Ad Tech

Ex-Googler Matt McGowan is president of Adestra, a leading martech company boasting double digit growth for more than a decade. McGowan believes that email as a martech solution has been often overlooked for many reasons, none of which have anything to do with its efficacy and results. We spoke with him about email’s unsung talents and the results that his clients have seen.

Email is often missing when it comes to high-level discussions of marketing strategy in the media. Why is that?

It’s not flashy, and compared to other marketing channels the costs to effectively reach customers and clients are considerably low. Email is the workhorse of the digital space and has been around for as long as the internet. Yet, it’s often overlooked cause it’s “just email”. It’s changing a bit as we have more conversations on the addressability of the consumer (identification) through email addresses and the marketer’s access to data. The other reason is that email is not broken enough. Even when done poorly, it performs higher in terms of ROI than other channels. Whereas in other channels, when you do it wrong, you don’t see the ROI. We should be talking more about email. We should be focusing on the importance of the proactive communicative power of email. We should be talking more about email as a tool to power a company’s retention and loyalty programs.

How do you begin to shift the narrative, since a lot of people seem to think of “spam” when they hear the phrase “email marketing”.

Often these thoughts originate with “I get a lot of emails that don’t resonate with me”. Not much different than “I see a lot of ads that don’t resonate with me.” It’s more a commentary on relevancy. It’s associated with spam merely because it’s email that the consumer does not want until they want it. But it’s their choice to engage, it’s not the email that gets them involved. If we want to change this stereotype, then what we need to do is focus on First-Person Marketing strategies that work to recognize the individual not the audience. Individual engagement is quite powerful and there are platforms out there that facilitate this.

In terms of results, what does email offer and how does it stack up against industry averages?

The DMA, IAB, AAAA, and other associations and regulatory bodies in the industry have for years have claimed that email has the highest ROI. The low-cost, high return marketing channel. What I would rather see is investment and budget allocation that align to the ROI levels. Invest more and make more.

There’s a lot of confusion with reference to data integration and email marketing. Can you run us through a quick primer?

What the marketer wants is access to data. Data that powers better decisions on consumer engagement strategies across the digital spectrum for both retention and acquisition based marketing. This data can be used to better target and appeal to the consumer in a relevant way. Yet, the marketer needs not only the data, but also the resources to do something with the data that is available. This takes a greater focus on strategy and operations. A greater focus on tactics that can empower the data to be used dynamically within the email. With this bridge established, the data integrations that are essential to a relevant conversation can be actualized. There are best-in-class point solutions that allow this to happen because they can “speak” to each other in ways the pre-packaged stacks cannot. Anti-intuitive I know.

What does a CMO need to be aware of in developing an email marketing plan?

That like any channel, it needs to be invested in. That the mere cost of an email is not the end-point. Like any good strategy, complexity is key and email cannot be seen as just a communication medium that is “easy”. Email should be intricate, complex and involve as much effort as we take with other channels. Moreover, the email marketer should not operate in a silo, she should be part of the team, fully integrated with her colleagues. Models and propensity analysis are key to making it work. For the CMO, do the research, invite the ESP into your office, put some working sessions in the calendar. There is a lot to learn and discuss.

What kind of results have you seen with clients who began adopting a more strategic approach to email?

Oddly enough, Adestra has an amazing content library of not only campaigns that had remarkable success, but case studies that show in every vertical, when email is really invested in, the results are astounding. For example, our client NakedWines.com, one of the largest and definitely most loved global wine distributors on the planet, implemented a propensity-based email that is constructed based on the individual user’s propensity for selecting certain wines. They achieved a 40% conversion rate. That number is enough to make any CMO blush. It’s these kinds of examples, and many more, that keep us excited about the future of the industry and the power of data.

Learn more about Adestra here.

Sprinklr is the embodiment of a tech unicorn. Solution-focused, data-driven, and generating buzz consistently, Sprinklr boasts a valuation far north of $1.8 billion (at the time of this piece). We spoke with the charismatic founder and CEO, Ragy Thomas, about his company’s startup journey and why NYC was the right place to launch.

Tell us about your company’s beginnings. What did you see (or not see) in the market that led you to launch?
In 2008, I was President of Epsilon Interactive Services Group, a division of Alliance Data Systems that provided email marketing technology and interactive agency services. During this time, I saw that email was changing the way that businesses communicated with customers and realized that the same thing would happen with social media. It was clear that social would create new opportunities and new challenges for how brands communicate with customers.

