Putting viewability to real use in RTB

Harley Norrgren, Head of Analytics at Infectious Media, responds to a recent AdExchanger article on viewability.

In his recent article in Ad Exchanger, Adrian Tompsett wrote about how working with viewability metrics requires changes to attribution models, rather than just CPMs. The latter solution might not provide any incremental value for the advertiser and can be exploited to increase margins for the media buyer; whereas the former provides a legitimate way to use the new metric as a means of getting closer to the true value of an impression.

The next real question for viewability seems to be; how can the demand side put it to use as an optimisation metric without simply reporting it back and adjusting CPMs accordingly?

There is huge potential for online display to benefit from optimisation towards viewability as it could provide legitimacy to the view conversion, also getting the ball rolling for wider attribution discussions. The knock on effects of viewability are also far reaching; informing smarter creative and site design as well as combatting fraud. The bad news is that this can only start by getting the advertisers to buy in to viewability at enough scale to get the industry moving and that media buyers currently need custom data integrations to make optimised viewability a reality.

However, once your impression level feed is in place, the good news is that you can make massive strides in campaign performance when measured against post-viewable conversions instead of post view conversions.

By optimising towards post-viewable conversions across a handful of our more digitally mature advertisers, we found that even the most basic of manual optimisation techniques could increase the proportion of post-viewable conversions by between 60 and 80% compared to the start of the campaign.

Good post-viewable CPAs and transparent pricing can help to encourage advertisers to switch away from the last view and, with the potential to optimise algorithmically towards post-viewable conversions quickly becoming a reality, I’m confident that the technology is both scalable and exciting enough to lead the charge against poor measurement and even poorer media buying decisions.

As Adrian summed up, viewability shouldn’t be just a standalone KPI, rather a tool for unlocking more effective media. I couldn’t agree more, and would like to add that it’s happening already; viewability will soon be available via many larger buying platforms and early adopters are already optimising towards post-viewable conversions as part of standard attribution models. If you’ve lost faith in post-view, then it’s time you had a look at post-viewable.

Making the case for banners

Rocco de Filippis is an intern on the client services team.  Rocco studied Behavioural Economics at University of Maastricht and the Sapienza University in Rome.  He spends much of his working day at Infectious Media analysing and optimising campaign performance.

As other forms of online advertising develop, the role and effectiveness of display online banners has been a source of much debate. Research (Dreze and Hussherr 2003; Ilfeld and Winer 2002; Internet Advertising Bureau 1997; Sherman and Deighton 2001) has shown that exposure to banner advertising leads to increased brand awareness, purchase intention, and site visits but the relationship between advertising exposure and actual purchase is still uncertain.

The main problem is “how do we measure the effectiveness of a banner?” The first and easiest way is through exposure based metrics: computing the number of impressions served gives an idea of the campaign’s reach. However, many advertisers prefer to allocate budget based on the sales target of the campaign rather than purely on its reach. Since they are not directly linked to sales volume, the number of impressions served has not been considered a good indicator for display advertising effectiveness. The next measurement evolution for banners, was then to look at click-through rates (number of clicks per impression served), but why is a click any better than reach? After all a click simply means a user has visited the advertiser’s webpage, but we know only a small number of these visitors actually go on to buy.   We then come to CPA (Cost Per Action) commonly considered the most reliable indicator for the efficiency of an online advertising campaign.  It is my opinion that CPA has its place but that it shouldn’t be considered as a measurement panacea for all banner advertising.

In few years there has been a proliferation of online advertising vehicles, so that today we can choose from:
* Banner Ads
* Mobile
* Paid-search (PPC) and SEO
* E-mail
* Video
* Social Media

It is my contention that, each has a different function. The time gap between becoming aware of a product and buying it can be quite long, and along this path to purchase different display ad formats can perform better than others: Social media ads can spread awareness among friend networks: Video ads are more suitable in convincing someone of the attractiveness of a product; SEO optimization can enhance the likelihood of a direct conversion, but what about banners?

Have you ever seen this picture?

It was shot in Burkina-Faso, one of the poorest countries in Africa, and one of the poorest countries on the planet. There are several examples all over the World of similar Coca Cola boards placed in villages where people are so poor they cannot afford to buy water and food, not to mention Coke…so why does Coca Cola spend money on ads which have a likely conversion to purchase of almost 0%?  I believe the answer is that they are not aiming for conversions at this stage of the ad-process.

In order to understand and measure the effectiveness of an advertising campaign a number of advertising hierarchy effect models have been developed. The most basic and interesting in my opinion is the Lavidge and Steiner’s one (1961) since it links the different steps a customer takes with three main psychological stages (see diagram below).  The idea is that rather than directly jumping to a purchase, consumers have to fulfil each step before moving to the next psychological stage. The gap between one step and the next can be short but reaching the next psychological stage generally requires a longer time.

