Monthly Archives: November 2020
Pinterest is getting into online events. The company has been spotted testing a new feature that allows users to sign up for Zoom classes through Pinterest, while creators use Pinterest’s class boards to organize class materials, notes and other resources, or even connect with attendees through a group chat option. The company confirmed the test of online classes is an experiment now in development, but wouldn’t offer further details about its plans.
The feature itself was discovered on Tuesday by reverse engineer Jane Manchun Wong, who found details about the online classes by looking into the app’s code.
— Jane Manchun Wong (@wongmjane) November 24, 2020
Currently, you can visit some of these “demo” profiles directly — like “@pinsmeditation” or “@pinzoom123,” for example — and view their listed Class Communities. However, these communities are empty when you click through. That’s because the feature is still unreleased, Wong says.
When and if the feature is later launched to the public, the communities would include dedicated sections where creators will be able to organize their class materials — like lists of what to bring to class, notes, photos and more. They could also use these communities to offer a class overview and description, connect users to a related shop, group chat feature and more.
Creators are also able to use the communities — which are basically enhanced Pinterest boards — to respond to questions from attendees, share photos from the class and otherwise interact with the participants.
When a user wants to join a class, they can click a “book” button to sign up, and are then emailed a confirmation with the meeting details. Other buttons direct attendees to download Zoom or copy the link to join the class.
It’s not surprising that Pinterest would expand into the online events space, given its platform has become a popular tool for organizing remote learning resources during the coronavirus pandemic. Teachers have turned to Pinterest to keep track of lesson plans, get inspiration, share educational activities and more. In the early days of the pandemic, Pinterest reported record usage when the company saw more searches and saves globally in a single March weekend than ever before in its history, as a result of its usefulness as a online organizational tool.
This growth has continued throughout the year. In October, Pinterest’s stock jumped on strong earnings after the company beat on revenue and user growth metrics. The company brought in $ 443 million in revenue, versus $ 383.5 million expected, and grew its monthly active users to 442 million, versus the 436.4 million expected. Outside of the coronavirus impacts, much of this growth was due to strong international adoption, increased ad spend from advertisers boycotting Facebook and a surge of interest from users looking for iOS 14 home screen personalization ideas.
Given that the U.S. has failed to get the COVID-19 pandemic under control, many classes, events and other activities will remain virtual even as we head into 2021. The online events market may continue to grow in the years that follow, too, thanks to the kickstart the pandemic provided the industry as a whole.
“We are experimenting with ways to help creators interact more closely with their audience,” a Pinterest spokesperson said, when asked for more information.
Pinterest wouldn’t confirm additional details about its plans for online events, but did say the feature was in development and the test would help to inform the product’s direction.
Pinterest often tries out new features before launching them to a wider audience. Earlier this summer, TechCrunch reported on a Story Pins feature the company had in the works. Pinterest then launched the feature in September. If the same time frame holds up for online events, we could potentially see the feature become more widely available sometime early next year.
Featured Snippet Answers Based on Context
Last month I wrote about answer passages when Google decides what answers to show in response to queries that are asking questions, in the post, Featured Snippet Answer Scores Ranking Signals. In that post, I wrote about an updated patent which made it clear that passages that might be shown in response to a query are given answer scores that are based on both query dependent and query independent signals.
A query dependent signal is one that includes relevance of a term in the query to some aspect of candidate featured snippet answers. A query independent signal doesn’t rely upon the terms in a query, and their relevance to terms in an answer passage, but could look at other aspects of answers, such as whether an answer is written in complete sentences or other query independent aspects of those answers.
At the end of September, Danny Sullivan, Public Liaison for Search at Google, posted on the Google Keyword Blog about some recent queries that were performed on Google that contained questions about smoke-related to wildfires in California. One frequent query in the area was, “why is the sky orange?” The blog post told us about how Google might use contextual information about location and freshness of content in featured snippet answers.
You may notice that the location of searchers is not expressly identified in the query, much like a search for different business types, such as restaurants or places to shop. The article about these queries is in the post at:
Danny tells us about how Google might respond to these queries:
Well, language understanding is at the core of Search, but it’s not just about the words. Critical context, like time and place, also helps us understand what you’re really looking for. This is particularly true for featured snippets, a feature in Search that highlights pages that our systems determine are likely a great match for your search. We’ve made improvements to better understand when fresh or local information — or both — is key to delivering relevant results to your search.
So this is pointing out that Google has worked on improving answers for questions that are asking about fresh or local information (Or both). The snippet from the post refers to critical context, and how Google may understand the context of a question is essential to how helpful it can be in answering questions.
Google tells us that “Our freshness indicators identified a rush of new content was being produced on this topic that was both locally relevant and different from the more evergreen content that existed.”
Since Google actively is engaged in indexing content on the web, they can notice bursty behavior about different topics, and where it is from. That reminds me of a post I wrote back in 2008 called How Search Query Burstiness Could Increase Page Rankings. So Google can tell what people are searching for and where they are searching from, by keeping an eye on their log files, and Google can tell what people are creating content about when it indexes new and updated webpages.
I liked this statement from the Google post, too:
Put simply, instead of surfacing general information on what causes a sunset, when people searched for “why is the sky orange” during this time period, our systems automatically pulled in current, location-based information to help people find the timely results they were searching for.
Danny also points out a query that sometimes surfaces from searchers in places such as New York City, or Boston: “Why is it Hazy?” to show that Google can use local context in those areas to provide relevant results for people searching from there.
We are told that this Google blog post provided information about a couple of queries specific to certain locations, but Google receives billions of queries a day, and they provide fresh and relevant results to all of those queries when they receive them.
Understanding the context of questions that people perform on different topics and from different places can help people receive answers to what they want to learn more about. The Google Blog post from Danny is worth reading and thinking about if you haven’t seen it
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- There are SEO tactics you can apply even without significant expertise.
- These tactics even the playing field a bit for those who can’t hire a huge team or outsource to an agency.
- Paying attention to things like images and hosting can give your site a boost.
- There are simple link building tools that are free and easy to use.
- Applying these tactics will help you get in the SEO game and give your website a boost in search.
SEO is not easy. In fact, there are around 200 factors that go into determining where your website appears in search results. As such, optimizing your site for search can be a daunting task. Companies hire full teams of SEO experts or outsource the work to agencies to handle the huge workload that can come with executing an effective SEO strategy. Many companies, like yours perhaps, don’t have the resources to do this, however. Fortunately, there are a number of quick wins you can take advantage of to give your website a boost in search.
Try these five tactics to gain some quick SEO wins for your website.
