Extra Crunch offers members the opportunity to tune into conference calls led and moderated by the TechCrunch writers you read every day. This week, TechCrunch’s Frederic Lardinois and Ron Miller offered up their analysis on the major announcements that came out of Google’s Cloud Next conference this past week, as well as their opinions on the outlook for the company going forward.

Google Cloud announced a series of products, packages and services that it believes will improve the company’s competitive position and differentiate itself from AWS and other peers. Frederic and Ron discuss all of Google’s most promising announcements, including its product for managing hybrid clouds, its new end-to-end AI platform, as well as the company’s heightened effort to improve customer service, communication, and ease-of-use.

“They have all of these AI and machine learning technologies, they have serverless technologies, they have containerization technologies — they have this whole range of technologies.

But it’s very difficult for the average company to take these technologies and know what to do with them, or to have the staff and the expertise to be able to make good use of them. So, the more they do things like this where they package them into products and make them much more accessible to the enterprise at large, the more successful that’s likely going to be because people can see how they can use these.

…Google does have thousands of engineers, and they have very smart people, but not every company does, and that’s the whole idea of the cloud. The cloud is supposed to take this stuff, put it together in such a way that you don’t have to be Google, or you don’t have to be Facebook, you don’t have to be Amazon, and you can take the same technology and put it to use in your company”

Image via Bryce Durbin / TechCrunch

Frederic and Ron dive deeper into how the new offerings may impact Google’s market share in the cloud ecosystem and which verticals represent the best opportunity for Google to win. The two also dig into the future of open source in cloud and how they see customer use cases for cloud infrastructure evolving.

For access to the full transcription and the call audio, and for the opportunity to participate in future conference calls, become a member of Extra Crunch. Learn more and try it for free. 

Source: Tech Crunch

New machine learning technologies, user interfaces and automated content creation techniques are going to expand the personalization of storytelling beyond algorithmically generated news feeds and content recommendation.

The next wave will be software-generated narratives that are tailored to the tastes and sentiments of a consumer.

Concretely, it means that your digital footprint, personal preferences and context unlock alternative features in the content itself, be it a news article, live video or a hit series on your streaming service.

The title contains different experiences for different people.

From smart recommendations to smarter content

When you use Youtube, Facebook, Google, Amazon, Twitter, Netflix or Spotify, algorithms select what gets recommended to you. The current mainstream services and their user interfaces and recommendation engines have been optimized to serve you content you might be interested in.

Your data, other people’s data, content-related data and machine learning methods are used to match people and content, thus improving the relevance of content recommendations and efficiency of content distribution.

However, so far the content experience itself has mostly been similar to everyone. If the same news article, live video or TV series episode gets recommended to you and me, we both read and watch the same thing, experiencing the same content.

That’s about to change. Soon we’ll be seeing new forms of smart content, in which user interface, machine learning technologies and content itself are combined in a seamless manner to create a personalized content experience.

What is smart content?

Smart content means that content experience itself is affected by who is seeing, watching, reading or listening to content. The content itself changes based on who you are.

We are already seeing the first forerunners in this space. TikTok’s whole content experience is driven by very short videos, audiovisual content sequences if you will, ordered and woven together by algorithms. Every user sees a different, personalized, “whole” based on her viewing history and user profile.

At the same time, Netflix has recently started testing new forms of interactive content (TV series episodes, e.g. Black Mirror: Bandersnatch) in which user’s own choices affect directly the content experience, including dialogue and storyline. And more is on its way. With Love, Death & Robots series, Netflix is experimenting with episode order within a series, serving the episodes in different order for different users.

Some earlier predecessors of interactive audio-visual content include sports event streaming, in which the user can decide which particular stream she follows and how she interacts with the live content, for example rewinding the stream and spotting the key moments based on her own interest.

Simultaneously, we’re seeing how machine learning technologies can be used to create photo-like images of imaginary people, creatures and places. Current systems can recreate and alter entire videos, for example by changing the style, scenery, lighting, environment or central character’s face. Additionally, AI solutions are able to generate music in different genres.

Now, imagine, that TikTok’s individual short videos would be automatically personalized by the effects chosen by an AI system, and thus the whole video would be customized for you. Or that the choices in the Netflix’s interactive content affecting the plot twists, dialogue and even soundtrack, were made automatically by algorithms based on your profile.

