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Google’s third-party cookie delay: Adtech reacts

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Infutor suite of identity resolution services integrated into Snowflake Media Data Cloud

Yesterday we reported that Google had again pushed back the target date for deprecating third-party cookies on Chrome. They will now start phasing them out in late 2024. The reason given was feedback from Google Privacy Sandbox participants that they needed more time to evaluate proposed alternatives to cookie tracking.

Reaction was quick to come, especially from the identity resolution and data platforms in the adtech and martech spaces.

Billions of dollars at risk. “As much as this announcement is a blessing for advertisers and partners looking to cement a strategy for tracking and measurement beyond the cookie, it also creates ambiguity around when this preparedness needs to be finalized,” said Matt Engstrom, VP marketing at adtech platform Digital Remedy. “Companies placing development resources into initiatives such as independent web IDs, may now face an additional setback as those alternatives aren’t required in the short term as Google continues to push out the deadline.”

Engstrom also echoed our opinion that Google’s advertising business is dictating this ultra-cautious approach. “This moving target could be the result of Google’s own concerns around having a viable sandbox alternative ready to deploy upon a finalization of cookie deprecation,” he said. “As the world’s largest advertising partner they have billions of dollars at risk.”


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Forget identities. Kelly Anderson, SVP and head of data privacy and compliance at adtech company Emodo is calling for a scorched earth approach when it comes to identity-based targeting. “The continuous delay by Google to deprecate third-party cookies proves that the industry should take a step back from focusing solely on identity solutions and think creatively about ID-less solutions,” she said. “There is an opportunity for businesses building and supporting alternative ID-less targeting solutions, like those using artificial intelligence and dynamic creative, to leverage this extra time to understand what’s really working and perfect their solutions.”

Iván Markman, Chief Business Officer at Yahoo, also highlighted ID-less strategies. “The future of identity lies in the ability to leverage direct, consumer-consented sources and to be smarter about signals that are not attached to a consumer’s identity.”

Accent on the positive. Some commentators saw opportunity here. “Encouragingly, we know that 30% of ad budgets are already allocated to cookieless ads and that the industry is testing privacy-first alternatives, such as first-party data solutions and contextual targeting,” said Sergeii Denysenko, CEO of programmatic platform MGID. “For now, the open web is at a huge competitive advantage; the postponement of the cookie’s demise gives platforms outside the walled gardens a chance to strengthen alternative targeting methods in order to thrive in the privacy-first world.”

Read next: MGID’s Ukrainian operations continue despite the bombs

Similar sentiments were expressed by Adib Karbouj, head of ad operations at BCNMonetize, a mobile ad platform specializing in inventory outside of Facebook and Google. “Google extending the phase-out of cookies gives some breathing room for those who haven’t yet adapted, but at this point the industry overall feels well-prepared. It will, however, be exciting to see what further innovations will emerge in cookieless tracking, targeting, measurement and audience segmentation over the next two years.”

Why we care. Everyone will be talking about this for the next week or so. Then they’ll get back to developing their preferred alternatives to cookies; and then Google will push back the deadline again — or it won’t.

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Or Congress might actually pass bipartisan federal privacy legislation which will set constraints on data collection and use, and will effectively tell the Privacy Sandbox what it can and can’t do.


About The Author

Kim Davis is the Editorial Director of MarTech. Born in London, but a New Yorker for over two decades, Kim started covering enterprise software ten years ago. His experience encompasses SaaS for the enterprise, digital- ad data-driven urban planning, and applications of SaaS, digital technology, and data in the marketing space.

He first wrote about marketing technology as editor of Haymarket’s The Hub, a dedicated marketing tech website, which subsequently became a channel on the established direct marketing brand DMN. Kim joined DMN proper in 2016, as a senior editor, becoming Executive Editor, then Editor-in-Chief a position he held until January 2020.

Prior to working in tech journalism, Kim was Associate Editor at a New York Times hyper-local news site, The Local: East Village, and has previously worked as an editor of an academic publication, and as a music journalist. He has written hundreds of New York restaurant reviews for a personal blog, and has been an occasional guest contributor to Eater.

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7 Critical Factors You Must Consider When Choosing RPA Tools

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Robotic Process Automation is a technology that makes it easy for businesses to build, deploy and manage bots that can replicate humans interacting with digital systems and software. These bots can perform structured and pre-defined tasks such as filling out a form, processing a financial transaction or sending messages.