1. Optimize images and visuals
The images and visual elements you place on your site, in articles, on pages, and all around, can be hugely valuable in giving an easy boost to your search rankings.
One example I like to point to is this image on the SE Healthcare website.
Image: SE Healthcare infographic ranking in image searches – Source
In working with SE Healthcare on the company’s SEO strategy for a new product launch, we were targeting keywords around the core of physician burnout. Over time, we noticed that this image actually started ranking. It started showing up for tons of searches for “physician burnout solutions” as a result. And those searches went straight to this image in an image search on Google.
Clicks on this result ended up with shares of our infographic appearing on social media as well as a serious lift in our search results for related searches. And we ultimately found that inquiries about related product lines began to rise as well.
So, make sure you’re doing the following to use images to give an easy boost to your search results.
Add visual elements throughout your site
First, adding images, infographics and other visual elements to your site just creates a better experience for users. Any time you can substitute a visual element to explain a concept rather than adding a thousand words of unnecessary text, it can go a long way in connecting with visitors.
Obviously, don’t eliminate text altogether or your SEO will suffer. But, be sure you add images in articles to enhance the articles. Add graphics to explain product features. Add high-quality images of your products. The list goes on, but you get the point. Images add tons of value to your site, and they can also help you rank in search. Google and other search engines love images.
Where to add images
To give you an idea of where you can place images to optimize your site, try the following:
Representative icons – Add representative icons above products and other elements to pull your visitors’ attention.
Image: Icons to represent services – Source
Infographics – Drop infographics into articles and other pages to visually explain concepts and add more value to keep readers on the page and scrolling.
Image: Example of an infographic to add value – Source
Demo Videos – These can really boost your ability to highlight your products by showing rather than telling.
Image: Demo video example – Source
Visual Coupon Codes – This is a great way to highlight discounts and entice shoppers on your site to make a purchase. Works great for ecommerce businesses.
Image: Visual discount codes – Source
Thumbnail Images – Make sure to add thumbnail images for your posts. These will show up as shown below.
Image: Example of using thumbnail images with posts – Source
Images in Blogs – Placing images through your blog is hugely important. You can use a header image as well as images throughout the post to illustrate important points.
Image: Example of adding a supporting image that expands on the info provided in the text within a blog post – Source
These are just a few ideas of how you can leverage visuals throughout your website to enhance the user experience and give your website a boost in search.
Embedding a YouTube video into your articles or your pages can really help boost stats like time on page and lower stats like bounce rate. When these stats head in a positive direction, Google will take notice.
Google loves sites that keep visitors’ attention and keep them on site. A video embedded in the middle of an article can add a minute or more to the time someone spends on your page. And the best part, you don’t even have to create the video.
For example, you could write an article about making Fall décor from egg cartons. Conduct a search on YouTube and find an example of someone doing this, and then embed it in the middle of the article. Not only will visitors read your copy, but they will likely also stop and watch the video, thus keeping them engaged longer.
Insert alt tags
Google is getting better at reading images and determining what they are showing, but the technology still has a way to go. To make sure Google understands the images on your website, you need to place alt tags in each one image upload describing the image. This helps Google determine what the image is showing and whether it relates to a specific search.
Images are super important for helping your site’s SEO performance, so be sure to follow the tips above to benefit.
2. Enhance website security
When you think of cyberattacks, what’s the first thing that comes to mind? Whatever answer popped into your head, I bet it didn’t have anything to do with SEO. Many site owners fail to realize the negative impact a cyberattack can have on your site’s search rankings.
Google, however, is paying attention to a variety of reasons. If your website is lacking in security, and Google takes notice, your site could be in serious trouble.
How Google treats cyber attacks
If Google crawls your website and finds it has been hacked, the search engine giant could actually blacklist your website. When this happens, site visitors will see a notice saying something like “This site may have been hacked.” It goes without saying that visitors seeing that notice will likely navigate away from your website and look for answers and solutions elsewhere.
People see this warning and instantly click away, which can seriously damage your site’s stats. Google will undoubtedly take notice, and your site could be demoted. You may not even notice anything until you see a huge drop in traffic or a major rise in your bounce rate and decide to investigate. By that point, the damage will be done, and you’ll be forced to spend tons of time making things right.
There are a number of types of attacks that can hurt your site. Let’s take a look at a couple types of cyberattacks that can have a seriously negative impact on your search rankings.
DDoS stands for Distributed Denial of Service. This type of attack is becoming more and more prevalent. The cybercriminal will send massive amounts of bot-related traffic to your site, which can cause significant downtime.
This significant downtime can cause your search rankings to drop. Even 15-minutes of downtime can be a negative signal to Google, so just imagine what a whole week could do. For this reason, you need to take steps to avoid a DDoS attack in order to prevent a drop in search rankings.
This involves bad bots crawling your site and scraping content or stealing data. Obviously, you want to avoid an instance of data theft. Just think of all the major headlines that have been made in recent years from companies being hacked and customer data being stolen. A lesser-known bad bot is the content scraper. These bots essentially scrape your content and place it elsewhere. This compromises your site’s originality and uniqueness and can lead to your search rankings dropping.
These are just a couple of the types of hacks that can hurt your SEO. There are plenty more to be aware of, so you’ll want to do your homework and make sure your site is prepared.
How to protect your site
Fortunately, there are a number of proactive steps you can take to protect your site to avoid this negative impact on your SEO. Here are a few things you should be doing:
- Make sure you have HTTPS setup
- Install a strong firewall
- Conduct regular testing to uncover potential vulnerabilities
- Use multi-factor authentication for your website logins and even for email
- Install a security plugin
- Update your website regularly
- Use secure logins and passwords for your team (and update them regularly)
Doing these things can position you to avoid the negative SEO impact of a cyberattack and help you maintain the search rankings you worked so hard to earn.
3. Speed up the hosting
Multiple studies confirm that faster site speed does indeed result in better search results. There are a ton of factors that go into optimizing the speed on your site, but one simple factor that’s super easy to control is your site’s hosting provider.
Many of the technical things you can do to speed up your site take time and often require an expert. Fast hosting, on the other hand, simply involves making the right choice and then working with the hosting providers to get your site up and optimized.
There are a ton of hosting providers that offer hosting for $ 2.99 a month (give or take), but often those are shared hosting, which can be significantly slower. To really get the most out of your hosting and truly experience an increase in site speed, I recommend looking at the following types of hosting providers.
Managed WordPress hosting
I start with this because 38% of websites are built using WordPress. It’s my preferred platform, and for WordPress users, managed WordPress hosting can really help optimize your site and give a boost to your site’s speed. I use a managed WordPress hosting provider for my own website.
