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Category: web 2.0

Personally I don’t buy the benefits of display ads for a long time. Speaking of my own experience as a consumer – I spent a lot time going to websites, reading articles or buying stuff, but I don’t feel the impact of  display ads on me. I always act purposefully online and I just disregard the irrelevant messages around me. However, my recent experience and some analytics results changed my thoughts.  Immersing myself in the internet marketing industry, I constantly see how evolving technology advanced the degree of relevancy that display ads could be. When the message reach to the right people, and as long as it is relevant,  people clicks.  A typical example is Facebook, Facebook showing ads by analyzing keywords from people’s profile and dialogs,  while the ad result is not perfect, it becomes better and better.  Here I summarized three reasons of “why Internet Display Ads” for advertiser after several rounds of discussion with my colleagues.

1. Reach audience that disappeared from traditional media, with increasing relevancy of messaging

I seldom watch TV and magazines/newspaper, I go to YouTube and Hulu for videos,  go to websites for editorial contents-even willing to pay for it. I also manged to grab the information whenever I want from various iphone apps – and i am willing to pay for it too.  I know more and more of my friends start acting like this way- probably not that extreme, but proportionally and gradually.  We are the part of audience that traditional media has limitation to reach to and the segment size is just growing. For  advertiser, “be where the target is” is the simplest rule, though the degree of which is varied across industries, companies or even campaigns.  But I keep seeing the smarter advertisers are always more likely to act ahead and learn from their early experiences, they are willing to try new technologies, try to expand the relevancy of their display campaigns – there are growing industry participants can help with it.  ranged from simple context/ site targeting (Google Adwords, adnetwork..) to complicated individual-level impression targeting (Ad exchangers, data providers and DSPs), all contributed by the beauty of technology and data.

2. Complementary to the limitation of  “Search”

In the states, almost half of the online marketing budget is spent on Search, and there is a reason for the growing speed: compared with other media, Search is efficient, transparent and trackable, and advertisers love its result-oriented, data heavy and ROI favored characteristics.  However, Search always performs the later funnel of a message communication process.  like the famous and powerful  sentence that describes its media advantage : “be there when and where your consumer want it!”. However, the sentence also hides the limitation of Search behind:  that is,  when advertiser, especially small-medium ones, spent their budget in search to some point, they will realize the limited impact of their campaigns due to a stable search volume and relatively constant click-through-rates – if without the help of other media.  With this, display reaches a similar digital audience as search, and it helps to build the upper funnel of communication process and eventually, grow the size of later funnel – increase search volumes . Secondly, when the display creative done its job, it also enhances the click through rates of  search campaigns.

3.  Messaging between “action-driven” and “branding”

Though there are “Branding” campaigns in Search, in general Search is pretty much action driven, For its role in a later funnel of  communication, search campaigns are calling for action, usually messaging with a deal or discount, or phrases like “buy today” or “sigh up now”-we can tell this either from the Ad title or Ad copy.  However, this is not enough for any advertisers who care about branding, who wants their brand to have a sense of personality.   Running branding campaigns in traditional media,  such as buying good slots in prime TV time or hiring expensive creative agencies can do the job, but it is expensive and not applicable for all advertisers. Well,  I think rather than an alternative, but an integrated channel, display can stand between. Generally speaking, with a combination of place,  size and format differences in image, flash, video, etc… display offers rooms for media creativity and innovation.  With its linkable nature and targeting technology, it could be messaging in either action driven or brand awareness, we are increasingly seeing if buying and messaging in a right way, display CPC could even outperforming Search, and growing its search volume at the same time!  But still,  I don’t think display media has a similar emotional impact as traditional media, not even close. esp. when compared with TV and  OOH. but thinking smartly, advertisers can still apply technology and media flexibility to their favor and keep optimizing and bringing in insights that they learned from digital across channels and campaigns.

