Behavior tracking data is the new black. It is a type of big data that can help you better understand your target consumers — everything from the amount of time they spend on each social media outlet to their most popular time of day to visit shopping websites. Compared with other data sources, it allows you to capture actions at a very detailed level with precision, eliminating measurement errors by analyzing usage of what consumers do, not what they say they do.
In our recent publication, Mobile Behavioral Data: UK, we analyzed Forrester's UK Consumer Technographics® Behavioral Study, November 2013 to March 2014, and found that:
WhatsAppkeeps UK smartphone owners engaged the longest. Forty-one percent of UK adults use the app for just over 8 hours per month (or about 2 hours per week). That is longer user engagement than for any of the other top 10 most popular apps that UK consumers use on their smartphone; this includes Facebook, the most popular app, which keeps smartphone users engaged for a little over 90 minutes per week.
Young UK smartphone owners are most likely to use finance/banking apps. More than half of 18- to 24-year-old UK smartphone owners use finance/banking apps, like the Lloyds Bank app and the NatWest app. These youngsters show the highest adoption of finance/banking apps in the UK, and rates decline with age; about 40% of 25- to 44-year-olds and 34% of 45- to 54-year-olds use finance/banking apps.
When it comes to data technology, are you lost in translation? What's the difference between data federation, virtualization, and data or information-as-a-service? Are columnar databases also relational? Does one use the same or different tools for BAM (Business Activity Monitoring) and for CEP (Complex Event Processing)? These questions are just the tip of the iceberg of a plethora of terms and definitions in the rich and complex world of enterprise data and information. Enterprise application developers, data, and information architects manage multiple challenges on a daily basis already, and the last thing they need to deal with are misunderstandings of the various data technology component definitions.
The tide is turning on privacy. Since the earliest days of the World Wide Web, there has been an increasing sense that the Internet would effectively kill privacy – and in the wake of the NSA PRISM program revelations, that sentiment was stronger than ever. However, by using our Forrester’s Technographics 360 methodology, which blends multiple qualitative and quantitative data sources, we found that attitudes on privacy are evolving: Consumers are beginning to shift from a state of apathy and resignation to caution and empowerment.
China faces a growing air pollution problem — one of the consequences of its significant economic growth over the past two decades. Surrounded by a large number of coal-burning factories in Hebei province, Beijing faces ever-worsening smog. To tackle this problem, city government has implemented new policies and laws, such as the Beijing Air Pollution Control Regulations, that provide guidance to technology vendors developing smog control solutions.
Optimized Energy Management Is The Key To Reducing Air Pollution
Beijing’s government is focusing on air quality monitoring and has invited tech vendors like Baidu, IZP Technologies, and Yonyou to develop solutions. The city wants to show the source of pollutants and how they will disperse across Beijing a couple of days in advance — but that doesn’t do anything to reduce the smog itself. Rather, the key to reducing air pollution is changing how China consumes energy. For example, the government could use big data analytics to:
Optimize factories’ energy consumption. Asset-intensive industries like steel, cement, and chemicals face challenges in analyzing the vast amounts of data generated by energy-monitoring sensors and devices. Tech vendors like Cisco and IBM could leverage their Internet of Things data analysis technology to help customers turn this data into actionable insights. For example, one steel factory in Hebei province is considering technology that identifies when an oxygen furnace is wasting energy because the temperature of the output smoke is too high.
The battle over customer versus internal business processes requirements and priorities has been fought — and the internal processes lost. Game over. Customers are now empowered with mobile devices and ubiquitous cloud-based all-but-unlimited access to information about products, services, and prices. Customer stickiness is extremely difficult to achieve as customers demand instant gratification of their ever changing needs, tastes, and requirements, while switching vendors is just a matter of clicking a few keys on a mobile phone. Forrester calls this phenomenon the age of the customer. The age of the customer elevates business and technology priorities to achieve:
Business agility. Forrester consistently finds one common thread running through the profile of successful organizations — the ability to manage change. In the age of the customer, business agility often equals the ability to adopt, react, and succeed in the midst of an unending fountain of customer driven requirements. Forrester sees agile organizations making decisions differently by embracing a new, more grass-roots-based management approach. Employees down in the trenches, in individual business units, are the ones who are in close touch with customer problems, market shifts, and process inefficiencies. These workers are often in the best position to understand challenges and opportunities and to make decisions to improve the business. It is only when responses to change come from within, from these highly aware and empowered employees, that enterprises become agile, competitive, and successful.
The Eyeo Festival took place in Minneapolis last week. I missed it. I missed it for a very good reason, which is that I just started a new job as a Principal Analyst at Forrester Research. But I still followed from afar, wishing I could hear firsthand about some of the fantastic projects and ideas that get presented there (and I’ll certainly check out the videos as they get posted).
