Smartphone Owners Aren’t Convinced to Upgrade for Foldable Designs and AI Integrations, CNET Finds


Flip phones are making a comeback, but most US adults aren’t convinced enough to upgrade. 

Smartphone brands are trying new phone concepts, like flip and foldable phones, to give us a bigger screen when we want it, while still maintaining the same functionality as the smartphones we’re used to. There’s the Samsung Galaxy Z Fold 7, for instance, and there’s even a rumor that Apple plans to release its first foldable phone

And if you remember the popular 2000s Motorola Razr, now there are rumors about the Motorola Razr 2026 — it reminds me of my old pink phone. But gone are the days of a basic keypad and a few ringtones. Smartphone brands are adding AI features, such as creating custom emoji, removing background objects from photos, and live translation. 

Yet a recent CNET survey says smartphone users aren’t sufficiently impressed by new features and concepts to consider upgrading their phones. Only 12% are motivated by AI integrations and 13% by new phone designs. Instead, price (55%) and longer battery life (52%) are the biggest drivers of their decision to get a new phone. 

If most US adults aren’t sold, why are tech brands so adamant? Let’s dive into CNET’s findings and what they mean for the future of smartphones.

  • The top three motivations for US adult smartphone owners to consider upgrading their devices are price (55%), longer battery life (52%) and more storage (38%). That’s the same top three as last year: In 2025, price was the top motivator (62%), followed by longer battery life (54%) and storage capacity (39%). 
  • Despite AI’s growing presence, only 12% of smartphone owners say AI integrations would motivate them to consider upgrading. 
  • Only 13% of smartphone owners would be motivated to consider upgrading to a new phone concept, such as a foldable or flip phone. 
  • Over half of smartphone owners (58%) experience frustration with their phone’s battery life, and 31% say their phone’s battery doesn’t hold a charge as well as it did when it was new.  

Most US adults aren’t motivated by new smartphone features and designs

Smartphone brands, like Samsung and Apple, are building in convenient features, such as a tool to remove unwanted objects from pictures, AI call screening and the ability to draft a message from a prompt. However, CNET found that US adults would consider upgrading for more practical reasons. Over half (55%) of US smartphone users are motivated by price, including 53% of Apple users and 56% of Samsung users. 

Yet brands are still exploring new concepts and features, like Apple Intelligence, a built-in AI feature. Then there’s the rumor of a book-style iPhone, potentially followed by a clamshell foldable design. But that’s not what most smartphone owners are after. 

Smartphone owners are more convinced by other design and feature factors when deciding on a new phone, such as camera features (27%) and the phone’s display or screen size (22%). Here are the top motivators to consider upgrading for all smartphone users.

Zain Awais / CNET

You’ve probably noticed the price of a basic smartphone has increased drastically over the years. Take the iPhone, for example. It was originally $600 for 4GB. But advanced features, the RAM shortage, inflation and tariffs are pushing prices even higher. Now, the baseline iPhone 17 (256 GB) is $800, and the Samsung Galaxy S26 (256 GB) starts at $900. 

There’s no way of knowing for sure, but these may be the lowest prices we’ll see on new models for a while, especially as features advance and designs become more complex. So if you’re already in the market for a new phone, you might want to think seriously about pulling the trigger now if you find a good deal.

The top upgrading motivators haven’t changed much over the years

Looking back at CNET’s survey data from 2024 and 2025, and now, people’s motivators for upgrading their phones haven’t changed much. Price, longer battery life and more storage have been top drivers in the past, and despite small dips this year, they’re still key upgrading factors.

Despite design upgrades and new features, smartphone owners are still focused on how much they’re paying and how long they can use their devices without needing a charger. Consumer sentiment about AI integrations dropped hard from 2024 to 2025, but it has edged up slightly in 2026. And smartphone owners aren’t as easily persuaded by phone color or the phone being thinner, either. 

Even with these nice-to-have capabilities, smartphone owners are looking at the basics. That includes practical features like battery life and more storage to hold their many important files, photos and apps. 