Personalized smart content is coming to news as well. Automated systems, using today’s state-of-the-art NLP technologies, can generate long pieces of concise, comprehensible and even inventive textual content at scale. At present, media houses use automated content creation systems, or “robot journalists”, to create news material varying from complete articles to audio-visual clips and visualizations. Through content atomization (breaking content into small modular chunks of information) and machine learning, content production can be increased massively to support smart content creation.

Say that a news article you read or listen to is about a specific political topic that is unfamiliar to you. When comparing the same article with your friend, your version of the story might use different concepts and offer a different angle than your friend’s who’s really deep into politics. A beginner’s smart content news experience would differ from the experience of a topic enthusiast.

Content itself will become a software-like fluid and personalized experience, where your digital footprint and preferences affect not just how the content is recommended and served to you, but what the content actually contains.

Automated storytelling?

How is it possible to create smart content that contains different experiences for different people?

Content needs to be thought and treated as an iterative and configurable process rather than a ready-made static whole that is finished when it has been published in the distribution pipeline.

Importantly, the core building blocks of the content experience change: smart content consists of atomized modular elements that can be modified, updated, remixed, replaced, omitted and activated based on varying rules. In addition, content modules that have been made in the past, can be reused if applicable. Content is designed and developed more like a software.

Currently a significant amount of human effort and computing resources are used to prepare content for machine-powered content distribution and recommendation systems, varying from smart news apps to on-demand streaming services. With smart content, the content creation and its preparation for publication and distribution channels wouldn’t be separate processes. Instead, metadata and other invisible features that describe and define the content are an integral part of the content creation process from the very beginning.

Turning Donald Glover into Jay Gatsby

With smart content, the narrative or image itself becomes an integral part of an iterative feedback loop, in which the user’s actions, emotions and other signals as well as the visible and invisible features of the content itself affect the whole content consumption cycle from the content creation and recommendation to the content experience. With smart content features, a news article or a movie activates different elements of the content for different people.

It’s very likely that smart content for entertainment purposes will have different features and functions than news media content. Moreover, people expect frictionless and effortless content experience and thus smart content experience differs from games. Smart content doesn’t necessarily require direct actions from the user. If the person wants, the content personalization happens proactively and automatically, without explicit user interaction.

Creating smart content requires both human curation and machine intelligence. Humans focus on things that require creativity and deep analysis while AI systems generate, assemble and iterate the content that becomes dynamic and adaptive just like software.

Sustainable smart content

Smart content has different configurations and representations for different users, user interfaces, devices, languages and environments. The same piece of content contains elements that can be accessed through voice user interface or presented in augmented reality applications. Or the whole content expands into a fully immersive virtual reality experience.

In the same way as with the personalized user interfaces and smart devices, smart content can be used for good and bad. It can be used to enlighten and empower, as well as to trick and mislead. Thus it’s critical, that human-centered approach and sustainable values are built in the very core of smart content creation. Personalization needs to be transparent and the user needs to be able to choose if she wants the content to be personalized or not. And of course, not all content will be smart in the same way, if at all.

If used in a sustainable manner, smart content can break filter bubbles and echo chambers as it can be used to make a wide variety of information more accessible for diverse audiences. Through personalization, challenging topics can be presented to people according to their abilities and preferences, regardless of their background or level of education. For example a beginner’s version of vaccination content or digital media literacy article uses gamification elements, and the more experienced user gets directly a thorough fact-packed account of the recent developments and research results.

Smart content is also aligned with the efforts against today’s information operations such as fake news and its different forms such as “deep fakes” (http://www.niemanlab.org/2018/11/how-the-wall-street-journal-is-preparing-its-journalists-to-detect-deepfakes). If the content is like software, a legit software runs on your devices and interfaces without a problem. On the other hand, even the machine-generated realistic-looking but suspicious content, like deep fake, can be detected and filtered out based on its signature and other machine readable qualities.

Smart content is the ultimate combination of user experience design, AI technologies and storytelling.

News media should be among the first to start experimenting with smart content. When the intelligent content starts eating the world, one should be creating ones own intelligent content.

