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…

Het ultieme doel van big data? Een unieke klantervaring creëren. Maar waarom lukt het een start-up zonder verleden om affectief te zijn, terwijl oudere bedrijven met tonnen data maar wat graag dichter bij hun klanten willen staan? Wat is de winnende formule?

Digitale gegevens opslaan en verwerken is niet nieuw. Datamining ook niet. Maar connected devices en mobiele toepassingen creëren letterlijk een tsunami aan gegevens. Sms'jes, chats, foto's, filmpjes, muzieklijsten, zoekopdrachten, clicks op het net, routeberekeningen op Google Maps en aanverwanten, onlinebetalingen, contacten met klanten via chatbots of e-mail, automatische bestellingen door slimme koelkasten ... We produceren de hele tijd gegevens zonder er ook maar even bij stil te staan! Ook als we akkoord gaan met geolocatie of wanneer we inloggen op een hotspot ...
Tegen 2020 zal het datavolume allicht vervijfvoudigen.  Zo genereert een geconnecteerde wagen in amper één uur miljoenen gegevens die niet alleen nuttig zijn voor de auto zélf, maar ook voor de verzekeraars en de e-commerce. Er staat veel op het spel: een strategie bijsturen, een service personaliseren, betere beslissingen nemen, tendensen opsporen, prognoses maken ...

Old-school statistici interpreteerden cijfers uit het verleden om voor een betere toekomst te zorgen. Hedendaagse  “data scientists' zijn geeks, er worden academische opleidingen georganiseerd en we zijn mentaal niet meer in staat om het explosieve groeitempo van de gegevens bij te houden. Alleen machines kunnen dergelijke gegevensstromen nog verwerken. Dankzij automatische leertechnieken ('machine learning') gebeurt dat beter en sneller. Er zou een standaard voor correct gebruik van artificiële intelligentie in de maak zijn op initiatief van kleppers als Google, Facebook, Amazon, IBM en Microsoft. Volgens Nicolas Méric, oprichter en CEO van de start-up DreamQuark, gespecialiseerd in deep learning in de gezondheids- en verzekeringssector, verhogen dergelijke technologieën de menselijke capaciteiten, maar zijn ze niet bedoeld om volledig autonoom  te werken.

Wie komt in aanmerking?

Geen enkele sector ontsnapt aan de behoefte om gegevens te verzamelen en die te gebruiken om zijn omgeving nuttig aan te passen. Maar de ene is al gehaaster – of opportunistischer– dan de andere. Telecommunicatie, transport, gas-, water- en elektriciteitsleveranciers nemen het voortouw: de Franse spoorwegen maar ook schoonheidsproductenfabrikant Nuxe speuren alle onlinekanalen af op zoek naar klantencommentaren om hun klanten beter te leren kennen. Liftenfabrikant ThyssenKrupp wil zijn liften en vooral de gebruikers ervan optimaal bedienen en verzamelt allerhande liftparameters om het onderhoud te optimaliseren en vervelende storingen te voorkomen.
Big-data-managers in bedrijven staan voor drie grote uitdagingen, ook wel bekend als de '3V's': grote Volumes verwerken, rekening houden met de oneindige Variatie van gegevens en omgaan met de Velocity of snelheid waarmee ze worden gegenereerd.
Banken ontsnappen daar niet aan. Ze hebben er zelfs enorm veel bij te winnen, want ze beschikken over tonnen transactionele informatie over hun klanten en creëren allerhande processen. Zij staan dus voor de uitdaging om zelf ook met die schat aan gegevens aan de slag te gaan en binnen een zo kort mogelijk tijdsbestek nieuwe diensten met toegevoegde waarde uit te testen.

Momentum

Jean-François Vanderschrick is Head of Marketing Analytics & Research bij BNP Paribas Fortis: "Wat mij fascineert is niet zozeer de hoeveelheid beschikbare gegevens en connected devices, als wel wat de technologie er tegenwoordig allemaal uithaalt. Er gaat geen dag voorbij zonder dat ik van iets nieuws opkijk. JP Morgan komt tendensen op het spoor door foto's te kopen van de bezetting van supermarktparkings. China ontwikkelt gelaatsherkenning om de lay-out van zijn interfaces aan te passen aan de gelaatsuitdrukking van zijn klanten. Sokken 'made in USA' kunnen we volgen zodra ze verzonden worden totdat we ze in huis hebben ... Het is allemaal onderdeel van ons dagelijkse leven. Net zoals een bank die zich wil gaan aanpassen aan de levensfase waarin haar klant – die ze volgt sinds hij een rekening heeft – zich bevindt om hem precies datgene aan te bieden wat nuttig voor hem is."

