Native Advertising Software Resources
Articles, Glossary Terms, Discussions, and Reports to expand your knowledge on Native Advertising Software
Resource pages are designed to give you a cross-section of information we have on specific categories. You'll find articles from our experts, feature definitions, discussions from users like you, and reports from industry data.
Native Advertising Software Articles
Spotify Ads: Types, Set Up, + Best Practices
Reddit Ads: Everything You Need to Know
Native Advertising Software Glossary Terms
Advertorials are advertisements that read like traditional editorial content. Learn about the types, elements, benefits, and best practices.
Explore our Technology Glossary
Browse through dozens of terms to better understand the products you purchase and use everyday.
Native Advertising Software Discussions
I'm researching native advertising platforms for promoting a mobile app inside other apps, the kind of placement that blends into the content instead of interrupting it. This one is tricky because a lot of app-install advertising leans on interstitials and pop-ups that annoy users, so I wanted to see which platforms in the native advertising category reviewers actually describe as non-intrusive. Five that came up:
- EVADAV: reviewers use it for offer-driven and app traffic and like how fast native campaigns set up. Has anyone measured whether its native placements retain installs better than push formats?
- MGID: users say the ads read like an article and feel friendly rather than invasive, and it serves both advertisers and publishers. Does that article-style unit still convert for app installs specifically?
- AdsKeeper: described as blending native ads into content and adapting cleanly across screen sizes. For app promotion, how does its in-feed unit hold up on smaller mobile placements?
- Sharethrough: reviewers point to inventory quality and enhanced native and video formats. Does its supply include enough in-app inventory for mobile app campaigns?
- inboxAds: noted for a natural, customizable native experience inside inbox and app environments. Has anyone run app-install creative through it at any real scale?
If you've promoted a mobile app through native rather than standard interstitials, which platform kept the experience feeling non-disruptive and still drove quality installs?
Article units like MGID's clear the non-disruptive bar by reading as content rather than interstitials. Install quality is uncertain: in-feed native can engage but may underperform on retained installs. Track post-install retention rather than click-through.
I'd separate the unit from the transition here. An in-feed native placement can read perfectly well in context and still feel disruptive at the click, because the interruption isn't the ad itself, it's being pulled out of the app you were using and dropped onto a store page mid-session. That's what decides whether an install is a considered one or an accidental one. It's also why article-style units like the MGID ones behave differently for content promotion than for app installs: the reader was promised something to read, and the payoff is a download prompt, so the creative has to do the work of making that feel like the natural next step rather than a swap.
The metric that exposes this is day-one retention by placement rather than install volume. An accidental install looks like a great CPI and a terrible retention curve.
Straight answer, most of the established native advertising platforms like Taboola and Outbrain are built for web content discovery, not specifically in-app mobile promotion. For genuinely in-app, non-disruptive mobile ad placement, you're looking at a different category of in-app ad networks, worth naming that distinction clearly before evaluating vendors.
Hey G2 community. I'm comparing native advertising platforms on how strong their analytics and A/B testing really are for content promotion, since a SaaS marketing team lives or dies by what it can measure and iterate on. Plenty of platforms show clicks and impressions, but fewer make testing and optimization genuinely usable. Going through the native advertising category on G2, here's what keeps mattering to reviewers:
- Reporting that's actually readable, not just a metric dump
- Room to test creative and audiences without rebuilding a campaign
- Optimization signals you can act on mid-flight
- Support that helps interpret the data, not just export it
A few platforms that come up for this:
- The Trade Desk: reviewers highlight its Kokai AI layer and how cleanly it turns messy cross-partner data into readable reporting.
- StackAdapt: called out for deep audience segmentation and in-platform optimization, with a Creative Studio that helps teams spin up and compare variations.
- Viant Technology: users mention an extra campaign hierarchy level that gives finer control for structured testing, plus responsive help on optimizations.
- illumin: its campaign journeys let people test different funnel paths and see reporting tied to each step, which fits content sequencing.
- Basis: described as easy to organize and analyze for optimization, with onboarding that gets teams comfortable reading the numbers.
For content promotion specifically, which of these gave you A/B tests you trusted enough to move budget on? And has anyone found the built-in reporting sufficient, or do you still push everything into a separate BI tool?
For content promotion, the platforms worth trusting for testing are the ones that make optimization signals readable mid-flight, not a metrics dump. The Trade Desk's Kokai reporting gets cited for that clarity. The opportunity is deciding up front which metric defines a winning test, or you will still export to BI.
For SaaS, I’d want to know whether the testing remains useful beyond CTR. A headline can win on clicks and still lose badly on demo requests or pipeline quality. For teams using The Trade Desk, StackAdapt, Viant, illumin, or Basis, how easily could you connect an A/B variant all the way to downstream conversions without stitching the analysis together elsewhere?
For content promotion, I’d trust StackAdapt or The Trade Desk most for making budget shifts off test results, especially when audience and creative variables can be isolated cleanly. I’d still push the data into BI for broader funnel analysis, but the in-platform reporting should be enough for mid-flight optimization.
illumin's campaign journeys are the one I'd actually want to test here. Reporting tied to each step in the funnel, rather than just the final click, fits content sequencing better than a flat A/B test would.
I've been mapping which native advertising platforms actually work for B2B SaaS teams that want quality leads from content-style ads rather than plain banner display, and it's harder to pin down than it looks. A lot of tools in the native advertising space are built for consumer arbitrage or publisher monetization, so the ones that suit account-based, content-led lead gen are a smaller slice. Pulling from G2 reviews left by software and agency users, here are the ones that keep coming up for this use case:
- StackAdapt: reviewers running B2B campaigns point to its intent data and company-level targeting, plus the ability to run native, display, CTV and audio from one dashboard, which fits full-funnel content promotion.
- AdRoll ABM (Formerly RollWorks): the HubSpot integration, ICP scoring and account-level intent signals get called out repeatedly by ABM teams trying to tie ad spend back to pipeline.
- AdRoll: described as an all-in-one multichannel option so you're not juggling separate tools for display, native and CTV, which smaller SaaS teams seem to value.
- illumin: its journey-based sequential messaging comes up a lot for moving people through a funnel instead of buying one-off impressions.
- Sharethrough: reviewers mention it hitting conversion KPIs while filtering inventory and holding brand safety, which matters when content ads run across a lot of sites.
For anyone who has run B2B SaaS demand gen through native, did it actually produce leads your sales team accepted, or mostly top-of-funnel traffic? And if you've used both an ABM-specific tool and a broader DSP, which gave you cleaner attribution?
Native for B2B tends to fill the top of the funnel unless you wire it to intent and account signals. StackAdapt gets picked here for company-level targeting and running native, display, and CTV from one place, which helps tie spend to pipeline. The opportunity is agreeing on lead quality with sales before you scale spend.
For B2B SaaS, I’d expect native to work best as a quality top-of-funnel channel unless the targeting is tied closely to account intent. Between the two approaches here, AdRoll ABM sounds stronger for clean attribution because its account-level intent signals and HubSpot integration give teams a clearer path from ad engagement to pipeline.
On the lead quality question, what sits behind the ad usually matters more than the platform. Content-style ads bring people in a reading frame of mind, so the teams getting sales-accepted leads tend to leave the first click ungated and lean on account-level signals to decide who's worth a follow-up. StackAdapt and RollWorks both come up for exactly that.
Lead quality in B2B native usually depends less on the platform and more on what sits behind the ad. Teams getting sales-accepted leads tend to leave first click ungated and rely on account-level signals to decide follow-up. StackAdapt and AdRoll ABM both come up because they sit at that intersection of intent data and account targeting.