INFOGRAPHIC: Spring Cleaning for Digital Marketers – 4 Things Every Brand Should Do Now

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Spring is here, and now’s the perfect time for brands to freshen up their digital marketing efforts. So, how do marketers eliminate the clutter from their marketing strategy? In MDG’s new infographic, readers will learn which old and tired digital tactics to throw out this spring, and which fresh, new marketing techniques will help them grow their businesses in the seasons to come.

MDG Advertising’s new infographic, “Spring Cleaning for Digital Marketers: 4 Things Every Brand Should Do Now,” shows:

  • Which social networks marketers should engage on
  • The importance of cleaning up data and securing it properly
  • Why mobile load speed is a top priority
  • Why marketers should go all in on marketing attribution

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Marketers Take Heed: Brands Must Show Loyalty to Earn Loyalty

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MMW was privy to a first look at new data this week in a freshly completed report from Alliance Data.

NextGen consumers are leading the retail industry to a new view on loyalty, according to Alliance Data’s card services business, a provider of market-leading private label, co-brand, and business credit card programs.

The newly released study, “The Rules of NextGen Loyalty,” reveals how Gen Z and Millennials have been empowered by unique experiences, technology, and the power of choice to engage brands and experience loyalty in truly new ways.

“This study really unpacks the shopping and loyalty preferences of today’s youngest consumer segment,” said Shannon Andrick, vice president of marketing advancement for Alliance Data’s card services business. “One-to-one conversations with real people supported by in-depth research has provided a unique view into the mindset of today’s youngest generations and what they expect from brand relationships. The loyalty landscape has truly shifted from brands driving loyalty to brands earning loyalty.”

Conducted by Alliance Data’s Analytics & Insights Institute, “The Rules of NextGen Loyalty” study used a combination of qualitative and quantitative research methods including mobile diaries and digital app tracking to determine behaviors, follow-up one-on-one Skype conversations to provide context, and a survey to identify the differences, perspectives, and preferences among younger generations.

Some highlights from the report:

  • Loyalty is earned. Understanding the role of and influences on choice is more important than ever before: 63% of younger consumers agree they have many choices of where to shop, so a brand must show them loyalty to earn their business. Once brands recognize the unique motivations of Gen Z and Millennials, they have taken the critical first step in building deep brand connectivity and earning lasting loyalty.
  • Loyalty is complex. Traditionally, loyalty has been viewed as one-dimensional. Yet, loyalty is anything but simple. Research shows when it comes to life loyalty and brand loyalty, a continuum emerges spanning a range from functional to emotional. Different types of loyalty span the continuum from traditional, mostly functional loyalty, to brand love, emotional loyalty. Re-thinking a brand’s approach to loyalty means understanding that true loyalty requires a combination of function and emotion.
  • Loyalty is fragile. Today’s younger consumers are increasingly unforgiving. They are empowered by instant access and greater choice to want more and “put up” with less. In fact, 76% of younger consumers only give brands two to three chances before they stop shopping them. One in three consumers said nothing could be done when asked what a brand could do to win them back.

To check out the full report, click here.

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Pinterest is slowly rolling out its automated shopping ads to more marketers

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Pinterest is looking to continue to increase its portfolio of ads, though sometimes that can take a little while to see the light of day — and that includes a new-ish tool called Shopping Ads that’s slowly getting opened to more marketers and advertisers.

Getting new ad formats is important for a smaller company looking to build out an advertising business, as it has to show potential advertisers it can offer an array of tools to play with as they experiment with that service. The company said today that it’s expanding those shopping ad tools to hundreds of additional advertisers after launching a pilot program last year as it looks to continue to ramp up that tool. Pinterest has to be able to convince marketers that it should be a mainstay advertising purchase alongside Facebook and Google, which are able to routinely show returns in value for their advertising spend.

Shopping ads automatically create promoted pins from an existing product feed for a retailer. That means it’s basically one less thing for retailers to worry about as they add more and more content to the service. Most of Pinterest’s content online is business content as users share products they might be interested in one day buying or already own. As Pinterest gets more and more data on this, they’ll have a better handle on what ads work best, and hope that businesses will hand off the process in full to something more automated.

