Tag Archive | "Content"

24 Ways to Give Your Content an Eye-Opening Shot of Vitality

At this point in January, I like to think that the new year has just had its second cup of…

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3 Steps that Superior Content Creators Can Take to a Badass 2019

Let’s get this out of the way: You are a badass. So how come no one else knows that yet?…

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Get a More Useful Perspective on Your Business and Content Goals

Sometimes in business, it’s a good idea to slow down and reflect on your real goals. Are you getting what…

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Content Comprehensiveness – Whiteboard Friday

Posted by KameronJenkins

When Google says they prefer comprehensive, complete content, what does that really mean? In this week’s episode of Whiteboard Friday, Kameron Jenkins explores actionable ways to translate the demands of the search engines into valuable, quality content that should help you rank.

Click on the whiteboard image above to open a high-resolution version in a new tab!

Video Transcription

Hey, guys. Welcome to this week’s edition of Whiteboard Friday. My name is Kameron Jenkins, and I work here at Moz.

Today we’re going to be talking about the quality of content comprehensiveness and what that means and why sometimes it can be confusing. I want to use an example scenario of a conversation that tends to go on between SEOs and Google. So here we go.

An SEO usually says something like, “Okay, Google, you say you want to rank high-quality content. But what does that really mean? What is high quality, because we need more specifics than that.”

Then Google goes, “Okay, high quality is something that’s comprehensive and complete. Yeah, it’s really comprehensive.” SEOs go, “Well, wait. What does that even mean?”

That’s kind of what this was born out of. Just kind of an explanation of what is comprehensive, what does Google mean when they say that, and how that differs depending on the query.

Here we have an example page, and I’ll kind of walk you through it. It’s just going to serve to demonstrate why when Google says “comprehensive,” that can mean something different for an e-commerce page than it would for a history of soccer page. It’s really going to differ depending on the query, because people want all sorts of different kinds of things. Their intent is going to be different depending on what they’re searching in Google. So the criteria is going to be different for comprehensiveness. So hopefully, by way of example, we’ll be able to kind of walk you through what comprehensiveness looks like for this one particular query. So let’s just dive in.

1. Intent

All right. So first I’m going to talk about intent. I have here a Complete Guide to Buying a House. This is the query I used as an example. Before we dive in, even before we look into keyword research tools or anything like that, I think it’s really important to just like let the query sit with you for a little bit. So “guide to buying a house,” okay, I’m going to think about that and think about what the searcher probably wanted based on the query.

So first of all, I noticed “guide.” The word “guide” to me makes it sound like someone wants something very complete, very thorough. They don’t just want quick tips. They don’t want a quick bullet list. This can be longer, because someone is searching for a comprehensive guide.

“To buying a house,” that’s a process. That’s not like an add-to-cart like Amazon. It’s a step-by-step. There are multiple phases to that type of process. It’s really important to realize here that they’re probably looking for something a little lengthier and something that is maybe a step-by-step process.

And too, you just look at the query, “guide to buying a house,” people are probably searching that if they’ve never bought a house before. So if they’ve never bought a house before, it’s just good to remember that your audience is in a phase where they have no idea what they’re doing. It’s important to understand your audience and understand that this is something that they’re going to need very, very comprehensive, start-to-finish information on it.

2. Implications

Two, implications. This is again also before we get into any keyword research tools. By implications, I mean what is going to be the effect on someone after reading this? So the implications here, a guide to buying a house, that is a big financial decision. That’s a big financial purchase. It’s going to affect people’s finances and happiness and well-being, and Google actually has a name for that. In their Quality Rater Guidelines, they call that YMYL. So that stands for “your money, your life.”

Those types of pages are held to a really high standard, and rightfully so. If someone reads this, they’re going to get advice about how to spend their money. It’s important for us, as SEOs and writers crafting these types of pages, to understand that these are going to be held to a really high standard. I think what that could look like on the page is, because they’re making a big purchase like this, it might be a good sign of trustworthiness to maybe have some expert quotes in here. Maybe you kind of sprinkle those throughout your page. Maybe you actually have it written by an expert author instead of just Joe Schmoe blogger. Those are just some ideas for making a page really trustworthy, and I think that’s a key to comprehensiveness.