This is why certain ad types perform better than others during a specific stage or step. There isn’t an absolute “best ad”, but: banners tend to be better than SEO in the cognitive stage, while video ads perform better in the affective stage. Using CPA as the only indicator for the efficiency of an online campaign will actually maximize the likelihood of a purchase but only once that the user is already in the Behaviour Stage. Getting rid of banners is an easy way to lose a very big slice of the pie, represented by users that potentially could buy the product but without banners may not even know it exists. I believe the efficiency of banner ads can go even far beyond this model: in fact this is a model based on “consciousness”, since in every stage described something is happening at a conscious level…but what about our sub-conscious? In the last 10 years, studies on the brain activity has been widely quoted in the academic and marketing frameworks: As part of my academic studies I looked at Neuro-economics and the first thing you learn about the brain is that we do not know the brain We know what happens at a conscious level which is only 2% of our brain activity, but the remaining 98% is the “un-explored sub-conscious” which accounts for almost all of our decisions. When we choose something, we think we are evaluating data to take the best decision but actually most of our mind is already made-up and we are just fine-tuning what our sub-conscious has previously evaluated using a huge amounts of data (most of which are images and keywords) stored through perceptions in some “un-reachable” part of the brain. Data that we aren’t even aware of but that have had an impact upon us.

That’s why it is more likely that a man from Burkina-Faso will buy Coca Cola rather than any other soda. That’s why it is wrong and reductive to measure the efficiency of banner ads using a last-click attribution model (see the previous blog article from Harley on this issue) or to say expenditure on banner ads should be reduced.  For an advertiser wanting to maximize the efficiency of his/her campaigns it is important to understand the synergies between adverts. CPA with a last click-attribution model will often show SEO and PPC to be the best performing advertising vehicles. Using this logic, it then seems wise for advertisers to transfer all their funds to this kind of advertising. Nevertheless, by doing so, it is my conjecture that they will observe a drop in the overall conversions as they lose those customers in the Cognitive and Affective stages. SEO and PPC seem to perform better than other online advertising simply because current measurement practice is completely tailored to them. A smart advertiser will use mix of online advertising,  measured in different ways. CPA can be used at a “universal” indicator but then the attribution model must change appropriately to take into account how every different advert along the path to purchase has contributed to the actual sale: the focus has to be redirected to the big picture rather than on a single vehicle of advertisement.

to put it another way, strategic planning is pivotal to maximize the efficiency of a campaign: you can build the most beautiful table with a surface of ebony but if you want the table to stand properly, you should not forget to take care of the legs as well.

Lies, Damned Lies

As technology and data shape the next wave of digital media buying, the need to approach the entire process from a statistical mindset is growing in importance. In the not too distant future it won’t be surprising for a day in the life of a digital media buyer (or trader should I say?!) working on a response brief at a typical agency to involve monitoring campaigns on multiple trading systems whilst working with a team of analysts, crunching campaign data using analysis packages such as R.

Google Chief Economist Hal Varian in an interview for The McKinsey Quarterly earlier in the year mentioned that statisticians will be the sexy job in the next ten years and with Numbers pulling in prime time audiences on TV it certainly seems that he’s not too far from the truth. This could happen a lot faster in the quickly evolving media buying industry and gazing into a crystal ball reveals that skill sets will also need to also evolve to keep pace with the technology infrastructure that is powering the industry.  Gone will be the Head of Trading whose lunch ability knows no bounds to be replaced by the Head of Data whose skill and value will be in interpreting the vast amounts of data that agencies will be generating through their trading platforms, and developing meaningful insights from this. Think of it as being more Wall Street (minus the suits of course!) than Mad Men. All in all, a combination not just of statistical techniques but also marketing know-how will be an integral part of the new agency product. It doesn’t take a huge amount of insight to spot the increasing importance of data but what does it mean on a practical level for your average digital media agency? Using statistical techniques to help analyse and optimise campaigns has multiple benefits ranging from improved ROI for advertisers through to greater operational efficiency for media agencies. In short it’s in everyones interest.

Infectious, as a ‘new breed’ agency has been built around this core belief. Our underlying infrastructure, skillsets and services are designed to get the most from this new world. It will be interesting to see how quickly the wider agency community embraces this shift.

What’s next for Google?

There’s an article on Business Insider today which in turn quotes a great Business Week article from 2000 that insightfully asked ‘How will Google ever make money?’

