Botify has raised a $55 million Series C funding round led by InfraVia Growth with Bpifrance’s Large Venture fund also participating. The company has created a search engine optimization (SEO) platform so that your content is better indexed and appears more often in search results.
Existing investors Eurazeo and Ventech are also investing in the startup once again. Nicolas Herschtel from InfraVia and Antoine Izsak from Bpifrance will join the board of directors. Valuation has tripled since the company’s previous funding round.
While there are a ton of good and bad practices in the SEO industry, Botify defines itself as “white-hat company”. They respect the terms of services of search engines, they don’t scrape search results for insights, they don’t create shady backlinks on other websites.
“We’re going to optimize every step of the search funnel from first the quality of the website, how it is designed, how is the content going to be enriched with, etc.” co-founder and CEO Adrien Menard told me.
There are now three different components in the Botify product suite. The startup first released an analytics tool that gives you insights about your website. Basically, it lets you see how a crawler analyzes your site.
The company then released Botify Intelligence, which hands you a prioritized todo list of things you can do to improve your SEO strategy. And now, the company is also working on automation with Botify Activation. When Google’s search engine bot queries your site, Botify can take over and answer requests directly.
“We’re not trying to trick Google’s algorithm. We’re defining Botify as the interface between search engines and our clients’ websites. Search engines are going to access higher quality content. And it’s probably cheaper than with a normal process,” Menard said.
Companies aren’t necessarily using all three tools. They may start with analytics and take it from there. “You can use different products depending on the size of the company,” Menard said.
Over the past few years, Google has increased the number of ad slots on search results. It also promotes its own services, such as YouTube and Google Maps, before you can see the organic search results. I asked Adrien Menard whether that could be a concern for the future of Botify.
“I agree with you that we’re seeing more and more sections of the search results coming from first-party or paid results,” he said. “But the traffic generated by organic results is growing. It represents 30% of the traffic of the websites of our customers and this average is not decreasing.”
According to him, search keeps getting bigger and bigger. When you invest in search, you can see a clear return on investment when it comes to online sales, traffic, etc.
Right now, Botify has 500 customers, such as Expedia, L’Oréal, The New York Times, Groupon, Marriott, Condé Nast, Crate & Barrel, Fnac Darty, Vestiaire Collective and Farfetch.
With today’s funding round, the company wants to improve its automation capabilities, sign partnerships with more tech companies and increase its footprint with new offices in the Asia-Pacific region.
Google is launching a new version of its Chrome Beta browser today that’s introducing some fairly notable changes to its user interface and design. The browser will introduce an updated New Tab page, which will now include cards directing you back to past web search activities, instead of only a list of shortcuts to favorite websites. Other changes aim to make it easier to navigate search results and to highlight and share quotes from the web.
The New Tab page’s update will be one of the first changes Chrome beta users may notice.
The idea behind this design change is about getting you back quickly to past web activities without a need to dive into your browsing history to remember which sites you had been using for things like recipes or shopping. It can also help you to return quickly to your recent documents list in Google Drive, in a handy bit of cross-promotion for Google services.
Image Credits: Google
The page will now feature what Google is calling “cards,” not just links, which could direct you to things like a recently visited recipe site where you had been browsing for ideas, a Google doc you need to finish editing, or a retailer’s website where you had left your shopping cart filled with things you may like to purchase at a later date. The latter ties into Google’s larger investment in online shopping, which has already seen the search giant trying to grab more market share in the space by making product listings free and partnering with e-commerce platforms like Shopify.
Google is rightly concerned about Amazon’s surging advertising business, which is a large part of the retailer’s “Other” category that grew 87% year-over-year to generate $7.9 billion in the second quarter. Now, it’s capitalizing on Chrome’s New Tab real estate to elevate shopping activity in the hopes of pushing users to complete their transactions.
Another change aims to make it easier to do web research. Google says that often, users searching for something on its platform will navigate to multiple web pages to find their answer. The new version of Chrome will experiment with a different way of connecting users to their search results by adding a row beneath the address bar on Chrome for Android that will show the rest of the results so you can navigate to other web pages without needing to hit the back button.
Image Credits: Google
A new “quote cards” experiment, also coming to Chrome Beta on Android, will allow users to create a stylized image for social sharing that features text found on websites. Taking a screengrab of a website’s text is something that’s already a common activity, and particularly for people who want to share a key point from a news article they’re reading with followers on platforms like Twitter, Facebook or Instagram. With this new feature, you’ll be able to long-press text to highlight it, then tap Share and select a template by tapping on the “Create Card” option from the menu.
All features are a part of the Chrome Beta browser. To enable experiments, you can type chrome://flags into the browser’s address bar or click on the Experiments beaker icon, and then enable the flags. The associated flags for these experiments are #ntp-modules flag (New Tab page), #continuous-search (search results changes) and #webnotes-stylize flag (quote cards).
Experiments don’t necessarily become Chrome features that roll out more broadly. Instead, they offer Google a way to capture large-scale user feedback about its new design ideas, so the features can be tweaked and fine-tuned before a public release.
I’m a native French data scientist who cut his teeth as a research engineer in computer vision in Japan and later in my home country. Yet I’m writing from an unlikely computer vision hub: Stuttgart, Germany.
But I’m not working on German car technology, as one would expect. Instead, I found an incredible opportunity mid-pandemic in one of the most unexpected places: An ecommerce-focused, AI-driven, image-editing startup in Stuttgart focused on automating the digital imaging process across all retail products.
My experience in Japan taught me the difficulty of moving to a foreign country for work. In Japan, having a point of entry with a professional network can often be necessary. However, Europe has an advantage here thanks to its many accessible cities. Cities like Paris, London, and Berlin often offer diverse job opportunities while being known as hubs for some specialties.