3. Subtopics

Number three here we have subtopics. There are two ways that I’ll walk you through finding subtopics to fit within your umbrella topic. I’m going to use Moz Keyword Explorer as an example of this.

Use Keyword Explorer to reveal subtopics

In Moz Keyword Explorer, you can search for different keywords and related keywords two different ways. You can type in a query. So you can type in something like “buy a house” or “home buying” or something like that. You start with your main topic, and what you’ll get as a result is a bunch of suggested keywords that you can also incorporate on your page, terms that are related to the term that you searched. This is going to be really great, because you’re going to start to notice themes emerge. Some of the themes I noticed were people tend to search for “home buying calculator,” like a can-I-afford-it type of calculator. A lot of people search financial-related things obviously, bad credit. I filed for bankruptcy, can I still buy a house? You’ll start to see subthemes emerge.

Then I also wanted to mention that, in Moz Keyword Explorer, you can also search by URL. What I might do is query my term that I’m trying to target on my page. I’m going to pick the top three URLs that are ranking. You pop them into Keyword Explorer, and you can compare them and you can see the areas of most overlap. So what you’ll get essentially is a list of keywords that the top ranking pages for that term also rank for. That’s going to be a really good way to mine some extra keyword ideas for your page to make it more comprehensive.

4. Questions

Then here we go. We have step four. After we’ve come up with some subtopics, I think it’s also a really good idea to mine questions and try to find what questions our audience is actually asking. So, for these, I like to use Answer the Public and Keywords Everywhere. Those are two really great tools that I kind of like to use in tandem.

Use Answer the Public to mine questions

Answer the Public, if you’ve never used it, is a really fun tool. You can put in a keyword, and you get a huge list. Depending on how vague your query is, you might get a ton of ideas. If your query is really specific, you might not get as many keyword ideas back. But it’s a really great way to type in a keyword, like “buying a house” or “buy a house” or “home buying” or something like that, and get a whole, big, long list of questions that your audience is asking. People that want to know how to buy a house, they’re also asking these questions.

I think a comprehensive page will answer those questions. But it can be a little bit overwhelming. There’s going to be probably a lot of questions potentially to answer. So how do you prioritize and choose which questions are the best to address on your page?

Use Keywords Everywhere to highlight keywords on a page

That’s where the Keywords Everywhere plug-in comes in handy. I use it in Chrome. You can have it highlight the keywords on the page. I think I have mine set to highlight anything that’s searched 50 or more times a month. That’s a really good way to gauge, just right off the bat you can see, okay, now there are these 10 instead of these 100 questions to potentially answer on my page.

So examples of questions here, I have questions like: Can I afford this? Is now the right time to buy? So you can kind of fit those into your page and answer those questions.

5. Trends

Then finally here I have trends. I think this is a really commonly missed step. It’s important to remember that a lot of terms have seasonality attached to them. So what I did with this query, I queried “buy a house,” and I wanted to see if there were any trends for home buying-type of research queries in Google Trends. I zoomed out to five years to see if I could see year-over-year if there were any trends that emerged.

That was totally the case. When people are searching “buy a house,” it’s at its peak kind of around January into spring, and then in the summer it starts to dive, and then it’s at its lowest during the holidays. That kind of shows you that people are researching at the beginning of the year. They’re kind of probably moving into their house during the summertime, and then during the holidays they’ve had all the time to move in and now they’re just enjoying the holidays. That’s kind of the trend flow that it follows. That’s really key information, if you’re going to build a comprehensive page, to kind of understand that there’s seasonality attached with your term.

Because I know now that there’s seasonality with my term, I can incorporate information like what are the pros and cons of buying in peak season versus off-season for buying a house. Maybe what’s the best time of year to buy. Those are, again, other ideas for things that you can incorporate on your page to make it more comprehensive.

This page is not comprehensive. I didn’t have enough room to fit some things. So you don’t just stop at this phase. If you’re really building a comprehensive page on this topic, don’t stop where I stopped. But this is kind of just an example of how to go about thinking through what Google means when they say make a page comprehensive. It’s going to mean something different depending on your query and just keep that in mind. Just think about the query, think about what your audience wanted based on what they searched, and you’ll be off to a great start building a comprehensive page.

