Why I’m betting my money on small creative agencies to thrive in this digital age?

July 4, 2017 Leave a comment

I recently outsourced my brain to a creative agency as the other parts of my body were busy rebuilding a house. It was an ad-hoc request to create a pitch for a well-known banking brand. Whether I could come up with a creative communications campaign based on a humdrum client briefing. Turned out I could. Turned out this is what a creative director does: A strategic and creative answer to a dull briefing. If you want to see the pitch slide deck, drop me a line.

This whole project got me thinking tough. On the role and type of agencies we have today. And which ones we will have tomorrow, or even the day after tomorrow. Contrary to current popular believe, I’m going all-in for the creative agencies. I’m pleased to detail my reasoning further below.

In 2017: Digital is basic by now.

I’m amazed that digital marketing is still a thing. It’s 2017. Digital is like electricity, it’s just basic. Everybody does it. Maybe it’s time to drop the term digital as such.

Back in 2006 when I started, digital (online) marketing was a true differentiator. Today, it’s not. It even might be the hardest way to catch the consumer’s increasingly selective (digital) attention.

Today, there is also the growing understanding that overall customer experience is the key differentiator that can make or break brand success. Back-to-basics, isn’t it?

Sure marketers need to drive tangible, data-driven results – something consultancy firms are traditionally good at. However agencies and/or in-house marketing teams have (or should have) those skills as well today.

But, the big, creative ideas are more necessary than ever for brands in search of the ultimate experience. Even, or should I say especially, in a digital space and age.

The big, creative ideas, concepts and stories are the key asset of a creative (ad) agency. And those things aren’t time-specific. Stories and creativity are for eternity.

In eternity: creativity & stories are channel-agnostic.

The core relevant ideas/concepts/creativity are just as relevant for any channel. That’s basically the adagio we’ve known for ages – integrated communications. Back-to-basics. Again.

We can finally make that happen. Over numerous channels. A unified, seamless experience. Some channels are fully traceable today, others will be soon. And that’s exactly where data comes in. But be aware, there isn’t gonna be a lot of (big) data when there’s no big story that resonates and draws the attention of many.

Data is important and it is at client’s side.

No single creative ad ever came out of the blue. It was always driven by insights. By understanding. By empathy with the “target audience” the message was meant for.

In today’s digital age, there’s of course the digital data trace of human behavior that lead to great insights and understanding. It’s a completely new game due to data science. But then again, doing something relevant based on these insights requires creativity.

What’s even more, the data is owned by the agency’s client. One can imagine that privacy may be of importance so it seems natural that agencies will also need to service at client’s side. Let’s say like martech companies do today. Marketing tech companies help marketers manage data, loyalty and CRM programs.

Next to this data thing, there’s another trend that “design” or “creativity” evolve into key hires at the client side. And we agree, those things really give a competitive advantage. But I believe it will not replace the creative agency – rather act as a bridge.

Where data meets creativity, innovation spurs.

We talked above about data and creativity. I firmly believe this is exactly where innovation happens. At the intersection of data and innovation.

And oh yes, innovation is the thing of a creative agency. No longer is advertising necessarily the best manifestation of creativity. Marketers are now looking towards innovation and effectiveness in terms of brand-experience. For the agencies, this is gold.

Agencies have a perfect position to foster innovation based on dull client requests. Due to creativity within a specific context (data). So agencies should not only conceive a new label on a package, they should conceive an innovative package for instance.

The great rebundling of “expertises” to offer full-fledged customer experiences.

With the above trends in mind, how does a successful marketing communication service provider of the future look like?

A one-stop shop that provides companies with all the support they need to deliver relevant, exciting experiences across all consumer touch points.

Companies need a streamlined, end-to-end solution to push creative thinking to the forefront. It doesn’t make sense to get business strategy advice from one firm and creative input from another—especially if the creative agency doesn’t understand how the company’s business works or how industry trends are impacting its bottom line.

Just as consulting improves the quality of creative work, consulting work benefits from the ingenuity provided by creatives. There’s going to be a blurred line between the folks who create amazing original content and big ideas and the more nerdy specialists that do all that personalization “data” and “tech”. People who understand data and omni-channel ultimately become the most responsible in this respect. 

As clients demand newly bundled support across commerce, digital content and media distribution, agencies transform to meet the challenge, investing in consulting and tech. At the same time non-agency players are getting their way into the marketing services industry. The threat of new competition lures behind the corner too: media owners/publishers & wide range of ‘consultancies’. 

