Digital technology offers increasing flexibility and choice to consumers. As a result, the retail industry is dramatically shifting toward more tailored and personalized experiences for shoppers, and businesses are rethinking how they deliver value to customers.

This couldn’t be more true for the beauty retailing industry where leading companies are turning to digital technology to create customized shopping experiences.

At Google Cloud, we’re particularly excited about our work with Ulta Beauty, the largest beauty retailer in the United States with more than 1196 stores in all 50 states, and how the company is using Google Cloud technology solutions to power personalization and redefine beauty retailing.

Established in 1990, Ulta Beauty has had incredible success as a company, and as customers become more discerning and curious about their purchases, the company is finding new ways to meet their changing needs.

Recently, leaders at Ulta Beauty recognized a huge opportunity to complement and enhance the shopping experience by helping beauty enthusiasts navigate through more than 500 brands and 25,000 products carried in their stores and online channel.

They decided to leverage the data from Ulta Beauty’s successful Ultamate Rewards loyalty program to create and offer more unique and personalized user experiences.

With more than 30 million members generating data through sales, transactions, product reviews, and social media engagement, Ulta Beauty’s Loyalty Program creates a comprehensive data set, and the company sought the right technology partner to help organize, analyze and transform that data into valuable insights for its customers.

Ulta Beauty’s leaders knew they had an opportunity to leverage data analytics and machine learning to reach customers in new ways, enhance the guest experience, and continue to grow their active loyalty member base. After considering a number of cloud providers, they chose to expand their existing partnership with Google Cloud.

“Google Cloud listened to our needs and worked in tandem with our engineering team to address our challenges,” said Michelle Pacynski, vice president of digital innovation at Ulta Beauty. “The ease of working with the Google Cloud team and their breadth of experience made the decision a no-brainer, laying the foundation for a great partnership.”  

In 2019, Ulta Beauty announced it was working with Google Cloud Platform to unify and organize its data, using:

• BigQuery to perform data analysis and generate dynamic content, personalized product recommendations, and event-based messages for customers.
• Cloud Storage to provide highly available, secure, resilient and cost-effective access to data across the entire enterprise.
• Compute Engine for the high-performance scalability needed to grow with customer demand while painlessly migrating existing applications to the cloud.
• Anthos to build a hybrid cloud foundation that allows their applications to take advantage of all this data, combining the power and flexibility of GKE with the ability to leverage their existing investment in secure infrastructure on-premises.

Our partnership with Ulta Beauty has enabled increased engagement with customers in store and online, and the creation of new tools and capabilities, including a new Virtual Beauty Advisor tool to deliver tailored recommendations and help shoppers choose the right products, and a Customer Conversation Platform that’s enabling deeper connections with guests, ultimately driving customer loyalty.

“It’s been a really efficient process so far due in part to the ease of working with the Google team,” said Michelle Pacynski, vice president of digital innovation at Ulta Beauty. “They’re experienced, approachable, and their can-do style makes for a great partnership. They listened to our needs and worked in tandem with our engineering team, figuring things out, and getting it done.”

The software development process requires complex, cross-functional collaboration while continuously improving products and services. Our customers who build software say that they value Google Workspace for its ability to drive innovation and collaboration throughout the entire software development life cycle. Developers can hold standups and scrums in Google Chat, Meet, and Spaces, create and collaborate on requirements documentation in Google Docs and Sheets, build team presentations in Google Slides, and manage their focus time and availability with Google Calendar.

Development teams also use many other tools to get work done, like tracking issues and tasks in Atlassian’s Jira, managing workloads with Asana, and incident management in PagerDuty. One of the benefits of Google Workspace is that it’s an open platform tailored to improve the performance of your tools by seamlessly integrating them together. We’re constantly expanding our ecosystem and improving Google Workspace, giving you the power to push your software development even further.

Make software development more agile

Google Workspace gives you real-time visibility into project progress and decisions to help you ship quality code fast and stay connected with your stakeholders, all without switching tools and tabs. By leveraging applications from our partners, you can pull valuable information out of silos, making collaborating on requirements, code reviews, bug triage, deployment updates, and monitoring operations easy for the whole team. This allows your teams to stay focused on their priorities while keeping everyone aligned, ensuring collaborators are always in the loop.

