner un souffle à notre nouvelle économie digitale. Un grand défi reste de trouver l’équilibre entre permettre et interdire. Un enjeu principal parce que notre économie digitale se base sur les données afin de pouvoir concurrencer avec tout ce que existe hors des limites de notre petite Europe. Je te conseille vivement d’aller prendre le thé chez Angela Merkel.

Ivan Vandermeersch”

How Artificial Intelligence is Changing the Face of eCommerce Industry

Source: http://www.iamwire.com/2015/09/artificial-intelligence-ecommerce-deep-learning-machine-learning/123423

September 26, 2015 by

source

eCommerce is one dynamic sector that has revolutionized the way a consumer shops for goods and services in a mobile world. The basic goal of every eCommerce company is to bring the best of offline shopping experience to the online space, by offering the consumers a seamless way to discover the products they are looking for.

The avenue is taking a big leap towards becoming the facilitator of a more efficient, personalized, even automated customer journey with the introduction of cognitive technologies and the employment of ‘smart data’. Today, the most important area of focus in eCommerce is hyper personalization which could be facilitated only by learning consumer behaviour and making predictive analyses with the help of the huge amount of data collected from user activities on smartphones, tablets and desktops, and intelligent algorithms to process them.

Machine learning and artificial intelligence are no more restricted to personal assistance technology, smartphone companies are creating. They have flouted these conventions to disrupt a much wider space with limitless possibilities. One of the areas radically transformed by AI is eCommerce.

AI in eCommerce is Already Moving Forward

Following are a few key areas in eCommerce which can be transformed by the application of Artificial Intelligence, some of them are already in existence-

Visual Search and Image Recognition

(Image Source)

It is an AI driven feature that enables users to discover what they want at the click of a button. All one has to do is, take a picture of what one likes and put it on the search bar of the eCommerce platform. The engine would then search through all the possible matches, rank them and prioritize them before placing the options before the user.

Product Recommendation

Recommendation is widely practiced by eCommerce companies to help customer find the best of what they are looking for. Recommendation algorithms work in multiple ways. For example, Amazon.com recommends its users depending on their activities on the site and past purchases. Netflix recommends DVDs in which a user may be interested by category like drama, comedy, action etc. eBay on the other hand collects user feedback about its products which is then used to recommend products to users who have exhibited similar behaviours. And this continues to evolve with several permutations and combinations in place.

Intelligent Agent

At present, Intelligent Agent negotiation system has become a popular tool used in eCommerce with the development of artificial intelligence and Agent Technology. The three main functions performed by this automated agent are:

  • matching buyers and sellers (determination of product offerings, search of buyers for sellers and sellers for buyers, price discovery)
  • facilitating transactions (logistics, settlement, trust)
  • providing institutional infrastructure (legal, regulatory)

These agents are fully automated and have control over their actions and internal state. They interact via an agent communication language. Further, they not only act in response to their environment but are also capable of taking initiatives like generating their own targets and act to achieve them.

Assortment Intelligence Tool

Consumers are forcing retailers to alter pricing strategies, so it is imperative for multichannel retailers to be flexible with their price structuring in order to retain their customers. To do the same, they are employing Assortment Intelligence, a tool that facilitates an unprecedented level of 24/7 visibility and insights into competitors’ product assortments. Retailers can keep a tap on their competitors’ product mix, segmented by product and brand, percentage of overlap, which gives them the ability to quickly adjust their own product-mix and pricing with high accuracy.

Voice Powered Search

In December 2014, Baidu unveiled speech recognition technology dubbed “Deep Speech.” Although the technology is still nascent, once it is developed optimally, it can make shopping literally interactive, enabling the customer to have a real time seamless voice conversation with the virtual shopping assistant on the eCommerce platform.

Employment of AI in Indian eCommerce

In case of India, eCommerce biggies like Flipkart, Snapdeal and Amazon are proactively investing fortunes in AI research and development. Apart from intelligent chat facilities, these companies have introduced image recognition feature to their platforms which is attributed to deep learning.

According to Sachin Bansal, CEO, Flipkart, artificial intelligence is a key differentiator in the fiercely competitive business of online retail. He believes, “the big disruption that is happening across the world is the rise of artificial intelligence.” Therefore, by combining social, mobile, big data analytics and AI, Flipkart attempts to build human brain-like capabilities to sell smarter to its more than 45 million registered online buyers. Recently, the company launched its messaging service on its app, called Ping. It serves as a shopping assistant embodying artificial intelligence, to help users easily discover the item they are looking for on its platform.

Likewise, Flipkart has just announced that it is working on automating its supply chain to reduce shipment time and increase accuracy to ensure zero customer complaint. Confirming the news, Adarsh K Menon, VP, Business Development said, “We want to use data smartly and intelligently at our backend for personalisation in customer offerings, service offering, supply chain offerings. We have regular customer base of 45 million. We will use technology, look at buying behaviour and preferences of customers and then personalized our offerings. If we use data, which is available with us, intelligently, we will be able to give best shopping experience to customers”.

Further, Flipkart owned Myntra is too is reportedly set to introduce apparels designed with the help of data science and artificial intelligence. The company has developed a smart bot that accumulates fashion-related information from across the online world by crunching a large amount of data centered around consumer demand in real time. Commenting on the same, Ganesh Subramanian, head of new initiatives at Myntra, maintained, “There is a big, emerging trend among internet companies which have accumulated tons of data to use it for personalization. Our platform is disrupting the current way of expert-based fashion forecasting as it is 100% tech-backed.”

Snapdeal is reportedly investing $100 million into a new multimedia research lab in Bangalore. The company’s app- findmystyle employs image recognition technology and machine learning algorithms, to make search results faster, accurate and tuned to the specific consumers.

The Way Ahead-

It would be an understatement if we say, “Artificial Intelligence is the next big thing”, for it is already here, and of course, with a bang!

Tech juggernauts across the world are advancing at an incredibly impressive pace towards the crux of this technology. Google for example, is conducting a highly advanced research on AI called Thought Vectors, in an attempt to infuse common sense into machines. Similarly, Apple, Facebook and Microsoft are working on their respective projects on AI development.

Expressing himself on the future scope of Artificial Intelligence in eCommerce, Navneet Sharma, Co-Founder & CEO of AI-linked startup Snapshopr, maintains, “Not very far from today, eCommerce apps will know in advance know what you need and will order them automatically for you.” Adding further, he stated with conviction that nothing is impossible with AI. It’s only limited by time and computing resources.