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Another new player in the field of behavioral
analytics and profiling targeting is the data cooperative, aCerno.com which acts as a clearinghouse for retailers
to share anonymous cookies for tracking and reporting on consumers shopping activities. The aCerno clearinghouse,
for example would allow one retailer to contribute purchasing information, such as a cookie associated to the sale of a lawn
mower, alerting another co-op member to instantly pitch an ad for say gardening supplies. The aCerno cookie
clearinghouse is an effort to network the shopping behaviors of thousands of consumers among online retailers.
Akamai recently
acquired Acerno for $95 million. Another new firm
33Across.com is looking at behavioral analytics for its targeting based on social media in order to find
influencers in specific product areas. The firm is so named because it targets the influential one-third
(33 percent) of ‘influencers’ across the web in the increasingly social Web. 33Across is an
agency which is exclusively focusing not simply on where people are and what they're doing on the Web, which has been
the model of most ad networks, but also where they sit in their "social graph." This social-relationship
data is critical in understanding the spread of viral marketing by word of mouth (WOM). 33Across is focused
on marketing and advertising along a social dimension and targeting and “engaging influencers.” This
agency clearly is based on the social networking marketing model. Still another company is Mindset-Media.com which
is taking another approach – it uses a combination of over 100,000 75-question personality surveys along with behavioral
analytics techniques to allow marketers to target consumers based on affinities like leadership, spontaneity, altruism, etc.,
in all twenty different personality bucket clusters with a minimum of two million consumers will be assembled by their Mindest
Media interactive affinities surveys. Clearly the field of behavior analytics is a fast evolving one with
new data aggregators, networks, services and software.
 Psychographics profiles for behavioral analytics Every Internet IP address can be traced back via servers, routers,
Internet Service Providers (ISP) and the like – enabling advertisers and marketers to know where consumers are originating
from. Geolocation is the process of pinpointing a browser’s physical location via their IP address;
this can be very specific down to the latitude and longitude of a consumer's home. Geolocation coupled with offline demographics
can be combined to enrich the behavioral data marketers and enterprises may have – all in an effort to make real time
segmentation and the positioning of specific product and services based on similar features of consumers. As
was mentioned in the earlier section NebuAd.com is partnering with several large ISP to track users across
all their Web activities. The objective – as with
ad networks is to create consumer clusters – in order to target relevant offers to consumers. Geolocation is determined by a user's IP
address, and this information can be culled over for behavioral analytics along with other consumer information. Each Internet
user, no matter how they connect to the Internet, is given an IP address by their Internet service provider. This identifies
them as they surf the Web, check their e-mail or talk on any number of instant messenger programs, this is how local ads get
placed. Every move online
can be traced back to that particular IP address broken down into a specific geographical location. Geolocation can assist marketers
and enterprises in knowing where revenue producing consumers are coming from, which may impact how and what ads and offers
to make. Some of geolocation service providers include the following firms: Quova.com offers its GeoPoint service, which provides geographic information
for IP addresses including continent, country, region (US only), time zone, state, city, postal code, longitude/latitude and
phone prefix (US and Canada only). Quova also provide demographic identifiers for IP addresses within the United States including
DMA codes (Nielsen Designated Market Areas) these Designated Market Area (DMA) are a group of counties in the United States
that are covered by a specific group of television stations. Finally, Quova provides network connection information for IP
addresses, including connection type and speed. Digital Envoy and their Digital Element service delivers
IP intelligence and geotargeting which is used by most of the world’s largest ad networks and publishers for non-invasive
IP intelligence for targeted advertising, content localization, geographic rights management,
behavioral analytics and local search. Digital Envoy argues that their IP Intelligence service guarantees
consumer privacy since it was designed to respect the privacy of the individual and
contains information collected solely from a user’s IP address, and that privacy-invasive techniques such as alien probes,
cookies and intrusive scripts are never used in their data collection methodology. Smaller geolocation
providers include GeoBytes.com and MaxMind.com enabling marketers to leverage this technology to clients
not requiring large investments for this type of service. Other methods by which consumers can be clustered
is along keywords used in arriving at a website, these keywords are readily available from log analyzer tools, such as WebTrends
or Google Analytics. One valuable technique is to match existing visitor behaviors to
the search terms they've used to gain an understanding of where they are in the shopping and comparison cycle. Then, the
marketer and enterprise can apply that knowledge going forward by providing content that is particularly useful in moving
consumers along the sales continuum. Still another method
of grouping consumers is by frequency and interval behavior, often sales are not made by first time visitors, especially for
high price services and products. Often the second and third time visitors are the most profitable. Knowing
how many visits it takes to convert and conclude a sale is something metrics can tell the marketer and enterprise.
