Enabling postbacks or sending natural in-app occasions is a vital a part of what makes our retargeting campaigns so profitable. Whereas it might look like a giant step for an app writer to open up their whole consumer database for retargeting, it’s utterly protected and a key a part of how we will ship unmatched retargeting efficiency.\

Table of Content

• organic in-app events
• buy cheap organic app installs
• shopping app ranking
• android app reviews

Some phrases, and why share natural knowledge

As an app marketer, you’re most likely conversant in the concept of enabling post-backs or sharing natural in-app occasions. Our inner nomenclature for that is the “knowledge stream” because it contains all natural knowledge and site visitors collected by your app. The first motive we encourage our purchasers to share their knowledge stream with us is as a result of it permits us to run dynamic cohorts as an alternative of static ones.

Static cohorts are merely lists of customers exported from the information stream and shared along with your retargeting associate. These are up to date internally and shared on an as-needed foundation. The issue right here is that if a writer’s lists are old-fashioned, then we could also be working with knowledge that’s additionally old-fashioned. For instance, if a consumer shares a static consumer listing with us that’s a 12 months, a couple of months or perhaps a few weeks previous, we don’t know if the consumer conduct remains to be related as we’re not capable of confirm the exercise in actual time. On this case, retargeting campaigns with old-fashioned consumer knowledge gained’t be practically as impactful as these run with dynamic cohorts.‍‍

Alternatively, dynamic cohorts replace in actual time, permitting Adikteev to optimize for consumer conduct immediately. It’s probably the most environment friendly method to goal customers as they’re interacting with the app within the present second, and adjustments in conduct might be registered as they happen.

An open knowledge stream can also be required for our pre-launch evaluation and every other facet analyses a consumer would possibly wish to execute. At Adikteev, we by no means wish to rush into launching a retargeting marketing campaign with out first understanding our prospects’ KPIs and the context of their targets. For this reason we conduct an in-depth audit of all purchasers’ app audiences to find out the perfect technique for his or her campaigns earlier than we start our retargeting efforts. With the intention to do that, our Enterprise Intelligence workforce will need to have the freshest knowledge attainable. If one thing doesn’t appear proper and we should test it, or the consumer desires to run a comeback conduct evaluation for instance, we will do all of this by way of the shared knowledge stream.

How you can share your knowledge stream and the way our knowledge is saved

Whereas it’s an enormous quantity of information being shared between the app marketer and Adikteev, in case you’re working with an MMP the method couldn’t be simpler. Now we have integrations with all main monitoring companions, permitting app entrepreneurs to hyperlink their knowledge stream to our DSP with just some clicks. We are going to then obtain all in-app behaviors from the time the information stream is open to us.

Our servers are hosted by way of Amazon Internet Providers (AWS) by way of a mixture of managed service and in-house frameworks. We hold all uncooked knowledge on the S3 safe cloud storage from AWS and our in-house platform handles all high-level knowledge.

Firstly, knowledge is obtained by our platform from app occasions, after which used to construct focusing on lists. The bidder structure searches for the units on the listing and bids on them by way of RTB. As soon as the impression is gained, the monitoring infrastructure is deployed and reporting might be shared.

Why it’s protected to share your knowledge stream with Adikteev

Though we would not have any instantly figuring out or extremely delicate consumer knowledge (similar to social safety numbers, house addresses, or full names), we take all precautions attainable to stop our purchasers’ consumer knowledge from entering into the incorrect palms. We hold all of our consumer knowledge siloed from each other, and solely staff with the mandatory accreditation can have safe and verified entry to it.

As a result of we’re based mostly within the European Union, we’re topic to the strongest knowledge safety requirements on this planet. This is applicable to our purchasers and the purchasers of our purchasers (app customers). We’re proud to be working inside a world framework that takes consumer knowledge as critically as we do: the European Information Safety authorities can audit our knowledge safety protocols at random, and all of our purchasers’ knowledge and consumer knowledge is out there upon request.

On the stage of our enterprise relationships, an NDA is in place to supply insurance coverage that purchasers’ consumer knowledge can’t be utilized in any means apart from its meant function. Not solely are we legally prevented from doing so, but it surely’s not attainable for us to make use of one consumer’s knowledge to optimize for an additional’s marketing campaign. Retargeting campaigns require a really particular algorithm that don’t make sense out of context. Additionally, we do not know how customers carry out in a special app context. As a result of we don’t run UA, there’s no threat of us utilizing this knowledge to optimize to your rivals.

Take advantage of your retargeting campaigns

A lot of choices issue into why a writer might or might not wish to share their knowledge stream with their retargeting associate. However for the overwhelming majority it’s one of the best ways ahead. With the intention to supply supplemental analyses and a pre-launch evaluation, it’s important to have entry to consumer knowledge and conduct. Dynamic cohorts are one of many key components that make our retargeting efficiency so robust, and entry to our purchasers’ knowledge stream permits us to supply optimizations in actual time.