- Following the passage of landmark consumer privacy laws, Google announced its intention to phase out third-party cookies by 2022
- Businesses that rely on these cookies for granular consumer data are now forced to rethink their strategies for accurate audience targeting
- Some businesses are turning to publisher walled gardens, while others are leaning more into contextual advertising
- Coegi’s Sean Cotton explores the challenges and opportunities marketers face in the absence of third-party cookies, as well as viable alternatives they can use to keep audience targeting on point
Following the passage of landmark consumer privacy laws, Google officially announced its intention to phase out third-party cookies on Chrome browsers by next year. This is certainly a victory for the conscious consumer wary of selling data to advertisers, but it’s also one that might leave businesses scrambling when the cookie jar disappears. But these businesses should be more excited than alarmed. While the death of third-party cookies is an obstacle, it’s also an opportunity: As alternatives to third-party cookies emerge, advertisers might find themselves better-equipped audience targeting and acquirement methods.
Third-party cookies haven’t always been perfect right out of the oven, and their quality was largely dependent on factors such as the data provider’s methodologies, the latency and recency of that data, and any related acquisition costs. Although occasionally stale, these prebuilt audiences allowed advertisers to quickly scale their audiences. The forthcoming phaseout will put pressure on marketers to rethink their strategies for accurately targeting audiences.
What are the alternatives to third-party cookies?
Publisher walled gardens (in which publishers trade free content for first-party data) are a solid starting point for advertisers seeking alternatives to third-party cookies. These audiences won’t come cheap, but it will be possible to find publishers with audiences that strongly align with your own customer base. And because these sources of data are generally authenticated, they’re also an accurate source of modeling data to use as you construct your own user databases.
Many purchases these days begin with online research, so savvy marketers are also exploring contextual advertising as a third-party cookie alternative. Mapping out the sales funnel for your product or service will help you identify opportunities for targeted advertising as your audience performs research, but it’s important to be precise at the same time. Be sure to use negative search terms and semantic recognition to prevent your brand or product from appearing in potentially embarrassing or unsafe placements. (Just consider the word “shot,” which in this day and age could relate to anything from COVID-19 or health and wellness to debates surrounding the Second Amendment.)
There’s still time for a smooth transition away from your dependency on cookies, but you shouldn’t wait much longer to get started. As you explore new ways to get your message out to precise audiences, these strategies are a great place to start:
1. Lean on second-party data
Second-party data (such as the kind provided on publisher walled gardens) can offer accurate audience targeting for advertisers in a hurry to replace third-party cookies. This type of data can inform people- or account-based marketing strategies, helping you identify individuals in a specific industry or those with a certain relevant job title. Similarly, integrating second-party data with your broader digital marketing strategy can create use cases for lookalike modeling or provide a strong foundation for sequential messaging.
Because second-party data will come at a potentially high cost, however, try to partner with publishers and providers for the long term to keep rates as low as possible. As an added benefit, this will give you time to experiment and use various types of data in different ways.
2. Implement mobile ad ID (or MAID) targeting
MAID targeting is based on an anonymous identifier associated with a user’s mobile device operating system. MAIDs have always been the go-to for application targeting because they’re privacy-compliant and serve as a great way to segment audiences based on behaviors and interests. In fact, everyone expected MAIDs to grow as mobile and in-app usage has accelerated. In the U.S., for instance, mobile users spend just over an hour more on those devices than their computers each day, and they spend 87 percent of the time on their smartphones in-app. But the death of third-party cookies will certainly accelerate the usage of these audiences across channels even more.
One of the most powerful insights offered by MAIDs is the ability to track a user’s location data. If a device is frequenting an NFL stadium, for example, you can infer that the user is a football fan, which allows a host of other inferences to form. You can also enrich MAIDs with offline deterministic data, allowing you to construct a more complete picture of the user, their demographic information, and their relevant interests.
Note that recent changes to Apple’s iOS 14 platform might limit this type of targeting on the company’s devices. Besides this, it’s also important to verify the precision and accuracy of the provider giving you location data.
3. Build custom models and indexes
Algorithmic targeting or lookalike modeling caught a bad rap from advertisers who worried the modeled audiences would broaden targeting too far. But as the quality of your audience input increases, the quality of your modeling output increases as well. In other words, concerns are justified only if you’re modeling audiences after modeled data.
On the other hand, models can be an excellent source of additional insight if you’re using deterministic data. This information comes from all kinds of sources, including social media platforms, questionnaires and surveys, and e-commerce sites that have information on user purchase history. In short, it’s data you can trust — meaning it can inform the creation of accurate audience segments and models that capture real customer intent. With deterministic data at the helm, you can create your own models and indexes to aid in your targeting efforts.