Managed WordPress hosting often comes with a higher level of support, enhanced security, and obviously since I’m bringing it up here, faster page load speed.
The cost can range from $ 50 to upwards of $ 200 per month, which makes this an affordable option for small- to mid-sized businesses.
The name speaks for itself. You won’t be sharing this hosting with anyone. It is 100% dedicated to your organization alone, which gives you a huge boost in speed. Unfortunately, this option also comes with a boost in cost.
That said, if you are seeing 100s of thousands of visitors to your site each month, this option is right for you. And if you’re seeing that level of traffic, and your site is optimized for conversions, you can likely afford it.
This option can cost a few thousand dollars, so if you aren’t quite there yet, it may be something to keep in mind for the future.
As you can see from the graphic below from Section.io, site speed can seriously impact the bounce rate of your website, which is why I stress the importance of the impact your hosting provider can have.
If these options aren’t the right fit for you, there are tons of other options. With shared hosting, for example, you can pay a bit more to get faster speeds. And with Cloud hosting, you get the benefit of lower downtime.
Whatever option you choose, make sure you talk to the hosting provider and ask questions about site speed and how their platform will help you boost the performance in this area. A faster site is an easy way to give a boost to your SEO.
4. Simplified link building
Link building takes a lot of time and effort. You need to conduct research upfront, and then the execution part, including the outreach to website owners, can be quite time intensive.
There are, however, a few methods you can use to grab some easy links and start slowly building up your arsenal of links.
Let’s take a look at two specific ways you can do link building effectively while saving some time and effort.
HARO (Help A Reporter Out)
This is a great resource. Help A Reporter Out, known in the industry as HARO, allows you to connect with journalists who are seeking sources for the content they’re creating.
You sign up for an account, and when you receive emails with a list of inquires each day related to the subject matter you select. For example, if you run a marketing agency, you can sign up for the business and finance emails. If you run a healthcare organization, you can sign up for the healthcare list.
Once you’re signed up, you’ll receive emails each day that list out queries from journalists asking for expert sources like yourself to provide your opinion or advice on particular topics. Those emails will look something like this:
Image: HARO email example
As you can see in the email, you’ll see a one-liner highlighting the subject of the query. If you see something that stands out (a subject you feel you could answer expertly), you can just scroll down through the email and you’ll see the full query.
The full query will have more details about the publication and what, specifically, the writer is looking for. Only answer queries where you truly feel you are an expert.
Once you find something that’s a fit, submit an email to the writer via the email link in the email you were sent. I recommend formatting it something like this:
By using this format, you’ll have a better chance of getting accepted, and when you get accepted, the writer will typically add a link back to your site from your quote.
If you keep an eye on your HARO emails and try to respond to 1-2 queries each day, you will gradually start to get your answers accepted, thus gaining valuable backlinks, sometimes from super high domain authority sites. I’ve personally grabbed links from sites like Content Marketing Institute (80+ DA) and Forbes (80+ DA), among others.
This is another easy link building win. All you need is the following information, and then you can start creating accounts for various directory sites.
- Elevator pitch for your business (aka, brief description)
- Your website’s URL
- Physical address and contact information
- Logo or image to accompany your listing
Some sites will allow you to enter more info, but you need to at least be armed with the basics above.
Start with the general sites like Yelp, Yellow Pages, and of course, Google My Business. Get those sites up, and then dig a bit deeper. Your industry will definitely have industry-specific directory sites, so don’t forget to fill out those as well.
By filling out directory sites, you are gaining links back to your website, but you are also setting up opportunities for your profile on those sites to appear in search when your site itself does not.
These are just a couple of easy ways to start building links. Begin with these tools, and as you start to get on a roll with HARO, and your directory sites are all set up, you can move onto more difficult efforts.
5. Check for broken links
One thing that can hurt your site is having broken links littering your pages. If you post a ton of content, it can be easy for broken links to slip past you.
For example, you link out to external posts to provide supporting information to your blog readers. Over time, the owners of the sites you link to may remove posts, or those pages themselves may become broken.
If you have a ton of broken links throughout your content, this can impact your SEO, and it can create a poor user experience.
Fortunately, there are lots of great tools you can use to check for broken links and then correct them. Here are a few options:
- SEMRush – This is a paid platform with lots of bells and whistles. There are a ton of great tools included, so if you want to go all-in on SEO, start here.
- Ahrefs – While Ahrefs has a great paid platform, they also offer a basic broken link checker for free. I highly recommend checking it out.
- Dead Link Checker – This is another free tool. You just type in your URL and the checker will scan your site and point out any issues with broken links that it finds.
Whatever tool you choose, you’ll want to locate broken links and either update them with links to new, relevant content or unlink them. Doing this can help keep your site clean and give your website a boost in search.
Applying these tactics can help you get a head start on your SEO efforts. While many SEO tactics are very time-intensive and super challenging, these four tactics are a bit easier and can give you some quick wins.
And the best part is that you don’t need to be a seasoned SEO vet to execute these tactics. Anyone can set up a hosting provider, for example. And typically, the hosting provider will move your site over to the new hosting, so all you’ll have to do is provide some login info.
And looking at HARO, connecting with reporters for high-quality publications can be extremely challenging. HARO helps level the playing field and gives you access to reporters in a much easier way.
So, get your team together and figure out the best approach to start applying these tactics. If you stay consistent and focus on the end goal, these tactics can really give your website a boost in search.
Anthony is the Founder of AnthonyGaenzle.com a marketing and business blog. He also serves as the Head of Marketing and Business Development at Granite Creative Group, a full-service marketing firm. He is a storyteller, strategist, and eternal student of marketing and business strategy.
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Proxyclick began life by providing an easy way to manage visitors in your building with an iPad-based check-in system. As the pandemic has taken hold, however, customer requirements have changed, and Proxyclick is changing with them. Today the company announced Proxyclick Flow, a new system designed to check in employees during the time of COVID.
“Basically when COVID hit our customers told us that actually our employees are the new visitors. So what you used to ask your visitors, you are now asking your employees — the usual probing question, but also when are you coming and so forth. So we evolved the offering into a wider platform,” Proxyclick co-founder and CEO Gregory Blondeau explained.
That means instead of managing a steady flow of visitors — although it can still do that — the company is focusing on the needs of customers who want to open their offices on a limited basis during the pandemic, based on local regulations. To help adapt the platform for this purpose, the company developed the Proovr smartphone app, which employees can use to check in prior to going to the office, complete a health checklist, see who else will be in the office and make sure the building isn’t over capacity.