Pinterest hopes to capture that routine user behavior of planning what they want to do next, whether that’s an outfit to wear that day or some kind of major event or purchase down the line. Getting a hold of those users in the moment they might be interested in a new product is key to the company’s pitch to advertisers. You can more or less consider this a continued test as the company starts to slowly give the tool to the advertisers it works with before it becomes generally available. If it works, it could probably end up down the line in the hands of all advertisers, which could help for small- to medium-sized businesses without a lot of experience build out their early marketing campaigns.

Mobile – TechCrunch

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Skills: UK nation of IoT marketers, not engineers warns critical report

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The UK has hundreds of thousands of IoT professionals – just not the right ones, suggests a new employment report. Chris Middleton explains why the UK needs to take urgent action to rethink its workforce.

There are 28 qualified professionals for every Industry 4.0 post advertised in the UK, according to a new report.

The document finds that there are an average of 14,368 Industry 4.0 jobs advertised every year in the UK, and nearly 400,000 qualified professionals in total (399,719 people).

Over 150,000 of those professionals are either actively or passively searching for new work, it says, meaning that there is an average of 11 experienced people for every new job opportunity in the IoT and related areas.

The report has been produced by a new organisation called i-AMdigital, which describes itself as a “talent partner” for enterprises working with digital technologies such as IoT systems, robotics, AI, big data analytics, and 3D printing.

A nation of marketers

Delve into the granular detail, and the report reveals a fascinating – if not altogether positive – picture of the UK’s new technology sector.

Despite the prevalence of skilled and talented professionals in analytics, engineering, and IT systems – with degrees from universities such as Oxford, Cambridge, Manchester, and London’s Imperial College and University College – the UK is overwhelmingly sales and marketing focused, it says.

Nearly one-third (31 percent) of the entire Industry 4.0 workforce is in business development and sales positions – in roles such as IIoT or big data sales managers – versus just five percent in research and development, across areas such as AI and robotics.

Over one-quarter of those sales professionals want to change jobs, it finds, while 31 percent of the UK’s researchers are actively looking for new opportunities too. The report implies that the marketers may find it much easier to do that than the researchers.

With recent findings that the UK spends too little on R&D – 1.4 percent or less of GDP – compared with countries such as the US, Japan, France and Germany, the figures are troubling. With Brexit on the horizon, the UK needs to at least double its R&D spend to compete on the world stage.

With its historic strengths in areas such as computer science, AI, and the Web, Internet of Business suggests that the UK should aim even higher than three percent of GDP.

At the recent Westminster eForum on AI policy, attended by figures from government, academia, and business, a senior civil servant told Internet of Business that the UK is now being “actively excluded” from European science and technology research programmes in which it has previously had a central role.

Too many unfilled jobs

So what of the rest of the UK’s Industry 4.0 workforce?

Nineteen percent work in engineering roles, such as data scientist or machine learning engineer, says the report, and a further 19 per cent in more traditional IT positions. In both cases, one-quarter of those professionals are looking for new opportunities, says the report.

The remaining seven percent of industry experts are consultants, according to i-AMdigital.

This employment breakdown reveals another big challenge for the UK’s IoT and Industry 4.0 sector: 37 percent of all the relevant jobs advertised in the UK are in traditional IT roles. That’s nearly twice the number that are in sales (20 percent) or specialist engineering (22 percent). Just four percent of advertised jobs are in marketing, and three percent in consulting.

In other words, the UK market is flooded with marketers and sales people when it really needs to be full of qualified IT workers who can fill tech positions.

There are seven active professionals for every sales job, adds the report, and also for every R&D post. However, the survey demonstrates that there are different explanations for this parity: there are far too many marketers and far too few research roles.

This reinforces both anecdotal employer evidence and the findings of several local jobs surveys: the UK has countless unfilled IT vacancies, even in supposed digital hotspots, such as Brighton or Manchester.

In a world of social platforms and surface noise, it seems that the UK is overly focused on selling things that it doesn’t know how to produce or run itself.

The report also finds a strong bias towards London and the South-East. Forty-three percent of Industry 4.0 jobs are in London, it says, versus just two percent apiece in other hotspots, such as Manchester, Birmingham, and Bristol, and just one percent in Edinburgh.

