Article

19.03.2018

GDPR: "legitimate interest" to the rescue of marketers!

What effect will the GDPR have on direct marketing? The general consensus is that life will be more complicated for companies after 25 May. But BPost doesn't think so, witness its white paper on the positive effects of the new European regulation on promotional communications, specifically the redefinition of a key concept: "legitimate interest".

The General Data Protection Regulation (GDPR) enters into effect on 25 May 2018 and will change the way that companies collect and process personal data. This is a frightening regulatory framework because it imposes a certain number of new obligations, which include keeping a written register of processing activity, analysing the risks for the people involved, implementing new procedures (security, processing, etc.), the arrival of the right to be forgotten and data portability for the public, etc. Nevertheless, change is often synonymous with opportunities too, as BPost highlights in a white paper that to some extent goes against the grain of current publications. Indeed, this document highlights and describes the positive effect of GDPR on direct marketing.

"Legitimate interest" better defined

This is the main message of the white paper published by the postal operations company: contrary to what is generally believed, the consequences of the GDPR on direct marketing (emailing, calls, text messaging, etc.) are somewhat limited, even positive, since the European regulation explicitly recognises the possibility of interacting with your customers without obtaining the notorious "prior consent". In fact, the GDPR envisages that "with existing business relationships, companies may possess a legitimate interest in using their customers' personal data to send them information intended to advertise and/or promote their services, products or activities". By further defining the concept of "legitimate interest", which is too often ignored these days because it lacks definition in current European legislation, the GDPR thus increases its appeal to marketers.

More rigorous "consent"

Let's look at the legislation: the European regulation recognises six legal grounds to justify personal data processing by companies, including the two most used in direct marketing: "legitimate interest" and "consent" (the other four are contract-based requirement, legal obligation, crucial interest and general interest). If a company currently favours prior consent, it will have to get on board with a more rigorous legal justification. Indeed, under the GDPR, this consent will have to be "unambiguous, specific, freely given and informed". In other words, customers will have to indicate their agreement by a "positive" act. No more boxes to tick to refuse information, pre-ticked boxes or even consent "hidden" in the general sales terms and conditions.

"Legitimate interest" becomes a viable alternative

In this respect, BPost thus presents "legitimate interest" as an interesting option to justify processing existing customers' personal data for direct marketing purposes. The main advantage is the ability to bypass the problem of obtaining customers' consent. Companies can thus communicate with all their existing clientele and also avoid having to implement complex processes for obtaining consent. From a legal perspective, moreover, the white paper underlines the soundness of this approach, given that the GDPR explicitly legitimises it.

An essential consideration

While the GDPR makes the life of companies easier with regard to direct marketing, they are not exempt from certain obligations. Firstly, companies have a duty to inform their customers beforehand, especially about their rights to the access, erasure, portability, etc. of data. Furthermore, the recourse to "legitimate interest" as a legal justification requires every company to rethink its approach to make sure it strikes a balance between its interests and those of the people concerned. Also, that its interests are real, specific and needed in order to pursue the "the legitimate interest" of the company. In other words, "ethical" consideration of communications that constitute the company's direct marketing is essential... and to every party's benefit.

For more information: the BPost white paper on "How to bring your direct marketing into line with the GDPR"

Article

18.11.2016

Big data: six questions to ask yourself before getting started

Big data is a new class of assets that companies must embrace, develop, protect and make work for them during their transformation into a digital enterprise. We have put together some points to help guide your strategy.

Is there a course in big data?

Most universities around the world have come to understand the importance of big data. More and more, they are using analysis, both in research and to improve the lives of students on campus and help guide them; however, there is little in terms of training on this topic. Nevertheless, some establishments have recently started to offer their own diplomas and programmes to train the next generation of data scientists.

Do I need to provide training for my staff?

Yes. However, it's difficult to send your IT teams back to the school room in order to train or bring them up to speed. Nevertheless, various training courses have been organised around the country by specialist service providers. A two-day training course already teaches its students about the specific issues surrounding big data and the potential technical solutions.

Do I need to hire a data scientist?

Not necessarily. Some figures: last year, there were 4.4 million jobs in this sector, of which only 40% were filled. Not everyone has the budget for a data scientist. You can instead call on an independent consultant to pave the way and get your company up and running with big data.

What main techniques are required?

Techniques such as machine learning and data mining are essential for those working with big data. They help you tackle tasks that are difficult or even impossible to complete using more classic algorithms. The art of Data Visualisation enables you to communicate discoveries from data analysis.

What keyword should I take away?