I hope that was helpful. If you have any ideas for building your own comprehensive page, how you do that, maybe how it differs in different industries that you’ve worked in, pop it in the comments. That would be really good for us to share that information. Come back again next week for another edition of Whiteboard Friday.

Video transcription by Speechpad.com

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How to Transform from Fan to Fanatic to Fantastic Content Creator

Building an audience involves a lot of trial and error. But those who wish to have their own audiences make…

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5 User-Generated Content Campaigns Your Brand Can Learn From

These days, shoppers are less impressed with celebrities and gurus telling them what to buy and prefer content that’s generated by their fellow consumers. A Nielsen report showed that 92 percent of consumers trust recommendations made by people they know while 70 percent believe the opinions consumers post online.

Some brands have been savvy enough to take advantage of this changing mindset and have successfully leveraged user-generated content (UGC) into their marketing campaigns.

User-generated content is essentially content that comes from customers. When customers have a positive experience with your brand, they are more inclined to tell others about it.

A ringing endorsement from a happy client is one of the fastest and cheapest ways to boost your customer base. And since the content comes from real people who have actually used the company’s products or services, consumers know that the information provided is authentic and reliable, thus improving a brand’s credibility.

There are several ways that smart brands can utilize UGC. Here’s a list of five companies highly-successful campaigns that show how to effectively leverage user-generated content in your marketing efforts.

1. Starbucks’ White Cup Contest

Starbucks hit a home run back in 2014 with its White Cup competition. The coffee giant asked their customers to doodle designs on their paper cups, take pictures, and post them on social media using the hashtag #WhiteCupContest. The best design would become the template for their limited-edition coffee cups. The contest generated around 4,000 entries in three weeks and created a lot of buzz even after it ended. When Starbucks finally unveiled the limited-edition cups, millions of customers took photos of the items and posting them on their social media accounts.

Takeaway: A contest with an interesting gift or a freebie is an effective way to interact with your target market. You can also generate revenue by turning the UGC into something you can repurpose or sell.

2. Apple #ShotOniPhone

User-generated content can solidify and expand a loyal fan base effortlessly. When Apple released the iPhone 8 and X, the company decided to take advantage of the fact that people were already using their product to take great pictures. The company’s #ShotOniPhone campaign saw Apple fans sharing the photos they took on their iPhones. Apple then showcased their favorite photos on its official Instagram account. While the campaign placed the focus on the photographers and their skill, it also emphasized their product’s features and capabilities.

Takeaway: Celebrate your loyal customers by showcasing their work in your website and social media accounts. The UGC will also drive more visitors to spend more time on your site.

3. Cast Me Marc by Marc Jacobs

Image result for cast me marc

Marc Jacobs reminded people why he’s such a trailblazer with the Cast Me Marc campaign. In 2014, the designer decided to cast models in a distinct way – by using Instagram and Twitter. People who were interested in modeling for the brand were asked to submit their photos with the #CastMeMarc hashtag. The company received 15,000 submissions within a day and 70,000 photos by the time the contest ended. The brand was also credited for starting a new movement as other fashion brands followed in its footsteps.

Takeaway: Pay attention to current trends. At the time, selfies were rapidly growing in popularity and Jacobs tapped into that phenomenon. You also shouldn’t be afraid to add your own twist to a new trend.

4. L’Oreal DermaBlend Transformations

The make-up brand placed their storyline in the hands of their loyal clients with its #DermaBlendPro campaign. L’Oreal encouraged users to share photos or videos of their makeup transformations. The company received thousands of submissions which were used in their brand story.

Takeaway: Trust your customers and include them in your campaigns. Happy customers make the best brand ambassadors.

5. Pura Vida Bracelets

UGC a good way to showcase products in real-world scenarios. Pura Vida’s colorful and unique bracelets already stand out on Facebook’s newsfeed, but when the company added photos of their customers wearing their products on their carousel ad, it provided better insight into the brand and led to a surge in conversions. It also helped that customers were taking photos of their bracelets while on the beach or traveling around the world, thereby encouraging everyone’s dream of a carefree lifestyle. The company was also started working with more artisans and small businesses around the world.

