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17 May 2019

Hyper-personalization takes experiences to the next level – Our key take-aways from Adobe Summit EMEA 2019

Hyper-personalization takes experiences to the next level. They are the result of personal, behavioral and transactional data processed in an intelligent way, powered by artificial intelligence (AI). The combination of data and technology enables companies to provide an advanced one-to-one experience at scale. Based on key take-aways from the Adobe Summit EMEA, we clustered building blocks together into a hyper-personalization loop.

Hyper-personalization Adobe Summit

Key building blocks to close the hyper-personalization loop

Hyper-personalization loop1. Connect Data

Personalization starts with the availability of the right data and the correct understanding of it. You need it, without data you are going in quite blind. On top of that it needs to be real-time and it needs to be qualitative. Good marketing, now and even more so in the future, falls or stands with your data.

However, nowadays there is an absolute overflow of data that marketers could use. There is demographical data like where your clients are based, when their birthday is and so on. There is behavioral data which can provide figures on how people actually interact with your brand. There is transactional data. There is so much data. This whole goldmine might just be laying there, waiting for you to mine it properly.

“Have a data-centric view of the customer versus a system-centric view.” 
—  Abhay Parasnis EVP & CTO Adobe


2. Leverage Technology

Of course, you need to be able to leverage the goldmine you’re sitting on. Having a data lake may be the first step to take. Here, the new Adobe Experience Platform can come in handy. Once all the data is poured into the lake, you can start by unleashing your data scientists to perform manual actions and manipulations. They will probably report back to you that they need the proper technology to manage.

“Every customer interaction is an opportunity to surprise & delight.” 
—  Paul Robson, President EMEA Adobe

3. General Insights

Once you can handle the abundant amount of data, you can start to extract insights. However, human brain power can be insufficient to absorb that huge amount of information and draw the right conclusions – in real time. Multiple speakers at the Adobe Summit confirmed this thinking. It can also occur that insights that you would never have thought of or considered come floating above water. We like to call them your hidden gems. We’ll get back to you on that.

“Analyzing at scale really fast is hard.”
 
—  Anjul Bhambhri, VP Platform Engineering

4. Personalize Experiences

Adobe tools, such as Target, Adobe Campaign and Adobe Experience Manager offer you the possibility to personalize. Once you have gathered the right insights from your data, the path for the next best action to personalize in a relevant way - including what to communicate to whom, when and through which channel - should get a lot clearer. No need for guessing anymore, or at least, the guestimation risk is mitigated.

“People don’t want to be marketed to – move on and engage on more personal levels” 
— Steve Lucas, SVP Digital Experience

5. Interact

Unleashing your communications should deliver impact - no impact is also impact. Your customer might show you click behavior, show interest, get ‘warmer’ for your product or might even show purchase behavior (yay). All of this generates more data and restarts your loop.

“Data and intelligence help scaling the experience.” 
— John Travis, VP Brand Marketing

Learn Continuously & Autonomously

But what would happen if you broke the loop and you added an extra step to it before it starts again? Automated Machine Learning. Feeding Adobe Sensei with historical and real-time data makes it smarter. It will tell you what time you should send out your next communication, what your subject line should be, the likelihood for cross-selling, it might even present you with segmentation that might benefit your product. The best part? You don’t have to do anything for this, except implement it.

During the exclusive SNEAK session, we experienced a possible new feature - #journeygenious – where the AI power of Sensei will be essential. It will suggest to marketers which message should be sent to which customers at what moment in their journey to (re)activate them by predicting the best possible performing email from Campaign and visualizing results in Analytics in real-time.

“Customers will no longer accept personalized experiences based on past interactions. Companies should instead offer value by giving them what they need, when they need it. Understanding their intent is key – this is where deep learning technology can play a role.” 
— Stijn Sommerijns, Senior Manager / Head of Data, The House of Marketing

Hidden gems lead to innovation and disruption

Data is the new gold. We all know this. But what is true is that the real value of data lies in the insights you can distill from it. Things you wouldn’t have thought of can rise up and can lead to differentiated positioning and innovation of your products and service. They can even lead to disrupting business models and industries. We all know the success story of Amazon, Uber and Airbnb but even midsize enterprises can make a difference and jump the curve when leveraging the right insights to perform the right actions. We like to call them the hidden gems that lie in your data.

“No company is too small not to succeed, no company is too big not to fail.”
 
— Priya Lakhani, Founder & CEO Century Tech

Changing role of the marketer

We believe the role of a marketer will change but won’t become redundant. Actually, we believe the opposite: he or she will become key in a hyper-personalized journey.

Why?

  • As a marketer you are also a customer and you feel delighted about a brand experience were a machine couldn’t care less. Creativity, instinct and emotion drive experiences and this won’t be done by a machine or a robot. A machine manages expectations, a marketer manages feelings.
  • We need both storytellers and analysts who can turn data into narratives. The data should be packed in such a clear way that compelling actions can be drawn from it, understood by everyone.
  • Machine learning. The name says it all: machines learn. Machines are not human beings and don’t possess the values and ethics both you and I have. When there is no real person acting as gatekeeper, it can become tricky when machines take over.
  • A marketer is a spider in a web of different stakeholders. A collaborative mindset and the ability to clearly describe the desired business outcome are skills every marketer of the future should possess.

“Esthetics should include ethics otherwise it’s just cosmetics.”
 
Massimiliano Pogliani, CEO illycafè

 


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