As mentioned in my previous post. I really looked forward to testing Google Analytics Intelligence out and here it happens. It is an amazing tool.  Avinash Kaushik, the author of the web analytics best- selling book, nailed it as “identifying the unknown unknowns!” The intelligence function is truly a great breakthrough for online marketers, check the intro video by Google out if you want to know more.

I particularly like the flexibility of the tool, details as following.

  1. I can choose the time period for data entry as “by day”, “ by week”  and “by month” . It tailored both my needs for real time campaign tracking and historically data mining.

daily alerts

2. It allows me to tell how sensitive of the changes I want to track.  In a particular case, if I get several alerts per time period, I always want to rank them by the extension of the changes first.

sensitive

3. Customize my alerts to the metric that I cared most about.

4. Another thing that I particular like is the segmentation tab. After helped me identifying the unusual pattern, Analytics Intelligence easily opens a door for me to go to further analysis for the segment that comes up with a significant changes, for understanding why.

segmentation

With all the good stuff that are exciting, here comes the critique: Is Google Analytics Intelligence intelligent enough?

Here are the things that need to be paid attention to.

1. Custom alerts not show up for past data

Like the goal and funnel setting, custom alerts don’t apply for historical data. Though it is not hard to draw a historical graph and found the changes I want to track, it would be another manually task for historical data miner who wants to do so.

2. After create the “alert” segment, so what?

I tried and found I could not adopt Intelligence to sub-segments in Google Analytics,  For example, if I identified 173% increases in New York visitors on my site. It would be perfect if Intelligence could tell me why. For instance, is it because a sudden increase in PPC or referring channel?  What keywords leading to that and what pages do they visit most?  It would be a huge time-saver if Intelligence could use its scientific method again to tell me that, other than I dig into them by myself.

3. Similarity in the massive alerts

In web analytics, we always found metrics are very much correlated with each other. A group of consumers that convert better always demonstrate a higher time on site, a lower bounce rate and more page views/session at the same time. Same happens in the alerts. If I got a 143% increase in visits, it could apply to a multiple geographic areas, different channels together.  If in the case, there is a total 143% increase for all visits but only 68% increase in Chicago, or 34% increase in PPC, actually the particular area and channel is below the average. But the alerts will still shows in “green”, while in some situation, could not be a good indicator.

4. How to calculate the expected value range.

In the alerts, GA identify the changes based on expected value. But the question is, how it calculate the value? There is no information in its help center, so I tried to pull out the data by myself , just curious to see how it works.  Take the New York sales data for example.

expectation

According to GA intelligent, sales data for New York is expected to hit between $1238 to $2754 yesterday, but reached $4322, hence caused a significant 162% increase. There are two way to come to the expected value range, one is to calculate average, find the frequency and standard deviation of historical sales data,  the other is doing predictive modeling. Let’s  look at the previous one first, I analyzed all the historical sales data in New York and here is the result generated by SPSS as descriptive analysis.

Descriptive

Due to the skewness of data, cause 2/3 of sales falls from 0 to $1905, apparently not the way GA is using, while the standard deviation is close to the range of expected value (it depends on what confidence level GA uses)

Now I change to another way, which is predictive modeling of time series.  Here is the result and the blue line is the forecasting value, and it was $2914 for yesterday.

time series

Actually if I adding the standard deviation I found in the descriptive analysis, the expected sales value for  yesterday could falls somewhere between 2300 to 3500, surprise to find it is more close to real data than what GA is coming up. Hence I would love to see if GA could disclose more about their calculation methodology here.

A couple of days ago, Google Analytics announced its new features,  below are some brief examples of the updates.

  • New goal setting features allow users to measure visitor engagement, such as time on site and page views
  • Up the number of goals that user could define to 20
  • Provide code snippet on mobile portal, enable users to track mobile traffic regardless whether the visitor’s device runs JavaScript
  • Introduced Analytics Intelligence, which could tell users what are the significant changes in data pattern in a defined period. e.g., a 300% traffic increase from a referring site yesterday. (It seems the feature has not launched yet since I couldn’t find it in my account)

Above all, the most sigificant change could be the new goal setting features.  So the question is , for marketers,  how can we leverage them in our marketing campaigns?