First-party data from customers and active social media followers generally provides the best source for models. Be aware of outliers when it comes to audience insights, though; signals should be strong enough to imply the target audience’s actual behavior.
4. Use Unified ID solutions
The death of third-party cookies doesn’t mean the death of all your strategies, and you can expect to see a variety of sophisticated solutions emerge in the coming years that offer audience segmentation with increased control for advertisers and enhanced privacy protections for consumers. In fact, some companies are already working collaboratively to create Unified ID solutions that modernize audience targeting and measurement.
The solutions they’re creating aim to collect user information (such as email addresses) in exchange for free content. Those addresses will then be assigned encrypted IDs that are transmitted along the bid stream to advertisers. If publishers widely adopt unified identity products, they’ll provide an excellent alternative to an overreliance on walled gardens.
However, one of the biggest hurdles for a unified ID solution will be scalability: It will likely not be a solution that can stand on its own for some time.
The death of third-party cookies will absolutely shake up the advertising world, but that’s probably a good thing. Cookies were never designed to be the backbone of digital advertising, and their disappearance makes room for alternatives to third-party cookies that actually deliver a better experience for advertisers and the audiences they’re looking to target. As advertisers gain more granular control over who hears their messaging (and when) and customer data is ensconced behind modern encryption and privacy protection tools, it’s not hard to argue that everyone wins when we put away the cookie jar.
The post Everything you need to know about audience targeting without relying on third-party cookies appeared first on Search Engine Watch.
- This week marks the 10 year anniversary of Google’s landmark web quality algorithm Panda
- It was a seminal moment for the SEO industry with 12% of US sites being targeted for poor quality and manipulative optimization practices
- Despite removing much of the worst black-hat tactics SEO is still hasn’t lived up to its experiential potential ten years on
- Many clients and practitioners still use outdated language and practices to position the value of Search in this vastly more mature marketing landscape
- To escape this pre-Panda legacy SEO needs to take the best of its constituent parts and shape a new customer-centric Search future once and for all
I was recently notified of a significant work anniversary which transported me back in time to the turbulent start of my SEO career just over 10 years ago. I was prompted to reflect on the industry I love, where it continues to fall short, and ultimately where I see it going. This professional milestone closely corresponded with what was a seminal event for the immature SEO business. On February 24th, 2011 the ‘Death Star’ took aim, and with a typically understated Tweet from the Head of Google’s Web Spam team, Matt Cutts confirmed it. Google had launched its landmark web quality algorithm that would forever be known as Panda.
Google just launched a new algorithmic ranking change. Here's the blog post: http://goo.gl/J1e0a
— Matt Cutts (@mattcutts) February 25, 2011
The day of reckoning had arrived for an industry that tied their client’s lucrative search fortunes to a house of cards built on the spammy and manipulative best practices that had become SEO’s calling card. Thin, duplicate and often stolen content was accompanied by on-site keyword stuffing and obvious over-optimization. This might have gamed the rankings for a time but provided little value to the users who bounced en masse giving Google a solid signal that many sites deserved an algorithmic slapdown.
What exactly happened in 2011 with Panda?
In what was a relatively short rollout, around 12% of US search queries were affected and the target of the rollout was poor quality sites relying way too heavily on content farms and directories to fabricate their popularity in search.
Shell-shocked webmasters stared at their Analytics dashboards like Wall Street traders on Black Monday, watching in disbelief as their search share plummeted and asked, “What do we do now?”
At the time, I was simply a fledgling Search Executive with a mere nine months’ industry experience under my belt, with the only thing protecting me from this fallout being the founders of our agency. As a start-up, luckily we were free and clear of this mess as they had seen the writing on the wall long before.
SEO was dead, or so we thought, and a new age of experience was dawning. We looked on as Rome burned.
But, despite its obituary being cynically written every year since SEO refused to die. At the time, practitioners paid lip service to profound change but were far too invested in their ways of operating, and clients, although badly burned, were addicted to the quick wins the hackers of the algorithm had peddled. And so, the dance went on.
Was Panda a missed opportunity for the industry?
Yes Panda, and its sister link-spam algorithm Penguin, had a profound effect and removed the absolute worst of the worst black-hat practices but a significant proportion of the industry simply did their best to clean up the mess they’d created – often charging clients to take out their own trash so to speak – and so the probing began for what was the new acceptable minimum you needed to meet in order to get your site ranking once again.
- “Is 300 words enough now?”
- “How many keywords can I get away with using without angering Google?”
- “How much content do I need to change for it to be considered unique, will 60% do it?”
This mentality of chasing the ever-evolving algorithmic goalposts is the continued failure of many in the industry who still largely prefer to please bots ahead of delivering real value for users.
