Text Analytics: A Key Trend To Watch Over The Next Three Years

Blog post info and actions

Blog post body

Leslie Owens

My colleague Gene Leganza, who serves Enterprise Architecture Professionals, compiled the top 15 technology trends EA should watch over the next three years. He highlights technologies that are new or changing, have the potential for significant impact, and require an IT-led strategy to exploit.

He highlights text analytics technology in the report because understanding unstructured data plays a critical part in daily operations. Enterprises have too much content to review and annotate manually. Text analytics products from vendors like Temis and SAS mine, interpret, and add structure to information to reveal hidden patterns and relationships.  In my 2009 overview of text analytics, I cite the primary use cases for these tools: voice of the customer, competitive intelligence, operations improvements, and compliance and law enforcement.

But there are a few other sweet spots for text analytics tools in the enterprise:

Analytics and search: Analytics tools surface and visualize patterns; search tools return discrete results to match an expressed need. But these disciplines are blending. People want to drill in to high-level analysis to find the specific thing customers buzz about.  And many searchers don’t know how to articulate their need as a query and are looking for the big picture on a topic or trend. Forrester expects these solutions to come together, as search tools mainstream semantic features like entity extraction out of the box, and analytics vendors introduce new ways to investigate relationships and data output.  

Read more

Want To Change Your CRM Game? Push Customer-Facing Processes Into The Social Cloud

Blog post info and actions

Blog post body

James Kobielus

As the year comes to a close, it’s good to put a wrap on it by reviewing all the shifts — both subtle and seismic — that have rocked the world of enterprise architecture (EA). I really enjoyed Gene Leganza’s recent look back — and look ahead — on the top 15 EA technology trends, and not just because he incorporated findings from my recent Empowered reports on social network analysis and analytics-driven engagement in multichannel customer relationship management (CRM).

You can read those Empowered reports to get a deep dive on how those trends evolved in 2010 and what we see on the horizon for 2011 and beyond. Fundamentally, Forrester considers deep customer engagement through social media as a hallmark of the leading-edge customer service operation. A growing range of companies have established social-media-based customer communities for service and support, involving various blends of social media, blogging, and other approaches.

Read more

Use Advanced Analytics To Spotlight People Who Have The Biggest Impact On Customer Satisfaction

Blog post info and actions

Blog post body

James Kobielus

Community is an ideal toward which all social networks should aspire. In a true community, everybody is pulling for everybody else, sharing whatever assistance, expertise, and insight they possess with anybody who might benefit.

We all know that most communities are a bit more one-sided than that. In most communities, most people are essentially there for the ride, contributing little while benefiting from whatever resources the more generous among them have chosen to share. This is not necessarily a criticism of individuals or of society in general, but rather a recognition that as communities scale beyond close personal relationships, the bonds of reciprocity and altruism often grow weak.

This truism applies just as much to customer communities as to any other. Enterprises have avidly adopted social networks as virtual extensions to such customer relationship management (CRM) functions as call centers and user groups. In the new world of social-network customer communities leveraging blogs, Twitter, Facebook, and other channels, it is not uncommon that a handful of individuals post most of the useful content and feedback while the majority simply consume without contributing. And that’s fine, as long as you keep encouraging and incentivizing these actively engaged individuals —whom Forrester refers to as CRM highly empowered and resourceful operatives (HEROes) — to keep the useful content coming. In the final analysis, these are the sorts of individuals — expert customer service professionals, longtime customers, or even highly enthusiastic hobbyists — who can spell all the difference between true community and a haphazard scattering of nominally affiliated strangers.

Read more

Interdictive Analytics: Catching Baddies At The Pass And In The Nick Of Time

Blog post info and actions

Blog post body

James Kobielus

Predictive analytics is not just about forecasting what’s coming down the pike. It’s also about keeping the bad alternative futures from happening. If you can see the nasty things that might happen far enough in advance, you have a better chance of neutralizing or squelching them entirely.

In fact, many real-world applications of predictive analytics are “interdictive,” a term often used in military and law enforcement contexts to refer to tactics that delay, disrupt, or shut down an adversary’s forces or supply routes before they can do damage. Anti-fraud is one of the principal interdictive applications of predictive analytics technology. Companies everywhere rely on data mining to determine who’s been engaging, alone or in groups, in stealing money, supplies, finished goods, cellular airtime, and other valuables — and also where they’re likely to strike next. Likewise, anti-terrorism efforts rely on predictive models to sift through massive collections of historical and real-time intelligence in a Jack Bauer-like race against time and imminent disaster. You best believe that social network analysis is a key weapon in your arsenal for predicting and interdicting these sorts of malignant social patterns.

Read more

Social Media Analytics vs Social Network Analysis: Is There A Real Difference Or Are You Seeing Double?

Blog post info and actions

Blog post body

James Kobielus

As an industry analyst, I’m part of the professional class that delights in defining standard marketplace terminology. More than that, many of us spend our working lives coaxing industry to march under marketing banners aligned with our pet definitions.

Yes, indeed, each analyst likes to feel that his or her marketecture terminology should rule school. Last month I did a Forrester podcast on a topic that’s extremely hot right now: leveraging the power of social media and social networks to manage your brand, drive marketing and sales campaigns, and manage ongoing customer relationships. In that session, I discussed the role of analytics in social media for multichannel customer relationship management (CRM).

My initial impetus for the podcast was to spell out the chief distinctions between two terms that, on first glance, appear almost synonymous: social media analytics and social network analysis. During the podcast I also trucked in another related closely related term—social media monitoring—and even alluded to social intelligence and other phrases that have gained currency.

What follows, for those of you who don’t listen to podcasts, or can’t find them, is the gist of what I said on this topic: 

Read more

Social, Spatial, & Temporal: The Coordinates of Community in the Cloud

Blog post info and actions

Blog post body

James Kobielus

Social networks have their foundations in the space-time continuum—you know, the funky coordinate system  that Einstein was so keen about.

Social network analysis is all about looking for patterns of “proximity” among people, considered in their cultural capacities as influencers and followers, innovators and imitators, first-movers and late adopters. Down deep, I consider social network analysis an important new branch of decision support systems as a discipline. The core question is: What unique situational chemistry causes various people, individually or collectively, to make various decisions at various places and times?

That’s where space and time enter the social network analysis equation. It’s not enough that I look up to your shining example and take my lead from what you say and do. It’s just as important that we be in the same city, neighborhood, or room. More than that, it’s important that you and I actually cross paths in order for you to actively influence me to buy that latte, or for you to calm me down and thereby stop me from storming out the door and severing my relationship with a retailer who has ignored my complaints one time too many.

Read more