While there has been an uptick in fully remote jobs thanks to the pandemic, extending the scope of your job search will provide more opportunities that match your interest.
I’m working at the technology spin-off of a luxury retailer, applying my expertise to product images. Approaching it from a data scientist’s point of view, I immediately recognized the value of a novel application for a very large and established industry like retail.
Europe has some of the most storied retail brands in the world — especially for apparel and footwear. That rich experience provides an opportunity to work with billions of products and trillions of dollars in revenue that imaging technology can be applied to. The advantage of retail companies is a constant flow of images to process that provides a playing ground to generate revenue and possibly make an AI company profitable.
Another potential avenue to explore are independent divisions typically within an R&D department. I found a significant number of AI startups working on a segment that isn’t profitable, simply due to the cost of research and the resulting revenue from very niche clients.
I was particularly attracted to this startup because of the potential access to data. Data by itself is quite expensive and a number of companies end up working with a finite set. Look for companies that directly engage at the B2B or B2C level, especially retail or digital platforms that affect front-end user interface.
Leveraging such customer engagement data benefits everyone. You can apply it towards further research and development on other solutions within the category, and your company can then work with other verticals on solving their pain points.
It also means there’s massive potential for revenue gains the more cross-segments of an audience the brand affects. My advice is to look for companies with data already stored in a manageable system for easy access. Such a system will be beneficial for research and development.
The challenge is that many companies haven’t yet introduced such a system, or they don’t have someone with the skills to properly utilize it. If you finding a company isn’t willing to share deep insights during the courtship process or they haven’t implemented it, look at the opportunity to introduce such data-focused offerings.
I have a sweet spot for early-stage companies that give you the opportunity to create processes and core systems. The company I work for was still in its early days when I started, and it was working towards creating scalable technology for a specific industry. The questions that the team was tasked with solving were already being solved, but there were numerous processes that still had to be put into place to solve a myriad of other issues.
Our year-long efforts to automate bulk image editing taught me that as long as the AI you’re building learns to run independently across multiple variables simultaneously (multiple images and workflows), you’re developing a technology that does what established brands haven’t been able to do. In Europe, there are very few companies doing this and they are hungry for talent who can.
So don’t be afraid of a little culture shock and take the leap.
Just days after Elastic announced the acquisition of build.security, the company is making yet another security acquisition. As part of its second-quarter earnings announcement this afternoon, Elastic disclosed that it is acquiring Vancouver, Canada based security vendor CMD. Financial terms of the deal are not being publicly disclosed.
CMD‘s technology provides runtime security for cloud infrastructure, helping organizations gain better visibility into processes that are running. The startup was founded in 2016 and has raised $21.6 million in funding to date. The company’s last round was a $15 million Series B that was announced in 2019, led by GV.
Elastic CEO and co-founder Shay Banon told TechCrunch that his company will be welcoming the employees of CMD into his company, but did not disclose precisely how many would be coming over. CMD CEO and co-founder Santosh Krishan and his fellow co-founder Jake King will both be taking executive roles within Elastic.
Both build.security and CMD are set to become part of Elastic’s security organization. The two technologies will be integrated into the Elastic Stack platform that provides visibility into what an organization is running, as well as security insights to help limit risk. Elastic has been steadily growing its security capabilities in recent years, acquiring Endgame Security in 2019 for $234 million.
Banon explained that, as organizations increasingly move to the cloud and make use of Kubernetes, they are looking for more layers of introspection and protection for Linux. That’s where CMD’s technology comes in. CMD’s security service is built with an open source technology known as eBPF. With eBPF, it’s possible to hook into a Linux operating system for visibility and security control. Work is currently ongoing to extend eBPF for Windows workloads, as well.
CMD isn’t the only startup that has been building based on eBP. Isovalent, which announced a $29 million Series A round led by Andreessen Horowitz and Google in November 2020, is also active in the space. The Linux Foundation also recently announced the creation of an eBPF Foundation, with the participation of Facebook, Google, Microsoft, Netflix and Isovalent.
Fundamentally, Banon sees a clear alignment between what CMD was building and what Elastic aims to deliver for its users.
“We have a saying at Elastic – while you observe, why not protect?” Banon said. “With CMD if you look at everything that they do, they also have this deep passion and belief that it starts with observability. “
It will take time for Elastic to integrate the CMD technology into the Elastic Stack, though it won’t be too long. Banon noted that one of the benefits of acquiring a startup is that it’s often easier to integrate than a larger, more established vendor.
“With all of these acquisitions that we make we spend time integrating them into a single product line,” Banon said.
That means Elastic needs to take the technology that other companies have built and fold it into its stack and that sometimes can take time, Banon explained. He noted that it took two years to integrate the Endgame technology after that acquisition.
“Typically that lends itself to us joining forces with smaller companies with really innovative technology that can be more easily taken and integrated into our stack,” Banon said.
Less than a year after raising its $6 million seed funding round, Tel Aviv and Sunnyvale-based startup Build.security is being acquired by Elastic. Financial terms of the deal are not being publicly disclosed at this time. The deal is expected to close in Elastic’s Q2 FY22, ending Oct. 31, 2021.
In an email to TechCrunch, Ash Kulkarni, chief product officer at Elastic, said that once the acquisition closes, the build.security technical team will continue as a unit in the Elastic Security organization. Kulkarni added that the acquisition will also become the foundation for a growing Elastic presence in Israel, with Amit Kanfer, co-founder and CEO of build.security set to become the site lead for the region.
Build.security is focused on security policy management for applications. A core element of the company’s technology approach is the Open Policy Agent (OPA) open source project, which is part of the Cloud Native Computing Foundation (CNCF), which is also home to Kubernetes. OPA was originally started by startup Styra, which itself has raised $40 million in funding to help build out policy management and authorization technology. Part of OPA is the Rego query language which is used to structure security and authorization configuration policies.
