Find out what’s trending on Twitter and why.
For each trend, they give you a quick explanation of WHY it’s trending.
You can also see the latest tweets, Flickr photos and news stories.
Filed under: CRM, Marketing Automation | Tags: Campaign Members, Marketing Automation, Salesforce.com
With the Summer ’09 release, there are some major improvements to how Campaign Members are managed within the Salesforce.com CRM application.
Does this mean Salesforce.com is entering the marketing automation space and will compete with its now partners? Sure looks that way.
To help make it more real, we’ll follow Whitney, a marketing manager who is responsible for putting together a webinar for her company TechCo. We’ll break this down into several parts:
1) Creating a basic trigger to keep a quick count of the # RSVP’s
2) Using workflow & triggers to auto-email non-respondents 7 days later (automated multi wave drip campaigns)
3) Using Salesforce Sites for event registration landing pages
4) Using campaign member custom fields to prioritize responses from the webinar
5) Using campaign member custom fields & reports for offer management across campaigns
Filed under: Research | Tags: AFR, Australian Financial Review, Marketing Directions 2009
Marketers face the challenge of keeping track of a myriad of measures that are applied directly to their performance, often as key performance indicators (KPI).
Marketers must understand the underlying data, forms of measurement and calculations of these measures to stay ahead.
Measurement is important at any time but particularly in the current economic climate, when solid data can make a significant difference to future budget allocation.
Filed under: Social Media, Web Analytics | Tags: Facebook, Omniture, SiteCatalyst, Social Media Measurement
While marketers understand it’s important to build a presence on Facebook by creating custom applications and pages to interact with customers, sometimes they (rightly) hesitate to make a substantial investment if they can’t track the success of those initiatives.
Omniture, a company whose SiteCatalyst product allows marketers to monitor the performance of their brands on websites by tracking traffic metrics such as page views, referrals, and time spent on a page, should be able to help solve that issue. Today, Omniture launched App Measurement for Facebook. The new product allows marketers to see just how users interact with their Facebook applications.
Omniture’s App Measurement tool tracks metrics like:
- Marketers will be able to understand which user demographic segments are adopting the application most vigorously.
- Marketers can segment users by number of friends they have, or by the social activity performed.
- Which users invited their friends to use an app.
- What sections of the app Facebook users spend the most of their time.
- How Facebook engagement leads to conversions.
Ideally, this product should allow marketers with no technical background to have an immediate analytics tool that shows a robust set of metrics of how their brands are doing on Facebook. There have been many analytics tools created by start-ups to monitor such activity, and developers have often built their own, but Omniture is one of the most mainstream players to get involved with Facebook analytics
Omniture executives say the new addition to its SiteCatalyst product will demystify the questions many marketers might have about their Facebook efforts.
More: http://www.insidefacebook.com/2009/05/28/omniture-releases-analytics-tools-for-facebook/
Filed under: Behavioural Targeting, Optimisation, Predicitive Modelling, Web Analytics | Tags: Omniture, Quantivo, SiteCatalyst
On-demand behavioral analytics provider Quantivo recently announced a product to integrate with Omniture’s Web analytics solution SiteCatalyst.
Whereas Omniture tracks the number of visitors to a company’s Web site, Quantivo’s integration product, which Chief Executive Officer Brian Kelly calls “the adapter,” will help SiteCatalyst users make sense of the identities of those visitors.
In doing so, companies can better understand customer behavioral patterns — based on Web-site visits, transactions, marketing responses, and other events — and improve the targeting accuracy of marketing messages and on-site recommendations.
According to Kelly, trends in online customer behaviors are emerging, changing, and disappearing so quickly that companies now demand a solution that can handle a sudden influx of data and quickly turn that data into something meaningful.
“Big massive trends develop and diminish within a week,” Kelly says. “You don’t have time for some Ph.D. statistician to build a predictive model. [Oftentimes], it’s not something you can predict.”
In other words, while historical transaction data (and common sense) may help predict that sweater sales rise in the winter, that information is of little use for a retailer hoping to foresee which color will be most popular.
More: http://www.linkedin.com/news?actionBar=&sik=1243508631845&aIdx=0&articleID=38491000
Filed under: Web Analytics | Tags: Adplanner, Analytics API, Google Analytics
Almost everyone uses Google Analytics to calculate overall site traffic as a way to measure the value of their website.
Many users are clamoring for a simpler way to share their Analytics traffic data with their external stakeholders. These stakeholders, such as investors and advertisers, typically use data reported by other services to evaluate the performance of a company. Many times these estimates are significantly different than that from Google Analytics.
One way to share your Analytics data with everyone is to use our recent integration with Google Ad Planner. With this, you can replace Ad Planner traffic estimates with actual data collected by Google Analytics.
More: http://analytics.blogspot.com/2009/05/share-your-google-analytics-data-with.html
Todd Fast, the chief architect of Sun Microsystems’ Platform as a Service (PaaS) cloud offerings is the author behind www.twitterdata.org
In 140 chars: Twitter Data lets people embed bits of data in their tweets so that computers can read the data and do cool stuff #twitterdata
Twitter Data is a simple, open, semi-structured format for embedding machine-readable, yet human-friendly, data in Twitter messages. This data can then be transmitted, received, and interpreted in real time by powerful new kinds of applications built on the Twitter platform. Here is an example Twitter Data message:
I love the #twitterdata proposal! $vote +1
The part with the dollar sign, $vote +1, is a piece of data embedded using the Twitter Data format.
When an application knows how to read this data, it can then display it to users or send it to other applications to make Twitter an even more interesting and useful platform.
Filed under: Marketing Automation | Tags: Eloqua, Marketing Automation, Prospect Profiler
Eloqua launches their Prospect Profiler dashboard, giving salespeople insight into marketing activity and consumer behaviour allowing them to drill down into specific data.
The idea is to make it easier for the sales person to see patterns and then to drill into the details.
More: http://customerexperiencematrix.blogspot.com/2009/05/new-white-paper-and-eloqua-prospect.html
Filed under: A/B Testing, Forms, Multivariate Testing, Optimisation, Testing | Tags: Landing page copy, Landing page design, Optimising Copy
Here is a great post and video from the guys at Market Motive via Grokdotcom.
The 10 Steps to Optimising Landing Page Copy
1.) Headlines
2.) First Mental Images
3.) WIIFM
4.) Check for We-We
5.) Remove the black words
6.) Reformatting for readability
7.) Improve your verbs
8.) Wording in links and calls to action
9.) Words exist in others places than just your copy
10.) When all else fails – use the sucking wind checklist
More: http://www.grokdotcom.com/2009/05/22/optimizing-website-landing-page-copy/
In an industry where the majority of ads go unclicked, even a small boost can make a big difference. One San Francisco advertising company, Rapleaf, carried out a friend-based campaign for a credit-card company that wanted to sell bank products to existing customers.
Tailoring offers based on friends’ responses helped lift the average click rate from 0.9% to 2.7%. Although 97.3% of the people surfed past the ads, the click rate still tripled.
Rapleaf, which has harvested data from blogs, online forums, and social networks, says it follows the network behavior of 480 million people. It furnishes friendship data to help customers fine-tune their promotions.
Its studies indicate borrowers are a better bet if their friends have higher credit ratings. This might mean a home buyer with a middling credit risk score of 550 should be treated as closer to 600 if most of his or her friends are in that range, says Rapleaf CEO Auren Hoffman.
More: http://www.businessweek.com/magazine/content/09_22/b4133032573293_page_3.htm
