Competitive Analysis Tool

Leveraging Big Data for B2B Applications

By | Big Data, Big Data Strategies, Competitive Analysis Tool, Data Asset, Profit, Search Web, Social Web, Uncategorized, Web Crawling | No Comments

Much has been said about the power of digital data as applied to business-to-consumer (B2C) opportunities.  But what about business-to-business (B2B) opportunities?  Are you missing an important opportunity to integrate digital data into your marketing programs?  What are the techniques and methods for accessing and harnessing digital data for bottom-line improvement in B2B organizations?

With a new set of data comes a new dimension in opportunity.  The classic approach to obtaining data is through traditional information service providers.  Most often, the data is compiled from such sources as Yellow Pages®.  The challenge with these sets of data has been timeliness and comprehensiveness.  Now, however, there are new sources available, offering greater and more up-to-date quality, data.  They come in the form of such sources and methods as social networks, web crawling and monitoring, Internet browsing behavior, ad networks / exchanges, and crowdsourcing, to name a few.

New opportunities may be realized through the use of these new digital data assets, such as identifying what companies are in-market for your products and services, as well as identifying key decision makers in the companies important to your marketing efforts, with the budgets to buy your goods.  By obtaining complete and timely digital data, you’ll be better able to augment your marketing programs.

There are a variety of ways to obtain these new sets of data, and best delivery methods can be customized for your specific business needs.

For example, if a company selling cloud computing services wants tofind prospects for its services, Big Data can facilitate their identification and targeting.  Big Data techniques can monitor and analyze enormous volumes of publically-available information sources and glean from them the best prospects for a variety of IT services.  The applications are numerous and can support the following:

  • Discovering new companies in emerging markets based on their network activity
  • Tracking the installation of hardware and software via network usage/installation data
  • Prioritizing key customer accounts based on previously unknown network activity
  • Developing and discovering corporate linkage hierarchies by mapping shared network assets (such as use of a specific e-mail server common to multiple locations)
  • Mapping digital data assets to physical assets using DUNS Number

Clearly, the value of digital data isn’t specific to B2C companies; it certainly extends into the B2B sphere.  The key is in understanding the best ways to collect and use the data resources at your disposal.

Using Social Media to Gather Brand Data

By | Big Data, Big Data Strategies, CMO, Competitive Analysis Tool, Data Asset, Social Web, Uncategorized | No Comments

You need to be where your customers are – that’s an understatement.  With the exploding popularity of leading social media platforms, like Facebook and Twitter, there are a number of conversations taking place that are both directly and indirectly affecting your brand and your company’s reputation.  But how do you insert yourself into the conversation?  What’s the impact of your customers’ social interactions on your brand?  And how does being part of the conversation impact your revenues?

The voice of the customer fuels the power of the brand.

By monitoring the social conversations underway every hour of every day, you can identify your brand’s most passionate customers and energetic detractors across a wide range of social media platforms.  From such extensive monitoring, key learnings can be gained, including how those customers engage with other brands and what motivates and interests them to stay engaged.  These insights, combined with additional demographic data, allow for smarter modeling and analytics.  The more you know about prospects and customers, the better your strategy will be.  Platforms like Facebook and Twitter are conduits to a robust understanding of ways to enhance your brand.

Actionable brand data powers your marketing efforts.

New information from new sources will drive more effective marketing.  In turn, more effective marketing accelerates your organization’s path to additional revenue.  With a clearer and more comprehensive understanding of both your prospects and current customers, you can identify best practices for engagement with your brand on social media outlets, know what motivates your best brand advocates, and integrate the voice of the customer into your brand strategies.  Such steps lead to a more tailored marketing approach, allowing your organization to better reach and engage with key audiences and expand its existing customer base.

The conversations taking place on social media may seem at times to carry little business weight.  However, when closely monitored, they carry key insights about your target audiences and carry the potential to greatly increase your revenue stream.

The Opportunity for CMOs to Exploit “Big Data”

By | Ad Spend, Big Data, Big Data Strategies, CMO, Competitive Analysis Tool, Crowd Sourcing, Innovation, Profit, Search Web, Social Web, Web Crawling | No Comments

Everywhere we turn these days, “Big Data” is top of mind.  For CMOs, the hype of “Big Data” will soon become a reality. When I think about “Big Data” from the CMO perspective, I divide the world by data source:   the Search Web, the Social Web, Web Crawling, and Crowd Sourcing.

Then, for each of the categorical sources of data we, at VDC, are building an inventory of use cases. For the CMO, for example, for the Search Web, the sources of data include both first-party (e.g., Expedia,, etc. ) and third-party sources (BlueKai, eXelate, etc.). When we view these companies as data sources, we can begin to create valuable, often-transformational applications using these new sources of “Big Data.”

For instance, by observing and understanding the quantity and geography of searches over time, we can improve the efficiency of a media buy.  Example:  if I am the CMO of a hotel property and I am a national advertiser using television, I can adjust the timing and targeted market(s) using these new sources of data. In this illustration:

  • If search volume for hotel bookings is currently low in Chicago but high in LA, I can adjust my television ad spend accordingly.
  • If search volume for hotel bookings are off-the-charts high, I can not only optimize my ad spend by market, but I can increase my overall ad spend in those markets that have exceptionally high traffic to capture more share. Another significant benefit: I can also increase my room rates.

Since high search volume is a leading indicator of the future high level of booking, I have an opportunity to set my rates and maximize profits.

In addition to using search data as a leading indicator of future bookings by market, the CMO can also use the data as a competitive analysis tool. This search traffic can further be broken down by brand:

  • How does the directed search volume for my property compare to that for my competitors?
  • How does it breakdown by market?

This data is not only useful for competitive analysis purposes but can be used to adjust the advertising message by market – and to emphasize my brand’s advantages over the competition.

Of course, this approach does not only apply to television, it applies to all targeted media:  direct mail, e-mail, display, mobile, etc.

Think about the power of these new data sources. What better leading indicator of future demand for a product could there be than to understand how consumers are planning to buy the product in the future as represented by their search activity today?  This data surely will transform our marketing processes.

This description represents just one use case of using search data to optimize ad spend and yield superior management strategies. There are many other use cases under development for the search web and there are an equal number of use cases under development for the other “Big Data” sourcing categories:  the Social Web, Web Crawling, and Crowd Sourcing.

While this example was for hotel properties, this same use case applies not only for many other aspects of travel-related services but also applies equally well for an almost endless array of consumer-driven industries:  auto, financial services, healthcare, etc.

This simple example illustrates the transformational power of “Big Data.” The capability to extract these insights from “Big Data” are here today and the practical application of these concepts to address the CMO challenges of today is just around the corner. It is truly a very exciting time for those of us who work in the “Big Data” business.

– Dr. Charles Stryker