“We see policy as a fundamental cornerstone of security,” Kulkarni said. “OPA and Rego provide an open, standards-based way to define, manage, and enforce policies everywhere.”
Kulkarni noted that security policy technology is complementary to Elastic’s efforts in security and observability. He added that Elastic sees potential for using OPA and the technology that build.security has built on top of OPA to power deployment time, and in the future, build-time security for cloud-native environments.
YL Venture partner John Brennan who helped to lead the seed round of build.security sees the acquisition as being a good fit for both companies, as they are both creating solutions for developers that are based on open source technologies.
“This move by a market leader like Elastic validates the need for transformation in the authorization space,” Brennan said. “This partnership will accelerate build.security’s shift left vision of efficiently embedding access protection from the start, rather than trying to bolt it on after the fact or, worse, ignoring it completely.”
Elastic is known for its Elastic Stack, which provides Elasticsearch search capability, Logstash log monitoring and Kibana data visualization. In recent years the company has expanded into the security space, acquiring Endgame Security in 2019 for $234 million. On Aug. 3, Elastic announced its Limitless XDR capabilities which brings together endpoint security with security information and event management (SIEM).
With its new acquisition, Kulkarni said the goal is to go even deeper into security moving toward cloud security enforcement. He explained that after the acquisition closes and as the technology is integrated, users will be able to leverage the Elastic Stack to visualize and manage compliance policies and policy decisions at scale. An initial use-case for the build.security technology will be developing a Kubernetes security and compliance product based on OPA.
Around 15% of website traffic comes through paid search ads. But to turn passive searchers into active shoppers, your ads should answer their question and entice them to click.
We’ve tested thousands of paid search ads at Demand Curve and through our agency Bell Curve. This post breaks down 14 questions your paid search ads should answer to ensure you’re only paying for the highest-intent shoppers.
An important distinction between paid search and organic search is that paid ads are an interruption. Users of search engines are simply looking for an answer to their question. The people who see your ads don’t owe you anything. Just because you’re paying to have your ad show up first doesn’t mean they’re going to pay attention to it.
To generate genuine interest in your paid ads, reframe your offer as a favor.
You can do this in two ways:
For example, reframing free delivery as an extra convenience makes the offer that much more attractive.
Use ad extensions by listing additional benefits in the description of the page. For example, including “customized plans” in the pricing extension page signals to your customer that they’ll have control over the cost. This will help to attract the curiosity of even the most cost-conscious buyers.
Image Credits: Demand Curve
Approximately 80% of e-commerce shopping carts are abandoned, mostly because shoppers don’t feel any urgency to complete the transaction. Online shoppers aren’t in any rush, as the internet is open 24/7 and inventory feels unlimited.
Use ad copy that bridges the gap between their problem and your solution. The easiest way to create that curiosity bridge is by asking a question.
To answer the question, “Why should I buy now?”, you’re going to have to create an incentive to get them to take action now.
The President’s Council of Advisors on Science and Technology predicts that U.S. companies will spend upward of $100 billion on AI R&D per year by 2025. Much of this spending today is done by six tech companies — Microsoft, Google, Amazon, IBM, Facebook and Apple, according to a recent study from CSET at Georgetown University. But what if you’re a startup whose product relies on AI at its core?
Can early-stage companies support a research-based workflow? At a startup or scaleup, the focus is often more on concrete product development than research. For obvious reasons, companies want to make things that matter to their customers, investors and stakeholders. Ideally, there’s a way to do both.
Before investing in staffing an AI research lab, consider this advice to determine whether you’re ready to get started.
Assuming it’s your organization’s priority to do innovative AI research, the first step is to hire one or two researchers. At Unbabel, we did this early by hiring Ph.D.s and getting started quickly with research for a product that hadn’t been developed yet. Some researchers will build from scratch and others will take your data and try to find a pre-existing model that fits your needs.
While Google’s X division may have the capital to focus on moonshots, most startups can only invest in innovation that provides them a competitive advantage or improves their product.
From there, you’ll need to hire research engineers or machine learning operations professionals. Research is only a small part of using AI in production. Research engineers will then release your research into production, monitor your model’s results and refine the model if it stops predicting well (or otherwise is not operating as planned). Often they’ll use automation to simplify monitoring and deployment procedures as opposed to doing everything manually.
None of this falls within the scope of a research scientist — they’re most used to working with the data sets and models in training. That said, researchers and engineers will need to work together in a continuous feedback loop to refine and retrain models based on actual performance in inference.
The CSET research cited above shows that 85% of AI labs in North America and Europe do some form of basic AI research, and less than 15% focus on development. The rest of the world is different: A majority of labs in other countries, such as India and Israel, focus on development.
It’s often said in baseball that a prospect has a high ceiling, reflecting the tremendous potential of a young player with plenty of room to get better. The same could be said for the cloud infrastructure market, which just keeps growing with little sign of slowing down any time soon. The market hit $42 billion in total revenue with all major vendors reporting, up $2 billion from Q1.
Synergy Research reports that the revenue grew at a speedy 39% clip, the fourth consecutive quarter that it has increased. AWS led the way per usual, but Microsoft continued growing at a rapid pace and Google also kept the momentum going.
AWS continues to defy market logic, actually increasing growth by 5% over the previous quarter at 37%, an amazing feat for a company with the market maturity of AWS. That accounted for $14.81 billion in revenue for Amazon’s cloud division, putting it close to a $60 billion run rate, good for a market leading 33% share. While that share has remained fairly steady for a number of years, the revenue continues to grow as the market pie grows ever larger.
