VCs aren’t falling in love with dating startups

Some 17 years ago, when internet dating was popular but still kind of embarrassing to talk about, I interviewed an author who was particularly bullish on the practice. Millions of people, he said, have found gratifying relationships online. Were it not for the internet, they would probably never have met.

A lot of years have passed since then. Yet thanks to Joe Schwartz, an author of a 20-year-old dating advice book, “gratifying relationship” is still the term that sticks in my mind when contemplating the end-goal of internet dating tools.

Gratifying is a vague term, yet also uniquely accurate. It encompasses everything from the forever love of a soul mate to the temporary fix of a one-night stand. Romantics can talk about true love. Yet when it comes to the algorithm-and-swipe-driven world of online dating, it’s all about gratification.

It is with this in mind, coincident with the arrival of Valentine’s Day, that Crunchbase News is taking a look at the state of that most awkward of pairings: startups and the pursuit of finding a mate.

Pairing money

Before we go further, be forewarned: This article will do nothing to help you navigate the features of new dating platforms, fine-tune your profile or find your soul mate. It is written by someone whose core expertise is staring at startup funding data and coming up with trends.

So, if you’re OK with that, let’s proceed. We’ll start with the initial observation that while online dating is a vast and often very profitable industry, it isn’t a huge magnet for venture funding.

In 2018, for instance, venture investors put $127 million globally into 27 startups categorized by Crunchbase as dating-focused. While that’s not chump change, it’s certainly tiny compared to the more than $300 billion in global venture investment across all sectors last year.

In the chart below, we look at global venture investment in dating-focused startups over the past five years. The general finding is that round counts fluctuate moderately year-to-year, while investment totals fluctuate heavily. The latter is due to a handful of giant funding rounds for China-based startups.

While the U.S. gets the most commitments, China gets the biggest ones

While the U.S. is home to the majority of funded startups in the Crunchbase dating category, the bulk of investment has gone to China.

In 2018, for instance, nearly 80 percent of dating-related investment went to a single company, China-based Blued, a Grindr-style hookup app for gay men. In 2017, the bulk of capital went to Chinese mobile dating app Tantan, and in 2014, Beijing-based matchmaking site Baihe raised a staggering $250 million.

Meanwhile, in the U.S., we are seeing an assortment of startups raising smaller rounds, but no big disclosed financings in the past three years. In the chart below, we look at a few of the largest funding recipients.

 

Dating app outcomes

Dating sites and apps have generated some solid exits in the past few years, as well as some less-stellar outcomes.

Mobile-focused matchmaking app Zoosk is one of the most heavily funded players in the space that has yet to generate an exit. The San Francisco company raised more than $60 million between 2008 and 2012, but had to withdraw a planned IPO in 2015 due to flagging market interest.

Startups without known venture funding, meanwhile, have managed to bring in some bigger outcomes. One standout in this category is Grindr, the geolocation-powered dating and hookup app for gay men. China-based tech firm Kunlun Group bought 60 percent of the West Hollywood-based company in 2016 for $93 million and reportedly paid around $150 million for the remaining stake a year ago. Another apparent success story is OkCupid, which sold to Match.com in 2011 for $50 million.

As for venture-backed companies, one of the earlier-funded startups in the online matchmaking space, eHarmony, did score an exit last fall with an acquisition by German media company ProSiebenSat.1 Media SE. But terms weren’t disclosed, making it difficult to gauge returns.

One startup VCs are assuredly happy they passed on is Ashley Madison, a site best known for targeting married people seeking affairs. A venture investor pitched by the company years ago told me its financials were quite impressive, but its focus area would not pass muster with firm investors or the VCs’ spouses.

The dating site eventually found itself engulfed in scandal in 2015 when hackers stole and released virtually all of its customer data. Notably, the site is still around, a unit of Canada-based dating network ruby. It has changed its motto, however, from “Life is short. Have an affair,” to “Find Your Moment.”

An algorithm-chosen match

With the spirit of Valentine’s Day in the air, it occurs that I should restate the obvious: Startup funding databases do not contain much about romantic love.

The Crunchbase data set produced no funded U.S. startups with “romantic” in their business descriptions. Just five used the word “romance” (of which one is a cold brew tea company).

We get it. Our cultural conceptions of romance are decidedly low-tech. We think of poetry, flowers, loaves of bread and jugs of wine. We do not think of algorithms and swipe-driven mobile platforms.