More, the report reveals that many Industry 4.0 professionals are working for a small number of major companies, such as Accenture, Google, IBM, Microsoft, Deloitte, PwC, KPMG, Boston Consulting Group, and EY. In short, the big consultancies and systems integrators are mopping up the UK’s talent – which is perhaps no surprise.

However, with so little investment being put into R&D nationally, that focus on working for big-ticket, overseas giants is likely to remain – despite the success of innovation zones and startup hubs, such as Tech City, Sensor City, and others.

Internet of Business says

The UK’s track record in innovation is second to none. And it’s good to know that the country’s IoT and Industry 4.0 market has 400,000 qualified and experienced workers: that’s a positive message. But in other respects, these findings ought to ring alarm bells in Whitehall and among employers. 

Here’s why. First, the government has refocused its industrial strategy on AI, robotics, and autonomous systems, with a new Office for AI and other welcome initiatives. This means that digital expertise is critical, and Whitehall is funding new PhD opportunities, and more. That’s good news.

However, it’s clear that – at present – the UK has the wrong workforce mix for an ambitious, independent future. The country urgently needs to refocus on R&D and on nurturing the hard skills and experience in the technology sector. Not just from the top down, but also from the ground up at local level.

At present, the UK has too few research positions for its world-leading experts, too many unfilled digital posts in its big towns and cities, and a job market full of marketers and sales people.

More, the UK is overly reliant on London and on a small number of big companies.

With reports that several banks are reconsidering their positions in London, post-Brexit, and news that Unilever – the UK’s third biggest company – is quitting the country for the Netherlands after almost a century, there is a risk that other major employers and IP owners may follow.

The facts are stark: if the big consultancies, IT giants, and systems integrators think about leaving too, then the UK will be in big trouble. And that’s not a message that will be easy for thousands of marketers to sell.

• i-AMdigital has produced similar reports on the US and European markets, which we will publish soon.

Read more: South Korea most automated nation on earth, says report. The UK? Going nowhere

Read more: IoT sends demand for mobile skills soaring, say recruitment experts

Read more: Inmarsat research: skills gap threatens IoT innovation in energy sector


IoTBuild is coming to San Francisco, CA on March 27 & 28, 2018 – Sign up to learn all you need to know about building an IoT ecosystem.IoT Build

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App Marketers Turn AI and Machine Learning To Drive Growth

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Did you know that 80 percent of users churn within three months of downloading an app? That’s because most apps are marketed to the masses and not necessarily to the right customers.

Oftentimes, the goal of app marketing is to reach as many consumers as possible with the hopes of recruiting en masse and converting at better-than-average ratios. But part of the challenge for marketers is that many of today’s strategies are driven by metrics that don’t link to advanced user targeting and growth.

More specifically, app marketers aren’t using available data strategically to deliver productive user experiences that ultimately drive greater business profitability.

Now more than ever, marketers must shift from tracking traditional vanity metrics to measuring the very things that contribute to retention and growth. More and more, successful companies are investing in customer-centric metrics such as CLV (customer lifetime value) to gain intelligent, consumer-centered insights that not only identify the most valuable customers but also key behaviors and preferences to continually improve consumers’ experiences and journey.

Next-generation marketing and CX are about identifying and engaging valuable consumers

CLV is more important than apps in isolation. It helps apps and other touch points work together to deliver value-added, cohesive experiences.

CLV measures the value a consumer represents to the business across all interactions over their lifetime, not just a single transaction or touch point. That is ultimately the definition of customer experience. It is the sum of all moments a customer has with your brand throughout their life cycle. Marketing and customer engagement is now a cross-functional mandate.

Not all app users are the right users. If you use the Pareto Principle, you can assume that 80 percent of business value is attributed to 20 percent of your active consumers. While these percentages aren’t by any means a standard, they do emphasize the need to identify and cultivate the important customers who drive your business.

Instead of casting a wide net and attracting as many users as possible in the hopes of retaining a reasonably active base, CLV tied to artificial intelligence (AI) and machine learning focuses marketers and also developers on targeted engagement and growth. The idea is to drive profit by investing in more value-added user experiences and personalized offers. Doing so intentionally cultivates meaningful relationships with key customers.