Microsoft grew even faster at 51%, and while Microsoft cloud infrastructure data isn’t always easy to nail down, with 20% of market share according to Synergy Research, that puts it at $8.4 billion as it continues to push upward with revenue up from $7.8 billion last quarter.
Google too continued its slow and steady progress under the leadership of Thomas Kurian, leading the growth numbers with a 54% increase in cloud revenue in Q2 on revenue of $4.2 billion, good for 10% market share, the first time Google Cloud has reached double figures in Synergy’s quarterly tracking data. That’s up from $3.5 billion last quarter.
Image Credits: Synergy Research
After the Big 3, Alibaba held steady over Q1 at 6% (but will only report this week) with IBM falling a point from Q1 to 4% as Big Blue continues to struggle in pure infrastructure as it makes the transition to more of a hybrid cloud management player.
John Dinsdale, chief analyst at Synergy, says that the big three are spending big to help fuel this growth. “Amazon, Microsoft and Google in aggregate are typically investing over $25 billion in capex per quarter, much of which is going towards building and equipping their fleet of over 340 hyperscale data centers,” he said in a statement.
Meanwhile Canalys had similar numbers, but saw the overall market slightly higher at $47 billion. Their market share broke down to Amazon with 31%, Microsoft with 22% and Google with 8% of that total number.
Canalys analyst Blake Murray says that part of the reason companies are shifting workloads to the clouds is to help achieve environmental sustainability goals as the cloud vendors are working toward using more renewable energy to run their massive data centers.
“The best practices and technology utilized by these companies will filter to the rest of the industry, while customers will increasingly use cloud services to relieve some of their environmental responsibilities and meet sustainability goals,” Murray said in a statement.
Regardless of whether companies are moving to the cloud to get out of the data center business or because they hope to piggyback on the sustainability efforts of the big 3, companies are continuing a steady march to the cloud. With some estimates of worldwide cloud usage at around 25%, the potential for continued growth remains strong, especially with many markets still untapped outside the U.S.
That bodes well for the big three and for other smaller operators who can find a way to tap into slices of market share that add up to big revenue. “There remains a wealth of opportunity for smaller, more focused cloud providers, but it can be hard to look away from the eye-popping numbers coming out of the big three,” Dinsdale said.
In fact, it’s hard to see the ceiling for these companies any time in the foreseeable future.
It’s hard to argue that any technology company has had a greater impact in the past decade than BioNTech, the mRNA-based therapeutics pioneer behind the world’s most widely-used COVID-19 vaccine. Developed in record time in partnership with Pfizer, thanks to an existing partnership to work on immunization for the common flu, BioNTech’s mRNA inoculation is without a doubt one of the biggest medical innovations of the past century.
BioNTech co-founder and CEO Uğur Şahin isn’t stopping there, of course: the company recently announced that it would be developing an mRNA-based vaccine targeting malaria, an illness that still kills more than 400,000 people per year. It also has treatments for a range of cancers in process in its development pipeline, and has announced plans to address HIV and tuberculosis with future candidates.
This year at Disrupt 2021, Şahin will join us along with Mayfield Fund Partner Ursheet Parikh, a key investor in BioNTech. Both Şahin and Parikh will be talking to us about how the COVID-19 vaccine came to be, but more importantly, about what the future holds for mRNA technology and its potential to address a wide range of chronic healthcare problems that have been tough challenges to solve for decades or even centuries. We’ll also be talking about what it means to build a biotech startup with true platform potential, and how that might differ now as compared to what investors were looking for just a few short years ago.
Şahin and Parikh are just two of the many high-profile speakers who will be on our Disrupt Stage and the Extra Crunch Stage. During the three-day event, writer, director, actor and Houseplant co-founder Seth Rogen will be joined by Houseplant Chief Commercial Officer Haneen Davies and co-founder and CEO Michael Mohr to talk about the business of weed, Secretary of Transportation Pete Buttigieg will talk about the future of getting around and the government’s role in partnering with startups, and Coinbase CEO Brian Armstrong will dig into the volatile world of cryptocurrency and his company’s massive direct listing earlier this year.
Disrupt 2021 wouldn’t be complete without Startup Battlefield, the competition that launched some of the world’s biggest tech companies, including Cloudflare and Dropbox. Join Secretary Buttigieg and over 10,000 of the startup world’s most influential people at Disrupt 2021 online this September 21-23. Check out the Disrupt 2021 agenda. We’ll add even more speakers.
Buy your Disrupt pass before July 30 at 11:59 pm (PT), and get ready to join the big, bold and influential — for less than $100.
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As we move toward a privacy-centric, less targeted future of growth marketing, the biggest lever will become creative on paid social channels such as the Facebooks of the world. The loss of attribution from our good friend iOS 14.5 has accelerated this trend, but channels have increasingly placed efforts toward automating their ad platforms.
Due to this, I believe that every growth marketing engine should have a proper creative testing framework in place — be it a seed-stage startup or a behemoth like Google.
After three years at Postmates, consulting for various startups, and most recently at Uber, I’ve seen the landscape of marketing change in a multitude of ways. However, what we’re seeing now is being orchestrated by factors out of our control, causing a dawn of shifts unlike anything I’ve seen. Creative has subsequently risen to become the most powerful lever in a paid social account.
If you’re looking to leverage the power of creative and succeed with paid social marketing, you’re thinking right. What you need is a creative testing framework: A structured and consistent way to test new creative assets.
Here’s a breakdown of the pieces a creative testing framework needs to be successful:
Creative has become the most powerful lever in a paid social account.
Testing creative should be a constant and iterative process that follows a defined testing schedule. A goal and structure can be as simple as testing five new creative assets per week. Inversely, it can be as complex as testing 60 new assets consisting of multiple themes and copy variations.