Dating sites, too, seem to prefer promoting themselves on practicality and effectiveness, rather than romance. Take how Match Group, the largest publicly traded player in the dating game, describes its business via that most swoon-inducing of epistles, the 10-K report: “Our strategy focuses on a brand portfolio approach, through which we attempt to offer dating products that collectively appeal to the broadest spectrum of consumers.”

That kind of writing might turn off romantics, but shareholders love it. Shares of Match Group, whose portfolio includes Tinder, have more than tripled since Valentine’s Day 2017. Its current market cap is around $16 billion.

So, complain about the company’s dating products all you like. But it’s clear investors are having a gratifying relationship with Match. When it comes to startups, however, it appears they’re still mostly swiping left.


Source: https://techcrunch.com/2019/02/17/its-valentines-day-but-vcs-arent-falling-in-love-with-dating-startups/

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Even years later, Twitter doesn’t delete your direct messages

When does “delete” really mean delete? Not always or even at all if you’re Twitter .

Twitter retains direct messages for years, including messages you and others have deleted, but also data sent to and from accounts that have been deactivated and suspended, according to security researcher Karan Saini.

Saini found years-old messages found in a file from an archive of his data obtained through the website from accounts that were no longer on Twitter. He also filed a similar bug, found a year earlier but not disclosed until now, that allowed him to use a since-deprecated API to retrieve direct messages even after a message was deleted from both the sender and the recipient — though, the bug wasn’t able to retrieve messages from suspended accounts.

Saini told TechCrunch that he had “concerns” that the data was retained by Twitter for so long.

Direct messages once let users to “unsend” messages from someone else’s inbox, simply by deleting it from their own. Twitter changed this years ago, and now only allows a user to delete messages from their account. “Others in the conversation will still be able to see direct messages or conversations that you have deleted,” Twitter says in a help page. Twitter also says in its privacy policy that anyone wanting to leave the service can have their account “deactivated and then deleted.” After a 30-day grace period, the account disappears and along with its data.

But, in our tests, we could recover direct messages from years ago — including old messages that had since been lost to suspended or deleted accounts. By downloading your account’s data, it’s possible to download all of the data Twitter stores on you.

A conversation, dated March 2016, with a suspended Twitter account was still retrievable today. (Image: TechCrunch

Saini says this is a “functional bug” rather than a security flaw, but argued that the bug allows anyone a “clear bypass” of Twitter mechanisms to prevent accessed to suspended or deactivated accounts.

But it’s also a privacy matter, and a reminder that “delete” doesn’t mean delete — especially with your direct messages. That can open up users, particularly high-risk accounts like journalist and activists, to government data demands that call for data from years earlier.

That’s despite Twitter’s claim that once an account has been deactivated, there is “a very brief period in which we may be able to access account information, including tweets,” to law enforcement.

A Twitter spokesperson said the company was “looking into this further to ensure we have considered the entire scope of the issue.”

Retaining direct messages for years may put the company in a legal grey area ground amid Europe’s new data protection laws, which allows users to demand that a company deletes their data.

Neil Brown, a telecoms, tech and internet lawyer at U.K. law firm Decoded Legal, said there’s “no formality at all” to how a user can ask for their data to be deleted. Any request from a user to delete their data that’s directly communicated to the company “is a valid exercise” of a user’s rights, he said.

Companies can be fined up to four percent of their annual turnover for violating GDPR rules.

“A delete button is perhaps a different matter, as it is not obvious that ‘delete’ means the same as ‘exercise my right of erasure’,” said Brown. Given that there’s no case law yet under the new General Data Protection Regulation regime, it will be up to the courts to decide, he said.

When asked if Twitter thinks that consent to retain direct messages is withdrawn when a message or account is deleted, Twitter’s spokesperson had “nothing further” to add.


Source: https://techcrunch.com/2019/02/15/twitter-direct-messages/

4 Ways to Improve Your Data Hygiene – Whiteboard Friday

Posted by DiTomaso

We base so much of our livelihood on good data, but managing that data properly is a task in and of itself. In this week’s Whiteboard Friday, Dana DiTomaso shares why you need to keep your data clean and some of the top things to watch out for.

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

Video Transcription

Hi. My name is Dana DiTomaso. I am President and partner at Kick Point. We’re a digital marketing agency, based in the frozen north of Edmonton, Alberta. So today I’m going to be talking to you about data hygiene.

What I mean by that is the stuff that we see every single time we start working with a new client this stuff is always messed up. Sometimes it’s one of these four things. Sometimes it’s all four, or sometimes there are extra things. So I’m going to cover this stuff today in the hopes that perhaps the next time we get a profile from someone it is not quite as bad, or if you look at these things and see how bad it is, definitely start sitting down and cleaning this stuff up.