Next-generation customer engagement is about cross-functional collaboration and data sharing

Unfortunately, customer experience today is largely siloed. Marketing, mobile, in-store, e-commerce, digital and so on are not collaborating nor operating against the same customer and market data. But that’s all about to change with the proliferation of AI and machine learning tied to smart CLV initiatives.

When the goal is to deliver targeted and integrated experiences, not just in-app, but across each touch point and the life cycle overall, companies create a truly customer-centric approach. AI then helps brands get a more complete, shared view and understanding of customer behaviors and expectations.

Additionally, AI-driven customer-centricity fosters cross-functional collaboration and data sharing that, by design, boosts customer experiences, along with CLV and business growth.

Identify highest-value customers and deliver targeted experiences

AI/machine learning platforms offer intelligent insights when pointed in the right direction. Successful brands study how much revenue highest-value customers drive over their lifetime and how much it costs to manage those relationships. And they examine CLV across all channels to get a holistic view of high-value behavior in all interactions. When the system can analyze important traits of high-value users, it can learn how to optimize CLV.

For example, to reach potential high-value customers, AI/machine learning uses data from existing high-value customers to optimize campaigns and touch points. In a study by Bain aimed at retail banking, it was found that it costs banks $ 4 every time a customer calls or visits. However, if consumers can complete the transaction via an app, it costs only 10 cents.

The key is to deliver capabilities in ways that consumers prefer and appreciate. Imagine how much AI and machine learning could additionally uncover when tasked with identifying friction points and new opportunities.

AI and CLV call for a new customer-centric playbook

You’ve probably heard time and time again that it costs more to acquire a new customer than to retain one. Brands that are winning prioritize CLV and AI and are drafting the playbook as they go. They:

  • develop a customer-centric mindset.
  • open doors between silos around in-store, digital and mobile so teams can focus on one clear business goal, rather than individual metrics (such as engagement or clicks).
  • align customer-facing groups to a business outcome such as CLV and promote cross-functional collaboration and data sharing to assemble a holistic view of the customer across all touch points.
  • understand who their highest-value customers are, how much revenue they drive over their lifetime and how much it costs to manage the relationship — across all channels.
  • focus on measuring and communicating clear business goals rather than individual or vanity metrics.

AI and machine learning improve both by using existing data without cognitive bias. The more the system learns, the more it optimizes.

In the end, not all customers are created equal. By identifying those who drive value, how and why, you can learn how to design and deliver personalized value to them and enhance customer engagement and experiences to grow your business now and over time.

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Amobee Unveils Custom Bid Algorithms for Marketers

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MMW learned ahead of the weekend that Amobee — a leading global digital marketing technology company serving brands and agencies — has rolled out enhancements to its platform that allow buyers to deploy custom data sets into Amobee’s bid modeling system. The feature launch empowers advertisers and their agencies to tailor their bid strategies against the data signals that matter most to them.

As an initial proof of concept, Amobee partnered with TruSignal, Inc., a leader in predictive score marketing, to ingest its custom-built, predictive, people-based scores into the existing Amobee bidder and influence the real-time bids from the platform. Advertisers can leverage their own data models, and/or take advantage of TruSignal’s custom-built predictive scores, as they are fully integrated into the platform.

Amobee’s platform integration works by applying data from any provider as a variable that triggers real-time changes in an advertiser’s bid. By leveraging the power of the Amobee platform’s ability to integrate data, marketers can better fuel omnichannel engagement through cross-channel, programmatic media campaigns. With this unified offering, leading brands and agencies can plan and buy media for specific audiences in a more integrated way to maximize their investments across desktop, mobile, video and social.

“At Amobee, we are constantly seeking ways to maximize the results of client campaigns through enhanced decision making capabilities within the platform,” said Maxwell Knight, Amobee’s Vice President of Analytics Services. “By leveraging the power of outside data and custom audience segments, we provide brands and agencies a highly customized solution that multiplies their ability to reach the right audience at the right place and right time, across every digital channel, on any device.”

Simplifying the delivery of advertising across all channels and screens, including video, display, mobile, and social, the platform includes the Amobee DSP, Amobee DMP, Brand Intelligence and DataMine analytics, which converts raw data into custom audience and campaign insights, empowering marketers to make more informed decisions.

To learn more, click here.