I’m not meaning to preach, my hands aren’t squeaky clean and these tactics do have a use but it’s a belief gaining momentum that they should not be allowed to ride roughshod over both brand and UX. I was lucky enough to have been scared straight from the start, firmly putting my focus on how to drive real value to the consumer, building great experiences, authority, and trust.
Panda’s pain is still real
This is the Jackal and Hyde reputation the industry has suffered through ever since. The straightest of strait-laced operators – who see search as a powerful and useful customer touchpoint, are tarnished with the same brush as the sketchiest of spammers and scammers who are still alive and well within the industry.
Their presence diminishes the overall value of search and can create a race to the bottom kind of mentality. Clients who are still sore with the industry ten years on sometimes expect “old-school” results without being willing to invest in long-term value – ironically because they’re terrified of being burned again by another update.
It’s crazy but it’s true, I’m still having these conversations on a basis that is more than is reasonable and it is because the discipline is haunted by the original sins of its birth.
It goes without saying that I want to scream every time I hear the words:
- “Can you do some quick SEO for me?”
- “I’d love it if you could build us some cheap links?”
- “Can you just get rid of this negative article from Google for me?”
- “Just tell me what keywords I should use!”
All with the retort of,
“… it will cost what?! I found a guy online who’ll do it for peanuts”.
The damage has been done and this is the cross that SEO has to bear, but is there a way to move out of the long shadow cast by a decade-old catastrophe?
The answer is resounding, “yes!” but we need to meet the revolutionary promise we made in 2011 and we desperately need to stop talking just about SEO and reposition the value of search.
What does our SEO past mean for our search future?
First let’s start with the term itself, what it means to clients and how it needs to be repositioned. SEO is a collection of data-driven tactics which are often seen as a cure-all by clients, a channel unto itself, this it is not.
Despite sitting at the critical crossroads of web development, content, and PR, SEO is far too often a siloed activity that does not play nicely with other marketing disciplines, even separated in mind and budget from its closest counterpart SEM.
Instead, we need to be evaluating search, not SEO, as a valuable driver in a customer’s path to purchase and how it can facilitate discovery, consideration, and purchase, driving an overall brand experience.
The reason SEO too often operates in a vacuum is that historically it’s far less complicated to manage and measure in isolation. But the impact and delivery of search should be more dynamic and incorporated across marketing departments as you can see above or agencies with the constituent tactics of SEO being greater as part of the search.
It’s fair to say that the Panda SEO ripples from 10 years ago have not yet matured nearly as quickly as the dynamic marketing ecosystem that’s grown up around it. 10 years ago, rich media, mobile and social media weren’t yet huge drivers or mediums, also with the arrival of personalized email and marketing automation being relatively new on the scene too.
Google has evolved well beyond its blue link roots providing a valuable blended search experience featuring products, local results, answers, reviews, news, video and is powered by advanced AI which actually understands user intent and voice searches.
Search is no longer the one-dimensional digital bottleneck it once was and consumers hold the power to choose how they interact with brands and follow the path that’s most convenient for them, not one that’s engineered by SEO alone.
Remember, people will always do what’s right for them.
Three considerations for how search should learn from SEO’s past
1. Put the customer first
A customer-centric approach is a given in most marketing disciplines but a lot of people in the SEO community did not seem to get the memo.
Instead of talking about search share and obsessing about the ranking opportunities we need to focus on, try to refocus the lens on what the customer feels, wants, and needs as the foundation of an experiential strategy from which, not only search will be the tactic it delivers on.
Beyond the implied minimum of a technically sound site, we need to put a greater emphasis on analyzing search behavior, not just keywords, to provide the customer with the right information at the moments that matter in their journey.
Marketing teams need to be asking themselves, “why?” more often and for search the answer needs to be, “because it’s what’s best for the customer”.
2. Change the tone and vocabulary
These points all have one thing in common in that we need to try and move away from the acronyms, verbiage, and lingo that was coined in a non-customer-centric world and based on optimization rather than value.
This will be one of the hardest things to move away from as so many veterans wear SEO as a badge of honor and clients will more than struggle to learn a new way of referring to a discipline they still don’t fully understand.
Obviously, I don’t have all the answers here, so from a quick poll I ran on LinkedIn, I wanted to gauge other industry opinions on this divisive topic.
As you can see, even from this small pool of 39 people in my marketing network, there are almost half of them who also sense that there is a problem but either feel that the hill is too high to climb or that the problem is there but can continue to be ignored. The conversation continues.
3. Create don’t build
Just showing up in the right search simply isn’t good enough and we know that we need to move away from the mentality of building SEO-optimized content and links as simply a means to an end.