The first players that master the smart content, will be among tomorrow’s reigning digital giants. And that’s one of the main reasons why today’s tech titans are going seriously into the content game. Smart content is coming.

Source: Tech Crunch

[Editor’s note: this is a free example of a series of articles we’re publishing by top experts who have cutting-edge startup advice to offer, over on Extra Crunch. Get in touch at ec_columns@techcrunch.com if you have ideas to share.] 

Even the best growth marketers fail to get content marketing to work. Many are unwittingly using tactics from 4 years ago that no longer work today.

This post cuts through the noise by sharing real-world data behind some of the biggest SEO successes this year.

It studies the content marketing performance of clients with Growth Machine and Bell Curve (my company) — two marketing agencies who have helped grow Perfect Keto, Tovala, Framer, Crowd Cow, Imperfect Produce, and over a hundred others.

What content do their clients write about, how do they optimize that content to rank well (SEO), and how do they convert their readers into customers?

You’re about to see how most startups manage their blogs the wrong way.

Reference CupAndLeaf.com as we go along. Their tactics for hitting 150,000 monthly visitors will be explored.

Write fewer, more in-depth articles

In the past, Google wasn’t skilled at identifying and promoting high quality articles. Their algorithms were tricked by low-value, “content farm” posts.

That is no longer the case.

Today, Google is getting close to delivering on its original mission statement: “To organize the world’s information and make it universally accessible and useful.” In other words, they now reliably identify high quality articles. How? By monitoring engagement signals: Google can detect when a visitor hits the Back button in their browser. This signals that the reader quickly bounced from the article after they clicked to read it.

If this occurs frequently for an article, Google ranks that article lower. It deems it low quality.

For example, below is a screenshot of the (old) Google Webmaster Tools interface. It visualizes this quality assessment process: It shows a blog post with the potential to rank for the keyword “design packaging ideas.” Google initially ranked it at position 25.

However, since readers weren’t engaging with the content as time went on, Google incrementally ranked the article lower — until it completely fell off the results page:

The lesson? Your objective is to write high quality articles that keep readers engaged. Almost everything else is noise.

In studying our clients, we’ve identified four rules for writing engaging posts.

1. Write articles for queries that actually prioritize articles.

Not all search queries are best served by articles.

Below, examine the results for “personalized skincare:”

Notice that Google is prioritizing quizzes. Not articles.

So if you don’t perform a check like this before writing an article on “personalized skincare,” there’s a good chance you’re wasting your time. Because, for some queries, Google has begun prioritizing local recommendations, videos, quizzes, or other types of results that aren’t articles.

Sanity check this before you sit down to write.

2. Write titles that accurately depict what readers get from the content.

Are incoming readers looking to buy a product? Then be sure to show them product links.

Or, were they looking for a recipe? Provide that.

Make your content deliver on what your titles imply a reader will see. Otherwise, readers bounce. Google will then notice the accumulating bounces, and you’ll be penalized.

3. Write articles that conclude the searcher’s experience.

Your objective is to be the last site a visitor visits in their search journey.

Meaning, if they read your post then don’t look at other Google result, Google infers that your post gave the searcher what they were looking for. And that’s Google’s prime directive: get searchers to their destination through the shortest path possible.

The two-part trick for concluding the searcher’s journey is to:

Go sufficiently in-depth to cover all the subtopics they could be looking for.

Link to related posts that may cover the tangential topics they seek.

This is what we use Clearscope for — it ensures we don’t miss critical subtopics that help our posts rank:

4. Write in-depth yet concise content.

In 2019, what do most of the top-ranked blogs have in common?

They skip filler introductions, keep their paragraphs short, and get to the point.

And, to make navigation seamless, they employ a “table of contents” experience:

Be like them, and get out of the reader’s way. All our best-performing blogs do this.

Check out more articles by Julian Shapiro over on Extra Crunch, including “What’s the cost of buying users from Facebook and 13 other ad networks?” and “Which types of startups are most often profitable?”

Prioritize engagement over backlinks

In going through our data, the second major learning was about “backlinks”, which is marketing jargon for a link to your site from someone else’s.

Four years ago, the SEO community was focused on backlinks and Domain Ranking (DR) — an indication of how many quality sites link to yours (scored from 0 to 100). At the time, they were right to be concerned about backlinks.

