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Monthly Archives: May 2020

Click Share Vs Impression Share – Which One Should You Care About?

May 31, 2020 No Comments

Which one does Google care about more? How to use demographics to decrease cost, increase click share, and be rewarded by Google.

Read more at PPCHero.com
PPC Hero


The data-driven approach to making backlink analysis decisions

May 31, 2020 No Comments

30-second summary:

  • The pandora’s box opened when the link building game got out of control at some point ultimately leading to lower-quality but better-linked pages on top of search results – and that’s when Google started taking counteractions.
  • Whether you or Google like it or not, backlinks remain the crucial part of Google’s algorithm, and consequently, backlink analysis remains the most important step to organic visibility.
  • However, everyone in our industry keeps facing the same question again and again: How to tell good links from the bad ones?
  • All of the SEOs working with sites with more than 20 pages and brands with more than $ 200 budget know that looking at each backlink is hardly possible.
  • Is there a data-driven approach to link building? Ann Smarty helps you create a data-driven backlink analysis strategy.

Backlink analysis has always been one of the toughest tasks of digital marketers and one SEOs have never really found an agreement upon.

And Google has never been really too helpful in ending that debate once and for all.

A quick look into the history of link building

A decade or so ago Google had told us to get other webmasters to link to our pages and even provided us with a tool – PageRank Toolbar – to measure the effectiveness of our link building efforts.

That’s when the Pandora box was opened and no one has been able to close it ever since.

The link building game got out of control at some point ultimately leading to lower-quality but better-linked pages on top of search results – and that’s when Google started taking counteractions.

Penguin updates and manual penalties followed discouraging the site owners from attempting to manipulate Google’s algorithms. “Get backlinks” in Google’s guidelines was revised into “Build high-quality content”, and “link building” acquired a “spammy tactic” connotation.

Yet, no matter how much Google is trying to push away the “link building” agenda, digital businesses are unable to put it aside. In fact, the more Google is fighting bad links, the more emphasis it puts on backlink analysis and acquisition services.

Whether you (or Google) like it or not, backlinks remain the crucial part of Google’s algorithm, and consequently, backlink analysis remains the most important step to organic visibility.

In fact, backlink analysis is helpful on both fronts:

  • Identifying and removing/disavowing low-quality links, those probably sending poor signals to Google, may trip a filter and revive previously earned high rankings.
  • Identifying high-quality link acquisition methods will improve rankings.

While the importance of backlink analysis is clear to everyone who is not living under the rock, everyone in our industry keeps facing the same question again and again: How to tell good links from the bad ones?

When you look at a backlink, you can mostly tell whether it is natural and helpful. But all of the SEOs working with sites with more than 20 pages and brands with more than $ 200 budget know that looking at each backlink is hardly possible.

There’s simply no business implications for “tell it when I see it” concept. So what to do?

Is there a data-driven approach to link building?

I was actually inspired to write this article by stumbling across this article on data-based decision making listing multiple benefits of using data over instincts when making business decisions.

Today, the top companies around the world use data to make decisions about their business. The reason they’re leading the way is that they’ve gained a strategic advantage over their rivals simply by shifting their focus to data rather than relying on business acumen alone. 

The question is, how does this apply to link building?

Simply put, link building and backlink acquisition are crucial for any business presence and visibility in organic search results. This means they fall under the “business decisions” category which means they are basically unthinkable without data to support them.

But while we recognize the importance behind data, which data can we use to make link building and link removal decisions.

Ever since Google’s toolbar PageRank has been deprecated, marketers have no reliable ways to automatically tell a good link from a bad link.

Or do they?

Focusing on a single source of data is dangerous

Lots of marketers are content to judge a link page quality by looking at one particular source, like Moz DA.

And if you have a hard time explaining to anyone why they shouldn’t rely on any particular number, let me make it very easy for you:

None of the current numbers assessing the authority of a web page or a quality of a particular backlink comes from Google.

Do you need a more convincing argument?

It should be clear to any business owner at this point: You cannot achieve success with one of the marketing channels by 100% relying on a third-party source.

Yet, good link building data exists

In fact, when we say don’t trust numbers when it comes to link building or analysis, we mean “no one source”.

Solid link building data exists and not using it means missing valuable growth opportunities.

The smartest link building approach is about learning to combine multiple data sources and learning to identify patterns (to embrace or avoid).

There are multiple backlink research sources including link-only ones (Majesting and Link Assistant) and multi-feature platforms (SEMrush and Ahrefs). There are also newer platforms that are entering the industry that are worth looking at. Serpstat is the most recent example that claims to include one trillion backlinks for 160 million domains:

This is how different two backlink databases can be: 50% on average.

Source: Serpstat

At Internet Marketing Ninjas, for every backlink we acquire, we pull a crazy amount of data, including:

  • Number of domains referencing a linking page (based on all of these: Ahrefs, SEMrush, Majestic, and Moz)
  • Number of links from Wikipedia pointing to that domain
  • Stats on the author assigned to the linking page (number of pages they authored, number of quotations from all over the web, and more)
  • Number of .gov and .edu links pointing to the linking page
  • How many other links that page has

Again, none of those stats is useful on its own but when looking at all of those numbers, you can be pretty confident of the value of that link.

To help you create your own data-driven link building decisions, here are a few helpful tools and resources:

  • Use multiple tools. I know it may be costly but some free or freemium alternatives may help. Many of these plugins, for example, are free and lots of them include the link analysis component.
  • It’s time we rethink how we measure influencers for SEO.

Conclusion

Backlink analysis is the most misunderstood task in our industry. You will see absolute extremes floating around: From experts solely relying on Mox DA to those denying the value of any number whatsoever.

Yet, the task cannot be successfully accomplished without accumulating and assessing data, so the answer is in embracing a holistic approach, that is, using a lot of data sources and making your decisions based on all of them.