When the employee arrives at the office, they get a temperature check, and then can use the QR code issued by the Proovr app to enter the building via Proxyclick’s check-in system or whatever system they have in place. Beyond the mobile app, the company has designed the system to work with a number of adjacent building management and security systems so that customers can use it in conjunction with existing tooling.
They also beefed up the workflow engine that companies can adapt based on their own unique entrance and exit requirements. The COVID workflow is simply one of those workflows, but Blondeau recognizes not everyone will want to use the exact one they have provided out of the box, so they designed a flexible system.
“So the challenge was technical on one side to integrate all the systems, and afterwards to group workflows on the employee’s smartphone, so that each organization can define its own workflow and present it on the smartphone,” Blondeau said.
Once in the building, the systems registers your presence and the information remains on the system for two weeks for contact tracing purposes should there be an exposure to COVID. You check out when you leave the building, but if you forget, it automatically checks you out at midnight.
The company was founded in 2010 and has raised $ 19.6 million. The most recent raise was a $ 18.5 million Series B in January.
F3, an anonymous Q&A app targeting Gen Z teens which blends a Tinder-style swipe-to-friend gamification mechanic, Stories-esque rich media responses and eye-wateringly expensive subscriptions to unlock a ‘Plus’ version that actually lets you see who wants to friend you — has raised a $ 3.9M seed round, including for a planned push on the US market.
The Latvian team behind F3 are not new to the viral teen app game having founded the anonymous teen Q&A app Ask.fm — which faced huge controversy back in 2013 over bullying and safety concerns after being linked to a number of suicides of users who’d received abusive messages. Not that they’ve let that put them off the viral teen app space, clearly.
Investors in F3’s seed round hail from the Russian dating network Mamba (including the latter’s investor, Mail.ru Group) and a co-investor VC firm with a marketing focus, called AdFirst.
Alex Hofmann (former musical.ly president) and Marat Kichikov (GP at Bitfury Capital) are also named as being among those joining the round as angel investors.
F3, which launched its apps in 2018, has 25M registered users at this point — 85% of whom are younger than 25.
The typical user is a (bored) teenager, with the user base being reported as 65% female and 60% Europe / 20% LatAm / 20% Rest of World at this point. (They’re not breaking out any active user metrics but claim 80% of users have been on the app for more than three months at this point.)
On the safety front, F3 is using both automated tools and people for content moderation — with the founders claiming to have learnt lessons from their past experience with Ask.fm (which got acquired by IAC’s Ask.com back in 2014, given them the funds to plough into F3’s development up to now).
“We’ve been solving problem of violating content in our previous company (Ask.fm), and now at F3 we’ve used all our knowledge of solving this problem from day one. Automation tools include text analysis in all major languages with database of 250k+ patterns that is continuously being improved, and AI based image recognition algorithms for detecting violating content in photos and videos,” says the founding team — which includes CEO Ilja Terebin.
“Our 24/7 content moderation team (8 in-house safety experts and 30+ outsourced contractors) manually reviews user reports and items flagged by automation tools,” they add.
However reviews of the app that we saw included complaints from users who said they’ve being pestered by ‘pedophiles’ asking for nudes — so claims of safety risks being “solved” seem riskily overblown.
Why do teens need yet another social discovery/messaging app? On that Terebin & team say the app has been tailored for Gen Z from the get-go — “focusing on their needs to socialize and make new friends online, ‘quick’ content in the form of photos and short videos, which is true and personal”.
“Raw & real” is another of their teen-friendly product market fit claims.
F3 users get a personalized URL that they can share to other social networks to solicit questions from their friends — which can be asked anonymously or not. (F3 users can also choose not to accept anonymous questions if they prefer.)
Instead of plain text answers users snap a photo or grab a short video, add filters, fancy fonts and backgrounds, and so on to reply in a rich-media Stories-style that’s infiltrated all social networking apps (most recently infecting Twitter, where it’s called Fleets).
These rich media responses get made public on their feed — so if an F3 user chooses to answer a question they’re also engaging with the wider community by default (though they can choose not to respond as questions remain private until responded to).
Asked how F3 stands out in a very packed and competitive social media landscape, they argue the app’s “uniqueness” is that the Q&A is photo and video based — “so the format is familiar and close to other social networks (‘stories’ or ‘snaps’) but in a Q&A style back-and-forth communication”, as they put it, adding that for their Gen Z target “the outdated text-based Q&A just was too boring”.
“We compete for eyeballs of Gen Z with Snapchat, TikTok and Instagram. Our key strength is that through the Q&A format one can make new friends and truly get to know other people on a personal level through the prism of ‘raw and real’ content, which is not central on any of those platforms,” they also claim.
In terms of most similar competitors, they note Yolo has seen “some traction” and concede there are a bunch of others also offering Q&A. But here they argue F3 is more fully featured than rivals — suggesting the Q&A feature is just the viral hook to get users into a wider community net.
“[F3] is a fully functional social platform, built around visual communication — users have content feed where they can view posts by people they follow, they can create photo/video content using editing tools in the app itself, there’s a messenger functionality for direct chats, follow-ships, content and user discovery. So for us, the anonymous messaging/Q&A format is just an entry point which allows us to grow quickly and get the users on our platform, but then they make new connections and keep engaging with their unique social circle they have only on F3, making it a sustainable stand-alone social network.”
“This whole app is literally just like all the other apps. Just another copy cat that you still have to pay for,” runs one review from July 2020. “Don’t download.”
How Are Featured Snippet Answers Decided Upon?
I recently wrote about Featured Snippet Answer Scores Ranking Signals. In that post, I described how Google was likely using query dependent and query independent ranking signals to create answer scores for queries that were looking like they wanted answers.
One of the inventors of that patent from that post was Steven Baker. I looked at other patents that he had written, and noticed that one of those was about context as part of query independent ranking signals for answers.
Remembering that patent about question-answering and context, I felt it was worth reviewing that patent and writing about it.
This patent is about processing question queries that want textual answers and how those answers may be decided upon.
it is a complicated patent, and at one point the description behind it seems to get a bit murky, but I wrote about when that happened in the patent, and I think the other details provide a lot of insight into how Google is scoring featured snippet answers. There is an additional related patent that I will be following up with after this post, and I will link to it from here as well.
This patent starts by telling us that a search system can identify resources in response to queries submitted by users and provide information about the resources in a manner that is useful to the users.
How Context Scoring Adjustments for Featured Snippet Answers Works
Users of search systems are often searching for an answer to a specific question, rather than a listing of resources, like in this drawing from the patent, showing featured snippet answers:
For example, users may want to know what the weather is in a particular location, a current quote for a stock, the capital of a state, etc.
When queries that are in the form of a question are received, some search engines may perform specialized search operations in response to the question format of the query.
