Monthly Archives: June 2018
Instagram’s meteoric rise continues, dwarfing the stagnant growth rates of Snapchat and Facebook. Today Instagram announced that it has reached 1 billion monthly active users, after passing 800 million in September 2017 with 500 million daily users.
That massive audience could be a powerful draw for IGTV, the longer-form video hub it’s launching for creators today. While IGTV monetization options are expected in the future, content makers may flock to it early just to get exposure and build their fan base.
While Snapchat’s daily user count grew just 2.13 percent in Q1 2018 to 191 million, and Facebook’s monthly count grew 3.14 percent to reach 2.196 billion, Instagram is growing closer to 5 percent per quarter.
Hitting the 1 billion user milestone could put pressure on Instagram to carry its weight in the Facebook family and bring home more cash. Facebook doesn’t break out Instagram’s revenue and has never given any guidance about it. But eMarketer estimates that Instagram will generate $ 5.48 billion in U.S. ad revenue in 2018, up 70 percent from last year. It reports that Instagram makes up 28.2 pecent of Facebook’s mobile ad revenue.
IGTV could open even more premium mobile ad inventory that traditional television advertisers crave, which helped push Facebook’s share price up more that 2.2 precent to $ 202.
The Instagram brand increasingly looks like Facebook’s life raft. Sentiment toward Facebook, especially amongst teens, has been in decline, and it’s constantly rocked by privacy scandals. But many users don’t even realize Facebook owns Instagram, and still love the photo-sharing app. With the 1 billion user badge, businesses and content creators may take the photo and video app even more seriously. Selling windows into your friends’ worlds is a lucrative business.
Drip Capital is raising a $ 20 million funding round from Accel, Wing VC and Sequoia India. The company is helping small exporters in emerging markets access working capital in order to finance big orders.
The startup also participated in Y Combinator back in 2015. Many small companies in emerging markets have to turn down orders because they can’t finance big orders. Even if you found a client in the U.S. or Europe, chances are companies will end up paying for your order a month or two after signing a contract.
If you’re an importer or an exporter, capital is arguably your most valuable resource. You know where to source your products and how to ship many goods. But you still need to buy goods yourself.
And in many emerging markets, you have to pay right away. It creates a sort of capital gap.
At the same time, local banks are often too slow and reject too many credit applications. Drip Capital thinks there’s an opportunity for a tech platform that finances exporters in no time.
The startup is first focusing on India because it meets many of the criteria I listed. This could be particularly useful for small and medium businesses. Large companies don’t necessarily face the same issues as they can access capital more easily.
So far, Drip Capital has funded more than $ 100 million of trade. After signing up to the platform, you can submit invoices and open a credit line to finance your next orders. Family offices and institutional investors can also invest some money in Drip Capital’s fund and get returns on investment.
This isn’t the only platform that helps you get paid faster. But larger companies tend to do it all and optimize the supply chain for the biggest companies in the world. Drip Capital is focusing on a specific vertical.
With today’s funding round, the company plans to get more customers and expand to other countries.
The case for testing Target ROAS bidding for AdWords shopping campaigns, plus tips on how to successfully set up such a test.
Read more at PPCHero.com
Since Google Hire launched last year it has been trying to make it easier for hiring managers to manage the data and tasks associated with the hiring process, while maybe tweaking LinkedIn while they’re at it. Today the company announced some AI-infused enhancements that they say will help save time and energy spent on manual processes.
“By incorporating Google AI, Hire now reduces repetitive, time-consuming tasks, like scheduling interviews into one-click interactions. This means hiring teams can spend less time with logistics and more time connecting with people,” Google’s Berit Hoffmann, Hire product manager wrote in a blog post announcing the new features.
The first piece involves making it easier and faster to schedule interviews with candidates. This is a multi-step activity that involves scheduling appropriate interviewers, choosing a time and date that works for all parties involved in the interview and scheduling a room in which to conduct the interview. Organizing these kind of logistics tend to eat up a lot of time.
“To streamline this process, Hire now uses AI to automatically suggest interviewers and ideal time slots, reducing interview scheduling to a few clicks,” Hoffmann wrote.
Another common hiring chore is finding keywords in a resume. Hire’s AI now finds these words for a recruiter automatically by analysing terms in a job description or search query and highlighting relevant words including synonyms and acronyms in a resume to save time spent manually searching for them.
Finally, another standard part of the hiring process is making phone calls, lots of phone calls. To make this easier, the latest version of Google Hire has a new click-to-call function. Simply click the phone number and it dials automatically and registers the call in call a log for easy recall or auditing.