For a lower spending account, the creative testing should be leaner due to limited event signal and vice versa with a higher spending account. The most important aspect is that the testing continues to move the needle as you search for your next “champion” asset.
4 themes x 3 variants per theme x 5 copy variations = 60 assets. Image Credits: Jonathan Martinez
After setting a testing schedule, define the core themes of your business and vertical rather than testing a plethora of random ideas. This applies to the creative asset as well as the copy and what the key value props are to your product or service. As you start to analyze the creative data, you’ll find it easier to decide what to double down on or cut from testing with this structure. Think of this as a wireframe that you either expand or trim throughout testing sprints.
For a fitness app like MyFitnessPal, it can be structured as follows:
It’s vital to make sure you have a channel-specific approach, as each one will differ in creative best practices along with testing capabilities. What works on Facebook may not work on Snapchat or the numerous other paid social channels. Don’t be discouraged if creative between channels perform differently, although I do recommend parity testing. If you already have the creative asset for one channel, it doesn’t hurt to resize and format for the remaining channels.
Equally important to the creative is proper event selection and a statistically significant threshold to abide by throughout all testing. When selecting an event to use for creative testing, it’s not always possible to use your north-star metric depending on how high your CACs are. For example, if you’re selling a high-ticket item and the CACs are in the hundreds, it would take an enormous amount of spend to reach stat-sig on each creative asset. Instead, pick an event that’s more upper funnel and a strong indicator of a user’s likelihood of converting.
Using a more upper-funnel event leads to faster learnings (blue line). Image Credits: Jonathan Martinez
It’s important to select a percentage that stays consistent across all creative testing when deciding on which statistically significant percentage to use. As a rule of thumb, I like to use a certainty of 80%+, because it allows for enough confirmation along with the ability to make quicker decisions. A great (and free) online calculator is Neil Patel’s A/B Testing Significance Calculator.
You’re scrolling through a social feed, a sleek gold pendant catches your eye, but all the messaging has is the brand name and product specifications. It hooked your attention, but what did it do to reel you in? Think about it: What are you doing to not only hook, but reel people in with “creative” — the make or break it factor in paid social growth marketing?
Creative testing is only getting tougher for mobile campaigns as iOS 14.5 obfuscates user data, but that doesn’t equal impossible and simply means we need to get craftier. There are a variety of hacks that can be implemented to help gain clear insight on how creative is performing — some may not last forever and others may be timeless.
Amid all the privacy restrictions, we still have access to a huge population of users on Android that we should take advantage of. Instead of running all creative tests on iOS, Android can be used as a clear way to gather insights, as privacy restrictions haven’t rolled out on those devices yet. The data gathered from Android tests can then be taken directionally and applied to iOS campaigns. It’s only a matter of time until Android data is also at the mercy of data restrictions, so use this workaround to inform iOS campaigns now.
If running Android campaigns isn’t a viable option, another quick and easy solution is to throw up a website lead form to gauge the conversion rate from creative asset to a completed form. The user experience will certainly not be nearly as amazing as evergreen, but this can be used to gain insight for a short period of time (and small percentage of budget).
When crafting the lead form, think of questions that are both qualifying and would indicate someone completing your north-star event on the evergreen experience. After running people through the lead form, communications can be sent to convert them so ad dollars are being put to good use.
The testing efforts for creative asset types should differ widely by account stage and can be broken down into three I’s: imitation, iteration, innovation.
The type of creative testing should vary over time. Image Credits: Jonathan Martinez
The earlier an account stage, the more your creative direction should rely on what’s proven to work by other advertisers. These other advertisers have spent thousands proving performance with their assets, and you can gain strong insight from them. As time passes, you can slightly slow derivation from other advertisers while focusing on iterating on the best performers. If a percentage had to be placed, I would target 80% of efforts on imitation early on, with iteration gaining steam, and innovation being the final, heavy-lagging prong.
This isn’t to say that innovation can’t be attempted early on if there are great ideas, but generally a more mature company can afford to spend heaps to validate their innovative ideas. Whether you have an in-house design team or are working with freelancers, it’ll also be much easier to spin up 50 variations than it will be to think of and design 50 different innovative assets. Imitating and iterating will make your early testing exponentially more efficient.
Brainstorming and trying to imagine the most beautiful, eye-catching, hook-inducing creative doesn’t always happen within seconds, let alone minutes or hours. This is where utilizing competitor insights comes into play. The most abundant resource is the Facebook Ads Library bar none, because it contains all the creative assets that every advertiser is using across the platform. It always surprises me how few actually know of this free and powerful tool.
When browsing through competitors or best-in-class advertisers in this library, a sign of a great performing creative is how long an advertiser has been running specific assets. How does one find that? The date of when an advertiser started running their creative is stamped conveniently on each asset — this is beyond powerful. I can spend hours scanning through creative assets, and each advertiser provides even more intel and inspiration.
Creative should be at the top of the list as you think of where to place efforts on your paid social growth marketing. We must have a hacky mindset as data becomes more obscure, but with that mindset comes separating the winners from the losers. The types of strategies put in motion will vary over time, but what won’t vary is the importance on strong creative, the make it or break it factor to success.
YouTube will begin pilot testing a new feature that will allow viewers to shop for products directly from livestream videos. The feature will initially launch with just a handful of creators and brands, the company says, and is an expansion of the integrated shopping experience YouTube began beta testing earlier this year.
That feature was designed only for on-demand videos, and allowed viewers to tap into the “credibility and knowledge” of trusted creators in order to make informed purchases, the company explained at the time. It said it would roll out to more creators over the course of 2021.
More recently, YouTube tested livestreamed shopping with a one-day shopping event focused on small businesses.