Plan and execute together

When combined with integrations, Google Workspace makes the software development planning process more collaborative and efficient. For example, many organizations use Asana—a leading work management platform—to coordinate and manage everything from daily tasks to cross-functional strategic initiatives. To make the experience more seamless, Asana built integrations so users can always have access to their tasks and projects with Google Drive, Gmail, and Chat. With these integrations for Google Workspace, you can turn your conversations into action and create new tasks in Asana—all without leaving Google Workspace.

“We’ve seen exceptional, heavy adoption of tasks being created from within the Gmail add-on. Our customers and community have also shown very strong interest in future development work, which is something we’ll continue to prioritize.” Strand Sylvester, Product Manager, Asana

To date, users have installed the Asana for Gmail add-on over 2.5 million times, as well as over 3.8 million installs of the Asana for Google Workspace add-on for Google Drive.

Start coding quickly

Google Workspace makes it easy for product managers, UX designers, and engineers to agree on what they’re building and why. By bringing all stakeholders, decisions, and requirements into one place—whether it’s a Gmail or Google Chat conversation, or a document in Google Docs, Sheets, or Slides—Google Workspace removes friction, helping your teams finalize product specifications and get started right away.

Integrations like GitHub for Google Chat make the entire development process fit easily into a developer’s workflow. With this integration, teams can quickly push new commits, make pull requests, do code reviews, and provide real-time feedback that improves the quality of their code—all from Google Chat.

Speed up testing

Integrations like Jira for Google Chat accelerate the entire QA process in the development workflow. The app acts as a team member in the conversation, sending new issues and contextual updates as they are reported to improve the quality of your code and keep everyone informed on your Jira projects.

Ship code faster

Developers use Jenkins—a popular open-source continuous integration and continuous delivery tool—to build and test products continuously. Along with other cloud-native tools, Jenkins supports strong DevOps practices by letting you continuously integrate changes into the software build.

With Jenkins for Google Chat, development and operations teams can connect into their Jenkins pipeline and stay up to date by receiving software build notifications directly in Google Chat.

Proactively monitor your services

Improving the customer experience requires capturing and monitoring data sources to improve application and infrastructure observability. Google Workspace supports DevOps teams and organizations by helping stakeholders collaborate and troubleshoot more effectively. When you integrate Datadog with Google Chat, monitoring data becomes part of your team’s discussion, and you can efficiently collaborate to resolve issues as soon as they arise.

The integration makes it easy to start a discussion with all the relevant teams by sharing a snapshot of a graph in any of your Chat spaces. When an alert notification is triggered, it allows you to notify each Chat space independently, precisely targeting your communication to the right teams.

Improve service reliability

Orchestrating business-wide responses to interruptions is a cross-functional effort. When revenue and brand reputation depends on customer satisfaction, it’s important to proactively manage service-impacting events. Google Workspace supports response teams by ensuring that urgent alerts reach the right people by providing teams with a central space to discover incidents, find the root cause, and resolve them quickly.

PagerDuty for Google Chat empowers developers, DevOps, IT operations, and business leaders to prevent and resolve business-impacting incidents for an exceptional customer experience—all from Google Chat. See and share details with link previews, and perform actions by creating or updating incidents. By keeping all conversations in a central space, new responders can get up to speed and solve issues faster without interrupting others.

Accelerate developer productivity

Integrating your DevOps tools with Google Workspace allows your development teams to centralize their work, stay focused on what’s important—like managing their work—build code quickly, ship quality products, and communicate better during service impacting incidents. For more apps and solutions that help centralize your work so you and your teams can connect, create, and get things done, check out Google Workspace Marketplace, where you’ll find more than 5,300 public applications that integrate directly into Google Workspace.

Editor’s note: James Fairweather, chief innovation officer at Pitney Bowes, has played a key role in modernizing the product offerings at this century-old global provider of innovative shipping solutions for businesses of all sizes. In today’s post, he discusses some key challenges the Pitney Bowes team overcame during its digital transformation, and some of the benefits it has enjoyed from building new digital competencies.

Pitney Bowes will celebrate its 100th birthday in April 2020. Over the past century, we’ve enjoyed great success in markets associated with shipping and mailing. Yet, as with so many established and successful enterprises, we faced slowing growth in the markets that served us so well for so long. While package growth was accelerating, the mail market was declining, creating opportunities and challenges.