While Microsoft has LinkedIn and Office 365, Google has G Suite and Google Hire. The strategy behind Hire is to allow hiring personnel to work in the G Suite tools they are immersed in every day and incorporate Hire functionality within those tools.
It’s not unlike CRM tools that integrate with Outlook or GMail because that’s where sales people spend a good deal of their time anyway. The idea is to reduce the time spent switching between tools and make the process a more integrated experience.
While none of these features individually will necessarily wow you, they are making use of Google AI to simplify common tasks to reduce some of the tedium associated with every-day hiring tasks.
The vast potential to create, interact and educate with augmented reality (AR) is quickly gaining popularity. In the past, AR gained media attention for simply existing, but recently, companies have been applying the strategy to their marketing campaigns and reaping the rewards.
As we move further into the digital world, the benefits of implementing AR are staggering. For instance, AR has an average dwell time of 75 seconds – affording companies an unprecedented chance to appeal to their consumers. Flow Digital, a Newcastle-based digital marketing company, are sharing why 2018 is the takeover of the media channel, and what it means for the future.
The statistics driving AR
In the past 2 years, the AR industry has experienced unprecedented growth. We can largely attribute the early success to the pioneers of AR, Pokémon Go which became the most downloaded app in 2016 with over 750 million to date.
By 2020, the number of AR users is expected to surpass one billion and by 2021, the market for AR, and VR, is estimated to reach $ 215bn. The benefits of implementing AR are reason enough in these statistics – particularly for ecommerce, marketing and automotive brands which are the industries that experience the largest growth with the communication tool.
Ikea Place demonstrated the potential for the natural partnership of AR and retail. Since launching in 2017 – using Apple’s ARKit tech – the Ikea Place has been downloaded two million times. The potential for allowing users to actually see what items look like in their home will significantly boost revenue.
Similarly, AR provides companies with the opportunity to target impulse shoppers. If you can showcase how their life can vastly improve with this cactus plant on their new coffee table (no doubt that it will), you can catch them before they even realised the need for such a product.
Estée Lauder recently rolled out AR into their marketing campaign – adopting the ‘try before you buy’ method. Users could ‘try’ various makeup products using their Facebook messenger chatbot, with the company experiencing a rise in social media engagement.
However, it’s important to note the limitations in an AR world for both ecommerce and marketing. While we can certainly appeal to more consumers and provide the ‘wow factor’ so many prospects look for, we must take into account the lack of adverts. Marketing ads and header bidding do not have a place in augmented reality, so companies will have to get creative.
Take the example of Pepsi, turning the average bus shelter into a fake window. Relying on a camera to capture people and vehicles in the street, they showcased images of crashing comets, a rogue cheetah and a man flying away while holding onto balloons. While it may not have been your ‘typical’ advertisement for the drink, the ad certainly proved engaging.
Future of video content
Video content has certainly seen a boom – particularly because of an increasing number of Facebook, Twitter, Snapchat and Instagram users. Today, there are more than 22m daily views on Facebook, Snapchat and YouTube, with the number continuing to grow.
360-degree views are universally appealing, enabling users to go behind-the-scenes with the brand. If there’s anything we can guarantee, it’s that consumers love a nosy. Typically, videos afford companies 2.5 seconds to catch the attention of their prospects. However, AR provides brands with an average of 75 seconds dwell time, offering a staggering amount of time to share relevant content.
We have touched on implementing AR above, and the reasons for doing so are almost endless. Essentially, you are bringing your products and services to life. A static digital advert becomes an interactive catalogue or brochure. In doing so, you are improving the experience of communicating with your brand, leaving more information at their disposal and helping them to make informed decisions. In return, you should see a substantial lift in consumers trusting your company, word-of-mouth sales and potentially ROI.
Social media will only benefit from AR. It’s likely that consumers will share their interactions with your brand on their social platforms – particularly with a specific hashtag – and thus build your following. There is also the opportunity for partnerships with social media platforms. For example, Fanta partnered with Snapchat for their Halloween campaign, offering users a unique Snapchat filter if they scan their limited edition cans.
In simple terms, using AR helps to build transparency. All successful relationships start with trust, and you can even take your customer behind-the-scenes with this communication channel. Share how the product was made, guide them through the delivery process and we can guarantee you will see an increase in interaction.
Partnership of AR and PR
There is a natural partnership between AR and the PR industry, for which we could see an increase in the use of the marketing channel for events. Something as small as including a QR code to your event invite – producing a unique illustration or even animated brand logo – creates a layer of interest. Similarly, product launches can experience the benefit. If you can take your audience into the augmented world, highlighting the key features of your product, you will likely see results. Perhaps, rather than share the product in detail, you could leave a trail of breadcrumbs. Each time a QR code is scanned, more is revealed about the product.