1. Filters

So what we’re going to start with first are filters. By filters, I’m talking about analytics here, specifically Google Analytics. When go you into the admin of Google Analytics, there’s a section called Filters. There’s a section on the left, which is all the filters for everything in that account, and then there’s a section for each view for filters. Filters help you exclude or include specific traffic based on a set of parameters.

Filter out office, home office, and agency traffic

So usually what we’ll find is one Analytics property for your website, and it has one view, which is all website data which is the default that Analytics gives you, but then there are no filters, which means that you’re not excluding things like office traffic, your internal people visiting the website, or home office. If you have a bunch of people who work from home, get their IP addresses, exclude them from this because you don’t necessarily want your internal traffic mucking up things like conversions, especially if you’re doing stuff like checking your own forms.

You haven’t had a lead in a while and maybe you fill out the form to make sure it’s working. You don’t want that coming in as a conversion and then screwing up your data, especially if you’re a low-volume website. If you have a million hits a day, then maybe this isn’t a problem for you. But if you’re like the rest of us and don’t necessarily have that much traffic, something like this can be a big problem in terms of the volume of traffic you see. Then agency traffic as well.

So agencies, please make sure that you’re filtering out your own traffic. Again things like your web developer, some contractor you worked with briefly, really make sure you’re filtering out all that stuff because you don’t want that polluting your main profile.

Create a test and staging view

The other thing that I recommend is creating what we call a test and staging view. Usually in our Analytics profiles, we’ll have three different views. One we call master, and that’s the view that has all these filters applied to it.

So you’re only seeing the traffic that isn’t you. It’s the customers, people visiting your website, the real people, not your office people. Then the second view we call test and staging. So this is just your staging server, which is really nice. For example, if you have a different URL for your staging server, which you should, then you can just include that traffic. Then if you’re making enhancements to the site or you upgraded your WordPress instance and you want to make sure that your goals are still firing correctly, you can do all that and see that it’s working in the test and staging view without polluting your main view.

Test on a second property

That’s really helpful. Then the third thing is make sure to test on a second property. This is easy to do with Google Tag Manager. What we’ll have set up in most of our Google Tag Manager accounts is we’ll have our usual analytics and most of the stuff goes to there. But then if we’re testing something new, like say the content consumption metric we started putting out this summer, then we want to make sure we set up a second Analytics view and we put the test, the new stuff that we’re trying over to the second Analytics property, not view.

So you have two different Analytics properties. One is your main property. This is where all the regular stuff goes. Then you have a second property, which is where you test things out, and this is really helpful to make sure that you’re not going to screw something up accidentally when you’re trying out some crazy new thing like content consumption, which can totally happen and has definitely happened as we were testing the product. You don’t want to pollute your main data with something different that you’re trying out.

So send something to a second property. You do this for websites. You always have a staging and a live. So why wouldn’t you do this for your analytics, where you have a staging and a live? So definitely consider setting up a second property.

2. Time zones

The next thing that we have a lot of problems with are time zones. Here’s what happens.

Let’s say your website, basic install of WordPress and you didn’t change the time zone in WordPress, so it’s set to UTM. That’s the default in WordPress unless you change it. So now you’ve got your data for your website saying it’s UTM. Then let’s say your marketing team is on the East Coast, so they’ve got all of their tools set to Eastern time. Then your sales team is on the West Coast, so all of their tools are set to Pacific time.

So you can end up with a situation where let’s say, for example, you’ve got a website where you’re using a form plugin for WordPress. Then when someone submits a form, it’s recorded on your website, but then that data also gets pushed over to your sales CRM. So now your website is saying that this number of leads came in on this day, because it’s in UTM mode. Well, the day ended, or it hasn’t started yet, and now you’ve got Eastern, which is when your analytics tools are recording the number of leads.

But then the third wrinkle is then you have Salesforce or HubSpot or whatever your CRM is now recording Pacific time. So that means that you’ve got this huge gap of who knows when this stuff happened, and your data will never line up. This is incredibly frustrating, especially if you’re trying to diagnose why, for example, I’m submitting a form, but I’m not seeing the lead, or if you’ve got other data hygiene issues, you can’t match up the data and that’s because you have different time zones.

So definitely check the time zones of every product you use –website, CRM, analytics, ads, all of it. If it has a time zone, pick one, stick with it. That’s your canonical time zone. It will save you so many headaches down the road, trust me.

3. Attribution

The next thing is attribution. Attribution is a whole other lecture in and of itself, beyond what I’m talking about here today.