To change our growth trajectory and “build a bridge” to Pitney Bowes’ second century, we needed to offer more value to our clients. We needed to move to growth markets, and that required new digital competencies. In 2015, we began a deliberate journey to transform our services, including shipping and location intelligence, for the digital world and make them available via the cloud. We learned a lot throughout this journey. In this post we’ll take a look at three things, in particular, that led to the success of this project—and will help future projects succeed, as well.

Setting expectations and realistic milestones

Organizations tend to undertake product development with a sense of optimism—and it’s often not particularly realistic. You set out thinking something will take a certain amount of time and that you will incur a specific cost, but estimates in technology and development may be optimistic, and costs almost always incrementally increase throughout the development process. 

With a digital transformation effort, there’s an additional challenge: You aren’t really heading to a well-defined destination, so the path your team takes can be even more ambiguous. Digital transformation doesn’t have an end state. It’s a process of constant evolution.

For these reasons, and more, it’s important to set informed, realistic expectations—in schedule, in budget, in project scope. It’s also critical that you identify milestones along the way, and recognize and celebrate when you reach them.

When you’re working on a massive, multi-year corporate transformation, after all, it can be hard to recognize that every little action you take each week, everything you win day-to-day, is a part of your progress, your change. So, it’s really important, as a leader, to bring consistency and execution discipline—and be able to point to the progress being made and celebrate accomplishments.

We did our best to follow this advice during our digital transformation. Late 2015 was a critical time for Pitney Bowes as we laid out the technology strategy that would get us to the next century. We were aware of the potential hazards that could arise. You set the strategy, celebrate its publication as an accomplishment… and then nothing happens. To avoid this issue, we broke our strategy out into specific tactics supported by numerous smaller, interim goals. When we started putting big, green checkmarks next to each accomplished milestone, people started realizing that we were making real progress, and were serious about our execution.

One key milestone, for example, was implementing an API management platform. This comprised several granular goals: Selecting a partner, training a subset of our 1,100 team members on the platform, and rolling out our first offering that was built on top of that capability. 

We knew that an API platform would be a key part of our digital transformation for three major reasons. First, we had acquired several companies, but their technologies were difficult to share for use cases across the organization. Every time a team needed to use our geocoding or geoprocessing capability, for example, they had to spin up a new environment. By building these capabilities as APIs across the organization, it made it easy to democratize their usage and speed up development. 

Secondly, we were running a big enterprise business system platform transformation program and wanted our product teams to be able to consume data from our back-end business systems. This meant that we needed a solid catalog of all these services, so new members of the team could easily find and use them.

Finally, we had a couple of business units that wanted to go to market with APIs. They had a business strategy that entailed selling a service or value, with a vision to build a platform or ecosystem around these capabilities. An API platform (specifically, Google Cloud’s Apigee API management platform) is a huge accelerant in enabling all three of these objectives—it’s how you do this well.

Reusability and the Commerce Cloud

The Apigee platform and team helped us build a key offering that arose from our digital transformation: the Pitney Bowes Commerce Cloud. It’s a set of cloud-based solutions and APIs that are built on our assets and connect our new cloud solutions to our enterprise business systems, such as billing and package management.

Today, we have close to 200 APIs delivered from the Commerce Cloud in the areas of location intelligence, shipping, and global ecommerce. The Commerce Cloud isn’t just a success as a customer-facing platform, however. We often talk about whether our development teams themselves have leveraged its services when developing new products. These discussions help us understand whether a product team has thought through the digital capabilities we’ve already built, assessed which capabilities fits into its roadmap, and adopted the right technology, capabilities, and practices to align with our corporate digital transformation strategy.

Internal use of these shareable services shaves up to 70% off of our design cycles, because so many decisions are already made. Commerce Cloud adoption means you’ve gotten on the path internally, lowered the friction, and are aligned with the broader company digital transformation strategy. 

Measuring success

We’re proud of what we’ve accomplished so far at Pitney Bowes. But pride only takes you so far. To determine a project’s success, you need to be able to measure it. 

We do have some encouraging external measures: our percentage of revenue from new products climbed to roughly 20% of sales in 2018, compared to 5% back in 2012. And our Shipping APIs, which enable customers to integrate U.S. Postal Service capabilities into their own solutions, has gone from a standing start to an over $100 million business in a few years.

On top of those external results, our business has transformed. We’re no longer just participating in a one-time sale of a product, software, or services; we’re participating in transactions every day that drive client outcomes. The more you can improve the quality and effectiveness of those services, the more you and your client enjoy the benefits of the commercial relationship. That’s a very big business model transformation for Pitney Bowes.