In 2009, I launched Sprinklr to solve the biggest problem facing every modern enterprise in today’s social world — managing experiences across every single customer touchpoint. Today, Sprinklr provides the most complete social media and customer experience management platform for the enterprise. We help more than 1,200 of the world’s largest brands do marketing, advertising, research, care, and commerce on Facebook, Twitter, LinkedIn, and 22 other social channels globally – all on one integrated platform.

What were some of the biggest challenges that your team faced at zero stage?
In the early days of Sprinklr, we were often ridiculed for our strategy. We pursued a platform strategy as opposed to a point solutions strategy, and we were ridiculed for this. If you go back six years, the startup world was going through the notion that you must be really specialized and simple and we just didn’t believe in that. We believed that big businesses needed a comprehensive, unified platform to interact with their customers in a human, intuitive way.

We learned not to get distracted by little things, and focus on the big picture. No matter what’s going on in the market, the philosophy I’ve used to build my business has always been the same: a relentless focus on fundamentals. We’ve focused on revenue growth and creating tangible value for customers with a credible solution to an incredibly pervasive problem. Those are the things that matter, and the things that will always win in the end.

Let’s look at the science behind your product. What makes it different from other offerings in this space?
Sprinklr is the only unified customer experience management platform purpose-built for today’s social world. From the beginning, we set out to build a powerful social media management platform that integrates with an organization’s existing infrastructure and allows employees across every customer-facing department to collaborate with unified data. We provide an external API available to build applications on Sprinklr and have over 100 total connections, including CRM, marketing automation, asset management, profile and message enrichment, and analytics systems.

We pride ourselves in the ability to drive real business results for brands. In fact, the average Sprinklr customer sees a 172% return on their investment in the first year of their contract and 236% in their second year.

Another key differentiator for Sprinklr is our vast relationships with channel partners. Unlike competitors, Sprinklr has a direct relationship and access to more than 21 channel partners, including Twitter, Instagram, Snapchat, Facebook and more. This, along with content for over 120 countries in over 110 languages, paired with the breadth of enterprise platform applications (i.e. Salesforce, SAP, Marketo, Adobe and more) allow brands to achieve a true 360-degree view of the customer by having a presence at every user touchpoint.

Lastly, Sprinklr’s platform is proudly secure for our customers. Leading financial services companies like JPMorgan Chase, Citi, and Wells Fargo depend on Sprinklr because of our governance, compliance and security capabilities. Sprinklr has top-tier security and compliance certifications, such as SOC 1 and 2 certifications, FFIEC, and more.

How do you translate your brand’s message in a way that gets you heard above the noise?
We only have one “true north” at Sprinklr: creating value for our customers. We obsess over it. Sprinklr creates value by helping companies solve their problems, and the Fortune 500 brands we work with have a very big one on their hands: figuring how to engage with each of their customers in a meaningful way, at scale, across every social channel. We provide a unique solution to an obvious problem, and that leads to immense value for our customers.

There is a lot of noise around digital transformation and social media crises, but we don’t feed into the noise. We provide the solution to the noise. And that’s how we get heard.

Let’s talk about brand values. What means the most to your company besides industry success?
Sprinklr is unique in that its core values come directly up from the company’s employees, not down from the boardroom. Our core values are: It’s ok; Sprinkle, don’t shout; Fix it don’t complain; Never ever give up; and Passionately and genuinely care.

These are the personality traits and core values that our company runs on. They’re written on our walls, woven into emails, mentioned in board meetings. They keep us unified.

Success to me is about the people. I want my team to feel empowered, inspired and equipped to tackle any challenge. As we continue to grow and scale as a business, maintaining strong values and a positive culture is critical.

There’s always been this rivalry between Silicon Valley and NYC in tech. What are some tangible benefits to being based in NYC?
New York was an easy choice for me to build our headquarters. My life is here and it’s truly a one-of-a-kind city. The business landscape in New York is incredibly challenging, without a doubt, but it’s the right kind of challenges you need as a startup. If you can do it in New York, you can do it anywhere.

For Sprinklr, we also had a big advantage by being physically close to our prospects. We knew we wanted to target the enterprise and Fortune 500 landscape. Being one of the biggest business meccas in the world, and having a big focus on the advertising and marketing space, it was a perfect fit.