The core purpose of robotic process automation is to automate mundane and repetitive tasks so that your employees don’t waste their time on those tasks and focus on more value-driven activities with automatic employee monitoring software. Yes, a human first has to define the workflow for a bot for it to work but once done, it can perform most tasks automatically.

Advantages of Robotic Process Automation

Here are some of the advantages of robotic process automation:

  • Optimal resource utilization
  • Save time
  • Reduces cost
  • Minimize errors
  • Increases business capacity

Disadvantages of Robotic Process Automation

Some of the disadvantages of robotic process automation are:

  • Requires monitoring and maintenance
  • Not capable to extract information from unstructured datasets
  • Can not automate complex tasks
  •  The time-consuming and costly setup process

In this article, you will learn about seven critical factors you must take into account when choosing robotic process automation tools for your business.

Before discussing factors you should consider when buying robotic process automation tools, it is important to understand that every robotic process automation tool has its own format and does not offer any kind of portability. This means that there are no standards so the one size fits all formula does not apply here.

Make sure that the robotic process automation software you are planning to buy has all the features you need along with some handy extras. Ask for proof of concept before rollout and only buy the software when you are sure that it is the right choice to meet your business needs.

7 Factors To Consider When Buying RPA Tools

Here are seven factors you must consider when buying a robotic process automation software

1.  Ease of bot setup

Setting up a robotic process automation software can be a daunting challenge for businesses as it can take a lot of time and resources. That is why it is imperative that enterprises invest in robotic process automation tools that are easy to set up and use.

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It must also allow a level of customization and let businesses create custom bots for different buyer personas. Developers should be able to call the robotic process automation tool API when writing code for automation.

2.  Low-code capabilities

Gone are the days when only experienced developers could create websites and apps. With the advent of low code tools, anyone can now create an app even with little to no coding knowledge(accounting app, management app, etc.). Low code development lets you drag and drop ready-made components from the tool library and write small code snippets for functions that are not present in the tool library of the tool. Choose robotic process automation tools that offer these low code capabilities.

3.  Machine learning capabilities

As mentioned before, robotic process automation software struggles when it comes to extracting actionable insights from unstructured datasets. Since a major chunk of company data is in unstructured form, it makes robotic process automation tools useless.

That is where the machine learning capabilities of these robotic process automation tools come in handy. With these capabilities, it can parse through documents, find information and return it to users. This can enhance the user experience and boost customer loyalty. Some vendors might give this a fancy name but the functionality remains the same.

4.  Integration with enterprise applications

Another important factor you can not afford to ignore when buying robotic process automation software is compatibility with enterprise applications. At the end of the day, your robotic process automation software’s utility is highly dependent on how these tools can integrate with your existing business application. This is about your data integration with supermetric alternatives and so on.

Its capability to extract data from your existing business applications matters most. Does your robotic process automation tool offer plugins to seamlessly connect it with your database, accounting systems, HR systems, appointment setting services and ERP systems? If yes, then you should certainly consider it as an option if it fulfills all your requirements.

5.  Orchestration and administration

Before these bots can take care of mundane tasks, you will have to first configure them and feed them with the right information as well as a secure credential. This secure credential is usually stored in a credential store. If you want other users to use your bots, you will first have to authorize and authenticate them.

You should also allocate resources for certain bots which trigger when a special event occurs. Once you have set it up, now you have to monitor it so it can work without human involvement. You will have to constantly improve its machine learning capabilities so it does not need human support when performing tasks.

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6.  Process and task discovery and mining

Identifying business processes you want to automate and prioritizing them is critical for the success of your robotic process automation implementation. Unfortunately, it is also the most time-consuming part of the process as well.

The more your robotic process automation software lets you mine for processes from system log and construct task flows by observations, the easier it will be for you to implement it and automate your business processes. Look for robotic process automation tools that make task discovery and mining painless.

7.  Scalability

If you are planning to implement robotic process automation throughout the organization, you will bump into scalability issues. The best way to resolve these scalability issues is to implement them in the cloud, in containers or via virtual machines. If the orchestration component can allocate extra bots when needed, solving the scalability problem is not a problem.

At the end of the day, the success and failure of your robotic process automation rest on identifying the best tasks and processes to be automated. Make sure to document every step involved in the process. Never cut corners in testing cycles because it can lead to some missing links in your robotic process automation systems.

What factors do you consider when selecting a robotic process automation software? Share it with us in the comments section below.

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