YouTube’s video platform, for years, has been a powerful tool for product discovery, as its over 2 billion logged-in users per month turn to the service to watch product reviews, demos, unboxings, shopping hauls, and other content that could inspire future purchases. But creators who wanted to sell from their YouTube videos would often have to promote affiliate links to online stores through the video’s description or in-video elements, like cards or end screens.
The integrated shopping experience, meanwhile, allows viewers to shop the products shown in the video itself by tapping on a “view products” button, which brings up a list of the items being featured.
Image Credits: YouTube
This feature allows YouTube to better compete with the growing number of video shopping experiences becoming available from both startups and competitors, including Facebook, Instagram, TikTok Pinterest, Amazon, and Snapchat. Many of those include support for livestream videos, too.
Over the past year, for example, startups like Bambuser, Popshop Live, Talkshoplive, Whatnot, and others have raised multi-million dollar rounds to invest in their own live video shopping businesses. Meanwhile, Facebook recently launched Live Shopping Fridays to test live shopping within the beauty, fashion and skincare space. And Walmart partnered with TikTok on livestream shopping events on multiple occasions.
YouTube’s own interest in this space has been heating up, as well, as just this week the company announced it was acquiring Indian video shopping app Simsim — an indication of Google’s interest in further integrating video shopping experiences into its own platform. Google also integrated video shopping into its Shopping search business, which included one effort from Shoploop, a video shopping product that graduated from Google’s in-house incubator, Area 120.
The expansion of YouTube’s integrated video shopping experience was announced today alongside other new Google Shopping features, including the addition of new section that organizes deals and sales on Google’s Shopping tab, which will be free for merchants who want to list.
Much has been made of the rise of the “creator economy” in the last year. With the Pandemic biting, millions flooded online, looking for a way to make money or promote themselves. The podcasting world has exploded, and with it platforms like Patreon, Clubhouse, and many others. But the thorny problem remains: Do you really own your audience as a creator, or does the platform own you? Companies like Mighty Networks, Circle and Tribe have tried to address this, giving creators greater control than social networks do over their audiences. Now another joins the fray.
Disciple Media bills itself as a SaaS platform to enable online creators to build community-led businesses. It’s now raised $6 million in funding in what it calls a ‘large Angel round’. It already claims to have garnered 2 million members and 500 communities since launching in 2018. Investors include Nick Mason (drummer in Pink Floyd), Sir Peter Michael (CEO of Cray Computers, founder of classic FM, Quantel and Cosworth Engineering), Rob Pierre (founder and CEO of Jellyfish), and Keith Morris (ex. chairman Sabre Insurance). It’s also announced a new Chairman, Eirik Svendsen, a expert in online marketplaces, SaaS and the publishing and media industry.
On its communities so far it has American country star and American Idol judge Luke Bryan, Gor Tex, and Body by Ciara. The platform is also available on iOS and Android and comes with community management tools, a CRM, and monetization options. The company claims its creators are now “earning millions in revenue each year.”
Benji Vaughan, Founder and CEO said: “The scale and rapid growth of the creator economy is extraordinary, and today that growth is being driven by entrepreneurial creators looking to build independent businesses outside of Youtube and the social networks.”
Vaughan, a Techno DJ and artist-turned-entrepreneur, says he came up with the idea after building similar communities for clients. He says the data created on Disciple communities is owned entirely by the host who built the network, “removing third-party risk and allowing insights to be actioned immediately”.
He told me: “We are moving from a position of effectively having ‘gig economy workers for social networks’ to owners of businesses who use social networks for their needs, not the other way around. Therefore, these people are starting to leave social networks to build their businesses and using social networks as marketing channels, as the rest of the world does. Once that migration happens where they move away from social networks as their prime platform, they need a hub where their data is going to get pulled together, they have an audience, which we see as a community that connects with itself as much as they do with the host.”
He thinks the equivalent of Salesforce or HubSpot in the creative economy is going to be a community platform: “That’s where they’re going to aggregate all the information about their valuable audience or community engagement. So, we are looking to, over time, to build out something very akin to what HubSpot sites they have for tech companies or SaaS businesses: a complete package, a complete platform to manage your engagement with your users, grow your user base and then convert that into revenue.”
Rob Pierre, founder and CEO Jellyfish said: “Creating and engaging with your community digitally has never been more important. Disciple allows you to do both of those things with a fully functional, feature-rich platform which requires very little upfront capital expenditure. It also provides numerous options to monetize your community.”
In nearly every Google algorithm update in recent memory, Google has rewarded old, megatraffic sites, sending their search rankings soaring at the expense of smaller, newer sites. Big sites have increased their search traffic by 28% year over year, according to GrowthBar’s organic search data on the 100 most visited sites.
Why? Large sites such as Wikipedia, LinkedIn, Pinterest, Amazon, Home Depot and Target have something the rest of us don’t — they’ve got years of built-up Google trust signals.
Start with best practices like making incredible content and securing backlinks to your best web pages, but also be willing to think a bit outside the box.
I’d contend that Google favors large sites more than ever before — and it’s a trend that doesn’t seem to be slowing down. After all, Google exists to deliver the best search experience to users. Bad search results would be a death sentence for their business, since Googlers would flock to alternatives like DuckDuckGo and Bing.
Especially today, where distrust of the media is at an all-time high, Google can’t risk its reputation by surfacing bad search results, so I think their algorithm errs on the side of caution. It’s simply safer for their business to surface household names at the top of the search engine results page, particularly in ultrasensitive your money, your life categories.
John Mueller, Google’s SEO mouthpiece, practically settled the debate that older sites are preferred by the algorithm when he said, ” … freshness is always an interesting one because it’s something that we don’t always use. Because sometimes it makes sense to show people content that has been established (SEJ).”