Different tools have different ways of showing attribution

But what I find frustrating about attribution is that every tool has its own little special way of doing it. Analytics is like the last non-direct click. That’s great. Ads says, well, maybe we’ll attribute it, maybe we won’t. If you went to the site a week ago, maybe we’ll call it a view-through conversion. Who knows what they’re going to call it? Then Facebook has a completely different attribution window.

You can use a tool, such as Supermetrics, to change the attribution window. But if you don’t understand what the default attribution window is in the first place, you’re just going to make things harder for yourself. Then there’s HubSpot, which says the very first touch is what matters, and so, of course, HubSpot will never agree with Analytics and so on. Every tool has its own little special sauce and how they do attribution. So pick a source of truth.

Pick your source of truth

This is the best thing to do is just say, “You know what? I trust this tool the most.” Then that is your source of truth. Do not try to get this source of truth to match up with that source of truth. You will go insane. You do have to make sure that you are at least knowing that things like your time zones are clear so that’s all set.

Be honest about limitations

But then after that, really it’s just making sure that you’re being honest about your limitations.

Know where things are necessarily going to fall down, and that’s okay, but at least you’ve got this source of truth that you at least can trust. That’s the most important thing with attribution. Make sure to spend the time and read how each tool handles attribution so when someone comes to you and says, “Well, I see that we got 300 visits from this ad campaign, but in Facebook it says we got 6,000.

Why is that? You have an answer. That might be a little bit of an extreme example, but I mean I’ve seen weirder things with Facebook attribution versus Analytics attribution. I’ve even talked about stuff like Mixpanel and Kissmetrics. Every tool has its own little special way of recording attributions. It’s never the same as anyone else’s. We don’t have a standard in the industry of how this stuff works, so make sure you understand these pieces.

4. Interactions

Then the last thing are what I call interactions. The biggest thing that I find that people do wrong here is in Google Tag Manager it gives you a lot of rope, which you can hang yourself with if you’re not careful.

GTM interactive hits

One of the biggest things is what we call an interactive hit versus a non-interactive hit. So let’s say in Google Tag Manager you have a scroll depth.

You want to see how far down the page people scroll. At 25%, 50%, 75%, and 100%, it will send off an alert and say this is how far down they scrolled on the page. Well, the thing is that you can also make that interactive. So if somebody scrolls down the page 25%, you can say, well, that’s an interactive hit, which means that person is no longer bounced, because it’s counting an interaction, which for your setup might be great.

Gaming bounce rate

But what I’ve seen are unscrupulous agencies who come in and say if the person scrolls 2% of the way down the page, now that’s an interactive hit. Suddenly the client’s bounce rate goes down from say 80% to 3%, and they think, “Wow, this agency is amazing.” They’re not amazing. They’re lying. This is where Google Tag Manager can really manipulate your bounce rate. So be careful when you’re using interactive hits.

Absolutely, maybe it’s totally fair that if someone is reading your content, they might just read that one page and then hit the back button and go back out. It’s totally fair to use something like scroll depth or a certain piece of the content entering the user’s view port, that that would be interactive. But that doesn’t mean that everything should be interactive. So just dial it back on the interactions that you’re using, or at least make smart decisions about the interactions that you choose to use. So you can game your bounce rate for that.

Goal setup

Then goal setup as well, that’s a big problem. A lot of people by default maybe they have destination goals set up in Analytics because they don’t know how to set up event-based goals. But what we find happens is by destination goal, I mean you filled out the form, you got to a thank you page, and you’re recording views of that thank you page as goals, which yes, that’s one way to do it.

But the problem is that a lot of people, who aren’t super great at interneting, will bookmark that page or they’ll keep coming back to it again and again because maybe you put some really useful information on your thank you page, which is what you should do, except that means that people keep visiting it again and again without actually filling out the form. So now your conversion rate is all messed up because you’re basing it on destination, not on the actual action of the form being submitted.

So be careful on how you set up goals, because that can also really game the way you’re looking at your data.

Ad blockers

Ad blockers could be anywhere from 2% to 10% of your audience depending upon how technically sophisticated your visitors are. So you’ll end up in situations where you have a form fill, you have no corresponding visit to match with that form fill.

It just goes into an attribution black hole. But they did fill out the form, so at least you got their data, but you have no idea where they came from. Again, that’s going to be okay. So definitely think about the percentage of your visitors, based on you and your audience, who probably have an ad blocker installed and make sure you’re comfortable with that level of error in your data. That’s just the internet, and ad blockers are getting more and more popular.

