Posts Tagged ‘advertising’
The big announcement at Google I/O last week was the release of details about Google TV. And it should make TV advertisers of all stripes angry and concerned. VERY concerned. So much so, in fact, that they should be actively seeking technologies and business models to deflect/prevent what is effectively an advertising power play by Google.
Google TV is the latest attempt to merge the television experience with a web-based TV (also called IPTV) experience on the television set (as compared to bringing TV to the web, as say a SlingBox does). There have been numerous attempts to bring the Web to the television, going back all the way to 1996 when Steve Perlman, Bruce Leak and Phil Goldman brought to market the WebTV set-top box, marketed by both Sony and Phillips. (Find a list of TV/Internet hybrids in the next post). None of these has been particularly successful, for numerous reasons:
- Most require an extra set-top box that is expensive (Google is no different. As an example of technology that uses the consumer’s computer or laptop as the interface to the TV, see Kylo).
- The experience doesn’t truly integrate. You either watch the web-based offerings or Live TV, but not both at the same time. In many cases, the box is meant for the delivery of movies or TV shows on-demand, as compared to being broadcast in real-time. The Roku/Netflix platform is an example of this. PopBox is another example, but they also deliver more content – websites, social media experiences from Facebook and Twitter, images, YouTube videos, games, and music from sources like Photobucket and Pandora.
- The interface requires a separate remote control, which adds another layer of complexity to the consumer experience.
None of these really impacts the effectiveness of a “single” broadcast TV advertisement in any meaningful way. They are separate experiences from broadcast television and, as a rule, they do not take away from live TV viewership. Some amount of consumers’ time is given to the Internet and movies on-demand nowadays. Whether I interface with that experience through my computer screen or TV screen doesn’t change the amount of time I spend in an “online” mode versus a TV viewing mode, and it does not impact my current behavior around the TV ads themselves.
Google TV has come up with a different approach which, at least during an initial search, overlays the Internet on top of the television experience (see first image). When it overlays, the interface is transparent so you can see your TV behind the browser interface that lets you search for the shows and information you want.
There are other times when the interface switches completely and the TV experience is put on hold while the viewer interacts with Web content (see second image), which is more like the experiences of the current generation of web-to-TV offerings. But the difference here is how easy and seamless Google TV makes it to switch between all three of these user experiences – live TV, TV in the background, and Internet-only. The other difference, and one of critical import for this article, is that Google intends to sell advertising within the Google TV platform. Where, how, and how much are still to be determined.
Google has definitely come up with something unique that I believe will be very compelling to television viewers as it now truly integrates the television and web experiences for the first time.
But if the consumer loves this, traditional TV advertisers should hate it.
Today, television advertising is a $70B market versus $25B for Internet and mobile search advertising.
In 2010, TV advertising is projected to grow 4.3%, or $3 billion on a base of $70.2 billion. This compares to non-search on-line advertising which is projected to grow 12.9% or $1.6 billion on a base of $12.2 billion during this period. So even though Internet advertising is growing at a faster rate, television advertising real-dollar growth is twice that of Internet advertising.
Google knows this. Rishi Chandra, the product manager for Google TV, mentioned the $70B factoid at Google’s I/O conference last week. Moreover, Google also gets that despite the fact consumers are spending an increasing number of hours per day online, television viewership is at an all-time high, with 180mm US consumers watching TV for over 5 hours/day on average. Rishi mentioned this, as well. The guys at the Googleplex are no dummies. As the old saying goes, they can see a mountain in time. In this case, the mountain they want to cash in on is TV advertising.
What both Google and the advertisers also know is that television advertising is broken. In 1987 an advertiser could reach 80% of viewers by airing a 30-second spot only three times. Today, that same commercial would have to air 150 times to reach 80% of viewers. The rapid decline of TV ad viewership is due to the “TiVo” effect and today’s viewers’ multi-tasking habits – texting, phoning, emailing and web surfing while watching TV. Brands are urgently seeking a solution to reengage viewers of their TV commercials as brand expenditures on television dwarf what they spend on all other ad mediums.
