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

Expert POV: Social Analytics interview (part 2)

Here we are with the second interview on Social Analytics; now with Seth Grimes, surely one of the most influential expert in analytics especially the “Text” ones. A brief introduction with his bio and then let’s read his answers full of interesting information.

He is an analytics strategy consultant. He is founding chair of the Sentiment Analysis Symposium and of the Text Analytics Summit series, contributing editor at TechWeb’s Intelligent Enterprise magazine, and text analytics channel expert for TechTarget’s BeyeNETWORK. Seth founded Washington DC-based Alta Plana Corporation in 1997. He consults, writes, and speaks on information-systems strategy, data management and analysis systems, industry trends, and emerging analytical technologies.

Question 1

One of the main problems that rise with the advent of Social CRM is the huge amount of unstructured data coming from the increasing number of social platforms and applications on the web. In your opinion, which is the better way to manage them for the successive insight and intelligence analyses? Will it be necessary to archive them all or do you think that filtering systems/specific access modality can (must) be applied? What do you think is necessary to pick up the more meaningful information in social data and how?

Seth Grimes

Unstructured sources are not a problem; rather they are a challenge, an opportunity. They contain a vast quantity of business-relevant information. They are the key to getting at the “voice of the customer” in real-time, to engaging with customers and prospects and stakeholder as routine business interactions move online.

Businesses need to find, filter, and harvest social intelligence that will help them further business goals… and ignore all the noise, all the conversations that don’t relate to them. Listening platform, semantic (meaning-based) search, and text and social-network analyses can all help, but you don’t have to do it all yourself. Set up your own systems if you wish, but most business are going to find “as-a-service” solutions to be very attractive. Software as a Service (SaaS) makes getting started easier, faster, and cheaper, and in addition, many of the service providers have already archieved years worth of social and online information.

If you do need direct access to social and online information, you may be able to get what you need from services such as Moreover, Spinn3r, and YellowBrix.

Question 2

During the last ITExpo Symposium 2010, Gartner has identified the 2011 Top 10 Strategic Technologies. Among these there are three that are directly connected to the Analytics world on which I’d like to hear your opinion. Let’s start with the most generic one: Social Analytics (Gartner says: “Social analytics is an umbrella term that includes a number of specialized analysis techniques such as social filtering, social-network analysis, sentiment analysis and social-media analytics”). Which do you think will be the possible developments of these techniques and their main support to the several aspects of Social CRM (advocate/influencer identification, proactive lead generation, etc.)?

Seth Grimes

Gartner’s definition of Social Analytics is a good one… for now, for 2010. The issue is that few businesses exist only socially, really only the social platforms themselves. For every other company — including online vendors such as Amazon, eBay, and Netflix — social-media success is (or should be) measured not by followers and page views but rather by sales conversions. So the challenge becomes linking social mentions and interactions with Web-site/store visits, inquiries, purchases, and customer experience.

Online advocate/influencer identification, lead generation: All good and getting better. But I want and expect to see the term Social Analytics disappear — I want to see the term Social CRM disappear — in favor for general, comprehensive customer/market analytics and CRM where social is just another touchpoint, just another channel.

Question 3

Now, what about Next Generation Analytics (Gartner says: “It is becoming possible to run simulations or models to predict the future outcome, rather than to simply provide backward looking data about past interactions, and to do these predictions in real-time to support each individual business action“)? Which will be the main Social CRM area that will benefit from the use of these predictive techniques, and how? Can you make some practical example?

Seth Grimes

Next-generation analytics (NGA) is comprehensive, pulling data as needed from the full spectrum of touchpoints and sources, including textual and geolocation data. NGA fuses information from these disparate sources, perhaps using semantic data-integration techniques, and it delivers information in flexible form both for self-service, visual analyses, including via mash-ups and for embedded predictive systems.

The underlying Big Data will make for more personalized customer interactions, for better targeted marketing, for customized products and services.

There are a few social-media analytics out there who tout an ability to predict future levels of social conversation. That’s ridiculous and it’s meaningless. I couldn’t tell you what new signer will be hot in 2 years, nor which nascent platform will be the next Twitter.

What we need instead is the ability to read “intent signals” in social messaging: phrases, patterns, and behaviors that suggest that someone is shopping for a product or is dissatisfied with a service and about to change providers. Link those signals to CRM analyses — does the customer have a projected high lifetime value or is he/she a chronic complainer whom we’d just as well not have as a customer? — and there you have true Next Generation Analytics in the service of unified — not just social — Customer Relationship Management.

Question 4

And finally what about Context-Aware Computing (Gartner says: “A contextually aware system anticipates the user’s needs and proactively serves up the most appropriate and customized content, product or service“)? How to really trigger coherent and proactive actions through social insight?

Seth Grimes

If Content is King — and I believe it is — Context is Prime Minister, responsible for the correct interpretation of content, for guiding the appropriate response to those “intent signals” I discussed earlier.

But really context awareness is only a part of a larger need. That larger need is situational computing, which takes into account not only current context but also past history (from behaviors and transactions), profile and identity, and also customer-user interests and preferences. It’s a mistake to blindly treat your community as content/product/service targets. Not everyone wants that. Many people will find Gartner-esque “anticipation” to be invasive, to be downright creepy.

Question 5

Do you believe that there are other important analytics techniques/technologies not considered in the Gartner forecast? If yes, which are and what are their business potentialities in Social CRM?

Seth Grimes

Gartner has long been a market-follower, reporting innovation only when it become established enough to hold some appeal for Gartner’s larger-firm clients. Further, the majority of Gartner’s work is published only to paying clients, and I’m just not convinced that Gartner gets social-media as users. All this is to say that I don’t closely follow Gartner closely and I’m guessing that there surely are important analytics elements not considered in Gartner’s forecast.