    • Set up your engagement goal

      Google Analytics Goal engagement 1

      Find out how many visitors out of the total are truly engaged visitors?  Is the number increasing / decreasing due to the change of website design and content? You may think the higher numer means your changes are effective, but be cautious, data could be misleading! The increase in time on site could also due to returning visitors not get used to the new features on your website as well.  In that case, you could test your hypothesis by choosing new visitors only in Google Analytics advanced segment function.

      If clearly, your site has a branding purpose and  you want to drive visitor’s brand awareness after bring them to the site, and then optimize your marketing channels such as paid search, banner ads, social media, etc.  this goal setting feature could be a valid measurement with a dollar value assigned – to test the effectiveness of  your branding efforts.

      Set up your relevancy  goal

      Google Analytics Goal engagement 2

      Generally speaking, the more people explore on your website, the more relevant they found of your website content. Do you want to track the ROI according to the degree of relevancy visitors find of your site? Now you can do it easily in Google Analytics.

      In marketing branding practices, if the “awareness” is the very first stage of consumers’ psychological behavior, the “relevancy” could be the next one, then normally it will come to “preferrence “ and in the end, “action” -close the deal.  Hence if you are running an ad campaign in order to capture your target at the right time, allocate your dollar value according to relevancy could tell you how valuable your campaign is.

      Questions about  Analytics Intelligence

      I feel the Analytics Intelligence is a quiet huge offering for a free tracking tool like Google Analytics, but since Google Adwords has  similar functions, it might be an easy movement for the Analytics product to have its own intelligence algorithm. What it means to the users is with this function, it saves marketers time to dig into the data and find unusual patterns (or for marketers who don’t even have time digging into it), but since I haven’t experienced it, it is hard to tell how smart it could be. Will it be smart enough to discover patterns in the sub-segment group? Will the findings be statistically significant? How flexible it allows users to define the confidence interval of the data string? – These will be the questions I have in mind and wanna to test later.

Last week I attended a marketing conference hosted by Northwestern, where there is a panel on the topic of social media. During the 30 minutes, the discussion ranged  from what is social media to how could marketers utilize social media, but still, missed the point that I really care about: how could companies measure the effectiveness of social media. Not until today, a friend kindly share with me an industry report, did I have some new thoughts on it.

First of all, why businesses need social media? Below diagram partly proves the importance of social media. I think for answering this questions, there are two types of companies’  advertising needs : One is for advertising on social media to increase brand awareness or drive sales, which is easy to measure. Another is for socializing with consumers to manage with a relationship, which is difficult to measure. However, there are much more reasons for a business to use social media besides advertising, such as listening to the market place and react, human resource purposes, etc..

How brands are discussed in the public

How brands are discussed in the public

Consumers use social media to share feelings with their friends. Different from paid searches, which is known as “search for the right thing, at the right time”, social media doesn’t born with a strong “action-driven” nature. That is why reported CTR is always lower than paid searches. However, on the other hand, advertisements on  gaming platforms to engage with consumers are proven to be quiet effective on some media, typically Face book, and this type of advertising is even more popular in Asia, though the measurement is more comprehensive than simple advertising. In terms of socializing with consumers, which is another major type of utilizing social media among business, always presented as a homepage on Face book, a channel on YouTube or an active account on twitter, for the purpose to influence brand reputation or increase brand awareness, really differs in the effectiveness among various marketers, where measurement needs to be played a key role here.

Spectrum of actions could take on social media

Spectrum of actions could take on social media

There are several vendors providing social media measurement tools. Radian 6 is a good example . Its application manages three different marketer’s needs, which is listening, measuring and engaging.