Now Google would argue that it has found the solution, and from its perspective I truly think they believe this. The Google culture is driven by data and metrics. Current television advertising with its lack of performance measurement is anathema to a Googler’s mindset. If you are a fanatic about data-driven marketing, Google TV “solves” this problem because of its ability to bring CPC and other easily measurable formats into the web-based part of the new integrated television experience.
Interesting and correct as far as it goes. But wrong – and I mean dead wrong – from the perspective of television advertisers who focus 3x of their dollars on television versus online advertising because it is still the most potent means of getting a message to the consumer. Moreover, it is a power play by Google to disconnect the brand advertisers from their traditional advertising providers and drive them, willingly and like lemmings, onto the Google platform(s), thus providing Google an even stronger power position relative to advertisers.
Let’s think about this. Television advertising is already much less effective than it used to be. Now along comes Google TV with its overlay and ability to seamlessly move away from the live television experience. Let’s say you are a viewer watching Lost, that you are using Google TV, and you have left your laptop in the other room because – heck – you don’t need a two-screen solution to access the Internet during live television now that you have Google TV. Something on the show triggers you to want to look up some factoid on the web at a Lost fan site. You plan to type in “Lost fan site.”
When are you going to type this in? During the time the episode is airing? Absolutely not. You’re not going to want to miss one minute because Hurley is about to tell Jack his real name. Or take another example – a sports case. Are you going to put the potential touchdown play in background mode while you look up Brett Favre’s completion percentage in third down and long situations? Absolutely, positively not, to the extent that the sports fan is thinking “don’t you dare touch the remote or there will be one less thumb in this family.”
No. You are going to switch to the Internet experience when the television ads come on and you can safely move away from the live broadcast to find what you need before your show comes back on.
There is another interesting fact that only makes this seem a more likely behavior on the part of cross-platform TV viewers, at least the early adopters of Google TV. In a recent study of US Online TV Viewership by Comscore involving 1,800 subjects, a majority (67 percent) of cross-platform (TV and online) viewers preferred online TV viewing because it has less interference from commercials. Since these folks are the likely early adopters of Google TV, the tendency to move away from live TV during commercials will be very strong.
So what does Google TV do? It makes the television ad spend of the major brands even less effective than currently. Because Google TV still provides an interruptive experience, it actually encourages cross-platform viewers who wish to increase the “information content” of their viewing experience from web-based channels to do so at the exact time that advertisers least want them to do so.
There is an even bigger implication of this for brand advertisers. In order to keep the cross-platform consumer’s attention as they move away from viewing television ads, the brand advertisers will be forced to place their ads on the web-based portion of the Google TV interface. And to a certain extent this makes sense going back to our previous point about measurability of TV advertising. The Google platform is measurable and consumers more and more are becoming habituated to interacting with web-based CPC or banner advertising. So the TV advertiser keeps the attention of the cross-platform viewer during the commercial break in the show and gets better metrics. It’s an obvious win-win for both Google and the advertiser, and a very seductive business proposition to marketing executives looking for better measurability around TV advertising.
But for TV advertisers, Google TV is the equivalent of the poison apple given to Sleeping Beauty. As Google TV penetrates households, more and more TV viewers will become habituated to the dual-use experience and will spend more and more time on the Google platform during broadcast television advertising pods. And despite the fact I haven’t said much about mobile in this article until now, Google TV will also move onto the mobile platform and will provide an even more integrated experience for the consumer across the two screens, with a whole host of implications for the two-screen experience that I won’t discuss here. Given the timing of historical consumer behavior transitions in the television market, this could take ten years. But over that time, Google will take a larger and larger share of the currently $70B TV advertising and the $2.7B mobile advertising markets. This means that as much as an advertiser is currently dependent on Google for web advertising, they will become even more dependent on the single provider that is Google because of its reach in these other channels.
If you as an advertiser aren’t concerned about the implications of this for your business, where Google can set effectively monopoly prices you pay for ads across every major advertising platform you have, you should be. You should be very concerned and mad as hell at this attempt to manipulate your advertising dollars even further into the maw of the machine that Google has become.
