Marketers have built a temple that needs to be torn down. Demographics have defined the target consumer for more than half a century — poorly. Now, with emerging interest graphs from social networks, behavioral data from search outlets and lifecycle forecasting, we have much better ways of targeting potential customers.
The rise of mass-produced consumer goods also brought the rise of mass-market advertising. In the 1950s and 1960s, the goal of television was to aggregate the most possible eyeballs for advertisers. In order to convince consumers that an advertising message was relevant to them, consumers had to buy the idea that they were just like everyone else.
Marketers created that buy-in by bucketing people into generations. When you lump 78 million people into one group called “Baby Boomers,” it’s much easier to sell them stuff, especially when consumers accepted their generational classification.
But now, that entire system has broken down.
The year that someone was born will not tell you how likely he is to buy your product.
Fragmentation is now the norm because
the pace of change is accelerating. Generations have been getting smaller because there are fewer unifying characteristics of young people today than ever before:
With the recent rise of the social web, people self-select into groups so small, so fragmented, and so temporal, that no overarching top-down approach could be successful at driving marketing performance.
Marketers have responded by adding more demographic information to the mix, but even that is a losing battle. I worked with one client who was introducing a technology product, and had identified a target market of “connected consumers.” Connected consumers were 34-55, had a household income over $120k, and read technology publications regularly. This target market represented 14 million consumers.
They were targeting 14 million consumers to sell 50,000 units — that means they were hoping for 3.5 sales for every 1,000 people with whom they connected through their marketing.
What if, instead, you could get 500 sales from every 1,000 people you marketed to?
It’s possible through psychographic profiling. Psychographics look at the mental model of the consumer in the context of a customer lifecycle. Amazon.com has long been a leader in this space, through innovations like “recommended products” and “users like me also bought.” Its algorithms have learned to predict its users, and what they are interested in. And now, there are a number of tools that any business can use to leverage psychographics.
Here’s how a psychographic profile might look different from a traditional marketing profile target for a childcare provider:
Psychographics provide much more useful information about users. There are multiple data sources making this possible today. Social profile data, behavioral data and customer lifecycle data can now finally be leveraged to contact people who are ready to buy.
Social Profile Data
Profile data from social networks consist of all the fields users grant permission for brands to use on their behalf. Most things that users track on social networks can be leveraged to create a closer relationship with a customer. Fields like relationship status, alma mater, interests and occupation can all be managed through social profile data management tools.
Social profile data is the critical cornerstone of psychographic insights. The level of nuance and insight provided by social data, when compared to standard demographics, is the difference between performing surgery with a scalpel or a butter knife. Previously unimaginable questions are now routine:
- Are customers who kayak more likely to buy water shoes than those who canoe?
- Who is more likely to spend over $100 on an order: Seattle Seahawks fans or Seattle Mariners fans?
- Are your customers more likely to purchase when they move across the state or across the country?
In addition, companies such as
GraphEffect are measuring purchase intent by doing semantic analysis on Facebook status updates. This type of qualitative analysis can move users into specific marketing funnels from their very first online experience with your brand.
Behavioral Data
Retargeting advertising messages is gaining popularity among marketers, but its very success has jeopardized its effectiveness. Ads that follow users around the web have been implemented —
usually poorly. Every ad network quickly incorporated the ability to place cookies in users’ browsers, and display specific ads to them any time they visit a site that’s part of their networks.
The next generation of ad targeting will focus more on telling the customer a story over time, based on specific behavior triggers. That means ad networks and clickstream data aggregators will work together to trigger when a customer moves forward in a mental model toward a purchase event.
Site content and product recommendations will also be informed by clickstream analysis. Companies such as
RichRelevance,
Certona,
Baynote and
Monetate all offer the ability to personalize information to specific visitors based on their behavior. Leveraging those alongside a payload of social profile data can turbocharge those services from the first moment a new user visits a site.
Customer Lifecycle Data
Social profile data can also be used to predict customer lifecycle. Imagine knowing not only if a customer has children, but the exact ages of those children. In addition, key indicator purchases, like buying diapers for the first time, indicate a customer entering a new lifecycle. Other key indicators, like shipping address changes, first purchases of furniture, or first purchases of substantially higher-value goods can all indicate the start of a new customer mentality and behavior pattern.
These patterns are predictable, so you know the future behavior of high school seniors by looking at the current behavior of college freshmen. By using demographics alone, all high school graduates would be marketed to identically. Using psychographics, we know who is likely to be interested in specific product or content recommendations at a specific time — such as when they actually start their first day of college.
This vision is starting to gain traction among serious marketers. At the 2009 Internet Strategy Forum, Xerox’s VP of Interactive Marketing, Duane Schulz, said that a 1% clickthrough rate was a huge failure — even though it is 10 times the industry average. In his mind, a successful campaign would never waste 99% of its impressions. Using psychographic data, you don’t
have to waste any impressions.
We have seen a similar upheaval in marketing before. In the 1960s, marketers who embraced the power of television, broad-based insights into psychology and demographic data created world-class brands and billions of dollars in value. At that time, if you didn’t advertise on TV, you lost. Today’s new tools offer a similar choice: Build a deep understanding of your customer, or risk irrelevance.
Image courtesy of iStockphoto, porcorex
小時候，希望自己快點長大 ✽
In brightest day, in blackest night, how many can come back see green Lantern fight? Warner Bros. is hoping that less-than-stellar reviews and a general unfamiliarity with the ring-bearing protagonist won’t keep moviegoers from packing in to examine the DC Comics superhero fly, fight, and, um, you know, perform general lantern-related activities. There isn’t an incredible amount of competition: The previous super-movie, X-Men: top quality, has settled down somewhat when 2 weeks; Super eight, which could prove to have legs, continues to be solely an economy-sized blockbuster; and the solely alternative major unharness in the week is the decidedly younger-skewing Mr. Popper’s Penguins. therefore let’s see what our foolproof, never incorrect, always dead-on box-office crystal ball* is telling us.
It’s no secret that two of the biggest enhancements in CS5 are the Mercury Engine and the new metadata workflow. What is surprising is how much faster CS5 previews and renders, especially when editing H.264 based formats (like AVCHD or footage from the Canon EOS 7D) or encoding to H.264 formats. This webinar will quantify these performance enhancements using real world projects and detail the optimal CPU, OS, RAM and graphics card configuration. If you produce script-based productions, and value metadata in the production and output pipeline, you’ll really appreciate the script to screen workflow that Adobe created in CS5, including the new Adobe Story, a script development tool, the enhanced Adobe OnLocation, for shot list creation and metadata collection during the shoot, to Premiere Pro for editing and out to Flash. There’s even a new time-based workflow for automatically matching OnLocation placeholder shots with clips shot with a non-tethered camera. In addition, there are several critical new features in Premiere Pro, SoundBooth and Adobe Media Encoder, like the Ultra Chromakey effect from Serious Magic, now a GPU accelerated effect in Premiere Pro. You’ll read a bunch of hype about the new release, this webinar will lay the new features out for you and tell you the investment in hardware and software that you’ll need to fully leverage them. If you’re considering upgrading from CS3 or CS4, you’ll find this 90 minutes very informative and worthwhile.