Takeaway: When your content is relatable, more shoppers will identify with your brand and hold it valuable. Transparency also attracts consumers who want to know where and how the product is made.

UGC is undoubtedly one of the best ways to show a brand’s authenticity and secure customer loyalty. So put the spotlight on your customer, and reward them to increase engagement. Shoppers are always happy to come back and talk about a brand when they feel like they’re part of the brand’s community. They’re also more willing to contribute to it and refer it to other people. 

[Featured image via Pexels.com]

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How to Turn One Content Idea into a Fascinating Four-Part Series

Be careful what you wish for … Once you’ve persuaded people to keep reading your content, you have to keep…

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How to Turn One Content Idea into a Fascinating Four-Part Series

Be careful what you wish for … Once you’ve persuaded people to keep reading your content, you have to keep…

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12 Easy Tweaks that Could Lead to Outsized Improvement in Your Content and Writing

We often write about big, strategic changes you can make to give your writing more power. But this week, we…

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Building Links with Great Content – Natural Syndication Networks

Posted by KristinTynski

The debate is over and the results are clear: the best way to improve domain authority is to generate large numbers of earned links from high-authority publishers.

Getting these links is not possible via:

  • Link exchanges
  • Buying links
  • Private Blog Networks, or PBNs
  • Comment links
  • Paid native content or sponsored posts
  • Any other method you may have encountered

There is no shortcut. The only way to earn these links is by creating content that is so interesting, relevant, and newsworthy to a publisher’s audience that the publisher will want to write about that content themselves.

Success, then, is predicated on doing three things extremely well:

  1. Developing newsworthy content (typically meaning that content is data-driven)
  2. Understanding who to pitch for the best opportunity at success and natural syndication
  3. Writing and sending pitches effectively

We’ve covered point 1 and point 3 on other Moz posts. Today, we are going to do a deep dive into point 2 and investigate methods for understanding and choosing the best possible places to pitch your content. Specifically, we will reveal the hidden news syndication networks that can mean the difference between generating less than a handful or thousands of links from your data-driven content.

Understanding News Syndication Networks

Not all news publishers are the same. Some publishers behave as hubs, or influencers, generating the stories and content that is then “picked up” and written about by other publishers covering the same or similar beats.

Some of the top hubs should be obvious to anyone: CNN, The New York Times, BBC, or Reuters, for instance. Their size, brand authority, and ability to break news make them go-to sources for the origination of news and some of the most common places journalists and writers from other publications go to for story ideas. If your content gets picked up by any of these sites, it’s almost certain that you will enjoy widespread syndication of your story to nearly everywhere that could be interested without any intervention on your part.

Unfortunately, outside of the biggest players, it’s often unclear which other sites also enjoy “Hub Status,” acting as a source for much of the news writing that happens around any specific topic or beat.

At Fractl, our experience pitching top publishers has given us a deep intuition of which domains are likely to be our best bet for the syndication potential of content we create on behalf of our clients, but we wanted to go a step further and put data to the question. Which publishers really act as the biggest hubs of content distribution?

To get a better handle on this question, we took a look at the link networks of the top 400 most trafficked American publishers online. We then utilized Gephi, a powerful network visualization tool to make sense of this massive web of links. Below is a visualization of that network.

An interactive version is available here.

Before explaining further, let’s detail how the visualization works:

  • Each colored circle is called a node. A node represents one publisher/website
  • Node size is related to Domain Authority. The larger the node, the more domain authority it has.
  • The lines between the nodes are called edges, and represent the links between each publisher.
  • The strength of the edges/links corresponds to the total number of links from one publisher to another. The more links from one publisher to another, the stronger the edge, and the more “pull” exerted between those two nodes toward each other.
  • You can think of the visualization almost like an epic game of tug of war, where nodes with similar link networks end up clustering near each other.
  • The colors of the nodes are determined by a “Modularity” algorithm that looks at the overall similarity of link networks, comparing all nodes to each other. Nodes with the same color exhibit the most similarity. The modularity algorithm implemented in Gephi looks for the nodes that are more densely connected together than to the rest of the network

