October 7th, 2010
My first title for this post was “top 5 ad-network mistakes”… then I realized that ad-network was a “bad” term… so intead I’m going to refer to a “media startup”. I’ll put networks, DSPs, trade-desks, dynamic creative providers… any company that buys & sells media (*cough* … looks like a network.. *cough*) under this new “media startup” bucket.
It seems every young media startup I talk to keeps making the same mistakes over and over. Well, here goes in no particular order (even though they are numbered #1-#5) my list of things every startup needs to watch out for… maybe I can help prevent someone from making the same mistake!
#1 – Credit / Payment Terms
A $1M insertion order is amazing.
A $1M insertion order where you get paid net-90 but you pay out net-30 can kill your business.
A $1M insertion order where you get paid net-60 but you pay out net-60… can also kill your business.
Here’s the problem. Agency margins have been on a nose dive downwards for years now. One of the ways agencies drive up their profitability by paying everybody late and making a little extra $ on the interest they earn by keeping the money in their bank account. Even if you think the payment terms line up, just one client that sits on their check for too long can be tdetrimental to your business. If you don’t pay your big sellers they cut you off, killing your network. If you push to hard on the agency, they cut you out of next quarter’s budget.
Proper float & credit management is a must for any network. Have an open conversation with agencies and understand when you can realistically expect to be paid, and then make sure there’s always enough cash in the bank to pay sellers and publishers (and employees!). Many a media startup has gone out of business by badly managing their float.
#2 – Boobs
Did you know that perezhilton.com, wwtdd.com and idontlikeyouinthatway.com are present in some shape or form on every single exchange and supply platform from the aggregators (PubMatic, Rubicon, Admeld, OpenX, etc.) to the big guys (Right Media, Google)? These “Entertainment” sites make liberal usage of pictures of scantily clad celebrities, their sexcapades and lots of other inappropriate content.
Now on a normal remarketing campaign the performance might be great, but there’s nothing worse than an angry email from your advertiser because your ads just showed up next to this page.
In the best case your reputation just took a little hit. In the worst case your advertisers simply refuse to pay out multi-hundred thousand dollar budget amounts…. ouch.
It’s imperative that a network or buying desk has a strategy in place for managing inappropriate and sensitive content. Don’t assume that the “Entertainment” channel is fun sites that you can run any advertiser on… you’ll be in serious trouble if you do. On RTB you obviously get the URL, so use it. Supply platforms also have various forms of brand protection… Advertising online is kind of like teenage sex… first take a sex-ed class to learn what the forms of protection are … and then don’t forget to use protection in practice!
#3 – Malvertisements
Here’s a very common story. One of your sales guys comes in super excited… he just closed an *amazing* deal. $0.75 CPM, no goals, all european countries for a major brand-name advertiser with a huge $100k budget. To top it off, the buyer will pre-pay $50k up front and promises net-15 payment terms.
The deal goes live… and within 24-hours exchanges shut you down and all of your publishers turn off their tags because for some strange reason all of their visitors are complaining that you are trying to install some sort of trojan/malware program with your ads
Yep, there’s bad guys out there that will pay you serious cash to run ads that are really viruses in disguise. When you load them from the office they behave. Enter night-time and they turn into nasty beasts that will cost you publisher relationships, a bad rap with Sandi and potential scrutiny from the feds.
General rule of thumb… if the deal is too good to be true, it probably is. Google has done a terrific job setting up a website to educate the industry about this on www.anti-malvertising.com. Make sure every single one of your sales & ops staff reads this entire site in detail.
#4 – Not Focusing on Sales
If you are building something that’s amazing & scientific, it’s probably the wrong thing to build. No seriously… If you have even one PhD on staff you’re probably doing something wrong.
Quarter after quarter at Right Media I’d work with a team of engineers to push out improvements & features to the optimization system to increase efficiency, ROI & spend. You’d think that in a business running several billion ads a day that this would be the single largest driver of company revenue. Yet… one sales guy at the original Right Media “Remix” Ad-Network single-handedly blew me out of the water one quarter with a single insertion order… and the deal didn’t even use optimization.
Relationships matter… a lot. Not every buyer out there just wants to buy into a magic black box that will auto-magically uber-optimize their life. Advertising is, believe it or not, about more than just clicks & conversions. There’s an inherent understanding of the target audience and the media and buyers want to work with companies that understand how they are thinking and who they are looking for. This means that the buyer wants to talk to someone he can relate to, who listens to him and who he can trust.
This is why every media startup needs a strong sales team. You might have the greatest technology in the world, but if you can’t sell it, it’s not going to get you far. The smart guy in the room? They’re the ones that hire the sales guy that will close the multi-million $ deal. [The above mentioned sales guy went to work for Invite Media, now of course a Google company...]
#5 – Over building technology
To some extent this is a follow-up on the previous point, but so many companies I talk to seriously over-build their technology. The market today is simple. Yes, we will definitely be in a world one day with “traders” sitting at terminals with tickers and fancy secondary future markets and involvement from some of Wall St’s finest…. just not today.
