TrafficGuard for Apps
Higher user acquisition with lower costs? Go on then.
To stand out in crowded app stores, marketers need to squeeze as much value from their ad budgets as possible. Fraud protection is the place to start.
Ad budgets and UA efforts are at risk...
Ad fraud is the enemy of ambitious user acquisition strategies. Bots and bad guys are targeting the app industry because of its big budgets and huge market, and it’s having some serious consequences. Apps are at risk of hampered user acquisition (as fraudulent clicks don’t convert), decreased ad budgets which have been drained by IVT, and misattribution when clicks and conversions are attributed to the wrong source.
Give your user acquisition efforts some oomph.
App marketers are often targeted on their UA metrics, so it’s worth paying attention to.
TrafficGuard verifies every advertising engagement, giving you complete trust and confidence in the data you use to drive performance and get the results you deserve.
So much more than your MMP.
Trusting MMP’s attribution data alone may leave you open to key vulnerabilities, as their anti-fraud tools only operate at or after the app install attribution, not the impression or click level.
Using Trafficguard as a complement, not an alternative, to your MMP ensures installs are correctly attributed and protected from the effects of invalid traffic.
TrafficGuard + Your MMP = 💸❤📈️
Stopping the misattribution snowball.
A single install attributed to the wrong source will inflate the value of that source not just by one install, but by the value of all the subsequent events of that new user. This leads marketers to underinvest in the channels that deliver the best results, restricting their advertising ROI.
With fraud prevention in place, bots can’t trick advertisers into wrongly attributing installs to themselves. The snowball is melted before it can get any bigger, and marketers can have total faith in the validity of their attribution data.
Ad fraud? In my industry?
Afraid so. Check out our CRO’s tell-all webinar exploring bots and baddies in the app industry.
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