BNP Paribas Fortis zette onlangs een nieuwe stap in de dataverwerking met de benoeming van een Chief Data Officer die lid is van het uitvoerend comité, Jo Couture. Dat betekent ook dat er meer mankracht, nieuwe tools en nieuwe capaciteiten onderweg zijn.

Jean-François Vanderschrick: "Data analytics moet ons in staat stellen om de klantervaring te verbeteren en de kosten onder controle te houden. Meestal gaat dat samen met een verhoogde efficiency."

Volgens hem belandt de leercurve nu pas in de exponentiële fase terecht.  

De timing is even belangrijk als de service zelf

Data komen in heel wat domeinen van pas: operationele excellentie, marketing, fraudedetectie, kredietrisico ... De bedrijven hebben intussen ingezien dat ze hun gegevens in kennis en diensten moeten omzetten en hebben vaak alles in huis om dat goed te doen, op voorwaarde dat ze zich niet door de oceaan van gegevens laten overspoelen. Het moeilijkste – en een bron van frustratie – is wellicht het ontsluiten en kwalificeren van de gegevens. Compliance-aspecten hebben de natuurlijke neiging om de ontwikkeling af te remmen, terwijl een kortere data -to -market juist heel belangrijk is. Dikwijls laat de marktintroductie te lang op zich wachten. Verder is het van belang om een service in real time aan te bieden. Supermarktketen Monoprix analyseert bijvoorbeeld het verwerkingsproces van de 200.000 dagelijkse bestellingen van zijn 800 winkels om onmiddellijk te kunnen ingrijpen op de supply chain. Voor de Franse winkelketen is dat een kritiek proces.

"Er moet een juiste dosering worden gevonden tussen tests (het prototype van de service oogt dikwijls bijzonder fraai, maar het veralgemenen ervan lukt niet altijd), risicometing en prioritering van de doelstellingen", zegt Jean-François Vanderschrick.

Het algoritme 'opvoeden'

Als je over de gegevens en de technologie beschikt en er financiële belangen meespelen, staat er geen grens op het ontsluiten van de gegevenswaarde. Je verbeelding is de enige beperking. Naast grote en complexe projecten zijn ook hier vrij eenvoudige quick wins mogelijk en wenselijk. Zo kunnen de operationele directies van de onderneming elementaire analyses verrichten op grote gegevensvolumes.

"Er zijn heel wat soorten gegevens die er misschien volstrekt onbelangrijk uitzien, maar die toch informatie verschaffen en tot actie aanzetten: een klant die met de concurrentie werkt, die elders kredietlijnen opent of een zeer groot bedrag leent, die met een ander land werkt ... Al die gegevens verdienen onze aandacht vanuit commercieel oogpunt,  in 70 procent van de gevallen zijn ze relevant", voegt de BNP Paribas Fortis manager eraan toe. Door het transactionele model van een klant te onderzoeken kunnen we betere kredietbeslissingen nemen. Relevante beslissingen liggen meer voor de hand met een model dan zonderweet Jean-François Vanderschrick. "Via machine learning leren we het algoritme om antwoorden te geven die meer en meer to the point zijn", voegt hij eraan toe.

'Big is better', ook voor kleine ondernemingen?

Dankzij de cloud hebben kmo's vandaag de nodige opslag – en rekencapaciteit – om de gegevens te verwerken. Bedrijfsmanagementprogramma's die gebruikmaken van de cloud-technologie, zoals CRM, tools om bestellingen of productiekosten of de traceerbaarheid van leveranciers te volgen, maken big data toegankelijk voor kleine en middelgrote ondernemingen. Op één voorwaarde: dat alle gegevens op dezelfde plaats samengebracht worden. Het verschil tussen corporates en kmo's speelt zich af op lange termijn. Maar kmo's voor wie eenstatisticus te duur is, kunnen altijd specifieke studies kopen en hun gegevens uitbreiden met externe databases ...

(Bronnen: 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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