Today, our data reveals that backlinks don’t matter as much as they used to. They certainly help, but you need great content behind them.

Most content marketers haven’t caught up to this.

Here’s a screenshot showing how small publishers can beat out large behemoths today — with very little Domain Ranking:

The implication is that, even without backlinks, Google is still happy to rank you highly. Consider this: They don’t need your site to be linked from TechCrunch for their algorithm to determine whether visitors are engaged on your site.

Remember: Google has Google Analytics, Google Search, Google Ads, and Google Chrome data to monitor how searchers engage with your site. Believe me, if they want to find out whether your content is engaging, they can find a way. They don’t need backlinks to tell them.

This is not to say that backlinks are useless.

Our data shows they still provide value, just much less. Notably, they get your pages “considered” by Google sooner: If you have backlinks from authoritative and relevant sites, Google will have the confidence to send test traffic to your pages in perhaps a few weeks instead of in a few months.

Here’s what I mean by “test traffic:” In the weeks after publishing your post, Google notices them then experimentally surfaces them at the top of related search terms. They then monitor whether searchers engage with the content (i.e. don’t quickly hit their Back button). If the engagement is engaging, they’ll increasingly surface your articles. And increase your rankings over time.

Having good backlinks can cut this process down from months to a few weeks.

Prioritize conversion over volume

Engagement isn’t your end goal. It’s the precursor to what ultimately matters: getting a signup, subscribe, or purchase. (Marketers call this your “conversion event.”) Visitors can take a few paths to your conversion event:

Short: They read the initial post then immediately convert.

Medium: They read the initial post plus a few more before eventually converting.

Long (most common): They subscribe to your newsletter and/or return later.

To increase the ratio at which readers take the short and medium paths, optimize your blog posts’ copy, design, and calls to action. We’ve identified two rules for doing this.

1. Naturally segue to your pitch

Our data shows you should not pitch your product until the back half of your post.

Why? Pitching yourself in the intro can taint the authenticity of your article.

Also, the further a reader gets into a good article, the more familiarity and trust they’ll accrue for your brand, which means they’re less likely to ignore your pitch once they encounter it.

2. Don’t make your pitch look like an ad

Most blogs make their product pitches look like big, show-stopping banner ads.

Our data shows this visual fanfare is reflexively ignored by readers.

Instead, plug your product using a normal text link — styled no differently than any other link in your post. Woodpath, a health blog with Amazon products to pitch, does this well.

Think in funnels, not in pageviews

Finally, our best-performing clients focus less on their Google Analytics data and more on their readers’ full journeys: They encourage readers to provide their email so they can follow up with a series of “drip” emails. Ideally, these build trust in the brand and get visitors to eventually convert.

They “retarget” readers with ads. This entails pitching them with ads for the products that are most relevant to the topics they read on the blog. (Facebook and Instagram provide the granular control necessary to segment traffic like this.) You can read my growth marketing handbook to learn more about running retargeting ads well.

Here’s why retargeting is high-leverage: In running Facebook and Instagram ads for over a hundred startups, we’ve found that the cost of a retargeting purchase is one third the cost of a purchase from ads shown to people who haven’t yet been to our site.

Our data shows that clients who earn nothing from their blog traffic can sometimes earn thousands by simply retargeting ads to their readers.

Recap

It’s possible for a blog with 50,000 monthly visitors to earn nothing.

So, prioritize visitor engagement over volume: Make your hero metrics your revenue per visitor and your total revenue. That’ll keep your eye on the intermediary goals that matter: Attracting visitors with an intent to convert

Keeping those visitors engaged on the site

Then compelling them to convert

In short, your goal is to help Google do its job: Get readers where they need to go with the least amount of friction in their way.

Be sure to check out more articles from Julian Shapiro over on Extra Crunch, and get in touch with the Extra Crunch editors if you have cutting-edge startup advice to share with our subscribers, at ec_columns@techcrunch.com.

Source: Tech Crunch

Updating the federal government’s digital infrastructure seems like a Herculean task akin to cleaning out the Augean stables. Where do you even start shoveling? Former Googler and current head of the U.S. Digital Service Matt Cutts says it’s not quite that hard — but he’s had to leave his Silicon Valley startup outlook at the door.

