Archive for big data

Gilbane Advisor 4-25-18 — deep learning value, martech size, no-click searches

Notes from the AI frontier: Applications and value of deep learning

In 2011 as the excitement about Big Data was becoming mainstream, McKinsey published what was the most useful early report for executives. Big data: The next frontier for innovation, competition, and productivity, took a smart and measured look at use cases and value across industries. Given the symbiotic relationship between data and AI / machine learning, companies who were paying attention and invested in Big Data then are likely positioned well ahead of others to benefit from today’s advances in machine learning technologies and techniques.

AI performance improvement by industry

McKinsey’s new report provides a knowledgeable overview using accurate terminology in their “… analysis of more than 400 use cases across 19 industries and nine business functions highlights the broad use and significant economic potential of advanced AI techniques.” Highly recommended. Read More

A flaw-by-flaw guide to Facebook’s new GDPR privacy changes

Josh Constine provides a useful take on the changes rolling out now to European users illustrated with screen shots. But I think it’s safe to say that whether they are meeting the “letter of the GDPR law” is still a matter for debate.

Overall, it seems like Facebook is complying with the letter of GDPR law, but with questionable spirit…Facebook struck the right balance in some places here. But the subtly pushy designs seem intended to steer people away from changing their defaults. Read More

Marketing Technology Landscape Supergraphic (2018)

Scott Brinker has just released the latest update to his famous “Supergraphic”. The number of marketing technology vendors continues to grow. As Scott puts it, “Water continues to flow into the martech tub faster than it’s draining out.” Check out his post on what it all means and to see/download the graphic and a spreadsheet. Read More

Uh oh, click counts count less

Click quality and measurement has always been a bit iffy. But the biggest challenge to click value yet may come from a combination of mobile trends and Google’s strategy of reducing the need to click away from the search results page. Rand Fishkin’s post, New Data: How Google’s Organic & Paid CTRs Have Changed 2015-2018, looks at some interesting numbers. Back to brand marketing banners?
No-click searches desktop vs mobile

Ultimately, I think this data shows us that the future of SEO will have to account for influencing searchers without earning a click, or even knowing that a search happened. That’s going to be very frustrating for a lot of organizations. Read More

Also…

The Gilbane Advisor curates content for content, computing, and digital experience professionals. We focus on strategic technologies. We publish more or less twice a month except for August and December. See all issues

Why Big Data is important to Gilbane Conference attendees

If you think there is too much hype, and gratuitous use of the term, big data, you haven’t seen anything yet. But don’t make the mistake of confusing the hype with how fundamental and how transformational big data is and will certainly be. Just turn your hype filter to high and learn enough about it to make your own judgements about how it will affect your business and whether it is something you need to do something about now, or monitor for future planning.

As I said yesterday in a comment on a post by Sybase CTO Irfan Khan Gartner dead wrong about big data hype cycle (with a response from Gartner):

However Gartner’s Hype Cycle is interpreted I think it is safe to say that most, including many analysts, underestimate how fundamental and how far-reaching big data will be. How rapidly its use will evolve, and in which applications and industries first, is a more difficult and interesting discussion. The twin brakes of a shortage of qualified data scientist skills and the costs and complexities of IT infrastructure changes will surely slow things down and cause disillusionment. On the other hand we have all been surprised by how fast some other fundamental changes have ramped up, and BDaaS (Big Data as a Service) will certainly help accelerate things. There is also a lot more big data development and deployment activity going on than many realize – it is a competitive advantage after all.

There is also a third “brake” which is all the uncertainty around privacy issues. There is already a lot of consumer data that is not being fully used because of fear of customer backlash or new regulation and, one hopes, because of a degree of respect for consumer’s privacy.

Rob Rose expanded on some specific concerns of marketers in a recent post Big Data & Marketing – It’s A Trap!, including the lack of resources for interpreting even the current mostly website analytics data marketers already have. It’s true, and not just for smaller companies. In addition there are at least four requirements for making big data analytics accessible to marketers that are largely beyond the reach of most current organizations.

Partly to the rescue is Big Data as a Service BDaaS (one of the more fun-sounding acronyms). BDaaS is going to be a huge business. All the big technology infrastructure firms are getting involved and all the analytics vendors will all have cloud and big data services. There are also many new companies including some surprises. For example, after developing its own Hadoop-based big data analytics expertise Sears created subsidiary MetaScale to provide BDaaS to other enterprises. Ajay Agarwal from Bain Capital Ventures predicts that the confluence of big data and marketing will lead to several new multi-billion dollar companies and I think he is right.

But while big data is important for the marketers, content managers, and IT who attend our conference because of the potential for enhanced predictive analytics and content marketing. The reach and value of big data applications is far broader than marketing – executives need to understand the potential for new efficiencies, products and businesses. The well-known McKinsey report “Big Data: The Next Frontier for Innovation, Competition, and Productivity” (free) is a good place to start. If you are in the information business I focus on that in my report Big-Data: Big Deal or Just Big Buzz? (not free).