Ann Smarty is the blogger and community manager at Internet Marketing Ninjas. She can be found on twitter @seosmarty.

The post The data-driven approach to making backlink analysis decisions appeared first on Search Engine Watch.

Search Engine Watch


COVID-19 has altered paid search: How marketers can adjust strategies

May 31, 2020 No Comments

30-second summary:

  • Since shelter-in-place rules were enacted, the way people use the internet has changed. They’re consuming more media and increasing web research and browsing. 
  • Paid search strategy is not one-size-fits-all. Each vertical must be treated differently, as some industries like ecommerce have seen improved performance while others have seen a declined performance. 
  • A pandemic is not the time to cut ad budget. Instead, investing in advertising now should pay dividends when the market normalizes. 
  • Ensure your ad copy is appropriate for the landscape. That means even going back to a campaign that started before the pandemic to update any language that isn’t applicable to the current landscape. 
  • Marketers must stay flexible and agile during this time and monitor what’s working or not working and creating a quick plan to adjust. 

When COVID-19 began spreading across the U.S., marketers scrambled to figure out how to respond. Sudden work-from-home mandates, cancelled business trips, postponed conferences and frozen budgets threw a wrench into usual expectations and plans. Users’ needs and online behaviours have changed in tandem, forcing marketers to meet them on their new terms.  

Search is more important than ever now because people are spending almost all of their time at home and online, consuming media, researching, browsing and shopping. According to Forbes, total internet hits have surged by 50% to 70% with people under lockdown, while 32% of people say they are spending longer on social media. Hours spent in non-gaming apps are up as people turn to TikTok, WhatsApp, Instagram and Twitter to keep entertained, connected and informed. To stay relevant in these turbulent times, it’s imperative that marketers maintain their paid search presence while adjusting to the needs of the moment.  

Vary strategy by vertical 

While no industry is immune from the impact of coronavirus, businesses are affected differently and should adapt their paid search strategies accordingly. Industries like B2B and ecommerce have seen improved performance, while industries like travel and healthcare have struggled with poor results.  

The fact that healthcare is struggling may seem paradoxical, given the overwhelming need for healthcare services right now. While hospitals are busy with COVID-19 patients, people who don’t have the virus are avoiding medical centres, hospitals, and non-essential medical services like bariatric surgery and physical therapy.

Users are shifting their searches for their healthcare needs. Notably, people under shelter-in-place orders are seeking to receive care while staying in their homes. eMarketer published data from CivicScience which found that between February and March 2020, the number of U.S. adults who reported intent to use telemedicine rose from 18% to 30%. As a result, healthcare providers have to switch their offerings – along with their messaging – to emphasize virtual and telehealth services. The same is true for many restaurants as they pivot to pick up or delivery only.  

The situation is different for B2B companies

The situation is different for B2B companies, which have longer sales cycles. While businesses like restaurants are worried about running out of money now, B2B companies are concerned about how they’ll fare months and, in some cases, years from now. The instinct may be to cut down on marketing budgets to save money, but extreme changes in paid search strategies can have long-lasting effects on performance. During this time, it’s important B2B companies continue filling the funnel and building brand awareness to alleviate large sales gaps that can occur later in the year.  

Financial service-related searches are surging

Financial service-related searches are surging right now as people explore their options for economic relief like loans. Many companies in this space are smartly increasing their ad spending and shifting the bulk of it toward campaigns that push their best performing service lines. The same is true for ecommerce companies, especially those that sell household products and cleaning supplies, loungewear, cooking equipment, workout gear and entertainment items like board games and puzzles. Shares of Hasbro, for instance, have soared. For these companies, the adjustment is less about the offerings and more about the messaging.  

Don’t stop advertising when times are tough 

There are universal principles for how to optimize paid search strategies that apply to marketers in every industry. The first is not to neglect paid search, even during difficult times. The World Federation of Advertisers (WFA) recently ran a survey which found 81% of large advertisers deferred planned ad campaigns and cutting budgets due to the coronavirus pandemic. Of those surveyed, 57% said they had decreased budgets greatly or somewhat due to the virus outbreak; however, cutting out advertising or marketing completely can make the road to recovery more challenging.  

Experts advise not to stop advertising during a downturn. Evidence from recent economic downturns like the 2008 housing crash show that companies come out stronger in the end if they continue investing in brand awareness. According to Google, “Even in categories where consumers have pulled back spending right now, creating a branding impact now will have a halo and pay dividends when the market normalizes. Research and historical examples of economic downturn have shown this to work.” It’s important to keep investing in your brand and branded keywords, regardless of industry. The last thing an organization wants is competitors monetizing on branded search results.  

Every cent counts these days. Not only is paid search cost-effective with a low barrier to entry, but it also enables companies to be extremely agile. A company can get a campaign up and running pretty quickly, run tests, collect data and easily alter the messaging as things change day-to-day. Marketers can also see the results of engagement, click-through rates and conversions in real time, so they know whether their investment is paying off. COVID-19 is an unprecedented situation, so testing and learning are critical during this volatile time in the market.  

Best practices for paid search 

For any marketer thinking about how to adjust during COVID-19, here are a few best practices for how to optimize paid search.

1. Pivot messaging

Messaging needs to be both accurate and appropriate for the current landscape. Confirm that messaging is updated with current business hours and offerings, and revise CTAs away from messages like “Visit in-store.”  

2. Keep an eye on the tone of messaging

Is your copy appropriate or empathetic? An ad for booking a vacation package could feel out-of-touch. Customers will be turned off by companies that seem like they are trying to profit or gain from the pandemic, so craft communication to focus more on brand identity and values. Businesses can also use marketing to let customers know how they are responding to the pandemic. A construction firm or ecommerce company could talk about safety practices for workers, for example.   

3. Adapt offerings to what your customers need

As mentioned above, healthcare companies are moving to telehealth, restaurants are moving to pick up, delivery and B2B companies are repurposing content planned for conferences into virtual webinars. Marketers should be connecting with customers virtually to let them know how you are supporting them.  

