Transforming Unstructured Data into Market Intelligence: An interview with WiseWindow

At the end of last year, I sat down with my good friend and former colleague Marshall Toplansky to talk about how he is driving marketing innovation at WiseWindow- a company that he helped found and now runs as President.   WiseWindow is a company that is taking the unstructured data found on the Internet and social media and turning that into streams of useful data that marketers can use to track customer attitudes around brand and brand attributes.

You will find excerpts from the interview in the video clip below.  We talk about the evolution of sentiment analysis, how WiseWindow is driving innovation in this area(7:45),  and the benefits that accrue to companies that have chosen to innovate using his technology(12:30).

My core insights from our discussion included the following:

• Sentiment analysis is rapidly gaining acceptance as an alternative/supplement  to traditional methods of measuring consumer attitudes including voice of customer, customer satisfaction, and net promoter score.

• In many ways, sentiment analysis is superior because it can account for a much larger population sample on a broader array of topics than traditional methods and do it continuously.  This creates the ability to track the changes in attitudes based on tactics that a company might employ to improve positioning in the marketplace.   In short, the fact that sentiment analysis  is orders of magnitude faster and cheaper, is leading to new paradigms in terms of how companies can track sentiment nearly real time and then focus resources to respond.

• Related to the point above, the predictive power of sentiment analysis is unleashed when companies are able to find relationships between customer attitudes and business performance.

• WiseWindow is driving innovation in this area by using pattern recognition technology to address the fact that different word combinations reflect different sentiments depending on the  context in which  a company operates. In sum, it is using web crawling technology in conjunction with natural language processing algorithms to not only track what people are saying about its clients, but also what they are saying about the specific attributes of the products, brands, and competitors.

• While financial services businesses have been early adopters of this technology, successful case studies are emerging in media and entertainment, autos, and election tracking.

For access to the full interview (a little over 60 minutes) I have included a podcast version of the talk.  Enjoy!

Transforming Unstructured Data into Market Intelligence: An Interview with WiseWindow

 

Video from Wharton San Diego Panel Discussion on Analytics

Wanted to finally post the video from a panel discussion I hosted a few months back onto my site.  Great discussion and stellar panelists.  I will update this post on my key takeaways, as well as create a short form of the talk with highlights, but for now, here is the full-length, unproduced video.

It’s been a while since I have had time to do much on the blog- have been spending the last few months ramping up new clients and also working on a new initiative that I will be launching next year.   Stay tuned, there is more interesting and exciting stuff on the way…

Software Eating Your World? Would You Like a Byte?

Last week, Marc Andreessen published an essay in the Wall Street Journal entitled “Why Software is Eating the World”.   A particular passage resonated with me:

‘Companies in every industry need to assume that a software revolution is coming. …new software ideas will result in the rise of new Silicon Valley-style start-ups that invade existing industries with impunity. Over the next 10 years, the battles between incumbents and software-powered insurgents will be epic.”

Since we are all going to be software companies (eat or be eaten), I think it is important to understand how/where value creation is shifting within the software industry itself. In short it is a tale of migration from features and functions to data – a trend which many of the enterprise software companies I work with see and understand, but are slow to adapt to- primarily because it is a trend highly disruptive to their existing business models.

To examine this shift, let’s look at how software has evolved over time.

Software as Tools

The first business applications were ones that helped individuals do tasks more effectively.  Remember Lotus 1-2-3? Wordstar?  In short, for roughly the first decade of the PC era, software was primarily a tool that you used to make some individual function/task more efficient to complete.  Software was an interface that allowed us to leverage the rapid advancements in computing power and get the work all of us were doing anyway, get done faster.

Software as a Repository of Best Practice

From point solutions that streamlined highly generic tasks, vendors began to create value (and charge for this value via licensing and services) by embedding specific business process knowledge into applications.  People could move down the learning curve more quickly and be managed more effectively by having them operate in a well defined and highly customized software environment.  Software became a way of capturing and propagating best practice within an enterprise and something that became critical in very specific functional areas of enterprises. CRM was an early example of this, integrated ERP (HR, financial accounting processes, inventory management, payroll) systems followed quickly thereafter.  The economics of SaaS/PaaS are generating a proliferation of these models across every industry vertical/ functional process imaginable.  All of these applications create standard work process and control mechanisms that drive productivity and consistency.

Software as a Communication Medium

As the various parts of a business process started to be connected, and common standards for connectivity (e.g., XML) evolved, communication/collaboration has become a central function integrated into applications.  Indeed, communication has given rise to a new value creation mechanism for software- transaction platforms.  Ebay? Paypal? Skype? They didn’t make money by selling software licenses- rather they made platforms for communication, collaboration and validation that allowed them to make money on the transactions that they brokered.

Software as a Data Collection Mechanism

So now we arrive at data.

Is Zynga a game or a data collection mechanism? Google search engine or data-based advertising platform?  Facebook communication tool or targeted marketing platform?

We now have access to literally millions of useful applications at little to no cost.  To be sure it is cheaper to create them, but firms are finding new ways to offer subsidized or free software because of the data they hope to compile through widespread distribution of their products.  Software has become a data collection mechanism and analytic competitors are hoarding data and learning how to make these data streams  useful to refine their own businesses and create value for others.

One thing is clear.  Across all of the disruptive models that have dominated “bubble 2.0”, none have involved licensing fees.  Indeed, the primary source of value that Mr. “no bubble here” Andreessen is so confident in is data.  The extent to which his investments will pan out will depend on whether they will be able to meaningfully realize value in the petabytes that his firms control.

What it all means?

If you are building a software product, you need to incorporate all of the means of generating value that I reference above.  Doing so not only maximizes value for your users, but provides you with flexibility to morph your business model for the future.

As you build, expect that at some point soon you will face someone willing to be highly disruptive that will be seeking to generate profits through business models that are vastly different to your own.

Recognize that value is shifting towards data and that to win, you had better become great at collecting, managing, analyzing, and MONETIZING all of the data streams that you control.

So  if you are in a business that charges fees for software licenses, or a platform that makes fees on transactions and have no vision or plan for how you will monetize the data you control, welcome to a decade of pain.  The “Silicon Valley-style” startups that Mr. Andreessen is funding are coming to eat your world.

Stay tuned for more on data and analytics- if you are in/around San Diego,  and interested in the topic, be sure to check out an event I am moderating on 9/13.