For example, some search engines may provide information responsive to such queries in the form of an “answer,” such as information provided in the form of a “one box” to a question, which is often a featured snippet answer.
Some question queries are better served by explanatory answers, which are also referred to as “long answers” or “answer passages.”
For example, for the question query [why is the sky blue], an answer explaining light as waves is helpful.
Such answer passages can be selected from resources that include text, such as paragraphs, that are relevant to the question and the answer.
Sections of the text are scored, and the section with the best score is selected as an answer.
In general, the patent tells us about one aspect of what it covers in the following process:
- Receiving a query that is a question query seeking an answer response
- Receiving candidate answer passages, each passage made of text selected from a text section subordinate to a heading on a resource, with a corresponding answer score
- Determining a hierarchy of headings on a page, with two or more heading levels hierarchically arranged in parent-child relationships, where each heading level has one or more headings, a subheading of a respective heading is a child heading in a parent-child relationship and the respective heading is a parent heading in that relationship, and the heading hierarchy includes a root level corresponding to a root heading (for each candidate answer passage)
- Determining a heading vector describing a path in the hierarchy of headings from the root heading to the respective heading to which the candidate answer passage is subordinate, determining a context score based, at least in part, on the heading vector, adjusting the answer score of the candidate answer passage at least in part by the context score to form an adjusted answer score
- Selecting an answer passage from the candidate answer passages based on the adjusted answer scores
Advantages of the process in the patent
- Long query answers can be selected, based partially on context signals indicating answers relevant to a question
- The context signals may be, in part, query-independent (i.e., scored independently of their relatedness to terms of the query
- This part of the scoring process considers the context of the document (“resource”) in which the answer text is located, accounting for relevancy signals that may not otherwise be accounted for during query-dependent scoring
- Following this approach, long answers that are more likely to satisfy a searcher’s informational need are more likely to appear as answers
This patent can be found at:
Context scoring adjustments for answer passages
Inventors: Nitin Gupta, Srinivasan Venkatachary , Lingkun Chu, and Steven D. Baker
US Patent: 9,959,315
Granted: May 1, 2018
Appl. No.: 14/169,960
Filed: January 31, 2014
Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for context scoring adjustments for candidate answer passages.
In one aspect, a method includes scoring candidate answer passages. For each candidate answer passage, the system determines a heading vector that describes a path in the heading hierarchy from the root heading to the respective heading to which the candidate answer passage is subordinate; determines a context score based, at least in part, on the heading vector; and adjusts answer score of the candidate answer passage at least in part by the context score to form an adjusted answer score.
The system then selects an answer passage from the candidate answer passages based on the adjusted answer scores.
Using Context Scores to Adjust Answer Scores for Featured Snippets
A drawing from the patent shows different hierarchical headings that may be used to determine the context of answer passages that may be used to adjust answer scores for featured snippets:
I discuss these headings and their hierarchy below. Note that the headings include the Page title as a heading (About the Moon), and the headings within heading elements on the page as well. And those headings give those answers context.
This context scoring process starts with receiving candidate answer passages and a score for each of the passages.
Those candidate answer passages and their respective scores are provided to a search engine that receives a query determined to be a question.
Each of those candidate answer passages is text selected from a text section under a particular heading from a specific resource (page) that has a certain answer score.
For each resource where a candidate answer passage has been selected, a context scoring process determines a heading hierarchy in the resource.
A heading is text or other data corresponding to a particular passage in the resource.
As an example, a heading can be text summarizing a section of text that immediately follows the heading (the heading describes what the text is about that follows it, or is contained within it.)
Headings may be indicated, for example, by specific formatting data, such as heading elements using HTML.
This next section from the patent reminded me of an observation that Cindy Krum of Mobile Moxie has about named anchors on a page, and how Google might index those to answer a question, to lead to an answer or a featured snippet. She wrote about those in What the Heck are Fraggles?
A heading could also be anchor text for an internal link (within the same page) that links to an anchor and corresponding text at some other position on the page.
A heading hierarchy could have two or more heading levels that are hierarchically arranged in parent-child relationships.
The first level, or the root heading, could be the title of the resource.
Each of the heading levels may have one or more headings, and a subheading of a respective heading is a child heading and the respective heading is a parent heading in the parent-child relationship.
For each candidate passage, a context scoring process may determine a context score based, at least in part, on the relationship between the root heading and the respective heading to which the candidate answer passage is subordinate.
The context scoring process could be used to determine the context score and determines a heading vector that describes a path in the heading hierarchy from the root heading to the respective heading.
The context score could be based, at least in part, on the heading vector.
The context scoring process can then adjust the answer score of the candidate answer passage at least in part by the context score to form an adjusted answer score.
The context scoring process can then select an answer passage from the candidate answer passages based on adjusted answer scores.
This flowchart from the patent shows the context scoring adjustment process:
Identifying Question Queries And Answer Passages
I’ve written about understanding the context of answer passages. The patent tells us more about question queries and answer passages worth going over in more detail.
Some queries are in the form of a question or an implicit question.
For example, the query [distance of the earth from the moon] is in the form of an implicit question “What is the distance of the earth from the moon?”
Likewise, a question may be specific, as in the query [How far away is the moon].
The search engine includes a query question processor that uses processes that determine if a query is a query question (implicit or specific) and if it is, whether there are answers that are responsive to the question.
The query question processor can use several different algorithms to determine whether a query is a question and whether there are particular answers responsive to the question.
For example, it may use to determine question queries and answers:
- Language models
- Machine learned processes
- Knowledge graphs
- Combinations of those
The query question processor may choose candidate answer passages in addition to or instead of answer facts. For example, for the query [how far away is the moon], an answer fact is 238,900 miles. And the search engine may just show that factual information since that is the average distance of the Earth from the moon.
But, the query question processor may choose to identify passages that are to be very relevant to the question query.
These passages are called candidate answer passages.
The answer passages are scored, and one passage is selected based on these scores and provided in response to the query.
An answer passage may be scored, and that score may be adjusted based on a context, which is the point behind this patent.
Often Google will identify several candidate answer passages that could be used as featured snippet answers.
Google may look at the information on the pages where those answers come from to better understand the context of the answers such as the title of the page, and the headings about the content that the answer was found within.
Contextual Scoring Adjustments for Featured Snippet Answers
The query question processor sends to a context scoring processor some candidate answer passages, information about the resources from which each answer passages was from, and a score for each of the featured snippet answers.