4. Adapt your strategy to your customers’ changing digital behaviour

During the quarantine, desktop usage has increased. Conversely, the rise of remote work conditions and people being less on-the-go has caused mobile search traffic to decline by nearly 25%. We’ve all become accustomed to a mobile-first world, but given the predominance of desktop, it’s especially important to ensure all search ads and landing pages are optimized for both mobile and desktop.

Move fast 

This pandemic has caused so much of what used to be normal out of the window. Whereas before, marketers might have used a multiphase process for developing campaigns that involved planning and back-and-forth and feedback, now they have to act fast to keep up with the rapidly changing world. Marketers need to craft campaigns that are affordable, cost-effective and agile – and that means paid search.  

As marketing and advertising professionals, we’re all trying to figure this out together as we go. There is no roadmap or rules, but there’s no doubt that staying flexible and using this time to connect with customers is a smart strategy.

 Brianna Desmet is Media specialist at digital and demand gen agency, R2i.

The post COVID-19 has altered paid search: How marketers can adjust strategies appeared first on Search Engine Watch.

Search Engine Watch


Job Search Engine Using Occupation Vectors

May 31, 2020 No Comments

I worked for the Courts of Delaware at Superior Court.

I started working there as the Assistant Criminal Deputy Prothonotary.

I changed positions after 7 years there, and I became a Mini/Micro Computer Network Administrator.

The Court used an old English title for that first position which meant that I supervised Court Clerks in the Criminal Department of the Court. In the second position, I never ever saw a mini/micro-computer but it was a much more technical position. I was reminded of those titles when writing this post.

What unusual job titles might you have held in the past?

A Job Search Engine Based on Occupation Vectors and a Job Identification Model

An Example of Job Search at Google:

job search example

For a two week period, Google was granted patents with the same name each of those 2 weeks. This is the first of the two patents during that period granted under the name “Search Engine.”

It is about a specific type of search engine. One that focuses upon a specific search vertical – A Job Search Engine.

The second patent granted under the name “Search Engine,” was one that focused upon indexing data related to applications on mobile devices. I wrote about it in the post A Native Application Vertical Search Engine at Google

The reason why I find it important to learn about and understand how these new “Search Engine” patents work is that they adopt some newer approaches to answering searches than some of the previous vertical search engines developed by Google. Understanding how they work may provide some ideas about how older searches at Google may have changed.

This Job Search Engine patent works with a job identification model to enhance job search by improving the quality of search results in response to a job search query.

We are told that the job identification model can identify relevant job postings that could otherwise go unnoticed by conventional algorithms due to inherent limitations of keyword-based searching. What implications does this have for organic search at Google that has focused upon keyword search?

This job search may use methods in addition to conventional keyword-based searching. It uses an identification model that can identify relevant job postings which include job titles that do not match the keywords of a received job search query.

So, the patent tells us that in a query using the words “Patent Guru,” the job identification model may identify postings related to a:

  • “Patent Attorney”
  • “Intellectual Property Attorney”
  • “Attorney”
  • the like

The method behind job searching may include (remember the word “vector.” It is one I am seeing from Google a lot lately):

  • Defining a vector vocabulary
  • Defining an occupation taxonomy includings multiple different occupations
  • Obtaining multiple labeled training data items, wherein each labeled training data item is associated with at least:
    • (i) a job title
    • (ii) an occupation
  • Generating an occupation vector which includes a feature weight for each respective term in the vector vocabulary
  • Associating each respective occupation vector with an occupation in the occupation taxonomy based on the occupation of the labeled training data item used to generate the occupation vector
  • Receiving a search query that includes a string related to a characteristic of one or more potential job opportunities, generating a first vector based on the received query
  • Determining, for each respective occupation of the multiple occupations in the occupation taxonomy, a confidence score that is indicative of whether the query vector is correctly classified in the respective occupation
  • Selecting the particular occupation that is associated with the highest confidence score
  • Obtaining one or more job postings using the selected occupation
  • Providing the obtained job postings in a set of search results in response to the search query

These operations may include:

  • Receiving a search query that includes a string related to a characteristic of one or more job opportunities
  • Generating, based on the query, a query vector that includes a feature weight for each respective term in a predetermined vector vocabulary
  • Determining, for each respective occupation of the multiple occupations in the occupation taxonomy, a confidence score that is indicative of whether the query vector is correctly classified in the respective occupation
  • Selecting the particular occupation that is associated with the highest confidence score
  • Obtaining one or more job postings using the selected occupation, and providing the obtained job postings in a set of search results in response to the search query
  • Feature Weights for Terms in Vector Vocabularies

    It sounds like Google is trying to understand job position titles and how they may be connected with each other, and developing a vector vocabulary, and build ontologies of related positions

    A feature weight may be based on:

    • A term frequency determined on a number of occurrences of each term in the job title of the training data item
    • An inverse occupation frequency that is determined based on a number of occupations in the occupation taxonomy where each respective term in the job title of the respective training data item is present.
    • An occupation derivative based on a density of each respective term in the job title of the respective training data item across each of the respective occupations in the occupation taxonomy
    • Both (i) a second value representing the inverse occupation frequency that is determined based, at least in part, on a number of occupations in the occupation taxonomy where each respective term in the job title of the respective training data item is present and (ii) a third value representing an occupation derivative that is based, at least in part, on a density of each respective term in the job title of the respective training data item across each of the respective occupations in the occupation taxonomy
    • A sum of (i) the second value representing the inverse occupation frequency, and (ii) one-third of the third value representing the occupation derivative

    The predetermined vector vocabulary may include terms that are present in training data items stored in a text corpus and terms that are not present in at least one training data item stored in the text corpus.