The crux of the article is this:

‘The company’s adamant refusal to use banner or other graphical ads eliminates what is the most lucrative income stream for rival search engines. Although Google does have other revenue sources, such as licensing and text-based advertisements, the privately held company’s business remains limited compared with its competitors.’

This is interesting for a couple of very different reasons.  Firstly, as a historical reminder that Google flipped the industry on it’s head in breathtaking fashion.  They did away with the predominant image based ad, borrowing the business model of Overture to serve text ads linked to an auction pricing model and took something new to market.  At the time (as a media buyer) I certainly didn’t believe it would work, preferring, instead, the glamour of AltaVista (RIP) banner advertising to the three line text ad on Google.  Fast forward to 2009 and Google is the biggest ‘media owner’ in the world, generating $6bn of advertising revenue per quarter.

The second interesting point to come out of the Business Insider article is linked to comments made recently by Eric Schmidt, speaking at the Morgan Stanley technology conference.  When asked about where Googles growth in revenues would come from, he replied:

‘Where is [our] next source of revenue? [The] next source is current business functioning better. Next and adjacent is a set of display businesses and an exchange being built from DoubleClick business.’

A slight change of tactics from their stance back in 2000 but the reality is that the market for text ads is maturing and growth is levelling off.

There are few details on the Google exchange product but this time they have bought the business that they will use to to leverage display (Doubleclick), instead of borrowing the model and being sued at a later date. So what could this product look like, given that Schmidt sees it as so crucial to revenues going forward?  Well, instead of thinking about Google as a purveyor of text ads on the search results page, think about them as the largest owner of intent data in the world through their search engine.  One way they’ve used this intent data is to serve text ads against search tems, but this is only one execution of an ad against a hugely powerful data set.  Through a display media exchange it becomes possible to intelligently  serve display ads against that data on any site, which will open up a huge new market to Google in highly targeted display advertising.

To make this a reality, a big challenge for Google to overcome is the issue of data privacy. Two weeks ago Google made a significant announcement around a basic ‘behavioural’ targeting product across You Tube and its Ad Sense network. It was only a matter of time before this happpened, but they have clearly gone to great lengths to introduce it in a simple, (relatively) transparent and cautious way. The media whipped up an ‘information privacy’ storm around Phorm in the UK, and it seems that Google may have been waiting for that to die down a little before dipping their toe in the water in a very controlled way (with plenty of user control and opt out-ability). The obvious omission from the announcement was the use of Googles search data in the targeting formula.  Make no mistake, this will come in the future (Yahoo! announced their own Search/Behavioral retargeting solution last week), but Google may be waiting for people to become comfortable with this simple behavioral model first, before ramping up the sophistication with the reams of data they hold.

Much of this is still speculation, as things are heavily under wraps, but the Google Exchange isn’t too far away and there’s little doubt they have both the data and the distribution channel to make this the market leading product in display, flipping the market back on its feet and with display advertising on a more even footing once again.

We’d love to hear what you think…

Binary Planning

I like data.

It has stood me in good stead in this industry as I’m sure it has many others. Our campaigns produce tons of the stuff and increasingly agencies are reliant on companies that process and present this data to push our thinking forward such as Atlas and Doubleclick.

But data isn’t (and shouldn’t be) the be all and end all. It’s easy to forget that data is a product of something that has already happened and as media planners we’re often trying to find something new, especially in digital. Take search for instance, the ultimate data driven medium. We analyse search patterns and use algorithms to determine bid strategies; all based on what has happened in the past. There’s nothing wrong with this but it can be a dangerous obsession and lead agencies to a one dimensional and commoditised offering.

To illustrate this point, I’ve seen and given hundreds of presentations that are based around a marketing funnel. Where data driven techniques are at their most potent is in pulling customers through that funnel and converting demand that is already there; think PPC search and retargeting. But this is an ever decreasing circle as it does nothing to actually create demand for a product or brand, it is just squeezing the most out of demand that’s already there.

Advising a brand on how to act strategically to create demand requires a different type of thinking. This is insight driven, takes an understanding of a advertisers business, their product, their brand, their market and shock horror: ‘people’ and how they behave. There shouldn’t be a spreadsheet in sight for planning purposes, no formulas or macros and definitely no definitive answers. Overlaying and translating all this thinking into media terms is a wonderful exercise and for us is what media planning is really about.

So as a digital media agency, the skill sets you need for a complete offering are hugely diverse and need truly different people, but that’s what agencies should be about:- a collection of people with different specialisms that integrate seamlessly for a client. It can be difficult to reconcile some of these skillsets but these are our challenges. Data skills are clearly hugely important but if that’s all it’s about then perhaps it’s time we started employing monkeys and bought some typewriters.