You can get a fair picture in about fifteen minutes by testing the app before you trust it: see whether it works with no connection and check its store privacy label against its privacy policy, then try the export and delete options before you add anything personal. Treat what you find as the developer's own account. Lab studies that captured app traffic found many apps sending data their labels and policies did not mention, and no study has tested whether a consumer check like this one catches those cases. So the evidence that a problem exists is strong, and the evidence for any particular checklist is thin.

What the research says

Almost nobody reads the policy. In an experiment with 543 participants joining a fictitious social network, 74% skipped the privacy policy through a quick-join button. Those who opened it spent 73 seconds on average, against an estimated 29 to 32 minutes needed to read it, and 98% missed clauses about sharing data with employers and a government agency (Obar & Oeldorf-Hirsch, 2020).

Store labels are unverified claims. Researchers captured the traffic of 1,687 iPhone apps from the German App Store and found at least 276 sending data their privacy labels did not declare, which suggests the labels were not checked during app review (Koch et al., 2022). A study of 474,669 iOS apps compared labels with privacy policies: of the apps labelled "Data Not Collected", 97% had a policy indicating some collection (Ali et al., 2024). The authors point to templates and confusing definitions as likely causes, so a mismatch is a reason to look closer and does not prove bad faith.

Policies miss sharing that does happen. In 36 top-ranked apps for depression and smoking cessation, traffic interception detected data going to third parties in 33. Of the 28 apps sending data to Google, 12 disclosed it; of the 12 sending data to Facebook, 6 did (Huckvale et al., 2019). In 24 medicines apps, 19 shared user data, and the recipients included analytics and advertising companies (Grundy et al., 2019). Those were health apps, and a to-do list can hold the same kind of detail, such as a clinic appointment or a salary negotiation.

Switching phones is no shortcut. A comparison of about 24,000 Android and iOS apps from 2020 found third-party tracking and shared identifiers common on both, and concluded that neither platform was clearly better for privacy (Kollnig et al., 2022).

Clear information does change choices. This cuts the other way. When a shopping search engine showed privacy ratings in a compact form, people tended to buy from the more protective sellers, and some paid a premium to do so (Tsai et al., 2011). In interviews with 24 phone users, some Android users found Google Play's data safety labels helpful, though most missed key details because they never expanded the collapsed sections (Lin et al., 2024). Labels are worth reading, as long as you open every section and check them against something else.

How to do it

Run the airplane-mode test (3 minutes). Turn on airplane mode, open the app, add a task with a duration and a time, then force-close it and open it again. If the task is there and the plan still works, your records are held on the phone. If the app refuses to load or asks you to sign in, they live on a server, and the rest of the check matters more.
Note whether it needs an account (1 minute). An email sign-up links everything you type to an identity. That can be fine, since it is what makes sync between devices work, but it means the company holds a copy.
Read the store label, every section (3 minutes). On iPhone, look for "Data Used to Track You" and "Data Linked to You". On Google Play, open "Data safety" and expand each heading, because the collapsed view hides the detail (Lin et al., 2024). Write down two things: any tracking, and any category that could include what you type, such as "User Content".
Search the policy for four words (4 minutes). Use find-in-page for "third part", "advertis", "train" and "retain". These show who receives data, whether it feeds ads, whether your text can train an AI model, and how long it is kept. Then compare with the label. If the label says nothing is collected and the policy lists analytics or ad partners, trust neither until you know more (Ali et al., 2024).
Find which features leave the phone (2 minutes). AI features and sync usually send content to a server. For each one, the policy or help page should say when content is sent (all the time, or when you tap) and whether it is kept.
Test the exit before you need it (2 minutes). Find the export option and the delete option in settings and use both on your test task. An app you cannot leave cleanly is a bigger commitment than it looks.

Then apply one decision rule. Put sensitive items, such as medical appointments or money, into an app when its label shows no tracking and matches the policy on third parties, and when its delete option works. If it fails either test, keep using it for the shopping list and keep the sensitive items somewhere else.

A worked example

Saturday morning, two planners side by side, phone on the kitchen table.

10:00. Say the first is a cloud planner that asks for an email at launch. With airplane mode on, it shows a "no connection" screen. The data lives on its servers.

10:04. Its App Store label lists "Usage Data" under Data Linked to You and nothing under Data Used to Track You. Two sections opened, two notes made.

10:07. Find-in-page on the policy: "third part" returns a list of analytics providers and a cloud host; "advertis" says data is not sold; "train" returns nothing; "retain" says data is kept while the account exists. The label and the policy roughly agree.

10:11. Settings has an export to CSV, and "delete account" opens an email form. Result: it passes the label and policy tests, and the delete test is uncertain. Fine for groceries and errands. The appointment with the specialist on Thursday goes elsewhere until the delete route is clear.