Hadoop! In the same way as Microsoft Office is known for productivity and Apache is synonymous with the internet, apps are the key in the world of Big Data. Hadoop should be the cornerstone of your strategy. Without such expertise, it is impossible to master big data. This open-source software framework is designed for distributed data storage. It is highly scalable and resistant to failures. Its role is to process and analyse new and old data silos to extract significant knowledge from them that can be used in a company's strategy. Your experts will have to become familiar with its components: ‘Spark’, ‘Hive’, ‘Pig’, ‘MapReduce’ and ‘HBase’.

Is big data relevant for SMEs?

Certainly, in particular for marketing: big data enables companies to sort data in order to gain a clear profile of its customers. Segmentation can be used to optimise campaigns. Analysis also allows you to  really observe how customers behave. SMEs don't have the same budget as a large group, and so they must primarily focus on data which is both crucial and can be exploited to reap the greatest reward: creating a stronger link with their customers.

Article

14.12.2016

Tant qu’il y aura des data…

Le graal des big data? Créer une expérience client sans précédent. Mais pourquoi une start-up sans passé réussit à être affective là où ses ainées croulant sous les data rêvent de proximité ? Quelle est l’alchimie gagnante ?

Stocker et traiter ses données numériques, ce n’est pas nouveau. Le datamining non plus. Mais avec les objets connectés et les usages mobiles, les données déferlent littéralement. SMS, chats, photos, vidéos, requêtes à un moteur de recherche, clics sur le net, demandes d’itinéraires sur google maps ou autres, paiements en ligne, contacts client par chatbots ou messagerie, renouvellement automatique des commandes à partir d’un frigo intelligent… des données, nous en produisons sans cesse sans même nous en rendre compte ! Même lorsque nous acceptons la géolocalisation ou que nous nous connectons à une borne wifi...

En 2020, le volume des données devrait être multiplié par 50. Une voiture connectée, par exemple fournit, en une heure de temps, des millions de données utiles à l’automobile, mais aussi aux assureurs aussi ou à l’e-commerce. Et les enjeux ne sont pas moins prometteurs qu’ajuster sa stratégie, personnaliser un service, prendre de meilleures décisions, détecter des tendances, établir des prédictions… 

Il y a toujours eu des statisticiens pour interpréter les chiffres du passé afin d’améliorer le futur, mais aujourd’hui les ‘data scientists’ sont des geeks. Des cursus universitaires voient le jour et l’explosion des données adopte un rythme quasi insoutenable pour que nos connaissances puissent suivre. Seules des machines sont encore à même de gérer de tels flux de données. Les techniques d’apprentissages automatiques (‘machine learning’) permettent de faire mieux et plus rapidement. Un standard pour une utilisation correcte de l’intelligence artificielle serait en cours à l’initiative de noms comme Google, Facebook, Amazon, IBM et Microsoft. Pour Nicolas Méric, fondateur et PDG de la start-up DreamQuark, acteur de deep learning appliqué à la santé et l'assurance, de telles technologies dopent les capacités humaines mais elles ne sont pas vouées à pouvoir s’en passer.

Qui est concerné ?

Aucun secteur n’échappe vraiment au besoin de récolter ses données afin de les faire fructifier en transformant son environnement. Mais disons que certains se montrent plus pressés – ou opportunistes - que d’autres. Les télécoms, le transport, les fournisseurs de gaz, eau, électricité, émergent : la SNCF mais aussi le fabricant de produits de beauté Nuxe épient tous les canaux en ligne en quête de verbatim client pour mieux le connaître. L’ascensoriste ThyssenKrupp, qui veut chouchouter ses cabines et surtout leurs utilisateurs, récolte moult paramètres sur celles-ci afin de parfaire la maintenance et d’anticiper les pannes désagréables.

Les responsables des Big Data en entreprise sont face à trois défis principaux, rassemblés sous la règle dite des ‘3V’: pouvoir gérer de gros Volumes, tenir compte de l’infinie Variété des informations, et parvenir à gérer la Vitesse à laquelle elles sont générées. Les banques n‘y échappent pas. Ces entreprises qui ont d’ailleurs beaucoup à y gagner puisqu’elles disposent de tonnes d’informations transactionnelles sur leur clientèle et créent des processus en tout genre, sont mises au défi : celui de se servir d’un tel trésor pour tester elles aussi de nouveaux services à valeur ajoutée dans un délai le plus court possible.