If I were a brand advertiser right now, I would be talking to my peers and looking for a second-platform solution from someone that can constrain this power play by Google before it becomes a fait accomplice. If I were Yahoo or Microsoft, I’d be developing or investing in a prototype of something I could show to brand advertisers today and get them to invest strategically in order to prevent Google from locking up this market before it is too late.
 “Advertising is Dead, Long Live Advertising” Himpe, 2008
 Yuki, Tania “Comscore Study of US Online TV Viewership.” http://www.comscore.com/Press_Events/Press_Releases/2010/4/Viewers_Indicate_Higher_Tolerance_for_Advertising_Messaging_while_Watching_Online_TV_Episodes
Let’s continue our discussion of Twitter economics.
The average Twitterer has 549 followers. Now this is skewed by corporate accounts (e.g. like our travel sites) and news sites that have a very large number of followers. I have gone through a number of accounts to determine what seems like a realistic average number to use – and I am going to assume 200 followers. Our experience is that for the first generation of followers, 10% pass along an offer (the theory of this is also quite enlightening but I will not cover it here). For subsequent generations it is much lower, usually in the 2-5% range. We mentioned previously that 15,000 is the average number of followers for the Big 3 sites (Expedia, Orbitz, Travelocity). The calculation therefore looks something like the following:
+ (15,000 * 200 *.1) = 300,000 (first generation pass along)
+ (300,000 * .02 * 200) = 1,200,000 (second generation pass along)
= 1,515,000 (total number of individuals)
The number of impressions is then this base of 1,515,000 multiplied by the number of offers “seen”. Expedia seems to be making offers every five minutes, as does Hotwire (they must have set up some kind of automated feed into their Twitter accounts). Travelocity and Orbitz seem to be making offers once a day (or even less). The big unknown is how many offers does the average follower actually see? They aren’t always online, or if online, they are doing other things and their attention is not focused on Twitter. Or they are on Twitter, but the offer doesn’t register through the noise of all the other tweets. Without any really good data, I will assume that each individual “sees” two offers/month – which I hope is a conservative number.
This means that the total number of impressions is: 1,515,000 * 24 = 36,360,000 per year
Given this number of impressions, what is the potential economic impact for Expedia, Orbitz, and Travelocity? Typical conversion rates on these sites runs 3-5% according to various published data I have seen. But, this is not a situation where someone has either typed in a keyword or clicked on an ad that appears when a keyword is typed in. This is much more of a grazing situation. Many offers are made, but only a few are relevant to any specific individual. So the response rates look more like email, and yet they are even smaller. Why? Because while the first generation is signed up to receive notifications (parallel notion to an email, in this case), the second and third generation are not. Our first benchmark is therefore an email conversion rate from the initial mailing – which is calculated as follows (I am ignoring losses due to bad addresses, since that is not an issue for online accounts - although see below for a related issue of dormant accounts):
# of impressions * open rate * conversion rate
Typical average open rates for good emailings are 10-12%, and conversion rates vary but let’s assume 2%, which is a number that comes from my experience with emailings. That would yield the equivalent of a .2% conversion rate for the first generation. But for the second and third generations, the response would be substantially smaller, maybe .1% or even as low as .05%. Since the first generation is such a small number of individuals, I will use .1% as the conversion rate for the entire base of impressions.
The last pieces of data we need are the number of tickets purchased, the number of purchases per individual in a year, and the average revenue to the travel agency from each ticket purchased. Again, I am going to use data that is fairly well known in the travel business. These are gross averages and do not take into account a number of variables, such as the type of travel (business vs. personal), destination (domestic vs.international), and type of flier (managed vs. unmanaged)
Number of trips per year: 2
Average number of tickets purchased/trip: 2.2
Avg revenue per ticket to agency: $25
So now let’s do the annual revenue calculation for the economic impact of Twitter for a large online travel agency:
36,360,000 * .001 *2 *2.2*25 = $3,999,600
For a big travel agencies, which have around $1B in annual revenue, this is small (.4% of revenue) but it isn’t chump change either.