10:15. The second planner is Flowo. There is no sign-up screen, since the app has no account. In airplane mode the test task saves, and the day still schedules, because planning records sit in encrypted storage on the phone and the scheduler runs there too. Analytics stay off unless you consent, and the events they send carry no content. AI features such as the assistant and task breakdown send the content a request needs to the app's own API on AWS when you tap them, and that content is not used to train models. Settings has an export to a JSON file and Delete App & Device Data, under Legal & Privacy. The same tests apply: open its label and policy and compare them yourself.

10:25. Two apps checked in twenty-five minutes, with a written note for each that you can recheck after a major update.

When this does not work

The check reads what the developer says and what the app shows you. It cannot see the network traffic, which is how the studies above found undeclared sharing, so a clean result means "nothing obviously wrong" and nothing more. Tools that monitor app traffic exist, but they take setup most people will not do.

Local storage has its own risk. If records live on the phone and you lose it without a backup or export, they can be gone for good. People who plan across a laptop and a phone may need sync, and with it a server copy, so for them the policy and the delete route matter most.

Work and school devices are different again. A managed phone can be monitored by the employer or school whatever the app does, so the app's privacy is one part of the picture. And the research here comes mostly from health apps and general app samples from 2018 to 2022; practices change, and planners may differ.

Questions

Can I trust the "Data Not Collected" label?

Take it as a starting claim. Apple does not validate the labels, and large studies found many apps whose traffic or policies contradicted them (Koch et al., 2022; Ali et al., 2024). Compare the label with the policy, and run the airplane-mode test.

Is an iPhone more private than Android for apps like this?

Not clearly. A study of about 24,000 apps found tracking and shared identifiers widespread on both platforms (Kollnig et al., 2022). The app you choose matters more than the phone you hold.

Is "encrypted" enough?

It depends on where the keys are. Encryption in transit protects data on the way to a server, and unless the service uses end-to-end encryption, the company can read it once it arrives. Storage encrypted on your phone, with keys held in the phone's secure hardware, means a copy taken off the device cannot be read without those keys. Ask which kind an app means.

References

Ali, M. M., Balash, D. G., Kodwani, M., Kanich, C., & Aviv, A. J. (2024). Honesty is the best policy: On the accuracy of Apple privacy labels compared to apps' privacy policies. Proceedings on Privacy Enhancing Technologies, 2024(4), 142-166. https://doi.org/10.56553/popets-2024-0111
Grundy, Q., Chiu, K., Held, F., Continella, A., Bero, L., & Holz, R. (2019). Data sharing practices of medicines related apps and the mobile ecosystem: Traffic, content, and network analysis. BMJ, 364, l920. https://doi.org/10.1136/bmj.l920
Huckvale, K., Torous, J., & Larsen, M. E. (2019). Assessment of the data sharing and privacy practices of smartphone apps for depression and smoking cessation. JAMA Network Open, 2(4), e192542. https://doi.org/10.1001/jamanetworkopen.2019.2542
Koch, S., Wessels, M., Altpeter, B., Olvermann, M., & Johns, M. (2022). Keeping privacy labels honest. Proceedings on Privacy Enhancing Technologies, 2022(4), 486-506. https://doi.org/10.56553/popets-2022-0119
Kollnig, K., Shuba, A., Binns, R., Van Kleek, M., & Shadbolt, N. (2022). Are iPhones really better for privacy? A comparative study of iOS and Android apps. Proceedings on Privacy Enhancing Technologies, 2022(2), 6-24. https://doi.org/10.2478/popets-2022-0033
Lin, Y., Juneja, J., Birrell, E., & Cranor, L. F. (2024). Data safety vs. app privacy: Comparing the usability of Android and iOS privacy labels. Proceedings on Privacy Enhancing Technologies, 2024(2), 182-210. https://doi.org/10.56553/popets-2024-0047
Obar, J. A., & Oeldorf-Hirsch, A. (2020). The biggest lie on the Internet: Ignoring the privacy policies and terms of service policies of social networking services. Information, Communication & Society, 23(1), 128-147. https://doi.org/10.1080/1369118X.2018.1486870
Tsai, J. Y., Egelman, S., Cranor, L., & Acquisti, A. (2011). The effect of online privacy information on purchasing behavior: An experimental study. Information Systems Research, 22(2), 254-268. https://doi.org/10.1287/isre.1090.0260

Conflict of interest: the author is a co-founder of Flowo, a planning app. None of the studies cited was funded by or connected to the company.

Flowo is free to download on the App Store for iPhone and on Google Play for Android, with optional in-app purchases.

How Do You Check Whether a Planner App Keeps Your Data Private?