How can mobile games publishers use ETL to win? Can ELT boost competitiveness and growth by providing better and richer mobile games analytics?
Mobile gaming companies are used to collecting data from dozens of sources. Traditionally those sources have been marketing partners: ad networks that they use to grow their games.
In fact, most do it via a mobile measurement platform like Singular.
But there are dozens of emerging data sources that can provide even more context and insight in this hugely competitive $140 billion industry. And ELT is opening a path for mobile games to get better, faster data to enable quicker growth.
Here’s how …
ELT for mobile games analytics
Mobile gaming companies live and die on data: fresh data. They need to know which campaigns work, which don’t, and why performance shifts happen across dozens of channels and platforms. They can do that with MMPs — mobile measurement platforms — but there’s also other sources of mobile games analytics data.
Like the App Store. And Google Play.
Or, frankly, existing marketing partners that don’t allow you to see or export all your data at once in their default dashboards, so you have to take multiple snapshots of it and do your best to sort of cobble it together later.
But when your marketing ecosystem includes 20, 30, or even 50 different data sources, each with its own quirks, limitations, and schema, getting clarity is no easy task.
That’s a challenge facing SciPlay, one of the world’s leading social and mobile game publishers.
SciPlay is an OG in gaming, with roots back to 1999: before modern smartphones were released. 800 team members develop and publish more than 200 games, including hits like Jackpot Party Casino Slots, Quick Hit Slots, and Bingo Showdown. And tens of millions of people worldwide enjoy SciPlay’s games.
To solve their data challenges, SciPlay’s tech and product teams are leaning on Extract.
I sat down with Gal Karniel, director of product for adtech at SciPlay, to talk about why ELT matters, what Extract brings to the table, and how his team is using it to turn messy, disconnected data into faster, smarter growth.
Turning 50 messy mobile games analytics sources into smarter marketing, via ELT
SciPlay already has an MMP: Singular.
So it’s already getting all the advertising campaign results and creative optimization data that its ad partners release, including data that major platforms only allow access to via approved marketing analytics vendors. And Singular is already combining that data with their own internal first-party activity, engagement, and monetization data.
But now there’s more data to get for even richer mobile games analytics.
One important source is App Store data.
“When Apple released the new App Store APIs … that was like brand new, 50 new APIs they released … you couldn’t get them anywhere unless you developed it yourself,” Karniel recalls. “By the time we talked to Extract, they already had it … that was a big winner for us because that was a lot of value, very fast and very easy.”
Those App Store APIs offer data on real‑time in-app purchase events directly to app and game publishers: think subscription renewals, expirations, refunds, and more … all of which is critical for game publishers who want to maximize growth and revenue
There’s also an API that enables developers to request a child’s age range (but not the exact birthdate) if the parent consents. That means app publishers can protect themselves legally in multiple global geos by not allowing minors access to games or material that they’re not legally allowed to experience.
And there’s more coming: a retention messaging API that will allow developers to present custom messaging, imagery, or special offers right inside the app cancellation flow. That’s in prerelease right now, but when it’s widely available, it will be a massive help in retaining paying subscribers.
Another gold mine of mobile games analytics that’s traditionally unavailable to mobile app and game publishers is complete data from Meta.
“On Facebook, you can’t get placement and country in the same data set, for example,” Karniel explains. “But here I can just set up parallel [data streams], however many I want, and pick up all of the different streams separately.”
They’re not combinable due to the lack of a primary key or unique identifier, but they still provide more data, insight, and depth, all of which are useful for a technical growth team.
Mobile mobile games analytics: competitive intelligence via Extract ELT
Another valuable source for SciPlay that Karniel can suck down into their BI with Extract: competitive intelligence from AppTweak.
AppTweak offers App Store marketing intelligence, which allows you to keep tabs on competitor app publishers, see emerging trends in consumer mobile game behavior, and correlate those trends to shifts in your own download and monetization trajectories. This is mobile games analytics on titles that compete with SciPlay’s games: critical competitive intelligence.
This dataset reveals external forces on player acquisition as gamer tastes change, competitors boost or kill marketing campaigns, and App Store/Google Play search algorithms morph.
This isn’t typically available in a format that growth teams can mix with their own first-party data. But now, with Extract’s fast and inexpensive ELT, SciPlay can pull all of these datasets, combine them internally in their BI system, and get better insights for future growth.
Add it up for all their partners and marketing insight vendors, and it’s a major boost.
The Goldilocks zone for ELT tools
When you want to grab data from a lot of different places quickly and easily, you’re probably looking for an ELT tool.
But there’s a problem.
Most aren’t very customizable. Most ELT tools are fairly rigid, in fact.
Not Extract.
“In most cases when you get out of the box products from third parties, you’re very limited in what you can actually do to customize for your specific needs,” Karniel says. “With Extract, I think that the thing we saw from the get-go is that it’s already built to be customized. It struck a nice balance between being too flexible, where you need data engineers to actually write code, and being simple enough that product managers and operations managers could set configurations and get it done.”
That’s the Goldilocks zone: not too rigid, but not so flexible ELT becomes hard to use.
SciPlay’s results using Extract’s ELT
So how is Extract ELT helping SciPlay?
Here’s 5 key ways:
- Less maintenance
SciPly had some internal code written for accessing a few APIs that brought in enrichment data. Now that’s all handled by Extract. The result: fewer custom scripts to maintain and less overhead in keeping APIs updated. - Deeper analysis
Because SciPlay can use Extract to pull in entirely new datasets and multiple views of datasets that are currently only available in part, they can now generate deeper analysis. Among other things, that means SciPlay can now analyze campaigns at a much more granular level. One example: checking placement-level performance for specific ad campaigns. - Richer contextual data
Enrichment data is great. Also great is contextual data from the wide competitive universe in mobile gaming. “If we have performance changes, contextual data like stuff from AppTweak that we added… can really help kind of frame together what impacts our performance on a daily and monthly basis,” Karniel says. - Transparency and trust
Thanks to Extract’s unique user interface, not only does SciPlay get the data they need quickly and efficiently, Karniel can see exactly what’s happening in real-time. That includes full real-time logs of what is actually happening behind the scenes, complete with timestamps for everything. This level of transparency builds trust, says Karniel: “we know what’s going on and we understand how the data flows.” - Faster adoption of new sources
As new sources of data become available, SciPlay will be able to instantly take advantage of them, thanks to Extract’s agility in supporting new sources and connectors.
The goal: better mobile games analytics for faster growth.
So much more in the full interview
Check out the full interview in the video above, or in our (brand new) YouTube channel.
You’ll get more info on:
- How SciPlay manages 20–50 different data sources for marketing
- How SciPlay balances in-house solutions vs. third-party tools
- How Extract solved the challenge of Apple’s 50 new App Store APIs
- How Extract can create parallel datasets for greater depth
- Why visibility, logs, and transparency matter for trust in data pipelines
- How Extract simplifies data enrichment pipelines and reduces maintenance
- How SciPlay built faster access to insights, better targeting, and better data for smarter decisions