Stuff like Apple is changing the way that they do tracking. So definitely make sure that you understand these pieces and you’re really thinking about that when you’re looking at your data. Again, these numbers may never 100% match up. That’s okay. You can’t measure everything. Sorry.

Bonus: Audit!

Then the last thing I really want you to think about — this is the bonus tip — audit regularly.

So at least once a year, go through all the different stuff that I’ve covered in this video and make sure that nothing has changed or updated, you don’t have some secret, exciting new tracking code that somebody added in and then forgot because you were trying out a trial of this product and you tossed it on, and it’s been running for a year even though the trial expired nine months ago. So definitely make sure that you’re running the stuff that you should be running and doing an audit at least on an yearly basis.

If you’re busy and you have a lot of different visitors to your website, it’s a pretty high-volume property, maybe monthly or quarterly would be a better interval, but at least once a year go through and make sure that everything that’s there is supposed to be there, because that will save you headaches when you look at trying to compare year-over-year and realize that something horrible has been going on for the last nine months and all of your data is trash. We really don’t want to have that happen.

So I hope these tips are helpful. Get to know your data a little bit better. It will like you for it. Thanks.

Video transcription by Speechpad.com

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Source: https://moz.com/blog/improve-your-data-hygiene-dana-ditomaso

TikTok spotted testing native video ads

TikTok is testing a new ad product: a sponsored video ad that directs users to the advertiser’s website. The test was spotted in the beta version of the U.S. TikTok app, where a video labeled “Sponsored” from the bike retailer Specialized is showing up in the main feed, along with a blue “Lean More” button that directs users to tap to get more information.

Presumably, this button could be customized to send users to the advertiser’s website or any other web address, but for the time being it only opened the Specialized Bikes (@specializedbikes) profile page within the TikTok app.

However, the profile page itself also sported a few new features, including what appeared to be a tweaked version of the verified account badge.

Below the @specializedbikes username was “Specialized Bikes Page” and a blue checkmark (see below). On other social networks, checkmarks like this usually indicate a user whose account has gone through a verification process of some kind.

Typical TikTok user profiles don’t look like this — they generally only include the username. In some cases, we’ve seen them sport other labels like “popular creator” or “Official Account” — but these have been tagged with a yellowish-orange checkmark, not a blue one.

In addition, a pop-up banner overlay appeared at the bottom of the profile page, which directed users to “Go to Website” followed by another blue “Learn More” button.

Oddly, this pop-up banner didn’t show up all the time, and the “Learn More” button didn’t work — it only re-opened the retailer’s profile page.

As for the video itself, it features a Valentine’s Day heart that you can send to a crush, and, of course, some bikes.

The music backing the clip is Breakbot’s “By Your Side,” but is labeled “Promoted Music.” Weirdly, when you tap on the “Promoted Music” you’re not taken to the soundbite on TikTok like usual, but instead get an error message saying “Ad videos currently do not support this feature.”

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The glitches indicate this video ad unit is still very much in the process of being tested, and not a publicly available ad product at this time.

TikTok parent ByteDance only just began to experiment with advertising in the U.S. and U.K. in January.

So far, public tests have only included an app launch pre-roll ad. But according to a leaked pitch deck published by Digiday, there are four TikTok ad products in the works: a brand takeover, an in-feed native video ad, a hashtag challenge and a Snapchat-style 2D lens filter for photos; 3D and AR lens were listed as “coming soon.”

TikTok previously worked with GUESS on a hashtag challenge last year, and has more recently been running app launch pre-roll ads for companies like GrubHub, Disney’s Kingdom Hearts and others. However, a native video ad hadn’t yet been spotted in the wild until now.

According to estimates from Sensor Tower, TikTok has grown to nearly 800 million lifetime installs, not counting Android in China. Factoring that in, it’s fair to say the app has topped 1 billion downloads. As of last July, TikTok claimed to have more than 500 million monthly active users worldwide, excluding the 100 million users it gained from acquiring Musical.ly.

That’s a massive user base, and attractive to advertisers. Plus, native video ads like the one seen in testing would allow brands to participate in the community, instead of interrupting the experience the way video pre-rolls do.

TikTok has been reached for comment, but was not able to provide one at this time. We’ll update if that changes. Specialized declined to comment.


Source: https://techcrunch.com/2019/02/14/tiktok-spotted-testing-native-video-ads/

First look at Twitter’s Snapchatty new Camera feature

Twitter has been secretly developing an enhanced camera feature that’s accessible with a swipe from the home screen and allows you to overlay captions on photos, videos, and Live broadcasts before sharing them to the timeline. Twitter is already used by people to post pictures and videos, but as it builds up its profile as a media company, and in the age of Snapchat and Instagram, it is working on the feature in hopes it will get people doing that even more.