Most smartphone owners want better battery life

Taking a closer look at smartphone users’ hope for longer battery life in a new phone, over half (58%) are frustrated with their current phone’s battery life. Roughly one in three (31%) say their phone doesn’t hold a charge. 

The reality is, battery life will decline the longer you have your phone, so you may find your phone’s battery charge doesn’t last as long as it used to. Even though you can replace your phone’s battery, most phone batteries have a lifespan of two to three years before they start degrading. 

CNET Director of Editorial Content Patrick Holland examined battery life tests on over 35 current smartphones. And it’s not just iPhones that pack impressive batteries.

Based on CNET’s lab testing, the $1,200 iPhone 17 Pro Max had the best overall battery life, with a 5,088-mAh capacity. Another top performer was the $900 OnePlus 15, with a 7,300-mAh battery. 

If you’re looking for a phone with better battery life, consider one with a silicon-carbon battery to increase capacity without requiring a larger phone. The OnePlus 15, Poco F7 Ultra, OnePlus 13R and OnePlus 15R all feature silicon-carbon batteries with large capacities and all performed well in Holland’s testing. Keep in mind that other factors can impact your battery life, like your carrier’s signal, software efficiency and processor. 

Methodology

CNET commissioned YouGov Plc to conduct the survey. All figures, unless otherwise stated, are from YouGov Plc. The total sample comprised 2,486 adults, of whom 2,407 owned a smartphone. Fieldwork was undertaken from April 29 to May 1, 2026. The survey was carried out online. The figures have been weighted and are representative of all US adults (aged 18 plus). 





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Informatica Data Quality tutorial – Table of Content

What is Informatica Data Quality?

Informatica Data Quality is an offering of Informatica that helps manage the quality of data across the whole enterprise. It offers features like data analysis, data cleansing, data matching, reporting, and monitoring capabilities, and many more. It ensures that data is consistent across the enterprise to meet the business objectives.

IDQ uses the Claire engine in the backend to make intelligent recommendations and assessments. It also uses AI-driven insights to streamline data discovery. It offers transformations like data standardization, validation, re-duplication. The IDQ is available on both Microsoft Azure and AWS public clouds. So the users can quickly spin up infrastructure on the cloud and start working with it.

Informatica Data Quality was awarded as the Data Quality Market Winner in 2018 by CRM Magazine.

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What are the advantages of IDQ?

Below are the advantages of the IDQ tool,

  • It can quickly deploy data quality for all real-time workloads.
  • The IDQ is very flexible that even non-developers can start working with it.
  • We can manage data quality from both multi-cloud and on-premises.
  • It enables collaboration between IT and business stakeholders.
  • We can reuse standard rules across the data from different sources.
  • It offers data profiling for data privacy and protection.
  • It improves data quality for enabling data protection.
  • It ensures that the relevance of the information is stored.
  • Improving data quality enhances data-driven digital transformation.
  • Regardless of volume or type of data, IDQ ensures the highest quality of data is delivered to get accurate insights.
  • We can easily integrate IDQ with other tools.

Core components of IDQ:

The IDQ has two core components.

Data Quality Workbench

It is like an IDE through which we can design, test, and deploy data quality plans. We can execute tests and plans through the workbench. It contains the Project Manager and File Manager on the left, and a workspace on the right where the plans are designed. Workbench offers 50 data components that we can use in our plans.

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Data Quality Server

It is used to run plans in a networked environment. We cannot create or edit plans on the server. It communicates with the workbench through TCP/IP connection. It also enables plans and file sharing across networks.

Both the workbench and server will be installed with a Data Quality engine and a Data Quality repository.

IDQ Workbench Match Algorithms

IDQ Workbench offers four algorithms that we can select from, to perform matching analysis. 

Hamming Distance algorithm

The hamming distance algorithm is useful when the positions of characters in a string are essential, for example, dates, telephone numbers, postal codes, etc. The strings to be analyzed should be of the same length because it implements transposing of one string into another. 