Question 6

In you opinion, there are vendors proposing interesting social descriptive and predictive analytical solutions? And how this market will develop in the next few months?

Seth Grimes

I know of a number of vendors in my speciality area, text analytics, that are focusing on those intent signals I discussed: OpenAmplify, Attensity, and Janya for instance. There are a number of other providers with strong (and getting stronger) sentiment analysis, semantic search, and complex data integration capabilities. IBM has one of the broadest set of semantic-social-enterprise analytics solutions, backed by some very deep technologies, and SAP is similarly on the cusp of bringing these forms of analytics to its enterprise customer base. It’s great stuff, with a constant flow of innovation.

Thanks again to Seth and to his valuable contribution. Stay still tuned for the next experts’ POVs and if interested on the topic, have a look at the previous interview with Jim Sterne.

Gartner indica il futuro del Social CRM

Dopo l’uscita dell’ultimo Magic Quadrant sulle suite che a vario titolo possono essere considerate come precursori tecnologici a supporto del Social CRM, la stessa Gartner conferma i suoi convincimenti sull’indispensabilità di ripensare le proprie strategie customer-centric nell’epoca del Social Customer, in occasione del recentissimo Symposium ITExpo 2010 che si è tenuto ad Orlando, pubblicando quelli che per lei sono le Top 10 Strategic Technologies del 2011 (vedere qui). La lista dei suddette tecnologie di frontiera è la seguente:

  • Cloud Computing
  • Mobile Applications and Media Tablets
  • Social Communications and Collaboration
  • Video
  • Next Generation Analytics
  • Social Analytics
  • Context-Aware Computing
  • Storage Class Memory
  • Ubiquitous Computing
  • Fabric-Based Infrastructure and Computers

Come si evince ci sono due categorie ben distinte di previsioni; quelle relative a topic puramente tecnologici e quelle che palesemente si riferiscono ad aspetti squisitamente legati al futuro del Social CRM e alla sua evoluzione in Social Business. Per comodità riporto il dettaglio dei 4 punti che ritengo fondamentali nelle previsioni strategiche di business fatte da Gartner:

Social Communications and Collaboration
Social media can be divided into: (1) Social networking — social profile management products, such as MySpace, Facebook, LinkedIn and Friendster as well as social networking analysis (SNA) technologies that employ algorithms to understand and utilize human relationships for the discovery of people and expertise. (2) Social collaboration — technologies, such as wikis, blogs, instant messaging, collaborative office, and crowdsourcing. (3) Social publishing — technologies that assist communities in pooling individual content into a usable and community accessible content repository such as YouTube and flickr. (4) Social feedback — gaining feedback and opinion from the community on specific items as witnessed on YouTube, flickr, Digg,, and Amazon. Gartner predicts that by 2016, social technologies will be integrated with most business applications. Companies should bring together their social CRM, internal communications and collaboration, and public social site initiatives into a coordinated strategy.

Next Generation Analytics
Increasing compute capabilities of computers including mobile devices along with improving connectivity are enabling a shift in how businesses support operational decisions. It is becoming possible to run simulations or models to predict the future outcome, rather than to simply provide backward looking data about past interactions, and to do these predictions in real-time to support each individual business action. While this may require significant changes to existing operational and business intelligence infrastructure, the potential exists to unlock significant improvements in business results and other success rates.

Social Analytics
Social analytics describes the process of measuring, analyzing and interpreting the results of interactions and associations among people, topics and ideas. These interactions may occur on social software applications used in the workplace, in internally or externally facing communities or on the social web. Social analytics is an umbrella term that includes a number of specialized analysis techniques such as social filtering, social-network analysis, sentiment analysis and social-media analytics. Social network analysis tools are useful for examining social structure and interdependencies as well as the work patterns of individuals, groups or organizations. Social network analysis involves collecting data from multiple sources, identifying relationships, and evaluating the impact, quality or effectiveness of a relationship.

Context-Aware Computing
Context-aware computing centers on the concept of using information about an end user or object’s environment, activities connections and preferences to improve the quality of interaction with that end user. The end user may be a customer, business partner or employee. A contextually aware system anticipates the user’s needs and proactively serves up the most appropriate and customized content, product or service. Gartner predicts that by 2013, more than half of Fortune 500 companies will have context-aware computing initiatives and by 2016, one-third of worldwide mobile consumer marketing will be context-awareness-based.

Come si vede ho sottolineato le dichiarazioni che ritengo più significative di ogni categoria. Da queste emerge in sintesi una previsione globale e sintetica che ci indica la strada della sempre più netta adozione di piattaforme collaborative, che consentano di amplificare le potenzialità relazionali con i vari stakeholder coinvolti nella creazione del valore per il proprio business, e inoltre l’affermazione di nuovi trend analitici che costituiranno l’impalcatura informativa (quello che Esteban Kolsy nel suo modello architetturale di Social CRM ha chiamato Actionable Layer Unit) grazie alla quale sarà possibile agire in maniera proattiva e reattiva (ma in near real-time) agli input provenienti dal social landscape.

La combinazione di questi trend ci consentiranno dunque di elaborare l’unione tra i social data e quelli tipici di utilizzo, transazionali e relazionali (ma su canali tradizionali) al fine di ottimizzare la relazione azienda-cliente nell’ottica di miglioramento continuo dettato dal modello di Continuum Experience.

A tale proposito mi sono dilettato anche a raffigurare qui sotto (cliccate per i dettagli) quale potrebbe essere l’ipotetica architettura che prenderebbe in carico il suddetto processo di miglioramento continuo.

Cosa ne pensate? Potrebbe essere una base di partenza per cominciare a declinare operativamente trend e vision accumulate fino ad oggi?