Search data should inform what kind of content people are looking for and also what they like to consume but owned branded content should not be the playground of optimization. There aren’t any shortcuts to creating great user experiences or content that is genuinely useful and deserving of press but you can use search data to make valuable decisions.
Search as a collaborative marketing discipline will win the day.
The final conclusion to all of this is that search holds extreme value but the industry still is not living up to its full potential because of the ghosts of its pre-Panda past.
The long-term beneficiaries of SEO will be those who can effectively rip it apart and piece it back together in everything marketing teams do, which is no easy feat.
If we educate the experience makers, everyone from the copywriter to the PR director, the developer to UX designer on the beneficial insights that search teams can provide then a new paradigm can be born.
Then, and only then, can SEO finally be put out to stud and enjoy the retirement it so desperately deserves.
Kevin Mullaney is MarTech Lead at Nordic Morning’s Malmö office. Kevin has over 12 years’ experience working with large global brands at established digital consultancies. A veteran of the SEO industry Kevin has been a speaker at BrightonSEO and other industry events and now leads the MarTech and Media team at Nordic Morning’s Malmö office in Sweden.
The post The Panda anniversary and what we desperately must remember about search appeared first on Search Engine Watch.
Now that the consumer electronics big-box store has shuttered, future generations need a place to go to touch and discover the next great piece of tech.
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- Affiliate marketers can use Google Analytics to do the following – Google Event Tracking to monitor on-site engagements, Google Dashboards for analyzing user behavior, and build custom Audiences for improving audience retargeting.
- As an affiliate marketer, Google Analytics does not provide you with off-site tracking, so you can’t see what actions a person performs on a merchant site after leaving your website.
- With server-side tracking and Google Analytics, you can monitor an entire affiliate funnel through one platform. Advantages include the ability to create lookalike audiences based on people who made a purchase, run improved retargeting campaigns, and export lookalike data across multiple ad platforms.
Google Analytics is a powerful tool that provides valuable insights for anyone managing a website. In this article, I will discuss how to use Google Analytics for your affiliate marketing campaigns. I will then show you how to use third-party tools to provide you with additional insights to generate more revenue from your existing traffic and make better use of your ad budget.
How marketers currently use Google Analytics for affiliate tracking
If you are using Pay Per Click (PPC) ads as your primary customer acquisition channel, your profit margins are directly tied to ad costs. Any edge you gain that improves your ROAS will provide you with a competitive advantage in the ad auction.
There are three primary levers of a PPC campaign, the ad copy, the audience targeting, and the landing page experience. The insights you gain through Google Analytics can help you improve audience targeting and the landing page experience.
Google Event Tracking allows you to track outbound clicks on affiliate links. Once set up, the dashboard is accessible through Behavior > Events. If you know the average conversion rate for a product, you can assign each click a value by setting up Goal Values.
You then need to make modifications to the GA tracking code or add a special configuration to your GTM tag. This article covers event tracking in more detail.
With Google Event Tracking, you can monitor your assumed profit margins for a campaign through Google Analytics. Of course, these figures are far from accurate.
When implemented effectively, Goal Values provide you with a theoretical model for predicting your campaign’s profitability. However, it does not reflect your actual sales. To access this data, you need to log in to your affiliate dashboard, check the sales, and see if the predicted profit margins align with the real results. Moreover, affiliate platforms provide differing levels of insights. That means you might only get a “gross sale value” that covers sales from all traffic, as opposed to traffic from one website.
The second thing most affiliate marketers will do is review the information provided through Google Analytics dashboards to monitor what people are doing on their landing pages. For example, you might monitor how far down a page people scroll, how much time they spend on the page, the bounce rate, and more. You can also see the number of affiliate link outbound clicks.
You can run A/B tests and other experiments to check how your actions impact the CTR to affiliate links. You can adjust the position of affiliate links and the placement of the products you are promoting to improve CTR.
Insights gained from Google Analytics provide you with essential data to test your assumptions. You can use this data to improve the landing page experience and boost your CTR.
Any improvements you make to the landing page experience can and should improve your ROAS.
The final thing you can do is use Google Analytics to improve your initial targeting. If you are tracking who clicked on the affiliate link, you can create a refined lookalike audience for Google AdWords through Google Analytics. The following guide discusses audience targeting and Similar Audiences.
Any improvement to your targeting will give you an edge in the ad auction.
What are the limitations of Google Analytics for affiliate tracking?
Google Analytics is a powerful tool for monitoring the on-site activities of your visitors. As a business owner that controls an entire funnel, you can place your Google Analytics tag across your site, including the checkout page where the transaction actually takes place. Therefore, Google Analytics provides you with all the data you might conceivably need to monitor and optimize a funnel.