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Rockerbox Introduces New Tech to Help Marketers Identify and Activate Audiences

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Rockerbox launched on Tuesday its Recency Marketing Platform, the first technology solution that “enables companies to leverage recent user behaviors to improve their customer acquisition and marketing analytics.”
Rockerbox’s comprehensive platform focuses on the last 60 minutes of a prospect’s online activity across all channels and devices, helping marketers to optimize their media spend and increase conversions.

Initial Rockerbox clients have increased their post-click conversions by as much as 300% and have reduced their cost per acquisition on prospecting campaigns by as much as 60%.

Rockerbox research shows the last 60 minutes of online activity is a much better indicator of intent to purchase than other forms of information, such as audience segmentation based on broad generalizations and old data.

“We believe that if you knew what your customers and prospects were doing in the last hour, you would buy media differently,” said Ron Jacobson, Rockerbox Co-Founder and CEO. “For any company looking to convert shoppers into buyers, the secret is understanding your prospects. Our recency technology enables advertisers to zero in on the audience they know is ready to buy based on their most recent behavior. Just as gold miners used rocker boxes to separate dirt from gold, Rockerbox analyzes millions of ad impressions daily to surface insights that deliver greater return on ad spend.”

If you’re not familiar, Rockerbox has worked with household-name brands such as Discover, Hewlett Packard Enterprise, and Vimeo, along with top ad agencies including Horizon and Richard’s Group.

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Giving Marketers an Edge: Triton Digital Integrates MobPro’s DSP with a2x

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Triton Digital, a global technology and services leader to the digital audio industry, announced today the integration of its audio advertising marketplace, a2x, with Amsterdam-based, mobile media agency, MobPro.

According to a statement emailed to MMW, the partnership provides MobPro’s advertisers with the ability to add online audio from thousands of podcasters, radio broadcasters, web radios, and online music services from around the globe to their programmatic, omnichannel buys.

“Nowadays, consumers are all over the place, moving across all sorts of mobile platforms and apps at the speed of light. Our challenge is creating meaningful brand experiences for our advertisers across all of these platforms with content that seamlessly fits the user experience,” said Dominiek van Esse, Managing Director at MobPro. “With the integration of Triton Digital and the a2x marketplace, we’ve further expanded our horizons when it comes to bringing together brands and their audiences on smartphones. Our advertisers were very enthusiastic hearing about the latest audio developments, and look forward to reaching consumers through mobile radio campaigns.”

“The streaming audio industry is burgeoning in the Netherlands,” said Benjamin Masse, Managing Director, Market Development and Strategy at Triton Digital. “We are proud to have integrated MobPro with a2x, and look forward to helping their buyers leverage this growing and powerful medium to extend their reach and increase the efficiency of their omnichannel buys.”

To learn more about Triton Digital, click here.

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New Partners Help Marketers Access Deterministic Mobile B2B Data at Scale

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180byTwo announced this week that their audience data is available on adsquare’s mobile-first data exchange, enabling advertisers to precisely reach their B2B target group on the most personal device. 180byTwo specializes in deterministic mobile audience data sourced from premium B2B offline and online partners.

Through the strategic partnership with adsquare, 180byTwo is able to leverage their extensive data assets, which includes verified business listings, public tax filings, beacons, memberships, loyalty programs, associations, co-ops, SDKs and WiFi access points as well as various other sources of high-quality data. All of this has been elegantly stitched together to form quality actionable audience segments providing marketers with access to hard-to-reach B2B audiences.

180byTwo empowers brands to enhance their ability to see the full 360-degree view of their prospects and customers. Using 180byTwo enhanced segments and profiles, marketers are able to more efficiently target people regardless of where they are – at home, at work or at play.

The partnership between adsquare and 180byTwo introduces a next generation of mobile marketing capabilities with a uniquely differentiated data offering.

A provided statement notes that 180byTwo’s data is engineered from a broad and extensive network of data sources. Through the linking of over 80,000 personal and professional attributes of known people, 180byTwo is able to create highly accurate and targetable audiences.

“180byTwo offers one of the best-in-class global B2B data solutions. As deterministic data is at the heart of our platform, we believe that the partnership will enrich our current offering with verified and precise data sources from multiple data points for holistic audiences,” says Tom Laband, CEO and co-founder at adsquare, about the partnership.