Jaro-Winkler algorithm

It is useful when the prefix of the string is essential. It measures the match percentage of the characters of two strings. It also calculates the number of transpositions required to change one string to another.

Edit Distance algorithm

It is useful for matching small strings like name or short address field. This algorithm is an implementation of the Levenshtein distance algorithm, and that helps in calculating the number of operations needed to transform one string into another. The operations include insertion, deletion, or substitution of characters.

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Bigram or Bigram frequency algorithm

It is useful for searching through long text strings like free format address lines and creates pairs of consecutive characters from both data strings and compares them to find common pairs. It will give a match score based on the common identical pairs between the two search strings.

Dictionaries

A dictionary in IDQ refers to a data set that we can use to evaluate data in sources and mapping. When we apply dictionaries to a mapping, it will compare each input field in the mapping against the dictionary, and performs the specified actions. There are two types of dictionaries available in Informatica.

Relational Dictionary

We can add a table in a database as a reference dictionary by using the relational dictionary. To connect to a table, we need to provide an ODBC data source, username, password, etc.

Flat File Dictionary

We can add a file from your local computer as a reference dictionary using the flat file dictionary. To read the data from the file, we need to give the name, description, and upload the file from your local computer.

Access level controls in IDQ

An organization implements role-based control to give access to individual users for specific data. Here are some of the types of roles that you want to define in your data quality project. 

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Platform Administrator 

The platform administrator installs software, performs version upgrades and emergency bug fixes. This person is responsible for maintaining subscription content. 

Effort Administrator

An effort administrator is a front-line manager (like a project lead) for the project. This person can either grant access or approve access to project resources.

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Developer

A developer builds mappings and workflows in IDQ workbench by taking advantage of the Effort Administrator’s service connections. The developer also uses the full-featured model repository.

Operator

An operator is the front-line reviewer of results. This person manages the platform’s effort to run data quality artifacts in the published and internal project folders. 

Analyst

An analyst manages specifications, reference tables, and scorecard notifications. This person is responsible for the identification of all data quality issues. The analyst role also includes all the capabilities of a basic analyst. 

Reports Developer

A reports developer creates and modifies reports using the developer tool and iReportsDesigner. The generated reports point to the dashboards and reports template star schema.

Integrating IDQ with MDM projects

Data cleansing will be a value-added feature for Master Data Management (MDM) project. We can easily integrate IDQ with MDM in three ways.

Informatica Platform Staging

Informatica has introduced this feature from version 10.x. Using platform staging, we can integrate MDM with IDQ thorough a setup. The setup requires configuring MDM hub, platform components, and connections to the data sources. Once the integration is complete, the tables will be available in the developer tool.

IDQ Cleanse Library

We can create functions in IDQ as operation mappings and deploy them as web services. These web services can be imported to Informatica MDM hub as a cleanse library. Features like delta detection, hard delete detection, audit trail are available in this process.

Informatica MDM as target

We can use Informatica MDM as a target for loading the data to landing tables in Informatica MDM. This way, we can create only one connection instead of multiple. Features like delta detection, hard delete detection, audit trail are available in this process.

Difference between IDQ and Powercenter

Both the Informatica PowerCenter and Informatica Data Quality tools have their features that serve different purposes.

  • Informatica PowerCenter is an ETL tool that extracts, transforms, and loads data. Informatica Data Quality ensures the highest quality of data.
  • We can create re-usable rules and validations in Data Quality and integrate them into PowerCenter.
  • Most of the transformations available in PowerCenter are also available in Data Quality. In addition to them, Data Quality has some more transformations.
  • The way we use passive transformation in PowerCenter is different from IDQ.

Conclusion

Using IDQ ensures that only consistent data is in use across the organization. The customer holds complete control of the transformations, validations, and rules applied through mappings. We can even identify distinct patterns available within the data. IDQ is the best possible way to achieve the highest quality of data. It generates profiling reports and Data Quality reports. We can validate duplication, conformity, and integrity of data with this tool.

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