Rather than relying on assumed transaction values, you can monitor everything through one or more Google Analytics dashboards. Unfortunately, as an affiliate marketer, since you can’t place your GA tag on the merchant “thank you” page, Google Analytics fails to provide you with these insights. You are forced to jump between your affiliate programs, the ads platform, and Google Analytics to monitor how your PPC campaigns are performing.
I discussed why you couldn’t use GA Event Tracking for the final stages of an affiliate funnel. It is an inconvenience that prevents the real attribution of transactions to an ad click.
This issue impacts your marketing at two crucial levels, which will inevitably increase your Cost Per Acquisition (CPA) and your ability to automate your campaign targeting and optimization:
- Your entire audience is blended into general “buckets,” which prevents you from displaying relevant ads according to the users’ positions in the funnel.
- You can’t build lookalike audiences of your best possible “customers” because you don’t know who’s done what.
While these two factors will undoubtedly reduce your profit margins, they will also undermine your long-term business objectives and ability to compete on the ad auction.
The final inconvenience you’ll face is that you can’t share custom audiences generated through Google Analytics across other ad platforms. To be fair, Google Analytics was never designed to provide off-site analytics tracking. However, as an affiliate marketer, enriching your Google Analytics data with off-site conversion data can bring a lot of value to your business. I’ll discuss how off-site tracking works in the next section.
How offline conversion tracking works
Offline conversion tracking ties actions taken by users on your site and actions taken on sites or systems outside the reach of the initial site’s Google Analytics tag. The most common methods for implementing off-site analytics tracking are through server-side tracking API (also known as postback tracking) and manual data / CSV upload.
With server-side tracking, unique click ID data is passed during the outbound click and is then sent back via a server-side URL. The unique click ID value is the common denominator that links a click from your website to actions on a separate site.
The data flow is managed through a postback URL. In the following blog post, I share technical information about how postback URLs work and why they’re important.
The main benefit of server side tracking is that it is not affected by ad blockers, ITP, ETP.
As an affiliate marketer, off-site marketing analytics provides you with a complete overview of your marketing funnel. You can track an off-site purchase. With this data, you get the same insights and advantages as a business where the end sale is made on their site.
An additional advantage of off-site tracking is that you can sync conversion data across multiple channels/ platforms and then use this data to create custom audiences. You can, therefore, test your marketing funnel utilizing cheaper traffic sources, then use the data to build lookalike audiences for ads on Facebook or Google, for example.
Unfortunately, not all ad platforms support off-site tracking. Google introduced off-site tracking in 2013. Bing Ads introduced the service in 2017, while social media platforms such as Twitter and TikTok have yet to provide a suitable solution for affiliate marketers.
Solutions for offsite tracking
Offsite tracking has multiple advantages for people operating in the affiliate marketing niche. That’s not to say that it’s not without problems. You need a lot of technical knowledge to set up a system to connect data from a browser to the server-side.
Google Analytics provides an extensive API that enables developers to implement server-side tracking. There are three primary methods for implementing off-site tracking:
- Google Analytics API: Requires the highest level of development skills. However, the Google Analytics API provides programmers with the best potential for complete server-side tracking.
- Google Tag Manager: A High level of technical skills. Google Tag Manager will only allow you to effectively track off-site actions if you can add Google Tags to the merchant’s site.
- Third-Party Affiliate Tracking Software: Plug & play solutions that connect Google Analytics and other Ads marketplaces (Bing, Facebook, and other platforms).
Due to the ever-evolving data and analytics space, developing and keeping up with the constant changes requires a significant investment of time and resources. Large companies might choose to invest in a custom in-house solution for off-site tracking. However, solutions that utilize the Google Analytics API are too expensive for most affiliate marketers.
Affiliate tracking software like AnyTrack.io, a company that I founded, provides a native server-side tracking integration with Google Analytics, Bing Ads, and other ad networks. It’s certainly a lot easier than hiring a developer to create a custom solution.
On balance, regardless of your approach, the limitations of offsite tracking are outweighed by the sizable benefits. That is, assuming you want to optimize your marketing funnel and increase your ROAS.
Integrating Google Analytics With Offsite Tracking
Implementing Google Analytics with offsite tracking software like AnyTrack.io is straightforward. Google Analytics already provides the standard dashboards for tracking visitor flow across a site from landing page to conversion.
When you integrate offsite tracking, you are, fundamentally, just gaining the same type of data as someone who manages an entire funnel across a single site would see. The benefit is that you get access to data you can use to improve your ROAS.
One of our clients, Cliverse.com, has six websites in the pet care industry. Most of the traffic to their sites comes from organic search. They were facing a data challenge that you may be familiar with; they found it difficult to understand what products were converting and from which pages those conversions were occurring.
In addition, PPC ads were more expensive than needed. For example, they were running retargeting ads to people who had purchased an affiliate product suggesting they make a purchase. With better data, they could improve ROAS.