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Opinion: Marketers Have to Start Thinking Seriously About Deep Learning

The following is a guest contributed post from Jeremy Fain, CEO and founder of Cognitiv.

A lot of people have asked me about my thoughts for 2018, and what I think the overarching trends in advertising technology and deep learning will be in the coming year. Far be it from me to disappoint my fans – so here’s my take on next year’s biggest topics:

  1. Marketers will have to start thinking seriously about deep learning.

AI has been a buzzword for the past several years, as clearly evidenced by the vast numbers of products claiming to be AI currently on the market. While most of these applications don’t really live up to the picture of AI that most people have in their heads of a Jetsons-like robot, there have lately been a series of discoveries, most notably in the field of deep learning, that are sure to have a serious impact on the way that most businesses operate.

Deep learning and neural networks are at the heart of some of the most astonishing machine learning developments, from image recognition to the natural language processing that enables gadgets like Amazon’s Alexa and Google Home to operate. But access to the technology and insights of deep learning is no longer limited to the big players, as new tools have arrived to bring the computing power and analytical insight of deep learning to marketers.

In some ways, the current wave of AI products is good, because it means that more people, including marketers, have become aware of what AI has the potential to do as well as its possible limitations. As more advanced forms of AI become market-ready, deep learning will be at the forefront of any of those conversations, and marketers will begin to understand the value of using deep learning to buy media and create audiences to advertise against, becoming better equipped to lead their businesses to success in 2018 and beyond.

  1. Mobile ad networks will be forced to become more transparent.

Before programmatic became a mainstay of digital advertising, ad networks performed an important function as an intermediary between digital advertisers and publishers. They could help publishers find buyers for their inventory, and they could put inventory from multiple publishers together to make it easier for advertisers to buy. Because most inventory came from smaller publishers, it cost less, and was a cost-effective value proposition for most advertisers.

The rise of programmatic, however, created a way for advertisers to directly buy from any publisher with added transparency into pricing and websites.  Suddenly, ad networks had to deliver more value than just inventory aggregation.  This transition took place in the traditional digital display world years ago but has yet to take place in mobile advertising.  2018 will be the year where mobile ad networks will have to prove their added costs or face the reality that mobile advertisers have begun to use programmatic for user acquisition and retention campaigns.

  1. Header bidding will become a problem on the agency side, so its use will diminish.

This relates in some ways to the general theme of greater transparency in the digital advertising markets. Header bidding code allows a publisher to offer the same impression in multiple exchanges at the same time, ultimately leading to the impression being sold for a higher price than if a single exchange was used. This means advertisers are bidding multiple times on the same inventory and, because of the nature of programmatic, they are likely paying more.  Originally, header bidding was meant to allow advertisers to compete programmatically for all of a publisher’s inventory, instead of just the unsold “dregs” that were left over after directly sold insertion orders had been fulfilled.  The technology, however, is now being used to offer the same impression through multiple exchanges to the same DSP.  This has driven DSP costs up because of the skyrocketing number of “duplicate” bid requests being received from multiple exchanges and has given rise to an entirely new ad tech industry of trying to sift through these duplicate impression requests.

A much more elegant, and likely solution in 2018, will be that advertisers through their agencies will require the use of the ads.txt standard.  This file is meant to be made available by every publisher wishing to sell their inventory programmatically.  It lists the exchanges their inventory is available in.  Ads.txt was created to stop a flagrant type of fraud where websites list themselves inaccurately as more valuable websites, but Ads.txt can also be a great tool to cut down on duplicate impressions.  A publisher has the right to sell its inventory any way it chooses, and different exchanges may have different strengths for different types of inventory,  so I do not predict (or advise) that advertisers will require pubs use only one exchange.  In the end though, I predict that header bidding as it is used today is on its way out.  The costs are too high for DSPs and advertisers will realize they are bidding on the same exact impression and ultimately paying a higher price.  I’ve never met an advertiser that liked that.

If there’s any overarching theme here, it’s the idea that marketers and advertisers are constantly getting more savvy about the tools they’re using, whether it’s AI, ad networks, or ad exchanges.  They will begin asking tough questions and demanding accountability in 2018 in new ways that will, as always, lead to big changes in the advertising ecosystem.

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