Surveys are yet another mechanism by which to group consumers for example, asking if they found a product or service
somewhat technical, by doing so the marketer and enterprise can gauge the skill levels of consumers and the appropriate dialogue. All of these consumer clustering techniques should be tested
and validated continuously, the metrics should not only provide number of visitors but more importantly conversion rates to
actual sales – that is the bottom line to behavioral analytics. There are commercial lifestyle data providers that can provide real-time demographic
streams to enterprises. These lifestyle demographics products can be used by enterprises to increase their
customer growth, loyalty and satisfaction. An advertising network or ad network is a firm that connects
web sites that want to host advertisements with advertisers who want to run advertisements. Increasingly ad networks are companies
that pay software developers as well as web sites money for allowing their ads to be shown when people use their software
or visit their sites. Increasingly behavioral or contextual networks are replacing the standard first generation ad networks,
these new networks focus on specific targeting technologies. Behavioral targeted networks specialize in
using consumer click stream data to enhance the value of the inventory they purchase. One of the most successful of these
behavioral ad networks is AOL’s Tacoda.
 A list of the website that are part of the Tacoda ad network
The following is a listing of various types
of ad networks: Primarily Cost Per Thousand
Views (CPM) Based Ad Networks Primarily Cost Per Acquisition (CPA)/Cost Per Lead (CPL) Ad Networks Primarily Cost Per Click (CPC) AND/OR Text Based/Contextual Ad Networks “Non-Standard”
Ad Networks (PopUps, Expandables, Pay Per Post, etc.) Specific Demographic Ad Networks NON-US
Primarily CPM Based Ad Networks NON-US Primarily CPC AND/OR Text Based/Contextual Ad Networks NON-US Primarily CPA/CPL Ad Networks
Marketers can sign up clients or partner with these various types of ad network to place their advertisements in
search engines, websites and mobile devices to drive traffic to its client’s site for behavioral analytics.
The ad network serves the advertisements from its servers, which responds to a site once a page is called.
A snippet of code is called from the ad server that represents the advertisement on a network of websites, RSS feeds,
blogs, instant messages, emails and other digital marketing sources and devices. There
are two levels of ad networks: first-tier and second-tier networks. First-tier networks have high volumes
of quality traffic, and include most of the major search engines, while the second-tier networks have some of their own advertisers
and publishers. These ad networks allow the creation and delivery to market segments that are customized
to the topics required by ad campaigns of publishers, advertisers and mobile providers. A new type of ad network
is Fetchback.com who calls itself the retargeting company they use a patent-pending
method to deliver targeted messages to visitors who’ve left a web site via an ad network. A one-line
piece of FetchBack code is added to subscriber websites. Visitors receive an anonymous cookie containing no personal information
whatsoever allowing the FetchBack networks to uniquely identify them anonymously, which is what behavioral analytics is about. There are also targeted ad networks, which focus on contextual content along specific
market sectors or consumer interests for the placement of their ads. There are over twenty-five contextual
ad networks to choose from, some of which are very narrow in their scope. These industry-specific networks
are also known as synthetic channels, each focusing on a single topic and are essentially virtual portals aimed at consumers
with very specific values, needs and preferences. In any event, whether targeted, first or second tier and now mobile – ad
networks are another conduit marketers can leverage and execute as part of their overall behavioral analytics strategy for
their clients. At the height of the dot.com era a new technology evolved from
the MIT AI Labs known as ‘collaborative filtering’ for driving recommendation engines. The
technology was designed to recommend products and/or services online to an individual based on the preferences of many users
with similar preferences and behaviors.
 The recommendation engine marketing cycle Recommendation engines can be leverage for behavioral analytics by using the concept of “mob targeting”
which involves the intersection of word of mouth, social media and influences of groups of consumers as the key to product
placement to drive brand response. The core technology of these recommendation engines is also referred
to as “expert mentality” and can be seen in action at Amazon.com with its “Customers Who
Bought This Item Also Bought…” as well as “Movies for You” at Netflix.com.The
technology relies on the actions of many users to determine what to recommend to an individual: ‘if you liked this,
chances are you will also like this.’ The
technology with variations is used by many merchants including Amazon, Barnes and Noble, Hollywood Video, Netflix, TiVo, etc.
These merchants use their own proprietary software; others use commercial recommendation engines and networks
such as the following: Lotame.com
uses
what it calls “Crowd Control Technology” to capture the most engaged users based on verbs such as blogging, uploading
videos, commenting, posting pictures, etc, for social behavioral analytics without using any personal identification information.
