The place where the Customer counts

Free thoughts on CRM, Business and the next big thing

The place where the Customer counts - Free thoughts on CRM, Business and the next big thing

“IoE, what’s in it for me?” said the CRM


Recently, lots of new buzz around about the “Internet of Everything” concept and impacts it will have on business and people’s life. And all this buzz is nurtured by big corporations like Cisco which foresees a huge potential on connections between processes, data, things and people (“The Internet of Everything is a $19 trillion global opportunity over the next decade: Private-sector firms can create as much as $14.4 trillion of value while cities, governments and other public-sector organizations can create $4.6 trillion.” – Cisco). With this kind of data, it is impossible to ignore what is happening and how much value will be generated. But first, let’s start with a Wikipedia definition of “Internet of Things” or “where all this stuff began”:

The Internet of Things (IoT) is the network of physical objects or “things” embedded with electronics, software, sensors and connectivity to enable it to achieve greater value and service by exchanging data with the manufacturer, operator and/or other connected devices. Each thing is uniquely identifiable through its embedded computing system but is able to interoperate within the existing Internet infrastructure.

Well, this is only a dimension of the whole story because, in order to exchange “Things” with “Everything”, you need to consider also:

  • People: we just know how new ways of communication have changed our habits through new devices (that introduced and enforced mobility), social applications (that has connected us with companies forcing them to change their customer strategy as social CRM) and, finally, collaborative workspaces (that allow us to create more value in our jobs).
  • Data: we are well aware of how big data and related analytics have given big opportunities to detail and enrich our knowledge and understanding in every aspect of our lives and businesses.
  • Process: digital transformation have just entered into corporates’ life deeply modifying their business models, and process digitalization is one of the main component of this revolution.

Connecting and acting on these four nodes is the starting point of IoE vision implementation and consequent benefits enjoyment. My personal point of view about the IoE building blocks can be summarized by the following image (that I’ll explain in a next post but that is quite self-explaining).


Even if the level of adoption of connected devices is still low (as pointed out by Altimeter in an interesting blog post by Jessica Groopman), companies strongly believe that this is the natural next evolution of internet application, and it is verified by various research analyses and estimates (one for all, the Business Insider Intelligence reportThe Internet of Everything: 2015”)

So what can we expect in the next future? A significant growth on adoption of devices and related economic profit, where the lion’s share goes on IoT.


The interesting point is that early adopters among companies realized that the most important benefit for their business comes from an enhanced customer service level. An improvement realized, probably, thanks to better relation/interaction/engagement with their customers, which allow to collect relevant information about their product/service usage and evaluation.


And looking a little bit further, we also see that companies strongly believe that this adoption will help them to better achieve their business goals, and among them we find the need to improve customer satisfaction through an improved level of engagement.


Obviously, enlarging the perimeter from the IoT to the IoE paradigm the main benefit for business will be an increased and optimized Operational Efficiency (which means to revolutionize internal processes), but immediately after companies confirm the importance of Customer Service as an area strongly affected by this adoption.


And if we want an effective confirmation on the Customer Service importance for business, we can see that even the Manufacturing sector (probably the main IoE early adopter) are practically using IoT ecosystem also to better understand their product usage and consequently fulfil customer expectations.


Finally, just to understand what exactly is happening on the CRM side I suggest to have a look at a post by Steven Van Belleghem where he discusses about the first examples of IoE as a real-time customer service enabler (now it’s really possible). Among other things, he tells about the electric car company Tesla that send their drivers a proactive message 7 days before a problem will occur (with evident advantages in terms of drivers time saving and safety increase) and airline company KLM that trained a special team focused on proactively solving customer problems (i.e. communicating gate changes to passengers).

The message is that people will pretend more and more from companies and the only way to fulfil their expectations is to solve problems before a critical event occurs and the customer becomes aware of it. A scenario where Customer Service, thanks to sensors, devices and connections, is able to endlessly monitor product/service performance and communicate mainly in a outbound logic, distributing proactive solutions.

That’s really fascinating, isn’t it?

Good news for/from CustomerKing

Decisyon logo

A really short post just to announce a good personal news. From October 1, I’m very proud to begin a new professional challenge in Decisyon, one of the most interesting enterprise with an outstanding Collaborative Decision Making & Execution (CDME) platform for rapid development and cloud delivery of operational analytics, planning, in-context collaboration and execution applications.

One of its main solutions, which I followed during the last years considering my interest on customer service evolution, is Decisyon/Engage, a social CRM tool strongly focused on social media analytics, social caring and monitoring which help businesses obtain sustainable competitive edge particularly thanks to the integration between customer data collected from outside and inside corporate boundaries.

And that’s the point for the next future of Social Customer Service, in my opinion. The capability to link data coming from different kind of sources in order to better outline and understand your customers from various perspectives, collaboratively find the best way to satisfy their requests and finally activate/execute the right corporate processes to induce mutual and shared value.

This is one of the biggest challenge Decisyion will face in the next years, thanks to the endorsement of important US Venture Capital firms.

This is one of the biggest challenge for the next social CRM phase.

So, good luck to me and see you soon.

Una piccola introduzione ai sistemi di raccomandazione

Il titolo può sembrare fuorviante ma ciò di cui mi voglio occupare in questo post sono i cosiddetti sistemi di raccomandazione alla base del successo di aziende come Amazon o Netflix. Sistemi che tengono traccia delle preferenze esplicite fornite dagli utenti sui prodotti e che, attraverso l’uso di algoritmi di machine learning, forniscono suggerimenti su nuovi prodotti/servizi che potenzialmente sono di interesse per l’utente. Chissà a quanti di voi sarà capitato di rimanere piacevolmente sorpresi nel constatare che uno specifico suggerimento vi ha indotto a comprare un nuovo prodotto come se qualcuno vi “leggesse nel pensiero”, indovinando i vostri gusti e le vostre preferenze. Eppure dietro a tutto questo non c’è nulla di magico, ma solo l’uso di sofisticate tecniche statistiche che consentono di analizzare approfonditamente le scelte effettuate in passato (acquisto, recensione, voto, ecc.) e le correlazioni tra comportamenti di utenti diversi, con il fine di scovare “affinità nascoste” e quindi prodotti da suggerire più consoni di altri.

Per poter cominciare a capire il funzionamento di questi sistemi, in cui la componente collaborativa è fondante per il successo del business model di aziende come quelle sopra citate, senza impazzire dietro a formule astruse o incomprensibili vi propongo questo breve ebook della O’Reilly (cliccate sul link e dopo la compilazione del form lo potrete scaricare) dove sono accennati alcuni semplici concetti su cui si basano le implementazioni di sistemi del genere.

Practical Machine Learning: Innovations in Recommendation

Practical Machine Learning: Innovations in Recommendation

Se invece avete delle solide basi statistiche e volete approfondire il tema in maniera dettagliata, vi suggerisco di comprare e leggere uno dei manuali più completi in circolazione dal titolo “Recommender Systems: An Introduction“, cominciando magari a scaricare gratuitamente le slide riepilogative dei capitoli dello stesso libro.

Buona lettura e buon divertimento.