Measurement Remains a Challenge: Q&A with Noelia Amoedo, mediasmart

Ad fraud has found its way into the world of mobile. In Europe, three-quarters of mobile app marketers cite ad fraud as their top concern, followed closely by attribution. In this Q&A with ExchangeWire, Noelia Amoedo (pictured below), CEO, mediasmart, discusses measurement and attribution in the mobile ecosystem, arguing for transparency as a way to control attribution and as a protection against fraud.

Where are we at with mobile measurement?

Measurement still remains a challenge for our industry. On one hand many media buyers believe “mobile measurement doesn’t work”, when the technology required for proper mobile measurement does in fact exist. The problem is that the tools considered “standard” by many media buyers are desktop-first measurement solutions, which are simply not fit-for-purpose, especially in the in-app environment.

Noelia Amoedo, mediasmart

Campaign optimisation can be achieved by measuring viewability, engagement and conversions, but any solution used for measurement needs to take into account the technical specifics of the mobile environments. These include for example, a lack of third party cookies on iphones or ipads, and no cookies whatsoever in apps, plus an absence of reliable IP addresses for tracking on cellular connections.

Effective campaign measurement is ultimately a question of trusting the right technology providers. The ones that have the right technical solutions to measure in mobile right now are mobile specialists, but they are often not considered “standard” by many buyers. And those that are considered as standard, have not evolved their technology enough for it to work well in the mobile environment. There’s some way to go until all the industry players are aligned.

On the other hand, when mobile first attribution tools are used, which is often when promoting mobile apps, it is key for advertisers to protect themselves from mobile attribution fraud. Attribution fraud exists in the non-mobile world also, of course, but it has taken a new form in the in-app environment; companies are finding very creative ways of attributing themselves application installs and engagements without having to even run a campaign. Fighting this type of attribution fraud is definitely a challenge.

How can you produce transparent attribution data that your clients can rely on?

Well, it is interesting that you mention transparency, because the biggest companies in the advertising world like Facebook and Google, aren’t transparent about their attribution methods. Despite this I believe transparency is important for advertisers to a) control the attribution rules and b) protect themselves from attribution fraud.

Advertisers should have the ability to control attribution models (post view versus post click, for example) as well as to define attribution windows for each, as what makes sense may vary a lot depending on the actual product or service being offered, or the channel in which it is being promoted. An attribution window that makes no sense on web-based products, for example, may be perfectly fine in an app. Or a fingerprinting model of attribution may make sense for users that are browsing on WiFi but not on a cellular connection. By trialling various attribution models you can analyse and test what works best for your product or service, and you should have the necessary transparency and levers in the attribution system to do so.

As I mentioned before, attribution fraud, specifically within the apps world, is a problem, and advertisers should work with trusted partners that provide the latest product features around attribution fraud prevention, and catch fraud automatically. But also, having transparent data and the necessary tools to navigate through it is what gives advertisers the ultimate control, and they should always demand it. As an advertiser you can demand the most granular information (access to session level data or real time info based on pixels and server calls) and/or reports that you drill down by hour, time span between click and conversion, etc. – and this will make it possible for you to identify suspicious behaviour.

Last but not least, a good way for advertisers to prevent fraud is to always be clear on their baseline. Running campaigns that don’t advertise your product – placebo campaigns – can help you understand the KPIs your organic users deliver, and non-organic channels that deliver KPIs that seem too good to be true, are probably just that.

What do you think would improve the ad tech ecosystem?

I think the incentives and pricing models need to change in order to reward companies that invest in proprietary technology – especially when it comes to the area of the ecosystem I know best: media buying. Companies that create platforms that allow advertisers to buy media in a highly effective way, and squeeze engagement from every single impression should really be given more recognition. I feel that today, a lot of the “ad tech” ecosystem is not so much about tech.

When advertisers focused on performance invest in advertising, companies that focus on developing great technology to effectively buy programmatically, with sophisticated algorithms that manage data to maximize engagement should be the winners. But instead, the winners tend to be those who take advantage of loopholes in attribution systems and play these to their advantage through attribution fraud.

When agencies and advertisers working with brand campaigns focus on low percentages of “media investment” as the criteria to choose a DSP, they often choose companies who are able to charge a lower percentage because they outsource the technology. The result is often a long chain of companies between the advertiser and the publisher, where advertisers end up paying more, without direct access to the underlying technology.

It saddens me to see an ecosystem that rewards those that bring the least value to it, and it infuriates me to see an ecosystem that rewards those who are plainly cheating. Education will hopefully solve this, but how long it takes remains to be seen.

What is your experience of gender diversity in the Spanish ad tech industry? As co-founder and CEO of media smart – is that an issue you are aware of and are making specific efforts at addressing in your company?

Well, I studied physics and engineering and since I was at school I am used to being surrounded by more men than women. In my professional life I have not been very conscious of my gender, except in a couple of isolated cases. Maybe that is very naïve of me, but I have professional relationships with people and that is independent of whether they are men or women. That being said, statistics cannot be ignored and women in leadership positions are still a minority. In Spain in particular, I think the industry overall is making an effort. I personally have had a lot of media exposure for being a woman entrepreneur, for example, and as younger women become more and more aware of other women in leadership positions out there, I am sure the trend is going to continue to change in the right direction.

In the digital world we have the advantage of being able to work remotely, and that helps reconcile your personal and professional life. I think this is one of the ways in which mediasmart is helping. We have a very flexible culture – both for men and women by the way – whereby we value a job well done, and not so much where or when exactly it is done.

I want to think that leadership skills and the ability to bring value to a team does not depend on your gender. The value is in each of us. There is a wide range of skills that can make you successful and none of them is driven by gender. Of course, it is always positive to have a diverse team where different members complement each other, and our approach is to simply look for the right people for each role, and not to necessarily fill a percentage. At mediasmart today 40% of us are women, and that could very easily go up with our next hire. Not sure where we stand versus the average in a tech start up, but that’s how we got there.

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