Today, one great trafficker/optimization analyst can beat almost any algorithm out there A team of 5 temps working for a week can apply categorizations to the top 1000 internet sites with similar accuracy to the fanciest semantic engine. A smart BD guy can buy KBB data w/out a deep API integration to a data exchange. A buying strategy of “remarketing” will out-perform any other campaign strategy or behavioral data by at least 10x.
Now don’t get me wrong… there is definitely a market for technology and technology is the only way in which you take the behaviors of brilliant individuals and scale them to be a hundred million $ business. Here’s the problem, most companies start by building technology, then trying to apply it. If you want to be a successful media business you should do the opposite. Hire some great people, watch how they operate, then build technology to automate what they do.
The above 5 are common mistakes… but there’s one very simple rule of thumb any and every CEO, investor or board member can use to judge the quality of a media startup.
If you ain’t making money, you ain’t doing it right.
Seriously. More than 3 months old with 0 revenue? Likely to fail. Low revenue with high burn? Doomed to fail. The simple answer is it’s easy to get at least one agency to buy in as an early adopter and throw you some $ to “test”. If you can’t do this, you’re doing something wrong!
PS: Shameless self-promotional use of the blog here but… AppNexus is HIRING!!
September 13th, 2007
Many publishers either don’t have a strategy for maximizing network revenue or use aging technies such as daisy-chaining to
Out of all the publishers that I’ve talked to many don’t have a solid strategy for maximizing revenue from ad-networks. Many simply don’t understand how networks price, since most are black-boxes that don’t publish how they optimize and choose which ads to display. Yet, there are a couple factors that I find can be large drivers of revenue.
The more times an individual user sees an ad, the less likely he is to respond to it. Ok, seems obvious right? What you may not realize is exactly how quickly user response to an individual ad drops. The following graph is fictitious but representative of the normal response curve of a user on a single site to repeatedly seeing the same ad.
What the above shows is that if you are to maximize revenue you need to start thinking about users and not impressions. A user that’s been on your site for hours and has seen a hundred ads is far less valuable than someone who just logged-on.
Of course every ad-network will tell you that they have a large # of advertisers and deals and that you shouldn’t worry about such things — but lets not forget the Pareto Principle, also known as the 80/20 rule. A small percentage of top advertisers will generate the majority of revenue (and hence higher rates). What that means is that each ad-network will only have one or a couple high CPM ads.
Hence the effective CPM that you receive per user from a network declines as that network continues to see him over and over again. The larger the network the slower the decline, but each will look similar — here’s a rather rough sketch of what various network payout look like (again, numbers are hypothetical, but shape of graph will generally be correct).
Obviously daisy-chaining will not work in this situation as both the medium and large networks have paying ads for each individual ad-view. In the hypothetical example above, you would want an individual user to see the following sequence of ads to maximize revenue:
Comparing the effective CPM of each network individually versus optimized together:
What you see is that you can vastly increase your CPMs by distributing your networks. Now — although these are fictional numbers — the concepts are real and they work. So how do you do it? Rather simple!
It’s impossible to allocate impressions on a per view basis as I did above so we must rely on a little bit of approximation. The way to do this is to setup multiple placements or zones with your ad-network and then to frequency cap them individually within your own adserver. The above could look something like this:
The key here is not to over-complicate. Sure, a Myspace, Facebook or Bebo may create hundreds of different placements each with different caps and priorities, but there are two reasons you shouldn’t
- It’s incredibly resource intensive to manage
- You don’t have enough inventory
Each placement needs to run a minimum amount of volume otherwise pulling out the effective CPM will be nearly impossible. A lot of pricing is based around user response to ads — eg CPC or CPA based pricing. Since clicks and conversions are rare events you need to have enough volume in each placement to get a predictable effective CPM. On CPC networks you can probably get away with a couple thousand impressions per placement per day but on CPA you’ll want to go closer to ten to twenty thousand.
There is some art here as you will have to update both the frequency caps and the pricing on your placements regularly. The first couple times chances are you’ll see your network cpms fluctuate as you play with the caps & inventory allocations but as you get a hang of it you should gain some serious lift.
Enough for today — next, how to effectively target network placements to maximize revenue.
February 28th, 2007
So you own a small site, you have about 5000 page views a day, and you start thinking to yourself, “Hey, it’d be awesome if I could make some money off of my great website.” So you start shopping around for advertisers and quickly get the sense that all small sites work primarily with google. Now why would this be? There are four key ways in which advertisers can monetize your inventory:
- Branded Display — e.g. Ad.com, Niche-networks
- Contextual — e.g. Google Adsense, Yahoo, Quigo
- Behavioral — e.g. Tribal Fusion, Tacoda
- Performance Display — e.g. Fastclick/Valueclick, CPA Empire
Before I delve into these into more detail, everyone has to understand something: advertising is all about reaching relevant eyeballs. Whatever the method used, the end goal is the same — if I’m selling sexy shoes, I want people to buy sexy shoes. I can go about this a couple ways but at the end of the day, I’m going to compare the amount of money I spent on advertising and the amount of profit I made from the sexy shoes that I sold. The smaller and the easier it is to purchase my good, the more likely I am going to be focused on ROI & performance. If I’m Netflix selling $4.99 subscriptions, it’s easy to track who signed up from where as I will have tens of thousands of people signing up per month. On the other hand, it’s difficult for Ford to track ad campaign performance… it’s hard to prove you bought a new Ford F150 because you saw an ad for it on automotive.com.
