Monthly Archives: November 2016
Marketers now turn to social for product launches
When it comes time to launch a new product, the majority of marketers in the US, the UK, and Australia are now turning to social media.
Five by Five, a marketing communications firm that specializes in product launches, polled more than 700 marketers in these countries and found that nearly three-quarters (74%) of them consider social media to be the highest-priority medium to promote new products.
Sales promotions and email were the second and third most popular launch marketing medium, respectively.
According to Five by Five creative director Martin Flavin:
“Social media has become the most important way to generate buzz for new products and services before they appear. Shareable content and social engagement allow brands to create a groundswell of pre-launch interest in a way no other channel can match.”
Social media is now more popular a launch marketing medium than PR/press, television and direct mail.
Is social enough?
Social’s popularity among marketers for product launches isn’t just based on the fact that social channels like Facebook, Twitter and Snapchat offer access to billions of consumers around the world.
According to Five by Five, social’s popularity is also based on the fact that it’s a readily accessible medium that marketers can turn to in a pinch, which is increasingly important given that products are being conceived, built and launched much more rapidly than ever before.
In fact, two-thirds of the marketers the firm surveyed indicated that they usually have no more than six months to prep a new product launch, which can make it more difficult to execute launch strategies that rely on mediums that aren’t as accessible.
But social isn’t necessarily a perfect medium. Despite its accessibility, it can be very difficult for marketers to cut through the clutter on the most popular social channels, and attracting attention is only likely to become more difficult as marketers put the bulk of their eggs in the social media basket.
For those that are able to attract an audience and generate buzz for a new product, that buzz can also be short-lived thanks to the speed with which the social media world moves, so marketers shouldn’t expect social buzz to sustain a new product.
Instead, they’ll need to plan for a relatively quick transition to post-launch marketing, which will usually include marketing mediums other than social, including search, which as PR Week’s Robert Smith notes, has been called a more powerful medium than social by WPP chief Sir Martin Sorrell.
AWS Snowball Edge offers 100TB of storage and compute functionality
Amazon’s popular Snowball storage container got a major update today at the company’s re:invent conference. Though largely overshadowed by the new batshit crazy AWS Snowmobile, the aforementioned Snowball will be getting a storage increase to 100 terabytes in addition to computing functionality. Users of the new Snowball Edge will be able to perform basic analysis on their data… Read More
Enterprise – TechCrunch
No, Gotham, That’s Not How Tightropes Work
In this scene from Gotham, Bruce Wayne holds a tight rope for Selina. It turns out this might be much more difficult than it looks. The post No, Gotham, That’s Not How Tightropes Work appeared first on WIRED.
Ranking Events in Google Search Results
This summer, Google was granted a patent that describes how the search engine might rank events based upon data that might indicate the popularity of those events, without relying on things such as the number of links pointed to pages about those events. The patent involves ranking events that occur in physical locations.
Examples of the kinds of events talked about in this patent include such things as music concerts, art exhibits, and athletic contests, all happening for specified periods of times at specified physical locations, such as concert halls, galleries, stadiums, or museums.
Since many events in a geographic region can happen at the same time or at overlapping times, interested individuals may at times find it difficult to determine which events to attend. For example, individuals may be unaware that events of interest are scheduled to occur or may have difficulty identifying the most interesting events when multiple events are occurring.
The patent lays out a general process flow to describe how the method in the patent works to rank events. It starts with receiving data about a physical location, and events taking place there during a certain time period, and computing signal scores for those events based upon things such as a mention of the event and a popularity score for the event based upon those signal scores.
Additional signals for ranking events can include: 1) generating an initial ranking of events based on the popularity scores; 2) computing a respective modified popularity score for each of the events based on the initial ranking, and 3) generating the ranking of events occurring in the physical location by ranking the events according to the modified popularity scores.
The patent describes the process of computing a popularity score for events, including: 1) obtaining information about a category for each event; 2) computing demotion values for each of the events, which is based on higher ranked events in the same category and 3) generating the respective modified popularity score for each event by applying the demotion value for the event to the popularity score for the event.