    This Job Search Engine Patent can be found at:

    Search engine
    Inventors: Ye Tian, Seyed Reza Mir Ghaderi, Xuejun Tao), Matthew Courtney, Pei-Chun Chen, and Christian Posse
    Assignee: Google LLC
    US Patent: 10,643,183
    Granted: May 5, 2020
    Filed: October 18, 2016

    Abstract

    Methods, systems, and apparatus, including computer programs encoded on storage devices, for performing a job opportunity search. In one aspect, a system includes a data processing apparatus, and a computer-readable storage device having stored thereon instructions that, when executed by the data processing apparatus, cause the data processing apparatus to perform operations.

    The operations include defining a vector vocabulary, defining an occupation taxonomy that includes multiple different occupations, obtaining multiple labeled training data items, wherein each labeled training data item is associated with at least (i) a job title, and (ii) an occupation, generating, for each of the respective labeled training data items, an occupation vector that includes a feature weight for each respective term in the vector vocabulary and associating each respective occupation vector with an occupation in the occupation taxonomy based on the occupation of the labeled training data item used to generate the occupation vector.

    The Job Identification Model

    Job identification model

    Job postings from many different sources may be related to one or more occupations.

    An occupation may include a particular category that encompasses one or more job titles that describe the same profession.

    Two or more of the obtained job postings may be related to the same, or substantially similar, occupation while using different terminology to describe a job title for each of the two or more particular job postings.

    Such differences in the terminology used to describe a particular job title of a job posting may arise for a variety of different reasons:

    • Different people from different employers draft each respective job posting
    • Unique job titles may be based on the culture of the employer’s company, the employer’s marketing strategy, or the like

    occupation taxonomy

    How an Job Identification Model May Work

    An example:

    1. At a first hair salon marketed as a rugged barbershop, advertises a job posting for a “barber”
    2. At a second hair salon marketed as a trendy beauty salon, advertises a job posting for a “stylist”
    3. At both, the job posting seeks a person for the occupation of a “hairdresser” who cuts and styles hair
    4. In a search system limited to keyword-based searching, a searcher seeking job opportunities for a “hairdresser” searchings for job opportunities using the term “barber” may not receive available job postings for a “stylist,” “hairdresser,” or the like if those job postings do not include the term “barber”
    5. The process in this patent uses a job identification model seeking to address this problem

    The job occupation model includes:

    • A classification unit
    • An occupation taxonomy

    The occupation taxonomy associates known job titles from existing job posts with one or more particular occupations.

    During training, the job identification model associates each occupation vector that was generated for an obtained job posting with an occupation in the occupation taxonomy.

    The classification unit may receive the search query and generate a query vector.

    The classification unit may access the occupation taxonomy and calculate, for each particular occupation in the occupation taxonomy, a confidence score that is indicative of the likelihood that the query vector is properly classified into each particular occupation of the multiple occupations in the occupation taxonomy.

    Then, the classification unit may select the occupation associated with the highest confidence score as the occupation that is related to the query vector and provide the selected occupation to the job identification model.

    An Example of a Search Under this Job Opportunities Search Engine:

    1. A searcher queries “Software Guru” into a search box
    2. The search query may be received by the job identification model
    3. The job identification model provides an input to the classification unit including the query
    4. The classification unit generates a query vector
    5. The classification unit analyzes the query vector in view of the one or more occupation vectors that were generated and associated with each particular occupation in the occupation taxonomy such as occupation vectors
    6. The classification unit may then determine that the query vector is associated with a particular occupation based on a calculated confidence score, and select the particular occupation
    7. The job identification model may receive the particular occupation from the classification unit
    8. Alternatively, or in addition, the output from the classification unit may include a confidence score that indicates the likelihood that the query vector is related to the occupation output by the occupation taxonomy
    9. The occupation output from the occupation taxonomy can be used to retrieve relevant job postings
    10. Specifically, given the output of a particular occupation, the job identification model can retrieve one or more job postings using a job posting index that stores references to job postings based on occupation type

    11. The references to job postings that were identified using the job posting index are returned to the user device
    12. The obtained references to job postings may be displayed on the graphical user interface
    13. The obtained references to job postings may be presented as search results and include references to job postings for a “Senior Programmer,” a “Software Engineer,” a “Software Ninja,” or the like
    14. The job postings included in the search results were determined to be responsive to the search query “Software Guru” based at least in part on the vector analysis of the query vector and one or more occupation vectors used to train the occupation taxonomy and not merely based on keyword searching alone

    Takeaways About this Job Search Engine

    In addition to the details about, the patent tells us how an occupation taxonomy may be trained, using training data. It also provides more details about the Job identification model. And then tells us about how a job search is performed using that job identification model.

    I mentioned above that this job search engine patent and the application search engine patent are using methods that we may see in other search verticals at Google. I have written about one approach that could be used in Organic search in the post Google Using Website Representation Vectors to Classify with Expertise and Authority

    Another one of those may involve image searching at Google. I’ve written about Google Image Search Labels Becoming More Semantic?

    I will be posting more soon about how Google Image search is using neural networks to categorize and cluster Images to return in search results.


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    Startups Weekly: Remote-first work will mean ‘globally fair compensation’

    May 31, 2020 No Comments

    Editor’s note: Get this free weekly recap of TechCrunch news that any startup can use by email every Saturday morning (7am PT). Subscribe here.

    Most tech companies base compensation on an employee’s local cost of living, in addition to their skills and responsibilities. The pandemic-era push to remote work seems to be reinforcing that — if you only skim the headlines. For example, Facebook said last week that it would be readjusting salaries for employees who have relocated away from the Bay Area.

    But Connie Loizos caught up with a few well-placed people who see something else happening. First, here’s Matt Mullenweg, CEO of Automattic (WordPress), which has been almost entirely remote for its long and successful history.