Lotame has cobbled together a social network of sites that aren't Facebook or MySpace, but that combined to give
clients a reach of 53 million users. Lotame
also provides an “End of Campaign Report” to clients with detailed summaries of the marketing results via a video format
and a written report to help the client understand the strengths and segments identified as well as the areas in need of further
improvement and refinement.
 Verbs of actions are used by Lotame to make recommendations Atg.com formerly CleverSet provides a complete commerce suite which incorporates a recommendation engine. To
help business clients dynamically entice customers with a personalized shopping experience and relevant merchandise they're most likely to want at
just the right time. Marketers and merchandisers have real-time control over the Web tools needed to quickly move inventory
out the door and strengthen their brand. Avail.net offers recommendations via its eMarketing Suite which is comprised of the following integrated
e-marketing modules: 1. Navigation Predictor™ utilizes ‘collective intelligence’
to automatically generate real-time recommendations for those products that are most relevant for each customer.
2. Social Search Optimizer utilizes collective intelligence by recommending
the search results that most probably appeal to the customer, based on a search word or phrase on the searched page.
3. Landing Page Optimizer™ uses collective intelligence to personalize
the contents of a website based on the search word that the visitor used with, for example, Google or any other external search
engine to find their way to your site.
4. Customer Interaction Broker™ utilizes collective intelligence to enable
your customers to help each other discover, become acquainted with and use your products.
5. Collaborative Searcher™ gives your eCommerce site visitors an intelligent
way of searching, discovering, navigating and being recommended products – faster and more relevant
– resulting on immediate and measurable contributions to conversion rates and average order values.
Avail also offers recommendations via its ASP/Web
Service, the cost of the service is a performance based monthly fee related to the actual improvement to sales that they generate
to subscribers via the ASP service.
ChoiceStream.com is yet another recommendation network, whose customers include
Overstock, Yahoo, AT&T, DirecTV, etc. Some success has been achieved by collaborative filtering engines
especially in the areas of consumer products, such as entertainment, music and books. Recommendation engines
can also increase the search experience and relevance in both the digital media and in how customers find products and services
and how they navigate via external search engines. When introduced over
a decade ago the collaborative filtering technology suffered from scalability problems but today’s software and networks
have overcome that problem. For marketers it is important to evaluate recommendation software and networks
on the following criteria: 1. The quality of the recommendations for all scenarios:
is there a measurable lift to sales? 2. The marketing and editorial
tools of the software or service: does it provide you total control of the recommendations to meet
your client’s business objectives? 3. Multi-channel support:
to ensure a seamless experience across all sales channels. 4. Ability to automatically
leverage data: concerning users’ interests and real-time recommendation to
optimize their online experience. 5. Performance and reliability:
to minimize latency and ensure 24/7 operation. 6. Reporting:
quantifiable evidence of up selling and cross selling results. 7. Easy integration:
to minimize start-up time and ongoing maintenance costs.
Loomia.com is a content recommendation service that uses a Facebook application to track what users
and their friends are reading on Loomia-supporting sites and then shows them what content is most popular among their social
circle.
This is increasingly important as influencers are increasingly important is social networking marketing – the SeenThis? is the Facebook application – which is increasingly going corporate and can be found in the content sites
of The Wall Street Journal Online, NBC.com, and CNET Networks.
Pique™ by Aggregateknowledge.com offers what it calls a ‘discovery network’ their Pique Network delivers targeted products and content based on what is actually
being purchased and viewed on the Web in real time. The Pique Discovery Network leads consumers to the hottest products, hidden
gems, and coolest content across the Pique network of companies. The objective of Aggregateknowledge is
to help drive sales conversions, engagement, click-through rates, and page views – the network consists of 100 websites
and over 60 million visitors.
These recommendation
software products and networks can bring social consumerism to marketers and enterprises by enabling consumer to interact
easily, allowing them to give each other tips about products and services. Allowing them to influence,
recommend and socialize exchanging communications about content or sites they have discovered. Social networking sites have added a whole new element of
communication; they introduce personal reputation systems and rankings on a global scale where influential consumers can become
new marketing champions, especially in the area of entertainment. The online buzz campaigns
have become a standard part of this new mode of marketing conducted by informed consumers, so that when shopping for a big
ticket items such as an automobile or a big screen TV, consumers often rely on the reviews of other impartial and knowledgeable
consumers rather than young sales persons at Best Buy or Circuit City. This new type of social
networking marketing by consumers is a powerful new advertising model which marketers and enterprises can leverage for behavioral
analytics in terms of identifying the influencing features of products, service and content. For the consumer behavioral
analytics and mob marketing can lead to the discovery of new artists, music, products, services, content and an assortment
of information and web sites the user was totally unaware of.
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