Computing a first signal score for the event can include: 1) determining, of the Internet sites including at least one mention of the event, a number that have been classified as ticket selling sites; and 2) computing the first signal score based at least in part on the count of Internet sites including at least one mention of the event and the number that have been classified as ticket selling sites.
Computing a plurality of signal scores for each of the events can also include: 1) determining whether the event has an official web page; when the event has an official web page, 2) determining a peak number of user selections of the official web page over a predetermined duration of time; 3) determining a measure of relevance of the official web page to the event; and 4) computing a second signal score of the plurality of signal scores for the event based at least in part on the peak number of user selections and the relevance measure.
Other signal score factors for events can include: 1) obtaining data identifying one or more entities that are relevant to the event; 2) determining a measure of global popularity of each of the entities; and 3) computing a third signal score of the plurality of signal scores for the event based at least in part on the measures of global popularity of the entities that are relevant to the event.
Additional signal scores can also include: 1) obtaining data identifying one or more event categories that are relevant to the event; 2) determining whether any of the event categories that are relevant to the event have been classified as promoted or demoted categories; and 3) computing a fourth signal score of the plurality of signal scores for the event based at least in part on whether any of the event categories have been classified as promoted or demoted categories.
More signal scores may include: 1) obtaining search results for a search query that includes a first term identifying the physical location and a second term indicating an interest in events occurring in the physical location; 2) determining a position in a ranking of the search results of a highest-ranked search result that mentions the event; 3) determining a frequency with which the event is mentioned in the search results; and 4) computing a fifth signal score of the plurality of signal scores for the event based at least in part on position of the highest-ranked search result that mentions the event and the frequency with which the event is mentioned in the search results.
Computing additional signal scores can include: 1) obtaining data identifying a venue hosting the event; 2) obtaining data identifying a seating capacity of the venue; and 3) computing a sixth signal score of the plurality of signal scores for the event based at least in part on the seating capacity of the venue.
The following advantages are described by the patent in following the approach it describes.
1) Events in a given location can be ranked so that popular or interesting events can be easily identified.
2) The ranking can be adjusted to ensure that highly-ranked events are diverse and different from one another.
3) Events matching a variety of event criteria can be ranked so that popular or interesting events can be easily identified.
4) The ranking can be provided to other systems or services that can use the ranking to enhance the user experience. For example, a search engine can use the ranking to identify the most popular events that are relevant to a received search query and present the most popular events to the user in response to the received query.
5) A recommendation engine can use the ranking to provide information identifying popular or interesting events to users that match the users’ interests.
US 9424360 B2
Publication number US9424360 B2
Granted: Aug 23, 2016
Filing date: March 12, 2013
Also published as US20150161128
Inventors Kavi J. Goel, Toshihiro Yoshino, Yang-hua Chu, Hidetoshi Shimokawa, Slaven Bilac, Mingmin Xie, and Satoru Yamauchi
Original Assignee Google
Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for ranking events. One of the methods includes receiving data identifying a physical location; obtaining data identifying a plurality of events occurring in the physical location during a particular time period; computing a respective plurality of signal scores for each of the events, wherein computing the respective plurality of signal scores for each of the events comprises computing a first signal score for each of the events based at least in part on a count of Internet sites that include at least one mention of the event; computing a respective popularity score for each of the plurality of events by combining the respective plurality of signal scores for the event; and generating a ranking of events occurring in the physical location during the particular time period based at least in part on the popularity scores.
The selection scores may include things such as Unique Mention scores, Ticketing Sites mentions, and Official Page (of the event) selections, and the patent describes how those factor into popularity scores.
An entity popularity score is a measure of popularity of entities that have been classified as being relevant to the event. Each entity may be given a topicality score and a confidence score, based upon the global popularity of the obtained entities. This can be based in part upon a number of search queries that include a reference to the entity that have been submitted to a search engine.
An Event Category Score might be used to determine whether the category has been previously classified as a promoted or demoted category. A trade show may be classified as a demoted category because they tend to appeal to a limited audience, while festivals and fairs may be classified as a promoted category because they tend to appeal to a broader audience but may not be well-publicized.
In order to compute the ranking score, the system obtains search results for the search query from a search engine. The obtained search results are ranked according to scores generated by the search engine. The system can then compute the ranking score based on a position in the ranking of search results of the highest-ranked search result that identifies a resource that mentions the event, the number of mentions of the event in resources identified by a pre-determined number of highest-ranked search results, or both.