    “Long term, I think market forces and the mobility of talent will force employers to stop discriminating on the basis of geography for geographically agnostic roles,” he told Connie for TechCrunch

    Mullenweg went on to detail how the process was still complicated, and that his company did not yet have a universal approach. But ultimately, he thinks that for “moral and competitive reasons, companies will move toward globally fair compensation over time with roles that can be done from anywhere.”

    Connie also talked to Jon Holman, a tech recruiter who is living and breathing the new world, in a separate article for Extra Crunch. The market forces will ultimately favor talent, he concurs, and companies that want talent will pay according to what they can afford. “If a good AI or machine learning engineer is working elsewhere and demand for those skills still exceeds supply,” Holman explained, “and his or her company pays less than for the same job in Palo Alto, then that person is just going to jump to another company in his or her own geography.”

    Taking stock of the future of retail

    Our weekly staff survey for Extra Crunch is about retail — will it exist? how? A few of our staffers who cover related topics weighed in:

    • Natasha Mascarenhas says retailers will need to find new ways to sell aspirational products — and what was once cringe-worthy might now be considered innovative.

    • Devin Coldewey sees businesses adopting a slew of creative digital services to prepare for the future and empower them without Amazon’s platform.

    • Greg Kumparak thinks the delivery and curbside pickup trends will move from pandemic-essentials to everyday occurrences. He thinks that retailers will need to find new ways to appeal to consumers in a “shopping-by-proxy” world.

    • Lucas Matney views a revitalized interest in technology around the checkout process, as retailers look for ways to make the purchasing experience more seamless (and less high-touch).

    We also ran two investor surveys this week, with Matt Burns producing one on manufacturing and Megan Rose Dickey and Kirsten Korosec following up on their autonomous vehicles series.

    How to think about strategic investors (in a pandemic)

    Maybe you could use some more money, distribution and partnerships these days? Those are the eternal lures of corporate venture funding sources, but each strategic VC has a different mandate. Some are there to help the parent company, some are just there to make money… and some may be on thin ice themselves given the way that they get money to invest.

    If you’re taking a fresh look at getting strategic funding now, check out this set of overview articles from Bill Growney, a partner at top tech law firm Goodwin, and Scott Orn of Kruze Consulting. The first, for TechCrunch, goes over how corporate funds are typically structured (and motivated). The second, for Extra Crunch, covers questions for startup founders to anticipate and other recommendations for dealing with this type of VC.

    Calm chooses a more enlightened path to growth

    It is high times for meditation and “mindfulness” apps, as people look for ways to adjust to pandemic life. Sarah Perez, our resident app expert, took a look at a new app store analysis on TechCrunch, shredded some of the top-ranked companies for opportunistic marketing, and came away with a positive feeling about the global market leader.

    Calm, meanwhile, took a different approach. It launched a page of free resources, but instead focused on partnerships to expand free access to more users, while also growing its business. Earlier this month, nonprofit health system Kaiser Permanente announced it was making the Calm app’s Premium subscription free for its members, for example — the first health system to do so.

    The company’s decision to not pursue as many free giveaways meant it may have missed the easy boost from press coverage. However, it may be a better long-term strategy as it sets up Calm for distribution partnerships that could continue beyond the immediate COVID-19 crisis.

    Mindfulness pays. On that note, subscribers can read her excellent This Week In Apps report every Saturday over on Extra Crunch.

    Around TechCrunch

    TechCrunch’s Early Stage, Mobility and Space events will be virtual, too

    Win a Wild Card to compete in Startup Battlefield at Disrupt 2020

    Extra Crunch Live: Join Initialized’s Alexis Ohanian and Garry Tan for a live Q&A on Tuesday at 2pm EDT/11am PDT

    Join GGV’s Hans Tung and Jeff Richards for a live Q&A: June 4 at 3:30 pm EDT/12:30 pm PD

    Across the week

    TechCrunch

    AI can battle coronavirus, but privacy shouldn’t be a casualty

    Living and working in a worsening world

    How to upgrade your at-home videoconference setup: Lighting edition

    Equity Morning: Remote work startup fundings galore, plus a major court decision

    Extra Crunch

    API startups are so hot right now

    Investors say emerging multiverses are the future of entertainment

    Dear Sophie: Can I work in the US on a dependent spouse visa?

    Fintech regulations in Latin America could fuel growth or freeze out startups

    The secret to trustworthy data strategy

    #EquityPod

    From Natasha:

    Hello and welcome back to Equity, TechCrunch’s venture capital-focused podcast, where we unpack the numbers behind the headlines. This week’s show took a break from regularly scheduled programming. Our co-host Alex Wilhelm, who usually leads us through the show, was on some much-deserved vacation, so Danny Crichton and Natasha Mascarenhas took the reigns and invited Floodgate Capital’s Iris Choi to join in on the fun. It’s Choi’s fourth time being on the podcast, which officially makes her our most tenured guest yet (in case the accomplished investor needs another bullet point on her bio page).

    This week’s docket features scrappiness, a seed round and a Startup Battlefield alumnus.

    Here’s what we chewed through:

    • LeverEdge raised seed funding to get you and your friends a volume discount on student loans. Fintech has been booming for years now, and startups often crop up around the painful world of student loans. Yet this startup still caught our eye, and it has a little something to do with its choice to use collective bargaining power as its modus operandi.
    • Stackin’ raised a $ 12.6 million Series B for a text-messaging service that connects millennials to money tips, and eventually other fintech apps. According to CEO Scott Grimes, Stackin’ wants to be the “pipes that port people around fintech.” We get into if the world needs a fintech app marketplace and how it targets younger users.
    • D-ID, a Startup Battlefield alumnus, digitally de-identifies faces in videos and still images and just raised $ 13.5 million. We’re all worried about our privacy concerns, so the funding news was a refreshing change of pace from the usual headlines we see around surveillance. Now the company just needs to find a successful use case beyond the goodness in people’s hearts.
    • ByteDance, the Chinese parent company that owns TikTok, hit $ 3 billion in net profit last year, reports Bloomberg. TikTok also recently snagged former Disney executive Kevin Mayer for its CEO. This one, as you can expect, made for an interesting conversation around privacy and bandwidth. We even asked Choi to weigh in on Donald J. Trump’s recent tweet threatening to regulate social media companies, as Floodgate was an early angel investor in Twitter.
    • We ended with a roundtable of sorts on how the future of work will look and feel in our new world, from college campuses to offices. We get into the vulnerability that comes with being on Zoom, the ever-increasing stupidity of “manels” and how tech talent might be flocking to smaller cities but investors aren’t just yet.