What is the Eyeo Festival, you might be wondering? It’s a small annual conference that “brings together creative coders, data designers, and creators working at the intersection of data, art, and technology for inspiring talks, workshops, labs, and events.” I’ve been to two out of the four conferences and have come away both times incredibly inspired and impressed. This is not just big data. This is big, beautiful, informative data. The coders, designers, and creators both at Eyeo and elsewhere provide living proof that big (and small) data doesn’t have to be ugly, messy, or impossible to understand.
It can have an emotional impact and make a point like this project by Kim Rees and Periscopic, which uses mortality data from the World Health Organization to estimate the number of years lost to gun deaths in 2013 alone.
Big data this, big data that. Hardly a day goes by when we're not bombarded with messages about the big data platforms and technologies that will solve all our marketing problems. Let's be honest though: these tools and technologies alone simply won’t solve the big data challenge. But the effect of all that media and market hype? A lot of confusion and mistrust on the part of marketing leaders about what big data really is, what it can do, and how it should be incorporated into business strategy. And that's holding a lot of firms back from maximizing the power of the data at their disposal.
By now you're asking yourself how anything I've said so far is different or unique. Here it is: "big data" isn't about exabytes or petabytes. It's not about velocity. It's not a project or Hadoop or any other single thing. Big data is a journey that every company must take to close the gap between the data that's available to them, and the business insights they're deriving from that data. This is a definition that business and technology leaders alike can understand and use to better win, serve, and retain customers.
My colleague, Brian Hopkins, and I have just published a pair of reports -- researched and written in parallel -- to help our marketing and technology management clients work together to tackle the opportunities and challenges of big data. Here are a few of the most interesting "a-ha" moments of the research:
Big data is undergoing big change, but most companies are missing it or just grasping at the edges. My colleague Fatemeh Khatibloo and I have just completed an exhaustive study of the big data phenomenon. We found a familiar pattern: business confusion in the face of stern warnings about the dangers of big data and vendor-sponsored papers extolling its benefits. Here’s what we found hidden beneath the buzz:
As data explodes, so do old ways of doing business.
Everywhere we look, we find businesses using more diverse, messier, and larger data sets to stay competitive in the age of the customer — like the consumer goods firm that allocated marketing dollars based on flu trend predictions and the oil and gas companies that used weather data to predict iceberg flows and extend their drilling season. Savvy businesses find ways to turn more data into a competitive advantage. If your firm doesn’t get this, it won’t be pretty — starting in the not too distant future.
Technology managers and architects can’t afford to sit back and think that their Hadoop project will deliver everything the business needs. Nor can you afford to think that big data isn’t for you because you don’t have that much data. Why? Because “big data” is really the practices and technologies that close the gap between the available data and the ability to turn that data into business insight — insight that your firm needs to survive and thrive in the age of the customer. Four things to understand:
BI is no longer a nice-to-have back-office application that counts widgets — it is now used as a key competitive differentiator by all leading organizations. For decades, most of the BI business cases were based on intangible benefits, but these days are over — today 41% of professionals, with knowledge of their firm's business case, base their business case on tangible benefits, like an increased margin or profitability. As a result, BI is front and center of most enterprise agendas, with North American data and analytics technology decision-makers who know their firm's technology budget telling Forrester in 2014 that 15% of their technology management budget will go toward BI-related purchases, initiatives, and projects.
But taking advantage of this trend by deploying a single centralized BI platform is easier said than done at most organizations. Legacy platforms, mergers and acquisitions (M&A), BI embedded into enterprise resource planning (ERP) applications, and organizational silos are just a few reasons why no large organization out there has a single enterprise BI platform. Anecdotal evidence shows that most enterprises have three or more enterprise BI platforms and many more shadow IT BI platforms.
But Avoid Ending Up With A Zoo Of Individual Big Data Solutions
We are beyond the point of struggling over the definition of big data. That doesn’t mean that we've resolved all of the confusion that surrounds the term, but companies today are instead struggling with the question of how to actually get started with big data.
28% of all companies are planning a big data project in 2014.
According to Forrester's Business Technographics™ Global Data And Analytics Survey, 2014, 28% of the more than 1600 responding companies globally are planning a Big Data project this year. More details and how this splits between IT and Business driven projects can be found in our new Forrester Report ‘Reset On Big Data’.
Or join our Forrester Forum For Technology Leaders in London, June 12&13, 2014 to hear and discuss with us directly what Big Data projects your peers are planning, what challenges they are facing and what goals they target to achieve.