A score based on the popularity of the venue where an event takes place may also play a role in the ranking score of an event. Events that are held in places that usually show more popular events may be assigned higher venue scores.
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How to Find Epic Keyword Opportunities That Turn Into Easy SERP Wins by @josephhhoward
Do you write content and never see it on page one in search results? Find less competitive keyword opportunities so you can finally win at Google!
The post How to Find Epic Keyword Opportunities That Turn Into Easy SERP Wins by @josephhhoward appeared first on Search Engine Journal.
Are You Thinking Of Account-Wide Goals? Let’s Change That Mindset
Don’t think: “what would be the easiest way to look at our data”, think: “what makes the most sense per each type of advertising” when deciding on goals for different areas of your account. Learn more on how to think through goals!
Read more at PPCHero.com
Car Insurance Pricing Is Broken, But Your Phone Could Fix It
Opinion: When car insurance companies base pricing on telematics rather than demographics, everybody wins. The post Car Insurance Pricing Is Broken, But Your Phone Could Fix It appeared first on WIRED.
CNN buys Casey Neistat’s Beme app, brings the YouTuber in-house
CNN has acquired Beme, the social app co-founded by YouTuber Casey Neistat. As part of the deal, Neistat will lead the Beme team as a new standalone media sub-brand operating under CNN’s umbrella as executive producer, and all 11 members of the Beme team will join the ranks of the news network, according to Variety. Beme’s had an interesting history, with a founding vision of… Read More
Social – TechCrunch
Drastically Improve Your Users’ Online Experience With A/B Testing
Performing A/B tests on your landing pages can pinpoint exactly what is working and what is failing on your site. In this new live webinar, Unbounce’s Duane Brown and Hanapin’s Samantha Kerr and Kate Wilcox will share their expert CRO advice on how A/B tests have shaped their clients’ success.
Read more at PPCHero.com
Falling in Love With Measurement
Why aren’t more marketers measuring their campaigns?
Which is a shame, because these two are perfect for each other.
Connecting the dots
Consumers often have dozens or even hundreds of digital interactions before they buy something today. The sheer amount of data created is staggering. There are more than enough dots to be connected for full visibility into the customer journey.
But, as much data as marketers collect today, the truth is many still struggle to make sense of it all. In some companies, you could say Marketing and Measurement find themselves sitting at opposite ends of the couch.
Only 5 out of 10 marketers said they think about measurement while developing campaign strategy, a recent survey of marketing decision-makers shows.1 If you don’t define your measurement goals from the beginning, you may not collect the right data — and understand what’s working and what isn’t.
Marketing and Measurement should get cozier sooner: at the front-end of the campaign process, while developing strategy. Yet, too many marketers said they think about measurement while building materials and assets (nearly 16%), after the campaign has deployed (9%), or even after the campaign has finished (nearly 6%). What’s more, 16% of the survey respondents said they don’t measure their campaigns at all.2
Clearly, it’s time for a relationship makeover. If you’re ready to play matchmaker in your own organization, try starting a strategic conversation between Marketing and Measurement with these three questions:
- Are we measuring the consumer interactions that really matter?
- How quickly can we spot the key insights hidden in this data?
- How do we turn those insights into better customer experiences?
When we close the gap between Measurement and Marketing, we can not only answer the question “How are we doing?” but also the more important question, “How can we do better?”
It doesn’t have to be complicated. When Marketing and Measurement go hand-in-hand throughout the customer journey, it can lead to more useful insights, higher revenues, and better experiences for everybody.
As Matt Lawson, Google’s Managing Director of Ads Marketing, says, “Measurement isn’t what happens at the end; it’s where the smarter and more successful future begins.”3
1-2Source: Google Surveys, “Measurement in Campaign Timeline”, Base: 1,092 marketing executives, U.S., August 2016.
3Harvard Business Review, “Rethink Measurement From the Ground Up,” sponsor content from Google Analytics 360 Suite, August 2016.
Posted by Karen Budell, Content Marketing Manager, Google Analytics 360 Suite