Momentum

Jean-François Vanderschrick est Head of Marketing Analytics & Research chez BNP Paribas Fortis : « Ce qui me fascine, c’est moins la multitude des données disponibles et des objets connectés que tout ce que la technologie permet désormais d’en tirer. Pas un jour ne se passe sans que je ne sois surpris par quelque chose de neuf. JP Morgan détecte des tendances en achetant les photos de l’occupation des parkings des supermarchés. La Chine développe la reconnaissance faciale pour adapter le lay-out de ses interfaces à l’expression de ses clients. Vous pouvez suivre à la trace votre paire de chaussettes made in USA de son expédition jusqu’au moment où elle franchit le seuil de votre domicile… Tout cela fait partie de notre quotidien au moment même où une banque manifeste ses intentions de s’adapter à la phase de vie que traverse son client – celui qu’elle suit depuis qu’il est actif – pour lui offrir juste ce qui lui est utile. »

Chez BNP Paribas Fortis, le management data franchit récemment un nouveau pas avec la nomination d’un Chief Data Officer membre du Comité Exécutif, Jo Couture. Ce qui signifie aussi des renforts humains, de nouveaux outils analytiques et de nouvelles capacités.

Jean-François Vanderschrick : « Les data analytics doivent nous permettre d’améliorer l’expérience client, ainsi que de garder les coûts sous contrôle et in fine, cela conduit généralement à une plus grande efficacité. »

Selon lui, la courbe d’adoption entame à peine sa phase exponentielle.

Le timing est aussi important que le service lui-même

Les données servent une multitude de domaines : excellence opérationnelle, marketing, détection des fraudes, risque crédit… Les entreprises comprennent désormais qu’elles doivent transformer leurs données en connaissances et en services et bon nombre d’entre elles ont tout pour y parvenir. Toutefois, il convient de ne pas se laisser noyer par la masse d’informations. Le plus compliqué - et source de frustration - est sans doute de pouvoir accéder aux données et de parvenir à les qualifier. Les aspects de compliance ont naturellement tendance à freiner les développements. Réduire le data to market reste cependant un défi majeur car souvent, le timing de la mise sur le marché s’avère bien trop long. Il s’agit aussi d’offrir un service en temps réel, comme c’est le cas chez Monoprix qui analyse le processus de traitement de 200 000 commandes quotidiennes de ses 800 magasins pour intervenir directement sur sa chaîne d’approvisionnement, un processus critique pour l’enseigne française.

« C’est une délicate alchimie à produire entre les tests (la maquette du service est souvent très chouette, mais encore faut-il réussir la généralisation), la mesure du risque et la ‘prioritarisation’ des objectifs », soutient Jean-François Vanderschrick.

Eduquer l’algorithme

Pour peu que l’on dispose des données et de la technologie, et qu’il y ait des enjeux financiers liés, l’imagination reste notre seule limite pour libérer la valeur des données. A côté de projets conséquents et complexes, des quick wins relativement simples sont ici aussi tout à fait possibles et souhaitables, notamment pour permettre aux directions opérationnelles de l’entreprise d’effectuer des analyses élémentaires à partir de grands volumes de données. « Aujourd’hui, une variété d’informations qui semblent peut-être anodines peuvent nous éclairer et servir de déclencheur d’actions : un client qui commence à travailler avec la concurrence, qui place des lignes de crédit ailleurs, ou emprunte un montant particulièrement important, traite avec un autre pays… autant d’informations qui commercialement parlant, méritent toute notre attention et qui sont jugées utiles dans 70 % des cas » ajoute le responsable de BNP Paribas Fortis. Analyser le modèle transactionnel d’un client permettrait de prendre de meilleures décisions de crédit. Il est possible d’améliorer de manière conséquente la pertinence des décisions, comparé à ce que nous pourrions faire sans modèle, prétend Jean-François Vanderschrick qui ajoute encore :

« Grâce au machine learning, nous éduquons l’algorithme à fournir des réponses de plus en plus pertinentes.» 

Si ‘Big is better’, est-ce accessible aux petites ?

Grâce au Cloud (espace en ligne), les PME disposent désormais des capacités de stockage - auxquelles s’associe la puissance de calcul nécessaire pour exploiter les données. C’est un des enjeux majeurs des Big Data. Le second est de savoir comment les traiter. Des logiciels de gestion d’entreprise usant de la technologie cloud, style CRM, outil de suivi des commandes ou des coûts de production, traçabilité des fournisseurs, rendent les big data accessibles aux petites et moyennes entreprises. Seule condition : rassembler toutes ses données au même endroit. La différence entre les corporates et les PME se jouera sur le long terme. Mais les PME pour qui un super statisticien serait impayable, peuvent toujours acquérir des études ciblées et enrichir leurs données par des bases externes…

(Sources : BNP Paribas Fortis, Les Echos, Transparency Market Research, IDC, Ernst & Young, CXP, Data Business)
Article

22.12.2016

Get on board with corporate responsibility

Customers are demanding quality products, and also companies that share their values. In the US, the B Corp example could redefine the commercial strategy of all new start-ups.