    And that was the show! Thanks to our producer Chris Gates for helping us put this together, thanks to you all for listening in on this quirky episode and thanks to Iris Choi for always bringing a fresh, candid perspective. Talk next week.


    Startups – TechCrunch


    Mirantis releases its first major update to Docker Enterprise

    May 29, 2020 No Comments

    In a surprise move, Mirantis acquired Docker’s Enterprise platform business at the end of last year, and while Docker itself is refocusing on developers, Mirantis kept the Docker Enterprise name and product. Today, Mirantis is rolling out its first major update to Docker Enterprise with the release of version 3.1.

    For the most part, these updates are in line with what’s been happening in the container ecosystem in recent months. There’s support for Kubernetes 1.17 and improved support for Kubernetes on Windows (something the Kubernetes community has worked on quite a bit in the last year or so). Also new is Nvidia GPU integration in Docker Enterprise through a pre-installed device plugin, as well as support for Istio Ingress for Kubernetes and a new command-line tool for deploying clusters with the Docker Engine.

    In addition to the product updates, Mirantis is also launching three new support options for its customers that now give them the option to get 24×7 support for all support cases, for example, as well as enhanced SLAs for remote managed operations, designated customer success managers and proactive monitoring and alerting. With this, Mirantis is clearly building on its experience as a managed service provider.

    What’s maybe more interesting, though, is how this acquisition is playing out at Mirantis itself. Mirantis, after all, went through its fair share of ups and downs in recent years, from high-flying OpenStack platform to layoffs and everything in between.

    “Why we do this in the first place and why at some point I absolutely felt that I wanted to do this is because I felt that this would be a more compelling and interesting company to build, despite maybe some of the short-term challenges along the way, and that very much turned out to be true. It’s been fantastic,” Mirantis CEO and co-founder Adrian Ionel told me. “What we’ve seen since the acquisition, first of all, is that the customer base has been dramatically more loyal than people had thought, including ourselves.”

    Ionel admitted that he thought some users would defect because this is obviously a major change, at least from the customer’s point of view. “Of course we have done everything possible to have something for them that’s really compelling and we put out the new roadmap right away in December after the acquisition — and people bought into it at very large scale,” he said. With that, Mirantis retained more than 90% of the customer base and the vast majority of all of Docker Enterprise’s largest users.

    Ionel, who almost seemed a bit surprised by this, noted that this helped the company to turn in two “fantastic” quarters and was profitable in the last quarter, despite COVID-19.

    “We wanted to go into this acquisition with a sober assessment of risks because we wanted to make it work, we wanted to make it successful because we were well aware that a lot of acquisitions fail,” he explained. “We didn’t want to go into it with a hyper-optimistic approach in any way — and we didn’t — and maybe that’s one of the reasons why we are positively surprised.”

    He argues that the reason for the current success is that enterprises are doubling down on their container journeys and because they actually love the Docker Enterprise platform, like infrastructure independence, its developer focus, security features and ease of use. One thing many large customers asked for was better support for multi-cluster management at scale, which today’s update delivers.

    “Where we stand today, we have one product development team. We have one product roadmap. We are shipping a very big new release of Docker Enterprise. […] The field has been completely unified and operates as one salesforce, with record results. So things have been extremely busy, but good and exciting.”


    Enterprise – TechCrunch


    The perfect SEO recipe to survive COVID-19 and the May core update

    May 29, 2020 No Comments

    30-second summary:

    • The latest broad core algorithm update, called the May core update, is making headlines in the SEO world. 
    • It was launched early May, but all leading digital marketers and webmaster community agree that it’s one of the biggest Google algorithm updates.
    • Award-winning digital agency, MintTwist’s SEO Manager shares a bunch of tips to survive and thrive in light of the new Google update.

    The latest broad core algorithm update, called the May core update, is making headlines in the SEO world. It’s the second update of 2020, but the last one didn’t cause as big of an impact as this one.  

    It was launched early May, but all leading digital marketers and webmaster community agree that it’s one of the biggest Google algorithm updates.

    Research of SEMrush connects this update to change in search intent after the pandemic. Queries that were once intended for just information may now be looking for a service or product on search engines.  

    That’s why industries like Travel and Real Estate that were already suffering due to lockdown and restrictions were most affected by the May core update.  

    On the other hand, News, Sports, and Entertainment sites saw an increase in their traffic after the release of this update. Their online channels were already booming as people have more spare time during the lockdown and May core update gave it a boost. 

    Other leaders of the digital marketing world also shared their insights on this new update that wasn’t contrary to those of SEMrush and brought new information to light. His tests show that sites with the following issues faced up to 10% decrease in their traffic.

    • That don’t update old content 
    • Have thin content 
    • Have SEO errors like duplicate meta tags 

    Likewise, the websites that were wary of these issues experienced growth in their traffic 

    Google faced criticism from a lot of webmasters for rolling out an update during COVID-19 outbreakWhile digital marketers are offering their resources worth thousands of dollars free of cost, it released such an update to make these difficult times more difficult 

    Hundreds of Webmasters shared their experience with May core update on WebmasterWorld explaining why they might have suffered or survived.  

    While many messages show a negative response complaining about how their rankings have been destroyedsome reported a growth in their website traffic 

    An update this big takes time to fully roll out. That’s why some websites experienced a temporary fall but got back on their position after a while.  