I imagine creative agencies will get smaller. The big idea doesn’t benefit from size. It flourishes in small cultures. What doesn’t get much smaller, beyond the roles that can be automated in time, is the data and analytics business that drives personalization

That’s exactly why I’m betting on small creative agencies to remain the marketing service provider of the future. 

Filed under Business, Marketing, Media, Software & Technology Tagged with , , , ,

Why the Semantic Web is the future and why the future is now?

July 16, 2015 Leave a comment

Today the web delivers information to us in the form of web pages – mainly HTML documents that are linked to one another through hyperlinks. It’s by scanning and following hyperlink after hyperlink that Google indexes and maps the entire world-wide web.

The sweet thing with HTML documents is that both humans and machines can read them. Whereas humans can read the content as such, interpret it and consequently link meaning to the words on the page, machines need to look at some clues to judge the content of a web page. Clues that SEO specialists truly understand. So they put the keywords in places where machines go looking for clues.

But as the web evolves, technologies alter. And moving beyond HTML to communicate information to machines might have a tremendous impact.
HTML is still important – and it will always be, most probably – but the importance for machine interpretation is in decline thanks to semantic technology.

The web has promised semantic for a while now, but nowadays it seems to hold true to the promise. For SEO, it means keywords are no longer the key element of SEO – as proven by Google’s default ‘not provided’ keyword parameter. The new normal for SEO is to do Semantic Web. It means marking up your content in a much more clever way then we previously did with a keyword-driven html-documents-based approach.

Semantics turns Google into both your start and endpoint of every search journey.

As happens with most searches these days, let’s start at google.com to explain what it is about. And as happens with most searches on google.com these days, this is exactly where your search journey ends as well. Why? Because Google provides you the things you need on its own page, not by redirecting you to a scanned page somewhere on the internet.

How do you think Google Shopping allows for online buying on Google at a retailer’s store? Or what about booking hotels and flights directly in Google? And what about the nice preview you get on your mobile phone to confirm your flight and hotel booking? Or something as simple as having your location and opening hours in Google?

Yup, Semantics. So, Hello, new SEO! What a bless that people can find you on Google and e.g. buy your service/product directly through Google, see your opening hours and location, …
Let’s take a look at two big (online) players, Lufthansa and Ebookers.com who are already doing semantic web and giving customers a superb experience on Google platforms.
How nice are those emails? What a brilliant customer experience is this? Quite sure you want to repeat this because it makes you feel good.

Inbox - semantics @ work?

Inbox – semantics @ work?

Book hotel in Google search - Semantics at work?

Book hotel in Google search – Semantics at work?

Running an e-commerce website? Watch out for Google shopping.

Google Shopping – semantics at work?

semantics - weather & location

semantics – weather & location

Semantics at work by Ikea?

Semantics at work by Ikea?

Many applications from Google, Microsoft, Pinterest and others are already using these vocabularies to power rich, extensible experiences. It’s important for brands and corporations to offer a smooth experience from your company on the Google, Facebook and other dominant web platforms today. It means that you need to get into the semantics game.

Particularly for the “Google Discoverability Purpose”, the semantic tech at work here is Schema.org. Schema.org seems one of the most important RDF schemes for businesses today to understand and deploy. I even would like to call it the new SEO – if only it was to build awareness by provoking.

Schema.org, the most important Semantic Web tech today.

Schema.org is a community that creates, maintains and promotes schemas for structured data on the Internet, on web pages, in email messages and beyond.

The vocabulary can be used with many different encodings (RDF, microdata, JSON). Many applications from Google, Microsoft, Pinterest and others are already using these vocabularies to power rich, extensible experiences. It’s important to provide a smooth experience from your company on the Google, Facebook and other dominant web platforms otherwise you’re lost. It means that you need to get into the semantics game.

But where do semantics come from? What’s the story behind it?
Be aware: here is where I try to explain the tech behind my marketing bla bla above.

The story behind schema.org: Semantic Web for machine readability.

In its very essence, semantic web, marks a shift in thinking from publishing data in human readable HTML documents to machine readable documents. The Web contains lots of information. But it’s hardly constructed from raw data. It’s marked up in HTML documents. The semantic web basically changes this core architecture of the Web.

The semantic web is a way that allows to describe models of data that can further be treated as if everything was in one database. Think of the web as one big jar of data. Think of a web page as a visualization of well-selected data from that jar. Mashup Gallore! You’ve seen it. And you’ll see it more in the future. Why does this happen now?