We’ve also sped up our time to market and tightened our service-level agreements. But perhaps most importantly, we’ve developed and adopted a new set of internal processes and a mindset that helps us quickly adapt to changing market conditions. Again, digital transformation isn’t a destination. It’s really a set of processes that enable us to be nimble and keep building a bridge to Pitney Bowes’ future.

For more on the Pitney Bowes transformation, check out these videos and this case study.

Updated for 2021: This post includes updated best practices including the latest from Google’s Best Practices for Password Management whitepapers for both users and system designers.

Account management, authentication and password management can be tricky. Often, account management is a dark corner that isn’t a top priority for developers or product managers. The resulting experience often falls short of what some of your users would expect for data security and user experience.

Fortunately, Google Cloud brings several tools to help you make good decisions around the creation, secure handling and authentication of user accounts (in this context, anyone who identifies themselves to your system—customers or internal users). Whether you’re responsible for a website hosted in Google Kubernetes Engine, an API on Apigee, an app using Firebase, or other service with authenticated users, this post lays out the best practices to follow to ensure you have a safe, scalable, usable account authentication system.

1. Hash those passwords

My most important rule for account management is to safely store sensitive user information, including their password. You must treat this data as sacred and handle it appropriately.

Do not store plaintext passwords under any circumstances. Your service should instead store a cryptographically strong hash of the password that cannot be reversed—created with Argon2id, or Scrypt. The hash should be salted with a value unique to that specific login credential. Do not use deprecated hashing technologies such as MD5, SHA1 and under no circumstances should you use reversible encryption or try to invent your own hashing algorithm. Use a pepper that is not stored in the database to further protect the data in case of a breach. Consider the advantages of iteratively re-hashing the password multiple times.

Design your system assuming it will be compromised eventually. Ask yourself “If my database were exfiltrated today, would my users’ safety and security be in peril on my service or other services they use?” As well as “What can we do to mitigate the potential for damage in the event of a leak?”

Another point: If you could possibly produce a user’s password in plaintext at any time outside of immediately after them providing it to you, there’s a problem with your implementation.

If your system requires detection of near-duplicate passwords, such as changing “Password” to “pAssword1”, save the hashes of common variants you wish to ban with all letters normalized and converted to lowercase. This can be done when a password is created or upon successful login for pre-existing accounts. When the user creates a new password, generate the same type of variants and compare the hashes to those from the previous passwords. Use the same level of hashing security as with the actual password. 

2. Allow for third-party identity providers if possible

Third-party identity providers enable you to rely on a trusted external service to authenticate a user’s identity. Google, Facebook, and Twitter are commonly used providers.

You can implement external identity providers alongside your existing internal authentication system using a platform such as Identity Platform. There are a number of benefits that come with Identity Platform, including simpler administration, a smaller attack surface, and a multi-platform SDK. We’ll touch on more benefits throughout this list.

3. Separate the concept of user identity and user account

Your users are not an email address. They’re not a phone number. They’re not even a unique username. Any of these authentication factors should be mutable without changing the content or personally identifiable information (PII) in the account. Your users are the multi-dimensional culmination of their unique, personalized data and experience within your service, not the sum of their credentials. A well-designed user management system has low coupling and high cohesion between different parts of a user’s profile.

Keeping the concepts of user account and credentials separate will greatly simplify the process of implementing third-party identity providers, allowing users to change their username, and linking multiple identities to a single user account. In practical terms, it may be helpful to have an abstract internal global identifier for every user and associate their profile and one or more sets of authentication datavia that ID as opposed to piling it all in a single record.

4. Allow multiple identities to link to a single user account

A user who authenticates to your service using their username and password one week might choose Google Sign-In the next without understanding that this could create a duplicate account. Similarly, a user may have very good reason to link multiple email addresses to your service. If you’ve properly separated user identity and authentication, it will be a simple process to link several authentication methods to a single user.

Your backend will need to account for the possibility that a user gets part or all the way through the signup process before they realize they’re using a new third-party identity not linked to their existing account in your system. This is most simply achieved by asking the user to provide a common identifying detail, such as email address, phone, or username. If that data matches an existing user in your system, require them to also authenticate with a known identity provider and link the new ID to their existing account.