Once visualized, important takeaways that can be realized include the following:

  1. The most “central” nodes, or the ones appearing near the center of the graph, are the ones that enjoy links from the widest variety of sites. Naturally, the big boys like Reuters, CNN and the NYTimes are located at the center, with large volumes of links incoming from all over.
  2. Tight clusters are publishers that link to each other very often, which creates a strong attractive force and keeps them close together. Publishers like these are often either owned by the same parent company or have built-in automatic link syndication relationships. A good example is the Gawker Network (at the 10PM position). The closeness of nodes in this network is the result of heavy interlinking and story syndication, along with the effects of site-wide links shared between them. A similar cluster appears at the 7PM position with the major NBC-owned publishers (NBC.com, MSNBC.com, Today.com, etc.). Nearby, we also see large NBC-owned regional publishers, indicating heavy story syndication also to these regional owned properties.
  3. Non-obvious similarities between the publishers can also be gleaned. For instance, notice how FoxNews.com and TMZ.com are very closely grouped, sharing very similar link profiles and also linking to each other extensively. Another interesting cluster to note is the Buzzfeed/Vice cluster. Notice their centrality lies somewhere between serious news and lifestyle, with linkages extending out into both.
  4. Sites that cover similar themes/beats are often located close to each other in the visualization. We can see top-tier lifestyle publishers clustered around the 1PM position. News publishers clustered near other news publishers with similar political leanings. Notice the closeness of Politico, Salon, The Atlantic, and The Washington Post. Similarly, notice the proximity of Breitbart, The Daily Caller, and BizPacReview. These relationships hint at hidden biases and relationships in how these publishers pick up each other’s stories.

A More Global Perspective

Last year, a fascinating project by Kalev Leetaru at Forbes looked at the dynamics Google News publishers in the US and around the world. The project leveraged GDelt’s massive news article dataset, and visualized the network with Gephi, similarly to the above network discussed in the previous paragraph.

This visualization differs in that the link network was built looking only at in-context links, whereas the visualization featured in the previous paragraph looked at all links. This is perhaps an even more accurate view of news syndication networks because it better parses out site-wide links, navigation links, and other non-context links that impact the graph. Additionally, this graph was generated using more than 121 million articles from nearly every country in the world, containing almost three-quarters of a billion individual links. It represents one of the most accurate pictures of the dynamics of the global news landscape ever assembled.

Edge weights were determined by the total number of links from each node to each other node. The more links, the stronger the edge. Node sizes were calculated using Pagerank in this case instead of Domain Authority, though they are similar metrics.

Using this visualization, Mr. Leetaru was able to infer some incredibly interesting and potentially powerful relationships that have implications for anyone who pitches mainstream publishers. Some of the most important include:

  1. In the center of the graph, we see a very large cluster. This cluster can be thought of as essentially the “Global Media Core,” as Mr. Leetaru puts it. Green nodes represent American outlets. This, as with the previous example, shows the frequency with which these primary news outlets interlink and cover each other’s stories, as well as how much less frequently they cite sources from smaller publications or local and regional outlets.
  2. Interestingly, CNN seems to play a unique role in the dissemination to local and regional news. Note the many links from CNN to the blue cluster on the far right. Mr. Leetaru speculates this could be the result of other major outlets like the NYTimes and the Washington Post using paywalls. This point is important for anyone who pitches content. Paywalls should be something taken into consideration, as they could potentially significantly reduce syndication elsewhere.
  3. The NPR cluster is another fascinating one, suggesting that there is heavy interlinking between NPR-related stories and also between NPR and the Washington Post and NYTimes. Getting a pickup on NPR’s main site could result in syndication to many of its affiliates. NYTimes or Washington Post pickups could also have a similar effect due to this interlinking.
  4. For those looking for international syndication, there are some other interesting standouts. Sites like NYYibada.com cover news in the US. They are involved with Chinese language publications, but also have versions in other languages, including English. Sites like this might not seem to be good pitch targets, but could likely be pitched successfully given their coverage of many of the same stories as US-based English language publications.
  5. The blue and pink clusters at the bottom of the graph are outlets from the Russian and Ukrainian press, respectively. You will notice that while the vast majority of their linking is self-contained, there seem to be three bridges to international press, specifically via the BBC, Reuters, and AP. This suggests getting pickups at these outlets could result in much broader international syndication, at least in Eastern Europe and Russia.
  6. Additionally, the overall lack of deep interlinking between publications of different languages suggests that it is quite difficult to get English stories picked up internationally.
  7. Sites like ZDnet.com have foreign language counterparts, and often translate their stories for their international properties. Sites like these offer unique opportunities for link syndication into mostly isolated islands of foreign publications that would be difficult to reach otherwise.