Why the time for Semantic Web is now.

Regardless of the fact that Semantic Web has been a topic for years now and that it did not get much traction outside the academic realms yet, the time for semantics is now:

  • artificial intelligence is coming strong and if we want to make the web work for us, we need a “language” for machines to understand. That language seems semantics.
  • internet of things is generating data and if we want machines to communicate with one another (M2M communication) and with humans, we need a language that both can understand. Hello, Semantics.
  • the growing usage of marketing automation at multiple digital touch points, makes an intelligent markup language crucial for machines to take over human activities.
  • the benefits of automated research of all data humanity has to offer on the internet…

Semantic Web: the tech side, the machine aspect

So far we did not clarify a lot. We agree. We did not do anything else than saying that the web as we know it – html pages linked via hyperlinks – is about to be replaced with a more clever way of organizing, structuring, retrieving and visualizing data and content.

Semantics is mostly defined as a “3.0 web technology” – a method of linking data between systems or entities that allows for rich, self-describing interrelations of data available across the globe.

One might think this is a rather complicated topic. However, it doesn’t have to be. The below learning curve helps you to understand what semantics is about. And how to get there from the ground up.

Semantic web learning curve

Semantic web learning curve

How to realize Semantics – a roadmap from Graph Data over RDF to Semantics.

Forget everything you know about databases. Because probably you only know hierarchical relational databases. This hierarchical architecture is what the semantic web leaves behind. It starts from a Graph Database instead of a relational and/or hierarchical database.

A graph consists of resources related to other resources, with no single resource having any particular intrinsic importance over another one. In this way, it’s easiest to understand a Graph as a visualisation of a series of statements about how things relate to each other. Let’s clarify things with a data graph example.

A Data Graph example

The below graph (or scheme if you want) actually makes several statements about two objects:

  • thing 1 has the name Bengie and has the animal type dog
    Bengie is a dog.
    thing 2 has the name Bonnie and has the animal type cat.
    Bonnie is a cat.
    Thing 1 is linked to Thing 2 through a relation “friends with”.
    Bengie and Bonnie are friends, despite being a cat and a dog.
Example of semantic graph

Example of semantic graph

Is it only me or are people also constructing meaning in this manner?

Anyway, let’s look at a method do translate this graph into something that can be used in Information technologies. Hello RDF!

RDF: the foundation of semantic web without describing the meaning (semantics) as such.

RDF is a formal manner of describing data graphs so that machines understand the structure behind the graph. An RDF statement always comes with the following 3 dimensions:

  • subject
  • property
  • object
example statement

example statement

The “triple” (subject, object, property) is the essence of RDF, the structural foundation of the semantic web.

In order to thrive in the semantic web, one needs to understand data and content within this non-hierarchical means of data modelling.

Semantic Modeling with metadata from formal vocabularies and ontologies

While the above RDF statements offer a graph-based model for recording and interchanging data globally, it doesn’t provide any clues for the meaning as such of the statements. In other words: there’s nothing semantic in yet. To include meaning, one needs common formats to collaborate. These common formats are realized through vocabulary and ontology:

  • vocabulary: terms with a well-defined meaning across contexts
  • ontology: defines contextual relations behind a defined vocabulary.

Standard vocabularies, or formal ontologies, are already available for a wide range of subjects: media terms, biomedical terms, scientific terms, etc.
For non-techies it might be the easiest to understand all this as “metadata”; data that describe the data. For SEO’ers it might be easiest to understand that “schema.org is the new meta data in the html head section”.

The real deal: RDFS & OWL, the actual semantic techology

In order to construct meaning in RDF data, one needs to mark them up or annotate them with semantic metadata: RDFS and OWL. And it this point, we’re really talking technical shit. So I think I’ll leave it for now. In fact, I’m quite unable to further explain this. I’m a non-technical guy. But I believed this was interesting. So I researched a little bit. So, yeah, it might be, this post has errors…

The web is undergoing a massive re-architecture. It’s called Semantics.

We’ve pointed out in the introduction that Semantic is getting increasingly important to the world because of the rise of artificial intelligence, internet of things, marketing automation and so on.

But we started from a “Google / Seo” perspective because we believe it’s shows the importance of semantics in the most tangible way. SEO is about getting a good spot in the search enginge result pages for a specific keyword. Clever marketers have already noted that Google’s search engine result page is not longer a gatekeeper. It is not the start of searches. It’s also the end of searches. Making sure your product, brand, service pops up in those end pages. Intelligently mark up your bits and pieces (data, content) with schema.org.

