How to Make App Campaign Data Behave (Sort of)

Or: turning conflicting reports into something that resembles insight.

Programmatic UA would be easier if data played by the rules. Instead, you get mismatched reports, shifting formats, and column headers that change mood weekly. Your job? Make it all line up. Make it make sense. Ideally before Slack lights up with “hey, quick question…”

Let’s break down the madness:

📦 Box #1: The DSP Universe

Your source for all things traffic. Campaigns, creatives, bids, bundles, impressions, clicks, installs, costs… it’s like a party where everyone showed up but forgot to wear name tags.

📲 Box #2: The MMP Dimension

This is where attribution lives. Installs, post-install events, funnels, LTV… if you’re lucky, you have clean access. If not, someone forwards you a raw CSV on a Friday evening with 300k rows and no headers. Classic.

📊 Box #3: The Land of Payouts & KPIs

Structured (ish) data on what you earn per app, per geo, or per bundle. Sometimes clear, sometimes… interpretative. Like abstract art, but in spreadsheet form.

Now, if you’re trying to make sense of ROI, profit or revenue without combining these three worlds… well, may the gods of pivot tables be with you 🧯

Because true performance insight doesn’t come from looking at one source, it comes from connecting the dots across all of them.

So… what works?

There’s no universal template. But there is a battle-tested combo we rely on—and it’s not glamorous, but it works like a charm.

Excel – The first aid kit 🔧

This is where the cleanup begins. Think of it as the triage room for incoming data.

You’ll use Excel to:

• Unify naming: when “DE”, “Germany” and “ger” all mean the same thing, but your VLOOKUP disagrees.
• Fix decimal madness: when 1.000,00 shows up and Excel thinks it’s a phone number.
• Remove noise: like 20 extra blank columns, or rows where the campaign name is “test 123 please ignore”.
• It won’t save your campaign, but it will save your dataset from immediate collapse.

SQL – The secret weapon 🧠

Once your data’s looking semi-respectable, SQL takes the stage. This is where real structure happens.

Use it to:

• Join datasets from DSP, MMP, and payout sources using keys like campaign_id, geo, or media_source.
• Aggregate metrics: for example, group installs and revenue by bundle and country to get a clearer view of performance.
• Flag mismatches: like when your MMP install count says 5,000 and your DSP shows 18.
• SQL is where the spreadsheets become strategy.

Power BI – The stage 📊

Now that your data is behaving, it’s time to make it speak. Power BI turns rows into stories.

Use it to:

• Create dashboards that compare ROI across geos, campaigns, or exchanges.
• Drill down into poor-performing bundles or top-performing creatives into clicks.
• Spot patterns at a glance—like which traffic source bleeds budget every Thursday without fail.

It’s how you go from “let’s increase spend” to “but not on iOS in CA after 5pm—it’s eating margin.” In the end, performance isn’t just about more traffic or better creatives. It’s about building systems that turn noise into signal.

And let’s be honest—nothing beats the feeling of watching a dashboard light up after days of data wrangling and thinking,

“Oh… so that’s where the money went.” 💸