AR transforming other industries
Ecommerce and marketing are industries experiencing a boom due to AR, but the medical sector is also seeing the technological advancements. Go Surgery, the brainchild behind Touch Surgery, offers step-by-step guides to performing surgical procedures, as if in real time. The procedure is holographically projected onto a screen. Likewise, the Microsoft HoloLens AR glasses have been used to aid in reconstructive surgery.
One industry in particular which should reap the benefits from the rise of video content is hospitality. For example, guests can explore the rooms before booking and companies can even go so far as to allow guests to review the room when using the app. Likewise, restaurants can share the experience of dining with the through AR.
Companies, such as WayRay, are offering Navion, a system that directs you while you drive. Basically, it’s like Google Maps on the road, but you don’t have to keep looking at the Sat Nav. Navion shows exactly where you want to go, continually adjusting to anything in front of the car.
Ultimately, AR spells the dawn of a different age. Those companies that embrace and adapt will certainly see the rewards, especially when labelled pioneers of the channel.
Social planning apps are a dime a dozen, but none have risen to become a mainstay in our digital lives. IRL, founded by Abe Shafi and Scott Banister, is looking to break the pattern, focusing on positivity to get people excited about hanging out offline.
When users first sign up, they’re asked a series of multiple choice questions about their friends: “Who is the best at building pillow forts?” or “Who has the best style?” with four of your contacts as possible answers. These ‘nominations’ are meant to catalyze making plans with those friends. Those nominations stay anonymous.
From there, users can choose from a wide variety of interests like “Netflix and Chill,” “Grab Burgers,” or “Watch the World Cup.” Once they’ve chosen an interest, they can mark the time (today, soon, or pick a date) and send an invite to friends, at which point the group comes up with the right time and place for the plans.
According to cofounder and CEO Abe Shafi, the structure of IRL is meant to take the pressure off of any one person from being the ‘host.’
“We designed IRL so that people could send out lightweight invitations,” said Shafi. “We want people to be able to say ‘hey, I want to do something’ and send it out to a larger group of friends, letting people opt in and decide what they want to do. Creating a safe container that lets people opt in helps with social anxiety around making plans.”
This isn’t Shafi’s first go-round in the world of tech startups. Shafi sold his startup GetTalent to Dice in 2013. Shafi said that one of the difficulties in enterprise software was that he felt less and less connected to the problems he was solving, and knew that he felt at his best spending time with friends and family.
“I knew I didn’t want to participate in the distraction economy,” said Shafi. “More and more articles came out saying the healthiest thing you can do is spend time with people. I thought more about creating an app to help people get together, which in many ways is the white whale of consumer web.”
Gather did an incredibly poor job of notifying users when it was sending out texts to their friends and contacts to join the app. While social apps have a limited window to get people on the app with their friends, Gather’s approach was reckless and ended up backfiring.
“That was our biggest mistake,” said Shafi. “We had a lot of really bad UX and UI that didn’t make it clear at all when you were inviting someone to Gather whether they were on or off the app, and it made people really confused.”
Shafi says that he and the team have learned a lot from Gather, and have implemented much more clear notifications around when a button in the app might send a text to someone who isn’t already on the IRL app. For example, during onboarding when the app asks you to send out nominations, it’ll show a couple of people already on the app and a couple of people from your contacts that haven’t downloaded the app. Those who aren’t on IRL will have an asterisk next to their name with a note on the page saying that those with an asterisk will be sent a text.
Some people still don’t do a great job of reading the fine print, so there are still some users in the app’s review section expressing their displeasure. But IRL has done a much better job of clarifying any step or action that might initiate a text send to a contact off the app.
Today, IRL launches its Android app, which you can find in the Google Play store.
In Iran, secure messaging app Telegram effectively is the internet. The government has blocked it since April.
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In a search engine that answers questions based upon crawling and indexing facts found within structured data on a site, that search engine works differently than a search engine which looks at the words used in a query, and tries to return documents that contain the same words as the ones in the query; hoping that such a matching of strings might contain an actual answer to the informational need that inspired the query in the first place. Search using Structured Data works a little differently, as seen in this flowchart from a 2017 Google patent:
In Schema, Structured Data, and Scattered Databases such as the World Wide Web, I talked about the Dipre Algorithm in a patent from Sergey Brin, as I described in the post, Google’s First Semantic Search Invention was Patented in 1999. That patent and algorithm described how the web might be crawled to collect pattern and relations information about specific facts. In that case, about books. In the Google patent on structured data, we see how Google might look for factual information set out in semi-structured data such as JSON-LD, to be able to answer queries about facts, such as, “What is a book, by Ernest Hemingway, published in 1948-1952.