Before I close, one other issue needs to be explored – and that is the issue of dormant accounts. The model presented assumes that every individual who is following or who receives a retweet or direct message is an “active” Twitter user. But as we all know, many from our own experience, you may set up a Twitter account and then never go back to it. Or you may visit it only rarely. I call these dormant accounts. There has been a lot written on this topic – just type “dormant twitter accounts” into Google. Nicholas Carlson recently wrote a post for BusinessInsider.com titled “60% Of Twitter Users Quit After A Month“. Carlson cites Oprah (@oprah) as an example of someone who has become “bored” with Twitter and reports that Nielsen Online estimates that 60% of Twitter users quit after a month. The post goes on to say that the 60% number may be misleading as Nielson only measures Twitter usage based off Twitter.com and not from mobile use or apps like TweetDeck. Given this data is pretty consistent with other social media sites, and the fact that a lot of tweets happen off of twitter.com, I think we can safely assume that the dormancy rate for Twitter is 50%.
In this case, our approximately $4mm in annual revenue has now become $2mm in annual revenue.
Not huge, but I think we could say that the ROI on the costs associated with maintaining a corporate Twitter account for this purpose are probably pretty spectacular.
I do not doubt that this post will cause a lot of discussion/controversy (at least I hope it will), and I look forward to all feedback.
All I hear about is what the value of Twitter is (hopefully) to investors. What is Twitter’s business model? How will it make money? As a business person, I really don’t care about how much Twitter’s founders and investors will make (which is no doubt a heck of a lot more than I ever will). I care about my favorite radio station – WIFM – better known as What’s in It For Me? The two questions are not unrelated. For Twitter to make money, it will almost certainly need a base of advertisers who want access to it’s audience. There may be other revenue streams that the creative minds at Twitter will conceive over time, including some form of CPM, CPC, CPA or CPL. That advertising opportunity, however, does not exist on today’s Twitter. Yet, advertisers are trying to leverage Twitter now to increase sales.
Is there a way to model the ROI from investing in a presence on Twitter as it exists today? Let me suggest that there is and provide the approach and calculations below.
First, we need to understand what Twitter is and how its audience uses it. I view Twitter as multithreaded Internet chat. It’s like being in a coffee house with conversations going on all around you and choosing which ones you want to participate in. Moreover, the form of communication – 140 characters – lends itself mainly to status updates and quick bursts of timely information. Twitter is at its best when it is used to communicate information whose value deteriorates at a rapid rate. It particularly does because the information is streamed – and the stream flys by so fast that anything much older than a few hours is effectively lost unless you actively search for it in historical tweets – which is a change in consumer behavior that few have associated with Twitter yet. Thus, Twitter in its near real-time form is perfect for businesses and business models whose information quality degrades quickly – e.g. stock prices, airline ticket prices and availability, exploding special offers/deals (an offer that has a specified end date), employment opportunities, immediate local expiring opportunities (e.g. ticket availability at the stadium just before a big game), among others.
So let’s say you are an online travel agency that sets up and maintains a Twitter account. Do you care? Is it worth the effort to put specials out through that mechanism? Let’s look at some numbers. Here are the number of followers of various travel agency Twitter accounts:
- Expedia – 13,281
- Orbitz – 14,087
- Travelocity – 16,133
- Cheapoair – 1,925
- Vayama – 1,193
- Travelzoo – 8,020
- Priceline – 16,212
- Hotwire – 3,769
Assume that you have a Twitter account with 15,000 followers (the average of the big sites) where you post daily specials on travel. They are obviously interested in the opportunities – so we have an audience that, relatively speaking, is highly motivated to purchase if they can find the deal they want. As active participants, they are likely to forward information to friends and family who have a similar interest – so they retweet or they forward via direct message. I call this the amplification effect.
The key question to consider in this is what percentage of people pass the information along and then, subsequently, what percentage of people subsequently retweet to the next level? We actually have good data on this from word-of-mouth marketing campaigns we have run for some of our travel industry clients and from Twitter follower data. There is also research (see Norman, A. T., and Russell, C. A. (2006). The pass-along effect: Investigating word-of-mouth effects on online survey procedures. Journal of Computer-Mediated Communication, 11(4), article 10. http://jcmc.indiana.edu/vol11/issue4/norman.html) that aligns well with our experience.
More in the next post.