    This reminds us that Google updates are not for penalties. They are just to ensure that all webmasters follow their exact guidelines. Only websites that fail to follow guidelines suffer consequences.  

    On the other hand, websites that have built a strong and clean SEO foundation always benefit from these updates.

    It means you can withstand these updates and, in fact, benefit from them. Now let’s get on to the SEO recipe to not just survive but use May core update to your advantage.  

    Follow EAT guidelines

    The only goal of search engine updates is to provide the best results when users search a query. Google has published comprehensive webmaster guidelines to show what it expects from a website. In order to ensure that all those guidelines are met and the user gets exactly what he expects, it keeps improving the search algorithm.  

    It has released several major updates over the past decade, but was there a specific reason behind May core update? Many asked and that’s how John MuellerSenior Webmaster Trends Analyst at Googleresponded.  

    Like always, they didn’t reveal how the update works and only shared some vague hints, and that was all we needed.  

    Mueller said everything we need to know is in the first official tweet about the May core update, which linked to its blog about Google’s core updates. 

    That blog post highlights two things: 

    • Focus on content 
    • Get to know the quality rater guidelines and E-A-T 

    Some of the most important Google algorithm updates like the Panda update in 2011, Pirate update in 2012, and Fred update in 2017 are more than enough to scrutinize the quality of content.  

    Next, Google wants us to focus on EATExpertise, Authoritativeness, and Trustworthiness. 

    • Does your content show expertise in your niche? You will simply feed rewritten content to the visitors without any value if you are not an expert of your niche.
    • Do you have an authoritative name? Reputation is a major ranking factor in SEO. People follow brands, and so does Google.
    • Do users and Google trust you? Trusted sites easily rank – Wikipedia and Forbes are the best examples. You will always find them in top ranks even if the page has thin content.

    Refresh old content

    It is believed that sites with outdated content saw up to 10% decrease in their traffic after the release of the May core updateSome researches showed that sites, where old content was regularly updated, saw an increase in their traffic.

    It was never a secret that Google prefers fresh content in its search engine results pages. Brian Dean listed the content freshness and magnitude of updates in his 210 Google ranking factors 

    Content losses its relevance as it gets olds. Users want the latest and accurate information that is not possible with outdated pages.  

    • They are unlikely to rank and they affect the ranking of your overall site.  
    • If a page is ranked on SERP, it may lose its position if it’s not up to date.  

    That’s why it’s suggested to either update or remove outdated pagesYou can ensure that almost every single one of your articles maintains top positions in SERPs for years by regularly updating content with fresh information, research, and surveys while removing unnecessary and outdated parts.  

    Build highquality links

    Many webmasters that suffered from May core update had lowquality backlinks. Low-quality links don’t necessarily mean comment spam or cheap directories.  

    Among many other characteristics of a bad linkit includes links from sites that are irrelevant, have low authority, or the content around link is not good enough.  

    Use of an irrelevant site, low authoritative site, or low-quality content as source are some of many characteristics that make a bad link. 

    You should try to get backlinks from ranked articles, preferably posted by niche relevant sites. One high-quality link is considered better than a hundred low-quality backlinks.  

    Furthermore, ensure that no penalised or bad site is linking to you even if you didn’t ask for it.  

    Private Blog Network (PBN) is also no longer a good strategy. You can randomize footprints all you want, but Google algorithm is smart enough to identify them, and it doesn’t go unpunished.  

    Publish long-form, unique content regularly 

    Google asks for in-depth content and covers every aspect of the topic. You don’t always have to write a twothousandword page although it is more likely to rank.  

    What you need to avoid is thin contentAutomatically generated, spun, duplicated or scraped content is classified as thin – in short, it has no value to offer to the user.  

    Websites with thin content also saw a decrease in their traffic and ranks as the May core update rolled out. 

    Some people use them as doorway pages, but they should never be left as they are on a site, either remove or update the pageEven John Mueller discussed this issue in one of his hangout videos and suggested to deindex thin content.

     

    You should update any page that has short content or doesn’t have a keyword focus; it will give you an edge even after this new update.

    Hopefully, these pointers will help you steer clear of the difficulties that the update could bring. Share your queries in the comments section. Bon appetite!

    Sergio Arboledas SEO Manager at MintTwist. He can be found on Twitter @sergi_seo.

    The post The perfect SEO recipe to survive COVID-19 and the May core update appeared first on Search Engine Watch.

    Search Engine Watch


    Five quick ways to speed up your ecommerce conversions

    May 29, 2020 No Comments

    30-second summary:

    • Many ecommerce stores struggle to boost conversions because 75% of people abandon the cart never to return.
    • Speeding up your ecommerce conversions seems hard, but it isn’t. Using scarcity, urgency, and exclusivity to influence your potential customers into buying can significantly improve your conversions.
    • Let’s have a look at five quick and lesser-known ways to speed up ecommerce conversions.

    The retail ecommerce revenues are predicted to grow to $ 4.88 trillion in 2021. But many ecommerce stores struggle to boost conversions because 75% of people abandon the cart never to return.  

    Fortunately, there are techniques to reduce cart abandonment and increase conversion rates. Let’s have a look at five quick and lesser-known ways to speed up ecommerce conversions.  

    1. Understand and fill the need gap – Scarcity, urgency, and exclusivity 

    Understanding scarcity, urgency, and exclusivity can be one of the best ways to influence your potential customers to make a purchase. 

    While the three terms are related to one another, the way they are implemented is different.  

    In scarcity, you inform customers that there are a limited number of items of a certain product left in the stock. And that you’re not sure when the product will be available next.   

    In urgency, you simply add a timer that says “order within the time limit to avail the offer”. Once the deadline is over, the customer won’t get additional benefits, such as a discount or free shipping.  