5. Don’t block long or complex passwords

NIST publishes guidelines on password complexity and strength. Since you are (or will be very soon) using a strong cryptographic hash for password storage, a lot of problems are solved for you. Hashes will always produce a fixed-length output no matter the input length, so your users should be able to use passwords as long as they like. If you must cap password length, do so based on the limits of your infrastructure; often this is a matter of memory usage (memory used per login operation * potential concurrent logins per machine), or more likely—the maximum POST size allowable by your servers. We’re talking numbers from hundreds of KB to over 1MB. Seriously. Your application should already be hardened to prevent abuse from large inputs. This doesn’t create new opportunities for abuse if you employ controls to prevent credential stuffing and hash the input as soon as possible to free up memory.

Your hashed passwords will likely already consist of a small set of ASCII characters. If not, you can easily convert a binary hash to Base64. With that in mind, you should allow your users to use literally any characters they wish in their password. If someone wants a password made of Klingon, Emoji, and ASCII art with whitespace on both ends, you should have no technical reason to deny them. Just make sure to perform Unicode normalization to ensure cross-platform compatibility. See our system designers whitepaper (PDF) for more information on Unicode and supported characters in passwords.

Any user attempting to use an extreme password is probably following password best practices (PDF) including using a password manager, which allows the entry of complex passwords even on limited mobile device keyboards. If a user can input the string in the first place (i.e., the HTML specification for password input disallows line feed and carriage return), the password should be acceptable.

6. Don’t impose unreasonable rules for usernames

It’s not unreasonable for a site or service to require usernames longer than two or three characters, block hidden characters, and prevent whitespace at the beginning and end of a username. However, some sites go overboard with requirements such as a minimum length of eight characters or by blocking any characters outside of 7-bit ASCII letters and numbers.

A site with tight restrictions on usernames may offer some shortcuts to developers, but it does so at the expense of users and extreme cases will deter some users.

There are some cases where the best approach is to assign usernames. If that’s the case for your service, ensure the assigned username is user-friendly insofar as they need to recall and communicate it. Alphanumeric generated IDs should avoid visually ambiguous symbols such as “Il1O0.” You’re also advised to perform a dictionary scan on any randomly generated string to ensure there are no unintended messages embedded in the username. These same guidelines apply to auto-generated passwords.

7. Validate the user’s identity

If you ask a user for contact information, you should validate that contact as soon as possible. Send a validation code or link to the email address or phone number. Otherwise, users may make a typo in their contact info and then spend considerable time using your service only to find there is no account matching their info the next time they attempt login. These accounts are often orphaned and unrecoverable without manual intervention. Worse still, the contact info may belong to someone else, handing full control of the account to a third party.

8. Allow users to change their username

It’s surprisingly common in legacy systems or any platform that provides email accounts not to allow users to change their username. There are very good reasons not to automatically release usernames for reuse, but long-term users of your system will eventually come up with significant reasons to use a different username and they likely won’t want to create a new account.

You can honor your users’ desire to change their usernames by allowing aliases and letting your users choose the primary alias. You can apply any business rules you need on top of this functionality. Some orgs might limit the number of username changes per year or prevent a user from displaying or being contacted via anything but their primary username. Email address providers are advised to never re-issue email addresses, but they could alias an old email address to a new one. A progressive email address provider might even allow users to bring their own domain name and have any address they wish.

If you are working with a legacy architecture, this best practice can be very difficult to meet. Even companies like Google have technical hurdles that make this more difficult than it would seem. When designing new systems, make every effort to separate the concept of user identity and user account and allow multiple identities to link to a single user account and this will be a much smaller problem. Whether you are working on existing or greenfield code, choose the right rules for your organization with an emphasis on allowing your users to grow and change over time.

9. Let your users delete their accounts

A surprising number of services have no self-service means for a user to delete their account and associated PII. Depending on the nature of your service, this may or may not include public content they created such as posts and uploads. There are a number of good reasons for a user to close an account permanently and delete all their PII . These concerns need to be balanced against your user experience, security, and compliance needs. Many if not most systems operate under some sort of regulatory control (such as PCI or GDPR), which provides specific guidelines on data retention for at least some user data. A common solution to avoid compliance concerns and limit data breach potential is to let users schedule their account for automatic future deletion.

In some circumstances, you may be legally required to comply with a user’s request to delete their PII in a timely manner. You also greatly increase your exposure in the event of a data breach where the data from “closed” accounts is leaked.