Filed under Marketing, Software & Technology

How to outperform a Big Data competitor with Tiny & Small Data?

April 16, 2014 1 Comment

“We’re lost. Competition has more intelligence through their Big Data solution.”

Size doesn't matter - on data

Size doesn’t matter – on data

If you recently ran up to a marketing manager slash director slash VP Marketing, you’ll probably have heard the above sentence. And it seems to make sense at first sight. After all, there are plenty of articles stating that marketers should do Big Data or otherwise their organization will become obsolete because Big Data-driven Competitors will make them irrelevant. So if you want to sustain your marketing credibility, you better start your Big Data Project.

“You’ll win. Outperform them by using smart Small and intelligent Tiny Data.”

I disagree. Strongly. Most companies shouldn’t do Big Data. First of all because most are unable to collect them. Second, most are unable to crunch them into meaningful insights. To get to these insights, look at Small Data and Tiny Data. Small & Tiny Data are key to outperform your Big Data-driven competitor. Here’s why.

Why Tiny & Small Data are more important than Big Data.

As life partly moved to the internet and the internet became mobile (phones, cars, houses,…) , traces of our life are recorded and consequently quantified. This is what makes Big Data well … Big. It’s a collection of large and complex data sets. Insights and understanding of these data bears a lot of potential in them. But on the other hand, Big Data starts from a shaky premise: “we don’t need to think if we analyze sufficient data the numbers crunched say it all”.

In case I remember my stats courses well, this is just plain Bullshit. First of all there’s the difference between a correlation and a causality. It’s not because things are correlated that we understand the causality of the phenomenon. Furthermore, adding more data points to a collection does not automatically takes away all data issues. Just think of a “biased sample” in this respect. What if all “Big Data” you gather are from those people who are totally off-focus? Or do you really believe you can gather “all data” to counter all statistical reasons against Big Data. I guess you’ll never have “all population data”.

“Big Data for the What. Tiny Data for the Why.”

Big data show you the what. Tiny Data prove the why of that what. Marketers need to understand the why and work towards that insight. In today’s world, most marketers need to rely on Tiny Data to get those crucial insights on the why.

What is Tiny Data?

Tiny Data is a collection of qualitative / interpretative information. The data sample is rarely big. You take a few well-selected data points (sample) and get in deep touch with these data points. Observe these data points in real-life (participatory observation), talk with them individually about the subject (interviews) or run collective discussions (focus groups) to retrieve the information you’re looking for.

The information generated through these research techniques are not quantified. Variables are described in a human language. Not through statistical numbers based on – wrong – assumption. This in turn results in a better understanding. In true insights. Insights that are actionable. Insights that help you understand your customer. Insights that help you talk the customer’s language, etc. Don’t you want that in times where “engagement” seems a crucial marketing KPI?

“Big Data is here already. Big insights too but through Tiny Data”

Data without knowledge and information is useless. Current Big Data initiatives (like e.g. predictive buying) mostly lack true insights. As shown above, this will always be its problem. As this is a problem linked to the very nature of statistical modeling.

But what does one need to do now when he’s convinced he needs to be a data-driven business? Well, get insights through Tiny data. Second focus on getting your small data right!

“The Small Data challenge is already big enough.”

Regardless of the Big Data buzz, I notice a lot of companies not even properly handling their Small Data. That’s a shame because handling your small data well drastically improves your customer relations, lead generation, lead nurturing, etc. How do you automate your digital marketing communication without any solid Small Data behind it?

What is Small Data?

Small Data are the “regular” data information about a customer. These aren’t big – not large and not complex – but are crucial to get the conversation going. Think of elements like first name, last name, address, e-mail, birthday, sex, language, locale, channel preference, purchase stage, current products / services, …

And yes keeping those small data up-to-date is more important than gathering more and more data without any purpose. Or did you never get that “personalized e-mail” addressing you with the wrong name yet? “That couple who used to order a case of wine every fortnight for dinner parties is now buying diapers and baby food. Like your products, customer data has a sell-by date.”

“Size doesn’t matter?”

When it comes to data, size doesn’t matter. The goal of data is to get those that solve our problem or provide answers to the questions we have. For most problems and questions, small and tiny data do the trick. That’s how you outperform a big data competitor.

Filed under Marketing, Software & Technology Tagged with , , , , , ,

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