Resources Case Studies Clean Data Only: TextNow Uses Adjust as a Source of Truth For Their Performance Marketing

Clean Data Only: TextNow Uses Adjust as a Source of Truth For Their Performance Marketing

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About TextNow

TextNow is a free texting and voice calling app that enables people to text and call without signing up for a wireless plan. Everyone needs a phone, but not everyone can afford wireless plans that seem to rise with every year. TextNow offers a way to enable anyone with a working smartphone to access unlimited local calling and texting for free. Users can also access subsidized data plans on the Sprint network.

The Importance of Trusting Your Data

Data that’s 80% accurate is 0% accurate.

Tyler Cooper

Head of User Acquisition,

TextNow

User acquisition is all about trusting the data that you see. Every single vendor and partner you work with will tell you that their data is the absolute truth. But anyone who’s worked in mobile UA will know that discrepancies and data muddiness happens.

TextNow’s marketing team is religious about accurate data. They need data that can stand up to deep scrutiny, as that data is what drives their day-to-day marketing operations. One example they ensure clarity of data is by using Adjust as a source of truth. They’ll even gut-check their Google Analytics data with Adjust trackers to see if we’re reporting the same thing.

This is especially important because like most apps, TextNow uses a healthy mix of self-attributing networks (SANs), such as Google AdWords, and other ad networks or mediation partners such as Liftoff or IronSource. TextNow spends roughly 60% of their total spend on SANs, and about 30% of their total spend on other ad/mediation partners.

Adjust is able to accurately count installs and provide solid last-touch attribution. While some networks maintain control of their attribution logic in claiming installs, Adjust is able to apply TextNow’s attribution logic to their marketing campaigns, resulting in metrics that reflect the efficacy of their campaigns in a much more precise and clear way.

Clean Data Means Fraud-Free Data

We wouldn’t be in this business if it weren’t for Adjust’s Fraud Prevention Suite.

Tyler Cooper

Head of User Acquisition,

TextNow

TextNow also uses Adjust’s Fraud Prevention Suite as the core filter for their anti-fraud engine. Having actionable data also means cleaning it from fraud. Fraudulent installs, events, and signals don’t just mean empty installs and wasted money, they also lead to tainted datasets that results in the wrong insights and cost brands even more further down the line.

Adjust FPS rejects around 20% of all incoming installs from TextNow’s campaigns. Networks do all they can to find fraudulent publishers and kick them off, but fraud is difficult to detect and dig out from the network side. Adjust’s Fraud Prevention Suite uses a variety of filters to combat click spamming, click injection, hyperengagement, SDK spoofing, and device farms, while simultaneously reporting each fraudulent install to both TextNow and their partners.

Given their dedication to clean data, TextNow takes their anti-fraud initiatives a step further, using third party tools and in-house analysis to find deeper fraudulent patterns based on the data that Adjust reports. Having a partner that can automatically prevent the vast majority of fraud you face can streamline your operations and make sure the data you see is the data you can trust.

The Importance of Having a Source of Truth

Using Adjust as a source of truth, TextNow has been able to test and vet over 100 marketing partners in the last four years. The value of Adjust being a plug-and-play solution that applies the same standards and fraud prevention to every ad source is key to vetting new sources of users.

With up to 20% of all incoming installs being rejected, TextNow is able to trust their data more without having to go through weeks of work to clean out their datasets and contest installs - which also has the negative side-effect of poisoning the relationship with their ad partners.

Having a trustable source of data can provide value beyond marketing as well. TextNow’s data science teams rely on Adjust data to calculate LTV models using Adjust’s in-app event tracking to see how long users were being retained. Normally, teams outside marketing rarely see the use of crucial parts of the marketing tech stack - which includes MMPs like Adjust. But given our commitment to providing clean and actionable data, our value isn’t just limited to TextNow’s marketing team.**

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