“In the Valley and San Francisco, they’re geared to move fast and break things. And that’s fantastic to explore a space,” Cutts told me in an interview. “But the government has to move purposefully and fix things. It’s more about finding the right decision, achieving consensus, creating good communication.”

The USDS is a small (and actively recruiting) department that takes on creaking interfaces and tangled databases of services for, say, veteran benefit management or immigration documentation, buffing them to a shiny finish that may save their users months of literal paperwork.

Some notes from the USDS’s work on modernizing the Medicare payment system.

Recently, for instance, the USDS overhauled VA.gov, which is how many veterans access things like benefits, make medical appointments, and so on. But until recently it was kind of a mess of interconnected sub-sites and instructional PDFs. USDS interviewed a couple thousand vets and remade the site with a single login, putting the most-used services right on the front page. Seems obvious, but the inertia of these systems is considerable.

“Oftentimes we build a front end and it still talks to an abysmal, or maybe antiquarian, system in the back end,” Cutts said. “VA.gov required a special version of Internet Explorer!”

There are always paper alternatives, but those can be so slow and clunky that they might take three or four months to complete, and can be so complex that people will hire a lawyer to do them rather than risk further delay. These are ostensibly free and open services available to all vets — but they weren’t in practice. And there were accessibility problems all over the place, Cutts noted, which is especially troubling with a disability-heavy population like veterans.

These projects are often short-term, putting modern web and backend standards to work and handing the results off to the agency or department that requested it. The USDS isn’t built for long-term support but acts as a strike team putting smart solutions in place that may seem obvious in startup culture but haven’t yet become standard operating procedure in the capitol.

The work they do is guided by impact, not politics, which is likely part of the reason they’ve managed to avoid interference by the Trump administration, which has treated many other Obama-era initiatives like pests to be exterminated. Yet the nature of the work is in a way fundamentally progressive, in that it is about bottom-up accessibility and helping under-represented or unprivileged groups.

For instance, they’ve been hard at work on immigration issues that would expedite both asylum seekers and seasonal farm workers at the Mexican border. That’s a political live wire right now, even if the decision to do it was strictly based on helping a large population frustrated by outdated digital tools.

The new farmers.gov, built for the Department of Agriculture, vastly streamlines the H-2A visa application process, centralizing documentation and services that were previously spread across several other major departments and websites. That’s unarguably a good thing, but like anything relating to immigration and foreign labor it is possible it could get swept up in the partisan twister. Fortunately that doesn’t seem to have happened.

The new, improved and simplified farmers.gov provides app integration and straightforward design.

“The fact is we get good support,” Cutts said when I asked him about the current political environment. It may not be loud in that support, but quiet actions like appointing former USDS officials and engineers to important roles within administration are common, he said.

There are plenty of other programs looking to modernize federal as well as state systems, he pointed out; it’s a rising tide and it’s lifting a lot of boats.

“I signed up for a three month tour, and that was three years ago,” he said. “It’s really a whole civic tech movement here, there are a ton of people sort of holding hands and working together. There’s also stuff happening at the state and local level, at the international level, from the UK to Estonia and Singapore — everyone’s starting to realize this matters.”

Recruitment, however, is more difficult than he’d like, perhaps partly because of self-imposed hiring practices made to reflect the diversity of the country.

“We get the best results when we represent all of America,” said Cutts. “So I go to Microsoft and Ann Arbor, regular events, but also like, Lesbians Who Tech or Grace Hopper Fest.”

Still, startups and big tech companies regularly poach talent or otherwise lure them away. “They’re just better at recruiting,” he said. And there’s some kind of fundamental disconnect at work, too, perhaps the comfortable contempt many young people have for the government — but he suggested that those seeking to do good might want to do a more serious evaluation of the tech landscape.

“I joined Google because I wanted to make the world a better place,” he said. “But if you look at the #metoo movement, how the tech industry has been acting lately… everyone at those companies has to ask that question, am I really having that impact?”

If you’re not sure, you might consider doing a tour at the USDS. They’re launching products and helping people just like startups aim to do, but they’re beholden to ordinary citizens in need, not investors. That sounds like a step up to me.

Source: Tech Crunch