Using AnyTrack.io, Cliverse could finally see from what page, and which link on a page was generating the conversions. Through analyzing the data, Cliverse was able to increase revenue by 30% thanks to page optimization. Because they have the complete picture, they are now able to run paid media campaigns to their site with full confidence.
Bridging the gap between your google analytics data and affiliate network conversions is the optimal way to improve your position at the ad auction. With a full overview of your affiliate funnel, you gain actionable insights on what triggers conversions and generates sales. It’s a vital edge that can help improve your ROAS.
In this guide, I showed you three ways to use Google Analytics as an affiliate marketer. You can use Google Event Tracking to monitor people who click on your affiliate links. With Goal Values set up, you can track your campaigns’ probable results. Moreover, you can run retargeting campaigns and create Custom Audiences for future ad campaigns.
Through the Google Analytics dashboards, you can gain insights into your site visitors’ actions. You can use these insights to validate the assumptions you make when running conversion optimization tests.
While Google Analytics is a powerful tool, you can’t see what actions people take when they leave your site. If you integrate off-site tracking, you get access to this data. Most third-party tools, such as the one we created, allow you to use Google Analytics to get a complete overview of your affiliate marketing funnel.
As an affiliate marketer, off-site tracking combined with Google Analytics provides you with valuable insights that can help you improve your ROAS. Follow the steps shared in this guide to see the results for yourself.
The post What affiliate marketers have missed about Google Analytics appeared first on Search Engine Watch.
One Sr. Strategists discusses the most useful elements to understand about how algorithms work in your PPC campaigns.
Read more at PPCHero.com
Startups need to live in the future. They create roadmaps, build products and continually upgrade them with an eye on next year — or even a few years out.
Big companies, often the target customers for startups, live in a much more near-term world. They buy technologies that can solve problems they know about today, rather than those they may face a couple bends down the road. In other words, they’re driving a Dodge, and most tech entrepreneurs are driving a DeLorean equipped with a flux-capacitor.
That situation can lead to a huge waste of time for startups that want to sell to enterprise customers: a business development black hole. Startups are talking about technology shifts and customer demands that the executives inside the large company — even if they have “innovation,” “IT,” or “emerging technology” in their titles — just don’t see as an urgent priority yet, or can’t sell to their colleagues.
Rather than asking large companies about which technologies they were experimenting with, we created four buckets, based on what you might call “commitment level.” (Our survey had 211 respondents, 62% of them in North America and 59% at companies with greater than $ 1 billion in annual revenue.) We asked survey respondents to assess a list of 16 technologies, from advanced analytics to quantum computing, and put each one into one of these four buckets. We conducted the survey at the tail end of Q3 2020.
Respondents in the first group were “not exploring or investing” — in other words, “we don’t care about this right now.” The top technology there was quantum computing.
Bucket #2 was the second-lowest commitment level: “learning and exploring.” At this stage, a startup gets to educate its prospective corporate customer about an emerging technology — but nabbing a purchase commitment is still quite a few exits down the highway. It can be constructive to begin building relationships when a company is at this stage, but your sales staff shouldn’t start calculating their commissions just yet.
Here are the top five things that fell into the “learning and exploring” cohort, in ranked order:
- Augmented reality/mixed reality.
- Virtual reality.
- AI/machine learning.
- Wearable devices.
Technologies in the third group, “investing or piloting,” may represent the sweet spot for startups. At this stage, the corporate customer has already discovered some internal problem or use case that the technology might address. They may have shaken loose some early funding. They may have departments internally, or test sites externally, where they know they can conduct pilots. Often, they’re assessing what established tech vendors like Microsoft, Oracle and Cisco can provide — and they may find their solutions wanting.
Here’s what our survey respondents put into the “investing or piloting” bucket, in ranked order:
- Advanced analytics.
- AI/machine learning.
- Collaboration tools and software.
- Cloud infrastructure and services.
- Internet of things/new sensors.
By the time a technology is placed into the fourth category, which we dubbed “in-market or accelerating investment,” it may be too late for a startup to find a foothold. There’s already a clear understanding of at least some of the use cases or problems that need solving, and return-on-investment metrics have been established. But some providers have already been chosen, based on successful pilots and you may need to dislodge someone that the enterprise is already working with. It can happen, but the headwinds are strong.
Here’s what the survey respondents placed into the “in-market or accelerating investment” bucket, in ranked order:
When large parts of the world were shutting down in March, we really didn’t know how we would move massive numbers of employees used to working in the office to work from home.
In early March, I wrote a piece on how to prepare for such an eventuality, speaking to several experts who had a background in the software and other tooling that would be involved. But the shift involved so much more than the mechanics of working at home. We were making this transition during a pandemic that was forcing us to deal with a much broader set of issues in our lives.