Described in Twitter’s code as the “News Camera”, the Snapchat-style visual sharing option could turn more people into citizen journalists… or just get them sharing more selfies, reaction shots, and the world around them. Getting more original visual content into Twitter spices up the feed and could also help photo and video ads blend in.

Prototypes of the new Twitter camera were first spotted by social media consultant Matt Navarra a week ago, and he produced a video of the feature today.

He describes the ability to swipe left from the homescreen to bring up the new unified capture screen. After you shoot some media, overlays appear prompting you to add a location and a caption to describe “what’s happening”. Users can choose from six colored backgrounds for the caption and location overlay card before posting, which lets you unite words and imagery on Twitter for the first time to make a splash with your tweets.

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Meanwhile, code digger and frequent TechCrunch tipster Jane Manchun Wong has found Twitter code describing how users should “Try the updated Twitter camera” to “capture photos, videos, and go live”. Bloomberg and CNBC had previously reported that Twitter was building an improved camera, but without feature details or screenshots.

Twitter confirmed to TechCrunch that it’s currently developing the new camera feature. A Twitter spokesperson told us “I can confirm that we’re working on an easier way to share thing like images and videos on Twitter. What you’re seeing is in mid-development so it’s tough to comment on what things will look like in the final stage. The team is still actively working on what we’ll actually end up shipping.” When asked when it would launch, the spokesperson told us “Unfortunately we don’t have a timeline right now. You could expect the first half of this year.”

Twitter has largely sat by as visual sharing overtook the rest of the social media landscape. It’s yet to launch a Snapchat Stories feature like almost every other app — although you could argue that Moments was an effort to do that — and it seems to have neglected Persicope as the Live broadcasting trend waned. But the information density of all the words on Twitter might make it daunting to mainstream users compared to something easy and visual like Instagram.

This month, as it turns away from reporting monthly active users, Twitter reported daily active users for the first time, revealing it has 126 million that are monetizable compared to Snapchat’s 186 million while Instagram has over 500 million.

The new Twitter camera could make the service more appealing for people who see something worth sharing, but don’t always know what to say,


Source: https://techcrunch.com/2019/02/14/twitter-camera/

Instagram confirms that a bug is causing follower counts to change (Updated)

Update: Instagram says the issue will be fixed by 9AM PST on Thursday.

https://platform.twitter.com/widgets.js

Instagram confirmed today that an issue has been causing some accounts’ follower numbers to change. Users began noticing the bug about 10 hours ago and the drastic drop in followers caused some to wonder if Instagram was culling inactive and fake accounts, as part of its fight against spam.

https://platform.twitter.com/widgets.js

“We’re aware of an issue that is causing a change in account follower numbers for some people right now. We’re working to resolve this as quickly as possible,” the company said on Twitter.

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No, your tweets aren’t awful. Twitter’s Likes are currently borked. (Update: It’s fixed)

Update: Twitter said the issues have been resolved.

https://platform.twitter.com/widgets.js

If you have been experiencing issues with the Like or Retweet count on Twitter and are desperately seeking validation, here it is: yes, it’s Twitter, not you (probably). The company confirmed today that it is working on a fix for a problem with notifications that’s been messing with Like counts.

https://platform.twitter.com/widgets.js

Many users around the world have reported seeing the number of Likes on their tweets fluctuate continuously, making them wonder if accounts were being suspended in mass or if Twitter was deleting them.

Instagram confirms that a bug is causing follower counts to change

Instagram confirmed today that an issue has been causing some accounts’ follower numbers to change. Users began noticing the bug about 10 hours ago and the drastic drop in followers caused some to wonder if Instagram was culling inactive and fake accounts, as part of its fight against spam.

https://platform.twitter.com/widgets.js

“We’re aware of an issue that is causing a change in account follower numbers for some people right now. We’re working to resolve this as quickly as possible,” the company said on Twitter.

https://platform.twitter.com/widgets.js

A guide to setting up your very own search intent projects

Posted by TheMozTeam

This post was originally published on the STAT blog.


Whether you’re tracking thousands or millions of keywords, if you expect to extract deep insights and trends just by looking at your keywords from a high-level, you’re not getting the full story.

Smart segmentation is key to making sense of your data. And you’re probably already applying this outside of STAT. So now, we’re going to show you how to do it in STAT to uncover boatloads of insights that will help you make super data-driven decisions.