Big data presentations at Gilbane Boston

This year we have six presentations on big data, two devoted to big data and marketing and all chosen with an eye towards the needs of our audience of marketers, content strategists, and IT. You can find out more about these presentations, including their date and time on the conference program.

Keynote

Bill Simmons, CTO, DataXu
Why Marketing Needs Big Data

Main Conference Presentations

Tony Jewitt, VP Big Data Solutions at Avalon Consulting, LLC
“Big Data” 101 for Business

Bryan Bell, Vice President, Enterprise Solutions, Expert System
Semantics and the Big Data Opportunity

Brian Courtney, General Manager of Operations Data Management, GE Intelligent Platforms
Leveraging Big Data Analytics

Darren Guarnaccia, Senior VP, Product Marketing, Sitecore
Big Data: What’s the Promise and Reality for Marketers?

Stefan Andreasen, Founder and Chief Technology Officer, Kapow Software
Big Data: Black Hole or Strategic Value?

Update: There is now a video of me being interviewed on big data by CMS-Connected.

What technologies is marketing spending on?

Spencer Ante reports in today’s Wall Street Journal that As Economy Cools, IBM Furthers Focus on Marketers. The title and the short article are focused on IBM’s well-known emphasis on marketers, but the article is of more general interest in driving home the extent of one trend in corporate technology spending – the growth of marketing spending on technology – and provoking a number of questions about what it means. At only 600 or so words the article may be useful for some of you to forward to others in your organization that would benefit by thinking more about the effects of this trend.

The article quotes some recent Gartner research that marketing budgets are roughly 3 times IT budgets as a percentage of revenue, and grew between 2011 and 2012 while IT budgets shrank. Current marketing and IT budgets are both expected to increase, but with marketing budgets increasing at twice the rate of IT budgets – 9.0% vs 4.7%. Gartner has also predicted CMOs will have more control over technology spending than CIOs by 2017. Also, “In total, Gartner says companies spent up to $25 billion worldwide on marketing software last year, up from about $20 billion the previous year. Overall corporate software expenditures totaled $115 billion…”. These are impressive numbers, and our own experience based on discussions with our conference attendees, consulting clients, and other analysts and investors, suggests a broad consensus with the trend. Certainly IBM is big believer.

But the next level of detail is even more important for technology vendors and all CMOs who want to benchmark their competitors spending and strategies – for example, what are CMOs spending money on? what should they be spending on” and how do they organize their infrastructure to learn about, purchase, and manage new marketing technologies, and work with IT?

A vocal segment of the technology press suggest that the future of marketing is all about “social”. A favorite prediction of analysts is that the “Web is dead” and the future is all about mobile. Savvy marketers are beyond such oversimplifications. As important as social and mobile are, I think it is safe to say they are still a small percentage of the $25 billion Gartner number. I would love to be enlightened by anyone who has more details on what the percentage is, and what technology categories others think will benefit most from the increase in marketing spending.

Why is this?

Part of the reason are expensive legacy systems and infrastructures. But a bigger reason is that everyone (not just marketing) is learning. Most of the new technologies have some learning curve, but are not rocket science. The really steep curve is learning how to integrate and utilize new technologies, and especially data they provide, effectively – and that is something we all: technologists, marketers, analysts, will be learning about for awhile.

Learn more at Gilbane Boston.

Marketing, big data, and content

“Content” in this context means unstructured data. The need to manage unstructured data is one of the main reasons big data technologies exist – the other being the need for dealing with scale and speed. This is why it is important for us to cover at our conferences. Not every company needs to build new infrastructures around Hadoop-like technologies… yet. But marketers need to manage the mostly unstructured content that is part of their world, and also process and manage the more structured analytic data that will rapidly become “big” for even small organizations, so big data technologies need to be on marketing organizations’ radar as they continue to increase their expertise and spending on technology. See yesterday’s post on Why marketing is the next big money sector in technology.

Endeca Now Integrates Hadoop

Endeca Technologies, Inc., an agile information management software company, announced native integration of Endeca Latitude with Apache Hadoop. Endeca Latitude, based on the Endeca MDEX hybrid search-analytical database, is uniquely suited to unlock the power of Apache Hadoop. Apache Hadoop is strong at manipulating semi-structured data, which is a challenge for traditional relational databases. This combination provides flexibility and agility in combining diverse and changing data, and performance in analyzing that data. Enabling Agile BI requires a complete data-driven solution that unites integration, exploration and analysis from source data through end-user access that can adapt to changing data, changing data sources, and changing user needs. Solutions that require extensive pre-knowledge of data models and end-user needs fail to meet the agility requirement. The united Endeca Latitude and Apache Hadoop solution minimizes data modeling, cleansing, and conforming of data prior to unlocking the value of Big Data for end-users. http://www.endeca.com/ http://hadoop.apache.org/