So, how can you hope to compete if you’re deploying an SEO strategy on one of the billions of smaller sites?
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Of course, you should start with best practices like making incredible content and securing backlinks to your best web pages, but you should also be willing to think a bit outside the box. The cards aren’t in your favor, so you need to be even more strategic than the big guys. This means executing on some cutting-edge hacks to increase your SEO throughput and capitalize on some of the arbitrage still left in organic search. I call these five tactics “advanced-ish,” because none of them are complicated, but all of them are supremely important for search marketers in 2021.
Businesses spent over $300 billion on content marketing last year. That’s in part because creating new content is the most straightforward way to draw in organic search traffic. Whether you’ve got a mature site or you’re just starting a WordPress SEO site, content is likely a large part of your SEO strategy.
But to scale content like a startup, you’ll need to devote a lot of time to it and/or manage a fleet of writers. Your time is probably better spent building your product or helping customers than on planning hundreds of blog articles. This is precisely where a content generator tool comes into play.
A whole new era of SEO tools is emerging, and some of these are augmented by OpenAI’s GPT-3 technology, the most advanced artificial intelligence language model. These tools have changed the game for SEOs and content creators by automating parts of the content creation cycle. Several tools utilize SEO signals and combine them with OpenAI to help you create blog outlines that include SEO-optimized titles, word counts, keywords, headlines, intro paragraphs and much more.
From the outside looking in, the construction industry appears ripe for tech innovation. The industry represents 6.3% of the U.S. GDP. There are close to 1 million general contractors (GCs) in the country, and anywhere between 3 million and 5 million workers on job sites every day.
Meanwhile, there’s a common (if somewhat justified) belief that construction firms are slow to adopt technology and are behind the digital curve.
Success in construction tech will come down to proving the need for the technology, delivering immediate ROI, and ensuring workers know how to use it on the first try.
But not every construction company is a technology laggard. While GCs are historically slower to adopt new technologies, this doesn’t necessarily make them behind the times. About 60% of construction companies have R&D departments for new technology, and the largest construction firms have substantial R&D budgets. Yet 35.9% of employees are hesitant to try new technology, according to JB Knowledge.
One way to interpret this is that there is a strong interest and need to take advantage of newer construction-centric technologies, but only if they’re easy to use, easy to deploy or access while on a job site, and improve productivity almost immediately.
These factors have made construction tech appealing to investors, who have poured at least $3 billion into the sector. Is construction tech the “it” place right now? Is it ripe for disruption, the way VC investors find attractive? If that’s true, what went wrong at Katerra? Is Procore justified in losing $1 for every $4 in revenue? And why does so little investment go into improving productivity at the job site where GC money is made — or lost — compared to back-office operations?
My experience to date says that construction is different from other sectors because of the significant variation among projects that originates in the way projects are financed, how risks are managed and the factors that drive variation among projects. Construction’s differences are not easily mitigated via data processing, as compared to fintech, for example, where all money is data-amenable to software processing. Addressing project variations will be key to succeeding in construction tech beyond the back office. Here are the critical factors to consider.
Project financing makes capital investment more difficult. While the Commerce Department reported that construction spending in the U.S. reached a record high of $1.459 trillion in November 2020, this doesn’t mean there are unlimited opportunities for construction tech. The reality is that GCs make few capital investments because they must fund investments in technology out of operating cash flow.
Construction projects are typically funded incrementally in phases as the project demonstrates progress. Delays or accidents can have a huge effect on cash flow. Overhead and G&A cost burdens are hated. Asking a GC to license technology as a capital purchase doesn’t always make sense.
GC ownership and business structure also make large capital investment more difficult. Most GC firms were founded by tradespeople and either started as, or remain, family-owned firms. Borrowing what’s considered the “family’s money” is a much more risk-averse decision compared to the way larger corporations evaluate productivity investments and put assets at risk.
Robots have a hard time improvising, and encountering an unusual surface or obstacle usually means an abrupt stop or hard fall. But researchers at Facebook AI have created a new model for robotic locomotion that adapts in real time to any terrain it encounters, changing its gait on the fly to keep trucking when it hits sand, rocks, stairs, and other sudden changes.
Although robotic movement can be versatile and exact, and robots can “learn” to climb steps, cross broken terrain and so on, these behaviors are more like individual trained skills that the robot switches between. And although robots like Spot famously can spring back from being pushed or kicked, the system is really just working to correct a physical anomaly while pursuing an unchanged policy of walking. There are some adaptive movement models, but some are very specific (for instance this one based on real insect movements) and others take long enough to work that the robot will certainly have fallen by the time they take effect.
Rapid Motor Adaptation, as the team calls it, came from the idea that humans and other animals are able to quickly, effectively, and unconsciously change the way they walk to fit different circumstances.
“Say you learn to walk and for the first time you go to the beach. Your foot sinks in, and to pull it out you have to apply more force. It feels weird, but in a few steps you’ll be walking naturally just as you do on hard ground. What’s the secret there?” asked senior researcher Jitendra Malik, who is affiliated with Facebook AI and UC Berkeley.
Certainly if you’ve never encountered a beach before, but even later in life when you have, you aren’t entering some special “sand mode” that lets you walk on soft surfaces. The way you change your movement happens automatically and without any real understanding of the external environment.
Visualization of the simulation environment. Of course the robot would not perceive any of this visually. Image credit: Berkeley AI Research, Facebook AI Research and CMU
“What’s happening is your body responds to the differing physical conditions by sensing the differing consequences of those conditions on the body itself,” Malik explained — and the RMA system works in similar fashion. “When we walk in new conditions, in a very short time, half a second or less, we have made enough measurements that we are estimating what these conditions are, and we modify the walking policy.”
