Originally posted on Destination CRM by Jamie Grenney
Internet forecaster Mary Meeker has produced a report on Internet trends for almost 20 years, and it never fails to uncover valuable insights on the current state of technology. Her latest report includes many observations about the worlds of mobile, data, advertising, and more.
The biggest trend in the just-released report is the massive increase in mobile and sensor-based devices, and in the data produced by them. Meeker found that shipments of sensors for wearables, phones, tablets, etc., have grown by 32 percent year-over-year, up to 8 billion in 2013. And mobile data traffic is increasing at an annual rate of 81 percent, although smartphones still only represent 30 percent of the 5.2 billion mobile phones in use.
What can marketers learn from this big-picture view? With today’s shift from print and desktop to all things mobile, forward-thinking marketers should be looking for ways to make sense of all the untapped signals available to them. Three types of up-and-coming data we should be thinking about are:
- Public. Behavioral signals about individual consumers are all around us. These can be found in various places on the Web, such as Instagram, Twitter, or Pinterest—where people have pinned a mind-boggling 30 billion items to date. Companies and other types of organizations leave similar footprints via updates to their Web sites, posts to social channels, and public filings.
- Private. Even more interesting signals live in places such as branded mobile apps (e.g., Starbucks or Uber) or in sensors and other machines. If your business collects any machine-generated data, you should be thinking about every possible way you can eke value from that information. As an example, Fitbit tracked 2.4 trillion steps last year.
- Brokered. A third type of signal might come from data providers that collect data and resell it. This data might come from the physical world (think satellite images and foot traffic) or the virtual world (think cookied users and Web crawling). It could also be data that users opt-in to share as part of a term of service.
Re-imagining products in a data-driven world is one facet of this transformation, but the landscape for marketers is also changing. If you can aggregate relevant data sources and identify patterns from there, there is an opportunity to eliminate a huge amount of dead weight from your activities. Marketers can accomplish this by:
- Sourcing new leads. The most efficient leads are warm leads that land on your doorstep. But what if you could use data to spot good leads, or better yet, their buying intent, before they even reach your Web site? For example, there are networks of media sites that collect IP information and can tell you who, or at least what companies, are reading what articles. Given the topics of that content, you might be able to infer whether they have an active initiative related to your product.
- Leveraging predictive lead scoring. With the rise of content marketing, online advertising, and freemium products, companies have considerably more top-of-the-funnel leads than ever. Forward-thinking marketers are tapping into external data to predict which are a fit for their product and which to route to nurture.
- Continuously personalizing. In the past, personalization was based upon what a customer told you at a given point in time. Going forward, personalization is going to be about monitoring behavior and predicting the right message at the right time. While we’re still at the nascent stages, companies have begun to serve up personalized content based upon IP, cookies, and marketing automation data.
The digital universe of data is growing rapidly and expected to reach 13 zettabytes by 2016, according to IDC. And while 34 percent of the data we’re creating is useful, only 1 percent is being analyzed today. That means marketers are sitting on a treasure trove of intelligence they’ll need to excavate in order to compete.
In this new era, companies must be vicious about acquiring data and partnering with experts that have the machine learning prowess needed to enable truly data-driven marketing decisions.