Yet here we are seven months later, and surely we must have learned some lessons along the way about working from home effectively, but what do these lessons look like and how can we make the most of this working approach for however long this pandemic lasts?
I spoke to Karen Mangia, vice president of customer and market insights at Salesforce and author of the book, Working from Home, Making the New Normal Work for You, to get her perspective on what working from home looks like as we enter our eighth month and what we’ve learned along the way.
As employees moved home in March, managers had to wonder how productive employees would be without being in the office. While many companies had flexible approaches to work, this usually involved some small percentage of employees working from home, not the entire workforce, and that presented challenges to management used to judging employee performance based for the most part on being in the building during the work day.
One of the things that we looked at in March was putting the correct tools in place to enable communication even when we weren’t together. Mangia says that those tools can help close what she calls the trust gap.
“Leaders want to know that their employees are working on what’s expected and delivering outcomes. Employees want to make sure their managers know how hard they’re working and that they’re getting things done. And the technology and tools I think help us solve for that trust gap in the middle,” she explained.
She believes the biggest thing that individuals can do at the moment is to simply reassess and look for small ways to improve your work life because we are probably not going to be returning to the office anytime soon. “I think what we’re discovering is the things that we can put in place to improve the quality of our own experiences as employees, as learners and as leaders can be very simple adjustments. This does not have to be a five year, five phase, $ 5 million roadmap kind of a situation. Simple adjustments matter,” she said, adding that could be measures as basic as purchasing a comfortable chair because the one you’ve been using at the dining room table is hurting your back.
- Recent data from Roku shows that 85% of Americans are now streamers. Making them feel excited about some new CTV app is not a piece of cake but also not totally unfeasible.
- In the dark, dark woods of AdTech, Connected TV (CTV) apps are a dime a dozen. This may sound spooky enough for a proper Halloween horror story.
- The market is currently dealing with many potentially brilliant content creators having cold feet when thinking of launching their own CTV channels.
- Alex Zakrevsky, CEO of Allroll, helps you overcome these fears.
In the dark, dark woods of AdTech, Connected TV (CTV) apps are a dime a dozen. This may sound spooky enough for a proper Halloween horror story. In reality, the impressive growth of the CTV market strengthened the competition and endowed it with many “survival of the fittest” features. As a result, the fact that the number of connected TV devices in the US reached 400 million this year, as per Leichtman Research Group, is not that appealing and comforting for channel owners anymore. The market is currently dealing with many potentially brilliant content creators having cold feet when thinking of launching their own CTV channels. To overcome these fears, it’s important to embrace them first.
1. Failing to start
There is a belief that developing a channel from scratch requires either proficient coding skills or paying a fortune to those who have such skills. So, instead of starting, let’s say a Roku channel, content producers tend to be terrified of the prospect of coding or not being able to make ends meet. To lower the level of anxiety, it’s always useful to look at available options.
If watching someone building a channel for you is the most preferable model, specialized agencies are the best choice to make. These companies usually have their own in-house developing teams and charge a set price or a revenue share, which gives room for maneuver. Alternatively, there are freelance developers whose price tag normally starts from $ 25/hour on Upwork.
The downside of both solutions is that they will depend on developers’ availability and may eventually turn out to be slow-moving and quite pricey. Yet, they will definitely help have less on one’s plate. At the same time, there are ways of developing a CTV app without going bankrupt or going full-on with programming languages.
In addition to custom channel development, some CTV platforms, such as Roku or Amazon Fire, offer their no-coding solutions for channel owners. Roku, for example, has its on-the-house model called Direct Publisher. Yes, this tool limits customization, monetization, and third party analytics options, but it does save time, money, and, more importantly, keeps channel owners with no coding experience sane. As a compromise between basic and advanced features, there’s a moderately-priced service for developing Roku channels that is cloud-based and code-free. Instant TV Channel costs $ 45.95/month. It creates and maintains a video feed as well as offers a range of customization opportunities. Consequently, if coding isn’t a channel owner’s strong suit, it’s needless to pay millions or spend months trying to make sense of programming. What’s crucial is the idea that drives a publisher and the content that will drive potential viewers.
2. Being mediocre
As CTV ad spend is surging and has already increased by 19% this year, based on IAB’s figures, more and more publishers are getting on board each day. This makes creating original content pretty challenging. Ultimately, channel owners are surrounded, on the one side, by fears of meeting their channel-doppelganger and, on the other side, being ‘eaten alive’ by channels-giants, like Netflix, Animal Planet, and others. Sounds quite dramatic, doesn’t it? If someone is still wondering whether there’s any space left for new apps in the CTV universe, it’s worth checking on how many people delightfully watch channels, which others would not even think of, in the screensavers or special interest sections on the Roku platform.