The system was trained entirely in simulation, in a virtual version of the real world where the robot’s small brain (everything runs locally on the on-board limited compute unit) learned to maximize forward motion with minimum energy and avoid falling by immediately observing and responding to data coming in from its (virtual) joints, accelerometers, and other physical sensors.
To punctuate the total internality of the RMA approach, Malik notes that the robot uses no visual input whatsoever. But people and animals with no vision can walk just fine, so why shouldn’t a robot? But since it’s impossible to estimate the “externalities” such as the exact friction coefficient of the sand or rocks it’s walking on, it simply keeps a close eye on itself.
“We do not learn about sand, we learn about feet sinking,” said co-author Ashish Kumar, also from Berkeley.
Ultimately the system ends up having two parts: a main, always-running algorithm actually controlling the robot’s gait, and an adaptive algorithm running in parallel that monitors changes to the robot’s internal readings. When significant changes are detected, it analyzes them — the legs should be doing this, but they’re doing this, which means the situation is like this — and tells the main model how to adjust itself. From then on the robot only thinks in terms of how to move forward under these new conditions, effectively improvising a specialized gait.
After training in simulation, it succeeded handsomely in the real world, as the news release describes it:
The robot was able to walk on sand, mud, hiking trails, tall grass and a dirt pile without a single failure in all our trials. The robot successfully walked down stairs along a hiking trail in 70% of the trials. It successfully navigated a cement pile and a pile of pebbles in 80% of the trials despite never seeing the unstable or sinking ground, obstructive vegetation or stairs during training. It also maintained its height with a high success rate when moving with a 12kg payload that amounted to 100% of its body weight.
You can see examples of many of these situations in videos here or (very briefly) in the gif above.
Malik gave a nod to the research of NYU professor Karen Adolph, whose work has shown how adaptable and freeform the human process of learning how to walk is. The team’s instinct was that if you want a robot that can handle any situation, it has to learn adaptation from scratch, not have a variety of modes to choose from.
Just as you can’t build a smarter computer vision system by exhaustively labeling and documenting every object and interaction (there will always be more), you can’t prepare a robot for a diverse and complex physical world with 10, 100, even thousands of special parameters for walking on gravel, mud, rubble, wet wood, etc. For that matter you may not even want to specify anything at all beyond the general idea of forward motion.
“We don’t pre-program the idea that it has for legs, or anything about the morphology of the robot,” said Kumar.
This means the basis of the system — not the fully trained one, which ultimately did mold itself to quadrupedal gaits — can potentially be applied not just to other legged robots, but entirely different domains of AI and robotics.
“The legs of a robot are similar to the fingers of a hand; the way that legs interact with environments, fingers interact with objects,” noted co-author Deepak Pathak, of Carnegie Mellon University. “The basic idea can be applied to any robot.”
Even further, Malik suggested, the pairing of basic and adaptive algorithms could work for other intelligent systems. Smart homes and municipal systems tend to rely on preexisting policies, but what if they adapted on the fly instead?
For now the team is simply presenting their initial findings in a paper at the Robotics: Science & Systems conference and acknowledge that there is a great deal of follow-up research to do. For instance building an internal library of the improvised gaits as a sort of “medium term” memory, or using vision to predict the necessity of initiating a new style of locomotion. But the RMA approach seems to be a promising new approach for an enduring challenge in robotics.
What do all companies, regardless of industry, say they want? Growth. Lighting-fast, continuous growth. The good news is you can quickly learn which growth marketing strategies work by studying other companies’ success and adapting it to your own business.
Most technophiles remember Dropbox’s referral program — the one that helped it grow 3,900% in 15 months. Its philosophy was simple: reward customers with free storage space for referring other customers. In 2008, it was an absolute revelation. A golden ticket.
Tell a story with your business’ proprietary data. You’re the only one with this information, and that makes it valuable.
In 2021, you’d be hard-pressed to find a company without a formal referral program. It’s a standard growth marketing trick. If you study other companies’ tactics, you’re going to be able to shortcut growth — it’s as simple as that.
The race to grow faster is more pressing than ever before. When you consider the speed with which venture capital funds need to return dollars to their investors and that consumer acquisition costs have increased by 55% over the last three years, forward-thinking entrepreneurs and growth marketers simply must make time to study their competition, learn best practices and apply them to their own business growth.
Of course, you should still run your own experiments, but it’s just more capital-efficient to emulate than to trial-and-error from scratch. Here are five companies with growth strategies worth emulating — including the most important lessons you can begin applying to your business today.
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SEO is going to spend this summer shaking in its boots. Google began rolling out a two-week core algorithm update on June 2, and it’s unleashing a page experience update through August. These updates usually come with significant volatility that makes organic Google rankings jump all over the place.
However, one clear winner of the 2021 SEO footrace is Flo, a women’s ovulation calendar, period tracker and pregnancy app. According to GrowthBar, a SEO tool I co-founded, Flo’s organic traffic has soared 192% over the past two months and it ranks on page one for some staggeringly competitive women’s health keywords.
If SEO is a strategy you’re pursuing, there are two key growth lessons to take away from Flo’s recent success.
1. Authority matters now more than ever. Healthcare websites fall into a category of sensitive sites that Google classifies as Your Money, Your Life (YMYL). Because of oodles of fake news and suspect web content, Google has rightfully raised its bar for expertise and factuality. Go to any one of Flo’s more than 1,000 blog posts (yes, content is still king) and you’ll see that nearly all of them are reviewed by gynecologists, primary care physicians or some other type of women’s health expert. Its site also has pages devoted to its writers and medical reviewers, content guidelines and peer-review specifications. Flo takes its information seriously. From the 2020 election to QAnon to vaccination side effects, Google is on high alert. Whatever your niche, you need to establish credibility to win Google searches.