10. Make a conscious decision on session length

An often overlooked aspect of security and authentication is session length. Google puts a lot of effort into ensuring users are who they say they are and will double-check based on certain events or behaviors. Users can take steps to increase their security even further.

Your service may have good reason to keep a session open indefinitely for non-critical analytics purposes, but there should be thresholds after which you ask for password, 2nd factor, or other user verification.

Consider how long a user should be able to be inactive before re-authenticating. Verify user identity in all active sessions if someone performs a password reset. Prompt for authentication or 2nd factor if a user changes core aspects of their profile or when they’re performing a sensitive action. Re-authenticate if the user’s location changes significantly in a short period of time. Consider whether it makes sense to disallow logging in from more than one device or location at a time.

When your service does expire a user session or requires re-authentication, prompt the user in real time or provide a mechanism to preserve any activity they have not saved since they were last authenticated. It’s very frustrating for a user to take a long time to fill out a form, only to  find all their input has been lost and they must log in again.

11. Use 2-Step Verification

Consider the practical impact on a user of having their account stolen when choosing 2-Step Verification (also known as two-factor authentication, MFA, or 2FA) methods. Time-based one-time passwords (TOTP), email verification codes, or “magic links” are consumer-friendly and relatively secure. SMS 2FA auth has been deprecated by NIST due to multiple weaknesses, but it may be the most secure option your users will accept for what they consider a trivial service.

Offer the most secure 2FA auth you reasonably can. Hardware 2FA such as the Titan Security Key are ideal if feasible for your application. Even if a TOTP library is unavailable for your application, email verification or 2FA provided by third-party identity providers is a simple means to boost your security without great expense or effort. Just remember that your user accounts are only as secure as the weakest 2FA or account recovery method.

12. Make user IDs case-insensitive

Your users don’t care and may not even remember the exact case of their username. Usernames should be fully case-insensitive. It’s trivial to store usernames and email addresses in all lowercase and transform any input to lowercase before comparing. Make sure to specify a locale or employ Unicode normalization on any transformations.

Smartphones represent an ever-increasing percentage of user devices. Most of them offer autocorrect and automatic capitalization of plain-text fields. Preventing this behavior at the UI level might not be desirable or completely effective, and your service should be robust enough to handle an email address or username that was unintentionally auto-capitalized.

13. Build a secure auth system

If you’re using a service like Identity Platform, a lot of security concerns are handled for you automatically. However, your service will always need to be engineered properly to prevent abuse. Core considerations include implementing a password reset instead of password retrieval, detailed account activity logging, rate-limiting login attempts to prevent credential stuffing, locking out accounts after too many unsuccessful login attempts, and requiring two-factor authentication for unrecognized devices or accounts that have been idle for extended periods. There are many more aspects to a secure authentication system, so please see the further reading section below for links to more information. 

Further reading

There are a number of excellent resources available to guide you through the process of developing, updating, or migrating your account and authentication management system. I recommend the following as a starting place:

• Our Modern Password Security for System Designers whitepaper (PDF)
• The related Modern password security for users whitepaper (PDF)
• NIST 800-063B covers Authentication and Lifecycle Management 
• OWASP continually updates their Password Storage Cheat Sheet 
• OWASP goes into even more detail with the Authentication Cheat Sheet
• Google Cloud Identity Platform is a multi-protocol customer identity and access management solution, with robust authentication features
• Google’s Firebase Authentication site has a rich library of guides, reference materials and sample code

The digital era turned the traditional formula for media and entertainment success on its head, ushering in new technologies that have changed how content is produced, distributed, experienced, and monetized. Audiences have more choice, flexibility, and power over what they consume, and today’s media companies have to embrace ongoing transformation or risk falling behind – or becoming irrelevant. 

A new wave of transformation is arriving with generative AI, a type of artificial intelligence that can interact with users in natural language and create novel data, ranging from story outlines, reports, and other text outputs to multimodal content like images, videos, and audio. Media and entertainment are inherently about content creation and creativity—so what does this new technology mean for the industry? 

At Google Cloud, we see tremendous opportunity for creative industries, from more efficient creation methods to improved user experiences. Let’s explore.

AI for media with Google Cloud

Google Cloud has a long history with large language models (LLMs) and other generative AI technologies—from their influence over the years on products like Document AI, to recent announcements like Generative AI support in Vertex AI, which lets businesses access and tune generative AI foundation models, and Generative AI App Builder, which lets developers build chatbots and other generative apps in minutes.  