Ok… so eyeballs it is… lets look at the four methods above now:
Brand: If your site is good enough to be on the brand wagon you’re in luck. Branded advertisers have high standards on the inventory they will run on. The demand that it is relevant to their campaigns (e.g. Ford will want to run only on Auto sites) and they are willing to pay a premium to get there. Campaigns are generally CPM with little or no concern for performance. The problem here is that unless a site’s users are extremely desireable it’s hard for a site with low volume to get onto a branded site list. Ford wants to sell cars — to do this they want to find car buyers and associate the ‘Ford’ brand with their target audience. They might run campaigns for a new sexy sportscar on gaming sites and ads for more fuel efficient sedans on the New York Times travel section (who knows?).
Contextual: Thanks to Google this has become the big mama of online advertising. Contextual engines scrape your pages content and choose advertisers that match the content. Got a site about shoes, expect to see shoe advertisements. Now, going back to the eyeball idea, if I’m selling shoes, I want people interested in shoes. If you have a site that reviews the latest and sexiest shoes, then I will want my ad on there. On the other hand, if you have a personal blog and are complaining about how the shoe salesman smelled bad at the mall today, I probably don’t want my ad on your page. Contextual rocks on relevant page content and sucks on most Web 2.0 sites. When was the last time you saw a relevant text ad on Myspace.com?
Behavioral: Unlike Brand and Contextual, this is the first type of ad where we don’t care much at all about the page-content. We have an idea of what the users eyeballs are like and want to show him ads that he is going to enjoy the most. If you’re not famiiar with behavioral networks, read my post here. The biggest challenge here is for a site to get INTO the behavioral network. Even though for the purposes of serving one ad they don’t care what your site content is like, they will most surely want to use your site and your users to expand their reach & user information databases. Tribal Fusion, for example, requires 2k uniques per day, “professional site design” and a “highly active user-base”.
Performance Banners: Ok, so I saved my favorite (and perhaps worst for a small site) for last. Performance based advertising means that somebody is tracking clicks and/or conversions (actions) on their campaign and either only paying out on an actual “action” or adjusting bids on different sites according to the performance. Don’t be fooled by networks that pay you on a ‘CPM’, unless the ads they are showing are brand advertisements, somebody somewhere is tracking ROI & performance, and it’s impacting the CPM you’re getting paid. So why doesn’t this work for small sites you may ask? Well, long story short… small sites suck. Ok, it’s a bit of an exaggeration, small sites suck for performance would be a more accurate statement.
Lets go back to eyeballs. Your site has eyeballs, and I’m going to pay you everytime one of your eyeballs buys a pair of sexy shoes. Lets say the shoes cost $30, my production cost is $0.50 (yay for sweat shops!) so I’m willing to pay you $14.50 for every person from your site that buys one of my pairs of sexy shoes. Now there is one other advertiser in the network I’m working with he is selling sports gear (hats and stuff) and is willing to pay $10.00 to the publisher for every purchase.
Now, when a users comes to your site, which ad should the network show? Lets say your site is brand new to the network. Well, this network has no contextual technology to tell me what the site is about and he also doesn’t have a behavioral engine, so what can the network do? The only thing he can, test his campaigns on the site and learn what the performance is like.
Ok, for the next 5000 impressions (1k unique users?) the network randomly chooses between the sexy shoes and the sports paraphernalia. Now what… what do you think the chances are that somebody actually bought a pair of shoes or a hat? On the average site, I would imagine, right around 5-10%. Think about it, if the average CPM on your site is around ~$0.50, and this offer were to be competitive, you shouldn’t be expecting a single conversion until you’ve run at least 30,000 impressions. For better statistical accuracy on the performance of this campaign on one site, think more like 300,000 impressions. Starting to see why small sites suck? The amount of volume necessary to ‘optimize’ the average campaign is simply too much for the measly 5k impressions a day. Imagine if the network had 500 campaigns. How can learning be done on 500 campaigns with just 5000 impressions a day?
Of course there are various techniques to limit the amount of learning that needs to be done, but the fact remains that significant volume must be sent to an performance advertiser before one can get a good idea of the actual performance.
So, what should the small site guy do? Think about your eyeballs & page content. Is your content very relevant to the eyeballs? Then go contextual. Do you have particularly valuable eyeballs? Go for behavioral or brand. None of the above? Try performance based networks, but don’t expect good CPMs until you get high enough volume for some sort of learning to be done.
Next up? Not sure, probably some thoughts on learning techniques, merging behavioral and performance, and other ideas…