    Here are four ways to work around scarcity and urgency

    • Let customers know that the product is exclusive and is manufactured on small batches so they might miss a unique item by not buying it right away.  
    • Highlight that the offer ends in a few hours/days.  
    • Let shoppers know how much time is left before they miss same-day shipping.  
    • Indicate how many people have bought the product (and are viewing it in real-time) to indicate that the item is in demand. This will make buyers feel a greater urgency to purchase before it gets sold out.  

    In exclusivity, you reward the customer if they make a purchase within a set timeline. Sephora, for instance, promises a free exclusive gift to customers on their birthday month. When the customer purchases something either online or in-store, they are entitled to receive a birthday gift from the brand.  

    2. Reduce price shock

    Most of the people abandon carts during checkout because the extra costs, such as shipping and tax, are too high. To reduce cart abandonment and improve conversions, reduce price shock.  

    Is the shipping free? No. How much will it cost? Is there any tax associated with the purchase? Yes. How much will the customer have to pay?  

    Let your customers know all the other prices associated with the product upfront. Don’t just add these at the time of checkout. You will need to calculate the volumetric weight for each product to display an accurate shipping price. If you ship your products internationally, you will also need to know import fees for each country you’re exporting your products to.  

    You can reduce price shock by a couple of ways

    • Avoid increasing the product’s price at the last moment, that is, during checkout.  
    • Highlight shipping costs and taxes on the products page. If you can’t calculate taxes or shipping fees up front, add a disclaimer stating “shipping and tax will be calculated during checkout”.

    3. Allow guest checkout

    More than 26% of shoppers don’t complete their purchase because the checkout process was too long or complicated.  

    Having people register on your site is great, but it can negatively impact your conversion rate. Sometimes all a customer wants is to place the order as soon as possible.  

    You will have their name and email address when they complete the transaction anyway.  

    Major ecommerce sites offer guest checkouts to streamline their checkout process.  

    Apart from allowing customers to purchase without an account, they have also added the option to “create an account” on the checkout page.  

    If you are sceptical about completely eliminating the need for the registration to complete the purchase, you can test the option for a few days to see how guest checkout impacts your conversions.  

    4. Follow up on abandoned carts

    It is essential to follow up with customers who browsed products, added it to their cart, and left without completing the transaction. That way, you will be able to understand the reason for cart abandonment.  

    One of the best ways to follow up with potential customers is by sending emails to remind them that they have left something in their cart.  

    Around 45% of people open cart abandonment emails, 21% of them click on the link, and 50% of people end up buying something. 

    ThemeIsle, a sister site of CodeinWP, sent a series of three emails to users who abandoned their cart over a period of five days.  

    They changed the subject line every time and saw a surge in email clicks.  

    • After 60 minutes: Subject line “Forgot something? It looks like you have items in your cart”. 
      The result: 50% of emails were opened, out of which 21% received clicks. 
    • After 24 hours: Subject line “What’s that in your shopping cart?
      The result: 41% of emails were opened, out of which 3% received clicks.
       
    • After 5 days: Subject line “Are you sure? One last reminder about the items in your cart (including a 10% welcome discount).”
    • The result: 39% of emails were opened, out of which 8% received clicks.  

    When sending emails to potential customers, follow the best copywriting practices to increase the chances of conversion. Also, add the images of the products and offer incentives, such as a discount coupon or free shipping, to entice users into taking action.

    GoDaddy sent me an email when I saved a domain in my cart but didn’t purchase it. The email had a promo code offering 30% off on anything new for a limited time to tempt me into purchasing a domain immediately.  

    5. Highlight Your Return Policy 

    Many ecommerce stores don’t highlight their return and refund policy, but you should. More than 50% of customers read the return policy before buying from a website.  

    Customers want assurance from ecommerce stores that if the product isn’t as they expected, then they would get their money back. So, ensure that your return policy is clear and concise. It helps in building trust with your potential customers.   

    There are two ways to highlight your return policy: 

    • Adding it on the product’s page.  
    • By creating a separate landing page that contains everything you would like your customers to know about the return policy.  

    It would be great if you can leverage both ways. There is a limit to what you can include on the product’s page, so people who want to know more about the policy can visit the landing page.  

    Final thoughts

    Speeding up your ecommerce conversions seems hard, but it isn’t. Using scarcity, urgency, and exclusivity to influence your potential customers into buying can significantly improve your conversions.  

    Allow prospects to checkout without having to create an account to streamline their buying process. Show all the price (shipping, tax, and others) right on the product’s page to reduce price shock. Follow up on abandoned carts through email and highlight your return policy to build trust and confidence with customers.  

    The post Five quick ways to speed up your ecommerce conversions appeared first on Search Engine Watch.

    Search Engine Watch


    3 bearish takes on the current edtech boom

    May 29, 2020 No Comments

    Edtech is booming, but a short while ago, many companies in the category were struggling to break through as mainstream offerings. Now, it seems like everyone is clamoring to get into the next seed-stage startup that has the phrase “remote learning” on its About page.

    And so begins the normal cycle that occurs when a sector gets overheated — boom, bust and a reckoning. While we’re still in the early days of edtech’s revitalization, it isn’t a gold mine all around the world. Today, in the spirit of balance and history, I’ll present three bearish takes I’ve heard on edtech’s future.

    Quizlet’s CEO Matthew Glotzbach says that when students go back to school, the technology that “sticks” during this time of massive experimentation might not be bountiful.

    “I think the dividing line there will be there are companies that have been around, that are a little more entrenched, and have good financial runway and can probably survive this cycle,” he said. “They have credibility and will probably get picked [by schools].” The newer companies, he said, might get stuck with adoption because they are at a high degree of risk, and might be giving out free licenses beyond their financial runway right now.


    Startups – TechCrunch


    Audit Google Display Placements Like a Boss

    May 27, 2020 No Comments

    Understand the importance of being diligent on display campaign auditing to reduce wasted spend, gather quality data, and narrow down your target audiences.

    Read more at PPCHero.com
    PPC Hero


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