The scores of the candidate answer passages could be based on the following considerations:
- Matching a query term to the text of the candidate answer passage
- Matching answer terms to the text of the candidate answer passages
- The quality of the underlying resource from which the candidate answer passage was selected
I recently wrote about featured snippet answer scores, and how a combination of query dependent and query independent scoring signals might be used to generate answer scores for answer passages.
The patent tells us that the query question processor may also take into account other factors when scoring candidate answer passages.
Candidate answer passages can be selected from the text of a particular section of the resource. And the query question processor could choose more than one candidate answer passage from a text section.
We are given the following examples of different answer passages from the same page
(These example answer passages are referred to in a few places in the remainder of the post.)
- (1) It takes about 27 days (27 days, 7 hours, 43 minutes, and 11.6 seconds) for the Moon to orbit the Earth at its orbital distance
- (2) Why is the distance changing? The moon’s distance from Earth varies because the moon travels in a slightly elliptical orbit. Thus, the moon’s distance from the Earth varies from 225,700 miles to 252,000 miles
- (3) The moon’s distance from Earth varies because the moon travels in a slightly elliptical orbit. Thus, the moon’s distance from the Earth varies from 225,700 miles to 252,000 miles
Each of those answers could be good ones for Google to use. We are told that:
More than three candidate answers can be selected from the resource, and more than one resource can be processed for candidate answers.
How would Google choose between those three possible answers?
Google might decide based on the number of sentences and a selection of up to a maximum number of characters.
The patent tells us this about choosing between those answers:
Each candidate answer has a corresponding score. For this example, assume that candidate answer passage (2) has the highest score, followed by candidate answer passage (3), and then by candidate answer passage (1). Thus, without the context scoring processor, candidate answer passage (2) would have been provided in the answer box of FIG. 2. However, the context scoring processor takes into account the context of the answer passages and adjusts the scores provided by the query question processor.
So, we see that what might be chosen based on featured snippet answer scores could be adjusted based on the context of that answer from the page that it appears on.
Contextually Scoring Featured Snippet Answers
This process starts which begins with a query determined to be a question query seeking an answer response.
This process next receives candidate answer passages, each candidate answer passage chosen from the text of a resource.
Each of the candidate answer passages are text chosen from a text section that is subordinate to a respective heading (under a heading) in the resource and has a corresponding answer score.
For example, the query question processor provides the candidate answer passages, and their corresponding scores, to the context scoring processor.
A Heading Hierarchy to Determine Context
This process then determines a heading hierarchy from the resource.
The heading hierarchy would have two or more heading levels hierarchically arranged in parent-child relationships (Such as a page title, and an HTML heading element.)
Each heading level has one or more headings.
A subheading of a respective heading is a child heading (an (h2) heading might be a subheading of a (title)) in the parent-child relationship and the respective heading is a parent heading in the relationship.
The heading hierarchy includes a root level corresponding to a root heading.
The context scoring processor can process heading tags in a DOM tree to determine a heading hierarchy.
For example, concerning the drawing about the distance to the moon just above, the heading hierarchy for the resource may be:
The ROOT Heading (title) is: About The Moon (310)
The main heading (H1) on the page
H1: The Moon’s Orbit (330)
A secondary heading (h2) on the page:
H2: How long does it take for the Moon to orbit Earth? (334)
Another secondary heading (h2) on the page is:
H2: The distance from the Earth to the Moon (338)
Another Main heading (h1) on the page
H1: The Moon (360)
Another secondary Heading (h2) on the page:
H2: Age of the Moon (364)
Another secondary heading (h2) on the page:
H2: Life on the Moon (368)
Here is how the patent describes this heading hierarchy:
In this heading hierarchy, The title is the root heading at the root level; headings 330 and 360 are child headings of the heading, and are at a first level below the root level; headings 334 and 338 are child headings of the heading 330, and are at a second level that is one level below the first level, and two levels below the root level; and headings 364 and 368 are child headings of the heading 360 and are at a second level that is one level below the first level, and two levels below the root level.
The process from the patent determines a context score based, at least in part, on the relationship between the root heading and the respective heading to which the candidate answer passage is subordinate.
This score may be is based on a heading vector.
The patent says that the process, for each of the candidate answer passages, determines a heading vector that describes a path in the heading hierarchy from the root heading to the respective heading.
The heading vector would include the text of the headings for the candidate answer passage.
For the example candidate answer passages (1)-(3) above about how long it takes the moon to orbit the earch, the respectively corresponding heading vectors V1, V2 and V3 are:
- V1=<[Root: About The Moon], [H1: The Moon's Orbit], [H2: How long does it take for the Moon to orbit the Earth?]>
- V2=<[Root: About The Moon], [H1: The Moon's Orbit], [H2: The distance from the Earth to the Moon]>
- V3=<[Root: About The Moon], [H1: The Moon's Orbit], [H2: The distance from the Earth to the Moon]>
We are also told that because candidate answer passages (2) and (3) are selected from the same text section 340, their respective heading vectors V2 and V3 are the same (they are both in the content under the same (H2) heading.)
The process of adjusting a score, for each answer passage, uses a context score based, at least in part, on the heading vector (410).
That context score can be a single score used to scale the candidate answer passage score or can be a series of discrete scores/boosts that can be used to adjust the score of the candidate answer passage.
Where things Get Murky in This Patent
There do seem to be several related patents involving featured snippet answers, and this one which targets learning more about answers from their context based on where they fit in a heading hierarchy makes sense.
But, I’m confused by how the patent tells us that one answer based on the context would be adjusted over another one.
The first issue I have is that the answers they are comparing in the same contextual area have some overlap. Here those two are:
- (2) Why is the distance changing? The moon’s distance from Earth varies because the moon travels in a slightly elliptical orbit. Thus, the moon’s distance from the Earth varies from 225,700 miles to 252,000 miles
- (3) The moon’s distance from Earth varies because the moon travels in a slightly elliptical orbit. Thus, the moon’s distance from the Earth varies from 225,700 miles to 252,000 miles
Note that the second answer and the third answer both include the same line: “Thus, the moon’s distance from the Earth varies from 225,700 miles to 252,000 miles.” I find myself a little surprised that the second answer includes a couple of sentences that aren’t in the third answer, and skips a couple of lines from the third answer, and then includes the last sentence, which answers the question.
Since they both appear in the same heading and subheading section of the page they are from, it is difficult to imagine that there is a different adjustment based on context. But, the patent tells us differently:
The candidate answer score with the highest adjusted answer score (based on context from the headings) is selected, and the answer passage.
Recall that in the example above, the candidate answer passage (2) had the highest score, followed by candidate answer passage (3), and then by candidate answer passage (1).
However, after adjustments, candidate answer passage (3) has the highest score, followed by candidate answer passage (2), and then-candidate answer passage (1).