This newer patent tells us that it might solve that book search in this manner:
In particular, for each encoded data item associated with a given identified schema, the system searches the locations in the encoded data item identified by the schema as storing values for the specified keys to identify encoded data items that store values for the specified keys that satisfy the requirements specified in the query. For example, if the query is for semi-structured data items that have a value “Ernest Hemingway” for an “author” key and that have values in a range of “1948-1952” for a “year published” key, the system can identify encoded data items that store a value corresponding to “Ernest Hemingway” in the location identified in the schema associated with the encoded data item as storing the value for the “author” key and that store a value in the range from “1948-1952” in the location identified in the schema associated with the encoded data item as storing the value for the “year published” key. Thus, the system can identify encoded data items that satisfy the query efficiently, i.e., without searching encoded data items that do not include values for each key specified in the received query and without searching locations in the encoded data items that are not identified as storing values for the specified keys.
It was interesting seeing Google come out with a patent about searching semi-structured data which focused upon the use of JSON-LD. We see them providing an example of JSON on one of the Google Developer’s pages at: Introduction to Structured Data
As it tells us on that page:
This documentation describes which fields are required, recommended, or optional for structured data with special meaning to Google Search. Most Search structured data uses schema.org vocabulary, but you should rely on the documentation on developers.google.com as definitive for Google Search behavior, rather than the schema.org documentation. Attributes or objects not described here are not required by Google Search, even if marked as required by schema.org.
The page then points us to the Structured Data Testing Tool, to be used as you prepare pages for use with Structured Data. It also tells us that for checking on Structured Data after it has been set up, the Structured Data Report in Google Search Console can be helpful, and is what I usually look at when doing site audits.
The Schema.org website has had a lot of JSON-LD examples added to it, and it was interesting to see this patent focus upon it. As they tell us about it in the patent, it seems that they like it:
I’ve used the analogy of how XML sitemaps are machine-readable, compared to HTML Sitemaps, and that is how JSON-LD shows off facts in a machine-readable way on a site, as opposed to content that is in HTML format. As the patent tells us that is the purpose behind this patent:
In general, this specification describes techniques for extracting facts from collections of documents.
The patent discusses schemas that might be on a site, and key/value pairs that could be searched, and details about such a search of semi-structured data on a site:
The aspect further includes receiving a query for semi-structured data items, wherein the query specifies requirements for values for one or more keys; identifying schemas from the plurality of schemas that identify locations for values corresponding to each of the one or more keys; for each identified schema, searching the encoded data items associated with the schema to identify encoded data items that satisfy the query; and providing data identifying values from the encoded data items that satisfy the query in response to the query. Searching the encoded data items associated with the schema includes: searching, for each encoded data item associated with the schema, the locations in the encoded data item identified by the schema as storing values for the specified keys to identify whether the encoded data item stores values for the specified keys that satisfy the requirements specified in the query.
The patent providing details of the use of JSON-LD to provide a machine readable set of facts on a site can be found here:
Storing semi-structured data
Inventors: Martin Probst
Assignee: Google Inc.
US Patent: 9,754,048
Granted: September 5, 2017
Filed: October 6, 2014
Methods, systems, and apparatus, including computer programs encoded on computer storage media, for storing semi-structured data. One of the methods includes maintaining a plurality of schemas; receiving a first semi-structured data item; determining that the first semi-structured data item does not match any of the schemas in the plurality of schemas; and in response to determining that the first semi-structured data item does not match any of the schemas in the plurality of schemas: generating a new schema, encoding the first semi-structured data item in the first data format to generate the first new encoded data item in accordance with the new schema, storing the first new encoded data item in the data item repository, and associating the first new encoded data item with the new schema.
By using Structured Data such as in Schema Vocabulary in JSON-LD formatting, you make sure that you provide precise facts in key/value pairs that provide an alternative to the HTML-based content on the pages of a site. Make sure that you follow the Structured Data General Guidelines from Google when you add it to a site. That page tells us that pages that don’t follow the guidelines may not rank as highly, or may become ineligible for rich results appearing for them in Google SERPs.
And if you are optimizing a site for Google, it also helps to optimize the same site for Bing, and it is good to see that Bing seems to like JSON-LD too. It has taken a while for Bing to do that (see Aaron Bradle’s post, An Open Letter to Bing Regarding JSON-LD.) It appears that Bing has listened a little, adding some capacity to check on JSON-LD after it is deployed: Bing announces Bing AMP viewer & JSON-LD support in Bing Webmaster Tools. The Bing Markup Validator does not yet help with JSON-LD, but Bing Webmaster Tools now helps with debugging JSON-LD. I like using this Structured Data Linter myself.
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