To show you what we mean, let’s take a look at a few ways we can set up a search intent project to uncover the kinds of insights we shared in our whitepaper, Using search intent to connect with consumers.

Before we jump in, there are a few things you should have down pat:

1. Picking a search intent that works for you

Search intent is the motivating force behind search and it can be:

  • Informational: The searcher has identified a need and is looking for information on the best solution, ie. [blender], [food processor]
  • Commercial: The searcher has zeroed in on a solution and wants to compare options, ie. [blender reviews], [best blenders]
  • Transactional: The searcher has narrowed their hunt down to a few best options, and is on the precipice of purchase, ie. [affordable blenders], [blender cost]
    • Local (sub-category of transactional): The searcher plans to do or buy something locally, ie. [blenders in dallas]
    • Navigational (sub-category of transactional): The searcher wants to locate a specific website, ie. [Blendtec]

We left navigational intent out of our study because it’s brand specific and didn’t want to bias our data.

Our keyword set was a big list of retail products — from kitty pooper-scoopers to pricey speakers. We needed a straightforward way to imply search intent, so we added keyword modifiers to characterize each type of intent.

As always, different strokes for different folks: The modifiers you choose and the intent categories you look at may differ, but it’s important to map that all out before you get started.

2. Identifying the SERP features you really want

For our whitepaper research, we pretty much tracked every feature under the sun, but you certainly don’t have to.

You might already know which features you want to target, the ones you want to keep an eye on, or questions you want to answer. For example, are shopping boxes taking up enough space to warrant a PPC strategy?

In this blog post, we’re going to really focus-in on our most beloved SERP feature: featured snippets (called “answers” in STAT). And we’ll be using a sample project where we’re tracking 25,692 keywords against Amazon.com.

3. Using STAT’s segmentation tools

Setting up projects in STAT means making use of the segmentation tools. Here’s a quick rundown of what we used:

  • Standard tag: Best used to group your keywords into static themes — search intent, brand, product type, or modifier.
  • Dynamic tag: Like a smart playlist, automatically returns keywords that match certain criteria, like a given search volume, rank, or SERP feature appearance.
  • Data view: House any number of tags and show how those tags perform as a group.

Learn more about tags and data views in the STAT Knowledge Base.

Now, on to the main event…

1. Use top-level search intent to find SERP feature opportunities

To kick things off, we’ll identify the SERP features that appear at each level of search intent by creating tags.

Our first step is to filter our keywords and create standard tags for our search intent keywords (read more abou tfiltering keywords). Second, we create dynamic tags to track the appearance of specific SERP features within each search intent group. And our final step, to keep everything organized, is to place our tags in tidy little data views, according to search intent.

Here’s a peek at what that looks like in STAT:

What can we uncover?

Our standard tags (the blue tags) show how many keywords are in each search intent bucket: 2,940 commercial keywords. And our dynamic tags (the sunny yellow stars) show how many of those keywords return a SERP feature: 547 commercial keywords with a snippet.

This means we can quickly spot how much opportunity exists for each SERP feature by simply glancing at the tags. Boom!

By quickly crunching some numbers, we can see that snippets appear on 5 percent of our informational SERPs (27 out of 521), 19 percent of our commercial SERPs (547 out of 2,940), and 12 percent of our transactional SERPs (253 out of 2,058).

From this, we might conclude that optimizing our commercial intent keywords for featured snippets is the way to go since they appear to present the biggest opportunity. To confirm, let’s click on the commercial intent featured snippet tag to view the tag dashboard…

Voilà! There are loads of opportunities to gain a featured snippet.

Though, we should note that most of our keywords rank below where Google typically pulls the answer from. So, what we can see right away is that we need to make some serious ranking gains in order to stand a chance at grabbing those snippets.

2. Find SERP feature opportunities with intent modifiers

Now, let’s take a look at which SERP features appear most often for our different keyword modifiers.

To do this, we group our keywords by modifier and create a standard tag for each group. Then, we set up dynamic tags for our desired SERP features. Again, to keep track of all the things, we contained the tags in handy data views, grouped by search intent.

What can we uncover?

Because we saw that featured snippets appear most often for our commercial intent keywords, it’s time to drill on down and figure out precisely which modifiers within our commercial bucket are driving this trend.

Glancing quickly at the numbers in the tag titles in the image above, we can see that “best,” “reviews,” and “top” are responsible for the majority of the keywords that return a featured snippet:

  • 212 out of 294 of our “best” keywords (72%)
  • 109 out of 294 of our “reviews” keywords (37%)
  • 170 out of 294 of our “top” keywords (59%)

This shows us where our efforts are best spent optimizing.