Accordingly, candidate answer passage (3) is selected and provided as the answer passage of FIG. 2.
Boosting Scores Based on Passage Coverage Ratio
A query question processor may limit the candidate answers to a maximum length.
The context scoring processor determines a coverage ratio which is a measure indicative of the coverage of the candidate answer passage from the text from which it was selected.
The patent describes alternative question answers:
Alternatively, the text block may include text sections subordinate to respective headings that include a first heading for which the text section from which the candidate answer passage was selected is subordinate, and sibling headings that have an immediate parent heading in common with the first heading. For example, for the candidate answer passage, the text block may include all the text in the portion 380 of the hierarchy; or may include only the text of the sections, of some other portion of text within the portion of the hierarchy. A similar block may be used for the portion of the hierarchy for candidate answer passages selected from that portion.
A small coverage ratio may indicate a candidate answer passage is incomplete. A high coverage ratio may indicate the candidate answer passage captures more of the content of the text passage from which it was selected. A candidate answer passage may receive a context adjustment, depending on this coverage ratio.
A passage coverage ratio is a ratio of the total number of characters in the candidate answer passage to the ratio of the total number of characters in the passage from which the candidate answer passage was selected.
The passage cover ratio could also be a ratio of the total number of sentences (or words) in the candidate answer passage to the ratio of the total number of sentences (or words) in the passage from which the candidate answer passage was selected.
We are told that other ratios can also be used.
From the three example candidate answer passages about the distance to the moon above (1)-(3) above, passage (1) has the highest ratio, passage (2) has the second-highest, and passage (3) has the lowest.
This process determines whether the coverage ratio is less than a threshold value. That threshold value can be, for example, 0.3, 0.35 or 0.4, or some other fraction. In our “distance to the moon” example, each coverage passage ratio meets or exceeds the threshold value.
If the coverage ratio is less than a threshold value, then the process would select a first answer boost factor. The first answer boost factor might be proportional to the coverage ratio according to a first relation, or maybe a fixed value, or maybe a non-boosting value (e.g., 1.0.)
But if the coverage ratio is not less than the threshold value, the process may select a second answer boost factor. The second answer boost factor may be proportional to the coverage ratio according to a second relation, or maybe fixed value, or maybe a value greater than the non-boosting value (e.g., 1.1.)
Scoring Based on Other Features
The context scoring process can also check for the presence of features in addition to those described above.
Three example features for contextually scoring an answer passage can be based on the additional features of the distinctive text, a preceding question, and a list format.
Distinctive text is the text that may stand out because it is formatted differently than other text, like using bolding.
A Preceeding Question
A preceding question is a question in the text that precedes the candidate answer question.
The search engine may process various amounts of text to detect for the question.
Only the passage from which the candidate answer passage is extracted is detected.
A text window that can include header text and other text from other sections may be checked.
A boost score that is inversely proportional to the text distance from a question to the candidate answer passage is calculated, and the check is terminated at the occurrence of a first question.
That text distance may be measured in characters, words, or sentences, or by some other metric.
If the question is anchor text for a section of text and there is intervening text, such as in the case of a navigation list, then the question is determined to only precede the text passage to which it links, not precede intervening text.
In the drawing above about the moon, there are two questions in the resource: “How long does it take for the Moon to orbit Earth?” and “Why is the distance changing?”
The first question–“How long does it take for the Moon to orbit Earth?”– precedes the first candidate answer passage by a text distance of zero sentences, and it precedes the second candidate answer passage by a text distance of five sentences.
And the second question–“Why is the distance changing?”– precedes the third candidate answer by zero sentences.
If a preceding question is detected, then the process selects a question boost factor.
This boost factor may be proportional to the text distance, whether the text is in a text passage subordinate to a header or whether the question is a header, and, if the question is in a header, whether the candidate answer passage is subordinate to the header.
Considering these factors, the third candidate answer passage receives the highest boost factor, the first candidate answer receives the second-highest boost factor, and the second candidate answer receives the smallest boost factor.
Conversely, if the preceding text is not detected, or after the question boost factor is detected, then the process detects for the presence of a list.
The Presence of a List
A list is an indication of several steps usually instructive or informative. The detection of a list may be subject to the query question being a step modal query.
A step modal query is a query where a list-based answer is likely to a good answer. Examples of step model queries are queries like:
- [How to . . . ]
- [How do I . . . ]
- [How to install a door knob]
- [How do I change a tire]
The context scoring process may detect lists formed with:
- HTML tags
- Micro formats
- Semantic meaning
- Consecutive headings at the same level with the same or similar phrases (e.g., Step 1, Step 2; or First; Second; Third; etc.)
The context scoring process may also score a list for quality.
It would look at things such as:
- A list in the center of a page, which does not include multiple links to other pages (indicative of reference lists)
- HREF link text that does not occupy a large portion of the text of the list will be of higher quality than a list at the side of a page, and which does include multiple links to other pages (which are indicative of reference lists), and/are has HREF link text that does occupy a large portion of the text of the list
If a list is detected, then the process selects a list boost factor.
That list boost factor may be fixed or may be proportional to the quality score of the list.
If a list is not detected, or after the list boost factor is selected, the process ends.
In some implementations, the list boost factor may also be dependent on other feature scores.
If other features, such as coverage ratio, distinctive text, etc., have relatively high scores, then the list boot factor may be increased.
The patent tells us that this is because “the combination of these scores in the presence of a list is a strong signal of a high-quality answer passage.”
Adjustment of Featured Snippet Answers Scores
Answer scores for candidate answer passages are adjusted by scoring components based on heading vectors, passage coverage ratio, and other features described above.
The scoring process can select the largest boost value from those determined above or can select a combination of the boost values.
Once the answer scores are adjusted, the candidate answer passage with the highest adjusted answer score is selected as the featured snippet answer and is displayed to a searcher.
More to Come
I will be reviewing the first patent in this series of patents about candidate answer scores because it does have some additional elements to it that haven’t been covered in this post, and the post about query dependent/independent ranking signals for answer scores. If you have been paying attention to how Google has been answering queries that appear to be seeking answers, you have likely seen those improving in many cases. Some answers have been really bad though. It will be nice to have as complete an idea as we can of how Google decides what might be a good answer to a query, based on information available to them on the Web.
Added October 14, 2020 – I have written about another Google patent on Answer Scores, and it’s worth reading about all of the patents on this topic. The new post is at Weighted Answer Terms for Scoring Answer Passages, and is about the patent Weighted answer terms for scoring answer passages.
