Archive for August, 2009

Building a Community, Not a Theatre

Thursday, August 6th, 2009

An unbelievable blog by Dave Evans from ClickZ on the appropriate and more efficient way to interact with your target market and consumers in general. I couldn’t have said it better myself, great blog Dave. Check it out below.

Advertising runs largely on messages created and conveyed much like the story in a Hollywood film: Actors present, and the audience watches. Communities operate more like “The Rocky Horror Picture Show,” involving its audience directly in the experience. Applying this simple analogy to your marketing program offers valuable insights.

Online communities work best — you could argue that they’ll only work — when members have both a reason to engage and do something. Otherwise, the experience is pretty passive, and what is supposed to be a participant sport devolves into a spectator sport. Facebook, Orkut, and high-traffic blogs that accept advertising (are there any that don’t?) can be used quite effectively as display channels. However, a brand that uses these channels only in this way misses out on substantial, deeper opportunities within social networks and social properties. When the campaign does all the talking, you miss out on what the community itself has to offer, and you risk paying too much for professional creative that could have been generated for free. How’s that for a step toward positive return on investment?

The point here is not to reduce agency fees. Creative professionals and account teams who manage an advertising delivery program are an important component of your marketing program. Rather, it’s this: Step beyond canned communities, hip language, and too-cool-to-be-real made-up profiles. Genuinely involve your audience, hand them the ball, and then let them run with it. Let them generate the content instead of paying an agency to do it. You’ll get a lot more from your marketing spend by reducing your own content expenses, tapping your customers for what they love to do anyway, and directing those same dollars back into proper awareness channels or product R&D. Following are some examples that show how to do this right.

Red Bull University: Empowering Student Brand Managers

Red Bull has built itself more or less completely through its association with an active lifestyle and the resultant word-of-mouth generated by a product that works. Anywhere on earth, if two people are competing in a sporting event, chances are high that one of them is sponsored by Red Bull.

To create its street marketing campaigns, Red Bull turns to its fans, empowering its “student brand managers” to promote its product while fully engaged in what they love: sports and active-lifestyle related happenings. Red Bull has created Red Bull University, an online/offline collection of students who learn from each other, developing and sharing effective techniques to further build the Red Bull presence on campus and in the surrounding community.

OK, I know what you’re thinking: “Sure, that’s Red Bull. My brand is not Red Bull.” The Red Bull brand is itself strong enough that a community can be built around it. Starbucks, Nike, and Apple fall into this same group. But what if your brand doesn’t have the same stand-alone conversation value? Lots of great products and services — established brands of toothpaste, hair care, snack foods, veterinary supplies, fasteners (you know, like nuts and bolts), and more can have strong market share in their categories, hold leadership positions, and command shelf space. Yet, by themselves they generate fairly low levels of pure talk. What if your brand is like one of these?

Tropicana: Tapping Women to Promote Better Living

Take a look at Tropicana’s “Juice” campaign, built out on Blogher and promoted through iVillage. The community is not built around orange juice: Where a certain number of fans might associate around a juice-based community (some people will do anything, right?), the real draw is the issues important to women: families, health, and nutrition. These are the kinds of things that a lot of women are interested in because they actually spend time thinking about these topics during the day. Trop 50 rides on this in a well-designed, sensible effort that places the product in a natural context. Where relatively few people will take the time to create a meaningful profile only to post about their favorite juice moments, a whole lot will share ideas on meals, snacks, and nutrition, creating a conversation into which something like the goodness of orange juice naturally flows.

Mitsubishi and Wakesites: Tapping Enthusiasts

Here’s an example that shows the value of customer contributions. When Mitsubishi introduced the Cedia Sports in India, it did it with a campaign built not around the car specifically, but around the passion of driving. Created by Experience Commerce in Mumbai, “The Great Driving Challenge” is a competition involving ordinary people, driving whatever car they happen to own now. They write and post stories, including photos, videos, and similar content about themselves and their love of driving. Winners are determined by a customer-led voting process. Check out the site; the pictures and stories are amazing.

The Great Driving Challenge is now down to 12 finalists, and guess what: Dealer showrooms have a waiting list for test drives. It’s similar to the Wakesites-based campaign created for Slingshot Sports using Friend-to-Friend’s Product Pulse: Artists and wake enthusiasts created designs for next year’s board line. Some 350,000 people viewed the results in Facebook, and their votes established the winning entries.

Building a Community: An Action Plan

I’ll boil it all down to a set of steps:

* Look for the larger human interaction or passion point that encompasses your brand. Generally speaking, you’ll have much better results if you ask people to rally around that instead of your specific product or service.
* Let your customers do the talking. You’ve got TV, radio, print, newspapers, magazines, outdoor, direct mail, end-aisle, keywords, and a Web site. Do you really want — or even need to have — your voice dominating the conversations on the social Web, too? Trust me: you don’t. And besides, you’ll save money.
* Place your message into the conversation that results by participating and adding value. Disclose your presence, and practice transparency.

Taken together, you’ll discover what millions of customers already know: The social Web is about conversations, not monologues.

Different Skills and People for Web Analytics Teams

Tuesday, August 4th, 2009

by Jonathan Marshall

Despite poor economic times, organizations are building out their Web analytics capabilities and teams. It’s a trend that is expected to continue. A number of agencies today are looking to bring on new people. The job market for Web analysts remains reasonably healthy, and in some cases, companies are looking to appoint their first person into a new role. Additionally, some organizations today are looking to expand the team to three of sometimes four people.Neil Mason from ClickZ goes on to talk about the challenges, necessary skills and combinations it takes to make a quality Web Analytics team below.