As for the chances of becoming a copycat of your own concept, great minds do think alike but most of the time not so literally. Therefore, becoming a successful channel owner calls for out-of-the-box thinking, doing some research, and being generally both strategic and brave.
3. Having zero installs
Recent data from Roku shows that 85% of Americans are now streamers. Making them feel excited about some new CTV app is not a piece of cake but also not totally unfeasible. So, if there is a genuine fear that no one will ever install a new Roku channel, here are several promotional techniques for not letting this happen.
First of all, it’s essential to make as many people as possible aware of a new channel via a website, emails, and social media. This is absolutely free, a bit time-consuming but worthwhile. Secondly, it’s important to attend online/offline events and accept all networking opportunities where a channel owner can meet potential viewers and introduce a channel to them. Then, it’s good to think of collaborating with like-minded channels so as to make friends with indirect competitors and promote each others’ content.
Additionally, it would be beneficial to be included in one of those guides with top new channels one should install. For this purpose and in general, getting feedback on the content from influencers can be really game-changing. Finally, in case there’s a request to level up the current promotional approach, it’s time to consider monetization.
Roku has its self-serve platform for growing publishers’ audiences using the tailored display and video ads. While its CPM rates can range significantly with no guaranteed number of installs, the platform is quite flexible in terms of budgets and can meet various needs and wants. What’s more, there’s the Allroll marketing platform aimed to drive viewers to Roku channels by the means of advanced targeting options and personalized advertising messages. It provides higher apps’ exposure and, ultimately, + 60% installs with the same budgets as those required for the native platform. So, there’s definitely a lot one can do to enhance the channel’s results without getting overwhelmed.
4. Surrendering to YouTube
When talking about video channels, there is always an elephant in the room. This elephant’s name is of course YouTube. Some publishers are still skeptical about CTV platforms, thinking their videos will never perform there as well as they do on good old YouTube. They might as well imagine having to stick to one platform to have windfall gains. In fact, there’s much more to this than meets the eye.
No matter how successful, YouTube is just a service. At least for a content owner and not an employee of YouTube. Thus, there is no need to choose between different stages on which to play the content. On the contrary, it is better to use as many platforms as one can manage to reach out to as many viewers as possible. This is the smart way of promoting video content, raising brand awareness, and maximizing profit in the soaring digital space.
5. Getting lost in streaming obscurity
It’s not particularly a secret that the world of streaming is currently run by four major operating systems: Roku, Amazon Fire, Android TV/Google TV, or Apple TV. The first two have the biggest share of 100.2 million (Roku) and 72.7 million (Amazon Fire) users, according to eMarketer. The rest of the players are of somewhat a lower caliber. Picking one platform for an app may seem like a tough job, bearing in mind their characteristics resemble each other in so many ways. For instance, Roku uses Audience Network with broad geolocation options for targeting and a revenue share model for monetization within its Direct Publisher mode. In the meantime, Amazon Fire’s code-free Amazon Creator offers extensive data on consumers’ preferences collected from Amazon devices and a commission-based monetization. This may rightly seem quite confusing.
The reasonable tactic for not getting puzzled by the best bets is to follow the audience. People mainly prefer streaming platforms that relate to an operating system they are plugged into in their everyday lives. So, if they have an Amazon Prime account that they actively use or they are fond of Alexa, these consumers are likely to go for Amazon Firesticks in their streaming experience.
Similarly, Apple products’ adepts will favor Apple TV, whereas Android users will stand for Android TV. Roku is sort of a black sheep in this family, as it has always been solely TV-oriented. Though, it’s extremely user-friendly, very affordable and its devices were voted the best of this crowd on numerous occasions. Without beating about the bush, knowing your audience is the key.
The CTV market has been on the rise offering publishers more advanced opportunities to reach their viewers. Meanwhile, the stakes of being bog-standard or outdated got higher, as the competition became more severe. This left some content producers panicked about their chances to succeed instead of being focused on bringing new creative ideas to life. After all, living in fear is counterproductive. Hence, the best method of facing fears is to meet them in person. The launch of a new CTV app will consist of a series of important rendezvous on each of the steps: a platform or platforms to use, development strategy, content ideas, promotional tools, and monetization models. It’s vital to pay attention to every single decision throughout this journey. Now, time to get down to business.
Alex Zakrevsky is the CEO of Allroll marketing platform for CTV/OTT channel owners. Innovator, product lover, CTV, and programmatic enthusiast. He believes that the quality of the product always wins.
The post Five fears of channel owners: What spooks you about creating your own CTV app? appeared first on Search Engine Watch.
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