I would encourage readers to explore this interactive more. Isolating individual publications can give deep insight into what syndication potential might be possible for any story covered. Of course, many factors impact how a story spreads through these networks. As a general rule, the broader the syndication network, the more opportunities that exist.

Link Syndication in Practice

Over our 6 years in business, Fractl has executed more than 1,500 content marketing campaigns, promoted using high-touch, one-to-one outreach to major publications. Below are two views of content syndication we have seen as a result of our content production and promotion work.

Let’s first look just at a single campaign.

Recently, Fractl scored a big win for our client Signs.com with our “Branded in Memory” campaign, which was a fun and visual look at how well people remember brand logos. We had the crowd attempt to recreate well-known brand logos from memory, and completed data analysis to understand more deeply which brands seem to have the best overall recall.

As a result of strategic pitching, the high public appeal, and the overall “coolness” factor of the project, it was picked up widely by many mainstream publications, and enjoyed extensive syndication.

Here is what that syndication looked like in network graph form over time:

If you are interested in seeing and exploring the full graph, you can access the interactive by clicking on the gif above, or clicking here. As with previous examples, node size is related to domain authority.

A few important things to note:

  • The orange cluster of nodes surrounding the central node are links directly to the landing page on Signs.com.
  • Several pickups resulted in nodes (publications) that themselves generated many numbers of links pointing at the story they wrote about the Signs.com project. The blue cluster at the 8PM position is a great example. In this case it was a pickup from BoredPanda.com.
  • Nodes that do not link to Signs.com are secondary syndications. They pass link value through the node that links to Signs.com, and represent an opportunity for link reclamation. Fractl follows up on all of these opportunities in an attempt to turn these secondary syndications into do-follow links pointing directly at our client’s domain.
  • An animated view gives an interesting insight into the pace of link accumulation both to the primary story on Signs.com, but also to the nodes that garnered their own secondary syndications. The GIF represents a full year of pickups. As we found in my previous Moz post examining link acquisition over time, roughly 50% of the links were acquired in the first month, and the other 50% over the next 11 months.

Now, let’s take a look at what syndication networks look like when aggregated across roughly 3 months worth of Fractl client campaigns (not fully comprehensive):

If you are interested in exploring this in more depth, click here or the above image for the interactive. As with previous examples, node size is related to domain authority.

A few important things to note:

  1. The brown cluster near the center labeled “placements” are links pointing back directly to the landing pages on our clients’ sites. Many/most of these links were the result of pitches to writers and editors at those publications, and not as a result of natural syndication.
  2. We can see many major hubs with their own attached orbits of linking nodes. At 9PM, we see entrepreneur.com, at 12PM we see CNBC.com, 10PM we see USAToday, etc.
  3. Publications with large numbers of linking nodes surrounding them are examples of prime pitching targets, given how syndications link back to stories on those publications appear in this aggregate view.

Putting it All Together

New data tools are enabling the ability to more deeply understand how the universe of news publications and the larger “blogosphere” operate dynamically. Network visualization tools in particular can be put to use to yield otherwise impossible insights about the relationships between publications and how content is distributed and syndicated through these networks.

The best part is that creating visualizations with your own data is very straightforward. For instance, the link graphs of Fractl content examples, along with the first overarching view of news networks, was built using backlink exports from SEMrush. Additionally, third party resources such as Gdelt offer tools and datasets that are virtually unexplored, providing opportunity for deep understanding that can convey significant advantages for those looking to optimize their content promotion and syndication process.

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