When organizations build up an analytics team, they encounter an interesting challenge. They must determine the right mix of skills to manage the variety of tasks that a Web analyst team must handle. There are three main competencies that companies must look for: insight generation, data integrity management, and data management and manipulation.

Insight Generation

An analytics team must be able to produce actionable insights that the organization can use to make decisions and drive the business forward. To do this, someone must extract value from investments that have been made in data and technology. This is the Web analyst’s true role. Skills and competencies for insight generation are business orientated rather than technically orientated. In my view, a good Web analyst is an internal SEO consultant with strong data pattern recognition skills, possessing the ability to communicate findings to the business in terms it can understand. Attributes of a good Web analyst include curiosity, a desire to understand why things are the way that they are, and what can be done about it. For me, most analysis is about pattern recognition, the ability to identify trends and associations in the data, and by the same token, things that don’t look right.

Data Integrity Management

Most people don’t like making decisions on dodgy data. It’s vital to get data integrity right. Generating good quality data from a Web analytics system requires continuous management and maintenance, representing another competency required in a Web analytics team. This attribute, which is more technical, requires a different set of competencies and skills than insight generation. Most Web data is collected using page tags these days and most data quality problems stem from data collection issues. Pages aren’t tagged in the first place or the tag is wrong and collects the wrong data or data isn’t collected at all. As an organization’s analytical requirements become more sophisticated, the data integrity issue becomes more complex. Deep-level skills are required to ensure that the right data is being collected in the right way and that the system configuration is right to produce the right databases and reports for insight generation.

Data Management and Manipulation

If organizations are building out their Web analytics team, it probably means that the Web is becoming a more strategic and mainstream channel for them. At the same time, the business wants to know how the digital channel interacts with other channels. As a result, integration becomes more of an issue, so the analytics team needs to have good data integration and management skills. Often, it’s necessary to take data from one system and import it into another or to take data from two or sources and created a new data repository.

Can One Person Do It All?

Can these competencies be found in one person or are different types of people needed in a team? In my experience, it is rare for one person to have all the competencies described here. Someone who has strong insight generation skills may have a good understanding about data integrity issues but is probably not the person best suited to wiring a specification document for tags for a new piece of the site’s functionality. In the same way, someone with good data management skills may not feel comfortable presenting findings to a group of executives. As digital analytical teams grow, organizations must determine more carefully the competencies required on those teams and recruit accordingly.

Image Search Engines

Monday, August 3rd, 2009

by Jonathan Marshall

Today there are major search engines that offer advanced search options based on image, this allows users to filter searches by size, colorization, and file type. Even with this evolution of search technology, there are still limiting issues. According to Julie Batten from ClickZ, until recently, most search engines had focused on alt tags and context surrounding images to categorize and index those images. A user would type in a text query, and the search engine would rank the images based almost exclusively on their relevancy to the keywords contained in the image’s alt text, surrounding body copy, and page metadata. Unfortunately, this has made image search the target of spammers undertaking keyword stuffing or similar black-hat SEO techniques. Batten goes on to talk about image search in her blow below.

New technologies are emerging that will take image search a step further, however. Instead of looking at the text associated with an image, these technologies can effectively scan and “see” what the image is to provide the user with information about it.

The applications of such technology are far reaching, including copyright protection, content moderation, censorship, and forensics investigations. Today, I’ll focus on its application to search specifically. Terms used to describe these advances include “visual search technologies,” “visual cataloguing,” “image recognition,” “image identification,” and “visual content analysis.” No matter what you call them, though, these technologies essentially attempt to do the same thing: decipher the content in an image so that queries can be performed.

Why should you care about all this? I’m sure you’ve experienced one of the following scenarios:

* When you go through your photos from the previous night, you find a picture with a random person in it. You want to find out who that person is.

* You take a picture of something and later notice something cool in the background (a painting, car, gadget, etc.) and want to know where to buy it.

* You vacation abroad and snap a photo of a historic landmark. Later, you can’t remember what the landmark is called.

* You find an image that you want to publish online or in print, but the resolution is too grainy.

The new visual search technology is the solution to all these conundrums. Instead of using text to querying for an image, you can upload a particular image and run a query based on the image’s contents. This is referred to as query by image, rather than query by keyword.

For example, according to LTU Technologies, a leader in visual search technologies, you can upload an image from your computer or the Web and ask its visual cataloging product to show you:

* Images identical to your image

* Variations of the image

* Images similar to the image

* A high-resolution version of the image

The search results will include the images the engine deems to be the most closely matched to your query. If you asked for images identical to your image, the top results would be those that most closely resemble your image’s visual content, which would be followed by images that are very similar but perhaps not exact replicas of the queried image.

In addition, depending on the visual search technology, it is possible to weight queries to emphasize a specific color, shape, or both. Existing engines leveraging such technology include the progressive visual search engine TinEye and the mobile visual search engine SnapTell.

All these technologies will no doubt help searchers more easily retrieve information about existing images or find new images that meet their needs. Image searches will return more relevant results, improving the user experience and satisfaction with this technology.

Let’s consider the implications for marketers for a moment.

Moving forward, we may no longer need to emphasize keyword tagging or contextual placement of images since image analysis can interpret and understand the image without textual content. Any advertiser whose products rely on images to do the selling (e.g., fashion retailers and car manufacturers) stand to benefit from increased visibility, literally, in search engines. You may see more traffic coming to your Web site as a result of the images your site has indexed in these new image search engines.

It is unclear just how much impact these new technologies will have on individuals and businesses, but it is an important trend to be aware of for all those who use search engine marketing strategies.