By clicking on the “best — featured snippets” tag, we’re magically transported into the dashboard. Here, we see that our average ranking could use some TLC.

There is a lot of opportunity to snag a snippet here, but we (actually, Amazon, who we’re tracking these keywords against) don’t seem to be capitalizing on that potential as much as we could. Let’s drill down further to see which snippets we already own.

We know we’ve got content that has won snippets, so we can use that as a guideline for the other keywords that we want to target.

3. See which pages are ranking best by search intent

In our blog post How Google dishes out content by search intent, we looked at what type of pages — category pages, product pages, reviews — appear most frequently at each stage of a searcher’s intent.

What we found was that Google loves category pages, which are the engine’s top choice for retail keywords across all levels of search intent. Product pages weren’t far behind.

By creating dynamic tags for URL markers, or portions of your URL that identify product pages versus category pages, and segmenting those by intent, you too can get all this glorious data. That’s exactly what we did for our retail keywords

What can we uncover?

Looking at the tags in the transactional page types data view, we can see that product pages are appearing far more frequently (526) than category pages (151).

When we glanced at the dashboard, we found that slightly more than half of the product pages were ranking on the first page (sah-weet!). That said, more than thirty percent appeared on page three and beyond. So despite the initial visual of “doing well”, there’s a lot of opportunity that Amazon could be capitalizing on.

We can also see this in the Daily Snapshot. In the image above, we compare category pages (left) to product pages (right), and we see that while there are less category pages ranking, the rank is significantly better. Amazon could take some of the lessons they’ve applied to their category pages to help their product pages out.

Wrapping it up

So what did we learn today?

  1. Smart segmentation starts with a well-crafted list of keywords, grouped into tags, and housed in data views.
  2. The more you segment, the more insights you’re gonna uncover.
  3. Rely on the dashboards in STAT to flag opportunities and tell you what’s good, yo!

Want to see it all in action? Get a tailored walkthrough of STAT, here.

Or get your mitts on even more intent-based insights in our full whitepaper: Using search intent to connect with consumers.

Read on, readers!

More in our search intent series:

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Source: https://moz.com/blog/a-guide-to-setting-up-your-very-own-search-intent-projects

Manipulating an Indian politician’s tweets is worryingly easy to do

Here’s a concerning story from India, where the upcoming election is putting the use of social media in the spotlight.

While the Indian government is putting Facebook, Google and other companies under pressure to prevent their digital platforms from being used for election manipulation, a journalist has demonstrated just how easy it is to control the social media messages published by government ministers.

Pon Radhakrishnan, India’s minister of state for finance and shipping, published a series of puzzling tweets today after Pratik Sinha, a co-founder of fact-checking website Alt News, accessed a Google document of prepared statements and tinkered with the content.

Among the statements tweeted out, Radhakrishnan said Prime Minister Modi’s government had failed the middle classes and had not made development on improving the country’s general welfare. Sinha’s edits also led to the official BJP Assam Pradesh account proclaiming that the prime minister had destroyed all villages and made women slaves to cooking.

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These are the opposite of the partisan messages that the accounts intended to send.

The messages were held in an unlocked Google document that contained a range of tweets compiled for the Twitter accounts. Sinha managed to access the document and doctor the messages into improbable statements — which he has done before — in order to show the shocking lack of security and processes behind the social media content.

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Sinha said he made the edits “to demonstrate how dangerous this is from the security standpoint for this country.”

“I had fun but it could have disastrous consequences,” he told TechCrunch in a phone interview. “This is a massive security issue from the point of view of a democracy.”

Sinha said he was able to access the document — which was not restricted or locked to prevent changes — through a WhatsApp group that is run by members of the party. Declining to give specifics, he said he had managed to infiltrate the group and thus gain access to a flow of party and government information and, even more surprisingly, get right into the documents and edit them.

What’s equally as stunning is that, even with the message twisted 180 degrees, their content didn’t raise an alarm. The tweets were still loaded and published without any realization. It was only after Sinha went public with the results that Radhakrishnan and BJP Assam Pradesh account begin to delete them.

The Indian government is rightly grilling Facebook and Google to prevent its platform being abused around the election, as evidence suggested happened in the U.S. presidential election and the U.K.’s Brexit vote, but members of the government themselves should reflect on the security of their own systems, too. It would be too easy for these poor systems to be exploited.


Source: https://techcrunch.com/2019/02/13/india-politician-tweets/