In 1970, the economist Milton Friedman wrote in the columns of the New York Times Magazine, ‘The Social Responsibility of Business is to Increase its Profits’. In a complete departure from the practices of the age, this innovative speech was not necessarily convincing. For 40 years, business has consisted of optimising the return on shareholder investment, with boards of directors putting profit above all else. To do this, they carried out redundancies and restructuring, paying little attention to the environment.

Nevertheless, as Steve Denning emphasised in 2011, maximising profits for investors, intended as an economic remedy, ended up becoming a disease. According to the editorial writer, we have reached “the limits of the model”. The figures prove it: capital ROI is now 25% of what it was in 1965.

More responsible growth

In 2016, everything has changed. There is a shift towards a corporate conscience, greater transparency and authenticity, values personified by a movement that now brings together such emblematic companies as Ben and Jerry's and Warby Parker, B Corps certification. This highly successful label is awarded by a not-for-profit organisation, B Corp, already present in 50 countries and adopted by more than 2,000 companies. One of them is the Belgian company Ecover.

Jay Coen Gilbert, the founder of B Corp, took the opportunity offered by the 2016 Net Impact Conference to explain the model he endorses:

"The tectonic plates of business are shifting beneath our feet. Sometimes they move so slowly that it’s hard to feel it, but now they are shaking the earth and transforming the landscape right before our eyes. We are seeing the change from one form of capitalism to another." For him, corporate responsibility no longer only concerns large enterprises, but all trade in goods and services around a common project: "The creation of jobs with dignity and purpose, concern for the environment and the need to create pathways out of poverty and reduce inequality.

Is Occupy Wall Street the solution? No, insists Jay Coen Gilbert:

"There are populist movements around the world in response to the realisation that the economic system is not working, but these are not enough. Hope is not enough to bring about profound social change. History has proved to us that this comes from the creation of viable and visible alternatives. And in our view, one way that’s happening is through companies themselves.” Whatever their size.

Article

27.12.2016

These 4 giants from Silicon Valley want to seduce your IT management

Already champions in everyday life, Google, Facebook, Slack and LinkedIn are adopting innovative and complementary approaches to convert companies. What strategies are they implementing in order to convince you?

Google: the value of data intelligence

Google is adopting an approach which goes beyond communication tools and suites of productivity apps/services. The company has largely transformed its business divisions so that they can exploit cloud infrastructures, big data, analytics and machine learning as a matter of priority. Two competitors are blocking it along the way: Amazon and Microsoft, but for different reasons. Developers have been using Amazon Web Services for a long time, which gives it a history of trust. Microsoft (Cloud, Office) also has a historical presence in IT departments around the world. In this approach, linked to the processing of sensitive data, Google still needs to evangelise: a company is not as easily convinced as a consumer, particularly when it comes to strategic or confidential data. Its weapon: the power of its artificial intelligence tools to process data silos.

Facebook: introducing WorkPlace, naturally

After more than a year of development with partner companies such as Danone, Starbucks, Royal Bank of Scotland and Booking.com, Facebook officially launched WorkPlace last October. This Facebook spin-off enables organisations to create an internal social network - completely private and secure - within an interface familiar to all employees in their everyday life, introducing head-on competition for already widespread tools such as Chatter (Salesforce) or Yammer (Microsoft). Unlike free Facebook, WorkPlace is billed monthly depending on the number of users: $3 for the first 1,000, $2 for the next 9,000 $1 for over 10,000 users.

Slack: real-time collaboration becomes mainstream

Despite the introduction of Microsoft Teams on its turf, Slack remains confident in its strategy of creating tools that allow greater communication and productivity within companies.

"We find this offensive both flattering as well as intimidating, given Microsoft's means, but we think there is sufficient space in the market for several players", declared April Underwood, VP of Slack at the beginning of November.

A market that Slack has largely contributed to opening and driving, by introducing the concept of real-time collaboration. Its weapon? Agility, despite its still limited size and its proven and copied tools. Result: 4 million active users everyday and constant growth.

LinkedIn: from B2B marketing for... Microsoft

Microsoft Closes Acquisition of LinkedIn at the beginning of December. The transaction, which runs into billions of euros, has been followed closely by the European Commission. Despite a strong position in the business, mainly at a human resources level, LinkedIn needs 25 billion euros from Microsoft to pursue its offensive in the domain of professional tools, in a hugely competitive climate. For Microsoft, the acquisition will enable the company to reach B2B marketing targets such as recruitment agencies, head-hunters and businesses. To explain the synergy sought in simple terms, the CEO of Microsoft, Satya Nadella, gives the example of a meeting where everyone present sees their LinkedIn profile, linked to their invitation.

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