Listening: a brand isn’t just what the company says. It’s also about what employees, customers, prospects, competitors, and world at large say it is.A buzz metrics like below will take all the relevant keywords for a brand.  So not only listen to your customers, listen to the world as a whole. A brand’s share holders are always more than you could think of, and social media do drives transparency out there.

listening

Measuring:My key take-away from Radian 6’s measurement is the use of share of conversation and buzz lifecycle.  Marketers are familiar with the term “share of voice”, but they may want to know, do share of voice generates compatible share of conversation in the market place? Share of conversation is how often your brand is discussed over the internet compared with your competitors, it could be case/event sensitive, but in the long run, it will be a fair measurement.   Or we could think of it in another way, if a brand could generate a good share of conversation, is that necessary for the marketer to invest in a large advertising budget? Maybe yes, maybe not.  A good example is iPhone in China, iphone has not been officially released in china, but the product sells itself without a penny of advertising budget, thousands of thousands people discussing it over the internet and trying to buy one from whatever channel they could get. This is a typical case of a successful brand with a large share of conversation but literally, no share of voice.

Buzz lifecycle tells marketers the influence of a topic of your brand, it could be the latest advertising campaign, or a new product just launched, enabling marketers has a better control and management over the buzz  in the long run.

Buzz life cycle

buzz life cycle


As far as engagement, there is nothing new worth mentioning, it’s all about respond to the right customer, at the right time. A good example I recalled I read somewhere else could be Bing’s  ” co-twitter” practice , Bing carefully follows the buzz on twitter and if there comes up a question or problem the person who responsible for the twitter account couldn’t answer, he or she will forward the question to other folks of the company to deal with. I think it is a mini example of integrated marketing communications from a company’s internal resource allocation.

Thare are other measurement tools out there too, I will discuss them in the future. Stay tuned :)

9月10号阿里巴巴十周年,有幸去参加了他们的庆典,去杭州的时间非常紧,上午急着在上海三个地方办完事,下午就来到了杭州,来到淘宝办公处正好碰上原阿里软件的人搬家。淘宝在杭州2000多人,给我的感觉像个大学。首先是员工都非常年轻,可能与其近三年扩招了很多应届生有关。其次办公室不像个房间,像个办事广场,很大,然后工作人员一个隔着一个位子的样子还真有点像大学里的图书馆。人员来来去去的很热闹,接触过一些淘宝人,很可爱的一群孩子,喜欢自己的工作,对他们的印象都不错。在淘宝,和同龄人一起工作的氛围应该挺轻松自由的,可能就是辛苦了些带孩子们的“小大人”们。

晚饭后去了庆典,由于某些原因去了内场,近距离地观摩。2万多人的体育场很壮观,外加众多激情的年轻人使整个黄龙体育场都沸腾了。

阿里巴巴十周年庆典

阿里巴巴十周年庆典

整个晚会的节目都是阿里巴巴内部员工自编自演的,无论是四个子公司的热场巡演,还是正式节目的编排,阿里巴巴引用了航班起飞,国际化等元素。传递了改变和发展的喜悦,还有一种具有社会责任的企业文化。当然,最雷人的无非是马云的视觉系表演,唱了狮子王的can you feel the love tonight,唱地还不错吧,呵呵。

马云

大概到了节目的后半段,我就有了一种莫名的感动,感动于中国的企业也可以如此成熟地向国人,甚至在场的外国人展示着过去的精彩和宏伟的未来蓝图。身在国外,我深知国家富强的重要性,而这种油然而生的自豪感是阿里巴巴带给我的。马云说,过去十年阿里的员工 “很傻,很纯”,确实,在创业和发展的阶段有数不清的可能性会阻断阿里的成长,幸运的阿里人靠着脚踏实地的精神和社会责任的信念坚持了下来。

阿里巴巴十周年

阿里巴巴创始人

晚会后去白鸦的咖啡店逛了逛,虽然去他店的时候颇费周折。咖啡店环境不错,很多互联网的人相聚于此(发现大家都是用Mac的),可惜与白鸦交流的时间短了点,希望以后有机会,或者白鸦以后可以考虑来别的城市开分店哈。^ ^

贝塔咖啡

贝塔咖啡