It is about identifying questions in resources, and answers for those questions, and describes using term weights as a way to score answer passages (along with the scoring approaches identified in the other related patents, including this one.)
Added October 15, 2020 – I have written a few other posts about answer passages that are worth reading if you are interested in how Google finds questions on pages and answers to those, and scores answer passages to determine which ones to show as featured snippets. I’ve linked to some of those in the body of this post, but here is another one of those posts:
- January 24, 2019 – Does Google Use Schema to Write Answer Passages for Featured Snippets?
Added October 22, 2020, I have written up a description of details from about how structured and unstructured data has been selected for answer passages based on specific criteria in the patent on Scoring Answer passages in the post Selecting Candidate Answer Passages.
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- A lot of debate has been going on as regards whether businesses should reduce or increase their marketing efforts. The conclusion is that reducing marketing will lead to a decline in sales.
- Out of all the many digital marketing channels available today, email marketing still proves to be the most effective as it gives the easiest and most direct access to the customer you want to reach.
- Is there anything about it that has remained effective in today’s business world?
- In this article, Toby Nwazor takes a critical look at four major things that made a difference in email marketing in 2020 like the use of predictive email marketing and what email marketers do to make sure their emails don’t land in the spam folder of their subscribers.
Since the outset of the pandemic, most businesses have constantly asked themselves whether to continue marketing the way they used to, reduce their efforts, scale-up, or stop. Stopping outrightly, however, is out of the question if you want to keep making sales and remain business. The best option is to re-strategize and discover how best to carry out your campaigns to suit the times.
So far, email marketing has remained one of the recession marketing channels that has proven to be reliable in spite of the uncertainty around us. Out of all the marketing channels, emails give you the easiest and most direct access to the customer you want to reach.
In this article, you’ll learn the best tactics that have been proven to work in 2020 which you can use to increase your reach and boost your sales using email marketing.
But first, a quick look at how email marketing was before now
Email marketers spent time creating emails that were relevant. To make this happen, they focused on sending personalized emails. In fact, Instapage reported that personalized email marketing generates a median ROI of 122 percent.
The use of personalized tags and list segmentation were some of the tools used to personalize emails while personalized email tactics like personalized messages tailored in accordance to customer data like their name, age, and location were used to give emails that personal touch.
Artificial intelligence (AI) made quite a notable appearance in 2019 and it was predicted to be used more in the years to come. Marketers have seen the wonders of AI when it comes to understanding email users, so it was only a matter of time before it became a household tool in email marketing.
The state of email marketing in 2020 so far
The good news is that the relevance of email marketing has shot through and remained at the roof with more people staying home since the outset of the pandemic. The 2020 predictions for email marketing have become more relevant than imagined.
Despite everything that was predicted, here are four things that really played a key role in 2020:
1. High-quality emails versus high volume of emails
This may seem counterintuitive especially at a time like this but the truth is that nothing beats high-quality emails. High-quality emails get read and are hardly ignored even if they are cold emails. Reducing the frequency of emails while increasing quality gives people something to look forward to. It feels like expecting a check in the mail.
Many companies focus on sending a high volume of emails every month. Some marketers believe you have to send an email every day. But according to research done by Hubspot, email open rates start to decline when the number of emails sent in a month gets beyond 16.
So instead of sending emails every day, you could choose to send a high-quality email every two to three days, and make sure that they are valuable to your subscribers. For instance, you could create a customer service email sequence for those who have made a purchase, or create a sales offer email that gives special discounts and coupons. And these will be different from the regular newsletter email sequence that your subscribers join when they land on your home page.
This has proven to in turn lead to higher opening rates as subscribers will be confident that they will get value out of every email, and the emails are specifically sent to meet their needs.
2. More personalized and optimized emails
Email marketers are becoming more conscious of the effectiveness of their emails. It’s no longer just about making sure that emails hit subscribers’ inboxes as when due. One strategy you must apply is personalization, as personalized emails have been reported to deliver six times higher transaction rates. So far, we have seen a heavier application of personalized emails, but this time with a higher reliance on automation to make this happen.
Automation allows marketers to leverage personalized touchpoints like the time when their subscribers are more likely to check their emails. Plus, automation makes the whole process of sending emails on those touchpoints more scalable. Retailers can now deliver more valuable and timely messages.
For instance, consider the issue of abandoned shopping carts, Fresh Relevance reported a 56.82% shopping cart abandonment rate in 2018. Email marketers tackled this problem in 2020 by sending automated emails to help trigger the fear of missing out (FOMO) in customers. A good example is the automated and personalized abandonment messages that BreadBrand sends to customers that abandoned their carts. See a screenshot below.
3. Whitelisting your emails out of the spam box
Email filters have never been as sophisticated as they are today, and if your emails end up in the spam box, it defeats your reason for sending the email in the first place. Many email providers, including Google, have heightened their spam protections by using AI to keep spam at bay.
In fact, Google incorporated Tensorflow in their spam filter in 2019 to enable Google to personalize spam protection for each Gmail user. Email marketers had to become more conscious of best email practices this year in order to avoid emails landing in spam.
One of the ways this is done is by whitelisting your emails. This is done by asking your customers to open the automated email they get immediately after subscription in order to get the lead magnet you sent and add you up. Or while sending them a “welcome email”, ask them to add your email address to their address books. When they do so, it ensures that subsequent emails from that address will get to their inbox and never the spam folder.
Ironically, from the screenshot below, this is very simple. Unfortunately, most marketers don’t do it.
Another way you can do this is to avoid the use of words that make emails look like spam. If your emails contain words like “rich”, “deal”, “prize”, “purchase”, “order”, and more. Many inboxes have been programmed to detect such words and automatically profile the emails as spam.
4. Use of predictive email marketing
Since email marketers have been using more AI-based applications this year, they have been able to write higher converting emails and subject lines. This was made possible this year through the use of predictive marketing.
Emails and subject line copy can now be guided by AI and machine learning so that better emails will be created with greater accuracy and in half the time. This means that email marketers will be able to work a lot smarter in their efforts to increase conversions and reduce the number of people who unsubscribe.
Although 2020 hasn’t looked as rosy as you thought it would, especially with the pandemic that hit us, a lot of progress has been made with email marketing. So many businesses have already bounced back, and the market is booming.
Adopting the already existing pointers above could result in a major change when it comes to increasing your reach, creating high-quality emails that are guaranteed to convert, and drastically reducing the number of people who unsubscribe.
Now that we have more people’s eyes checking their email, this is the best time to start investing more time and energy into email marketing.
Have any observations you would like to share with us? Feel free to drop a comment.
The post Email marketing in 2020: Four key things that made the difference appeared first on Search Engine Watch.
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