Posts Tagged ‘Hotwire’
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.