We’ve helped our global media and entertainment customers with AI for personalization, search and recommendations, predictive analytics, and much more — and with generative AI now on the rise, we have some ideas to help media leaders, technologists, and creators think about and prepare to utilize powerful AI in their work. 

Three lenses on innovation in media

The media and entertainment industry is increasingly diverse and complex, with companies spanning over-the-top (OTT) subscription streaming services, 24-hour linear channels, live broadcasts of sporting events, digital journalism, traditional publishing, short-form user-generated social video, and more. More and more, the boundaries between these segments of the media industry are blurring — but common to them all is the focus on providing compelling content in an engaging audience experience that can be directly or indirectly monetized.

With this in mind, we suggest media and entertainment companies look at the application of innovative technologies like generative AI through the following three lenses:

1. Improving content creation, production, and management
2. Enhancing and personalizing audience experiences
3. Improving monetization

Improving content creation, production, and management

Generative AI democratizes many aspects of content creation, opening new ways to create written material, illustrations, sound effects, special effects, and more. Its recent maturation has been so rapid, some in the media industry have expressed concern that generative AI implies the end of creative professions. We think the opposite is more likely: just as photography, audio recordings, and computer generated images have enabled new modes of creativity, rather than making old ones obsolete, generative AI has the potential to both enable new forms of expression and enhance familiar ones. 

For example, journalists could use generative AI to speed up research by helping them synthesize and analyze large volumes of information, or to help them create initial drafts or summaries of editorial content. Film and television producers could leverage the technology to accelerate the post-production editing process, with new AI-enabled interfaces for rapidly adjusting or enhancing scene details such as lighting and color. Broadcasters could use generative AI to make vast libraries of video footage searchable and accessible for use in telling more compelling stories. The potential use cases go on and on.

Far from undermining incredible creative professions, generative AI is poised to free writers, artists, editors, and many others from the tedious and mundane aspects of their work, empowering them to focus more of their time on creativity.

Enhancing and personalizing audience experiences

Every media organization in the world today faces the reality that for most consumers, switching costs are extremely low. This puts incredible pressure on these companies to invest in delivering low-friction and compelling audience experiences that help mitigate subscribers from churning and viewers from abandoning content experiences for competitive platforms. 

Generative AI can help media companies engage and retain viewers, such as by enabling more powerful search and recommendations on their digital content platforms. With its increasingly multimodal capabilities extending from natural language to both audio and video content, generative AI is well-positioned to power more personalized audience experiences. 

Consumers often complain about “the paradox of choice” or their inability to find something interesting to watch on streaming platforms that have incredibly vast libraries of content available on demand. Imagine a not-too-distant future wherein a consumer can simply ask the content platform they’re using to help them find a specific show to watch based on mood, specific types of scenes, combinations of actors, award nominations, or practically anything they can think to ask. And that’s just the tip of the iceberg — imagine generative AI’s potential to curate, assemble, and even create personalized content for a viewer to consume!

Improving monetization

As consumers’ content consumption further expands from traditional theatrical and linear television programming to include digital offerings across an array of platforms, devices, and content types, media companies face the challenge of maintaining and improving monetization. The conventional economics and approaches to advertising and subscription models are proving, in many cases, not to deliver sufficient ROI. 

Generative AI has the potential to help media companies improve their monetization of audience experiences. As mentioned previously, enhanced personalization can play a role in mitigating churn, which in turn can help sustain and grow subscription and advertising revenues. Going beyond this, generative AI can be leveraged to drive even greater advertising revenues via more targeted, contextual, and personalized advertisements. Imagine both display and video advertisements that are generated on the fly to personalize product specifics, messaging, style, colors, and innumerable other characteristics to drive greater engagement and higher click-through rates (CTR), and thus higher advertising CPMs (cost per thousand impressions).

Coming up next

Generative AI presents a significant opportunity for media companies to fundamentally transform content creation, engagement, and monetization. Compelling services are already on the market — but there is far more to come. 

Google Cloud continues to build on its deep experience and expertise with AI, and we are committed to working with the industry to develop compelling, accessible, trusted, and responsible AI solutions that will drive meaningful business outcomes. We are excited to create the future together with our global media customers and partners across the ecosystem. To learn more about this disruptive topic, read “Debunking five generative AI misconceptions” from Google Cloud vice president of AI & Business Solutions Phil Moyer, or explore our Trusted Tester Program for generative AI.