Name one place in your company’s NYC neighborhood (restaurant, cafe, etc) that you and your team just can’t live without.
Many employees in our NYC office occasionally moonlight as karaoke superstars and head to Koreatown for all the karaoke spots. Our office is also close to Bryant Park, which is our year-round destination for grabbing a breath of fresh air and our go-to outdoor spot to hang out and relax.

 

Sociomantic, part of dunnhumby, is an ad tech company that has grown in 8 years from a bootstrapped startup to reach 6 continents, 60+ markets, and employ 250+ team members. We sat down with JB Brokaw, North American President of Sociomantic Labs, to discuss the company’s incredible trajectory.

Tell us about your company’s beginnings. What did you see (or not see) in the market that led you to launch?

Sociomantic got its start in Berlin at a time when online advertising was just taking off. The founders recognized the opportunity to help advertisers cut through the noise and increase engagement with their audiences, and by 2010 Sociomantic made waves as the first European demand-side platform to develop real-time bidding for e-commerce advertisers. The company name is a combination of sociology (study of people) and semantics (study of meaning in language), and represents our ability to help advertisers reach individuals across the globe by delivering personalized, meaningful messaging that inspires action.

Five years in, we were acquired by dunnhumby, a leading customer science company that harnesses consumer data to drive loyalty for retailers. This partnership has offered even more opportunities to provide relevant, personalized advertising at scale.

What were some of the biggest challenges that your team faced at zero stage?

When we launched in the US, the market was already quite saturated. We definitely experienced the “small fish in a big pond” syndrome and had to prove ourselves amidst competitors that were much larger than us in terms of headcount and marketing budget. It was daunting at first, but we soon saw that we can hold our own against the competition, and today the US is our largest market.

We also struggled with having fewer people on the ground here in the beginning; initially our creative service team was based out of Berlin, which posed some challenges as were are often under strict design deadlines from clients. Fortunately, as we’ve grown over the years we’ve built out a strong team here in NYC, including some very talented in-house designers.

Let’s look at the science behind your product. What makes it different from other offerings in this space?

The real-time bidding aspect of programmatic advertising is quite complex and it’s often criticized for its lack of transparency relating to where and how ad exchanges and supply-side partners place ads and spend advertisers’ dollars. One thing that truly sets us apart from our competitors is the Supply Quality Index (SQX), our proprietary bidding algorithm that allows us to grade the programmatic inventory suppliers we work with based on their levels of transparency, performance and inventory quality. Simply put, if they don’t measure up to our high standards, we refuse to work with them.

Another key differentiator is the complete customization of our dynamic creative, an area where we continue to receive rave reviews. Unlike other companies that only provide templates for their banner ads, our creative services team works closely with each client to build custom display ads that are aligned with its brand image. Our designers are constantly experimenting with new types of formats as well, and our portfolio of creative offerings continues to evolve each day.

How do you translate your brand’s message in a way that gets you heard above the noise?

In this industry, there are a hundred different companies all touting that their platform is the best, and when you examine the nuts and bolts, the features all seem rather similar. I’m confident that our technology works and is superior to many of our competitors — after all, we were 100% bootstrapped up until our acquisition, and we would not have survived if our technology was not legit. However, we don’t lead our messaging based off the strength of our technology alone, but on a joint stage with our excellent level of service.

Our commitment to service means that we operate more like an agency, and deliberately assign a select few clients to each of our account managers to ensure that every account is getting the full attention it needs. Programmatic advertising is often mistaken to be synonymous with automation, but it’s the human aspect of the business — analyzing the daily reporting, making data-fueled recommendations on optimizations, and knowing when to pull back spending to avoid unnecessary waste of ad dollars — that is the most important. We find that by leading with service, we keep our clients’ happy and we also get new prospects through valuable word-of-mouth marketing, too.

Let’s talk about brand values. What means the most to your company besides industry success?

I’ve seen a lot of changes at Sociomantic during the four years I’ve been on board, but the company’s continued focus on integrity has remained consistent throughout and has shaped our business model. Maintaining integrity in what we do means being as honest and transparent as possible about our technology, which is why we’ve made it a priority to unveil features on our platform that you wouldn’t see from our competitors. On the other hand, it could also mean turning down potential business that we do not feel would have long-term success for the brand. As a trusted industry partner, we strive to be upfront at all times, even if it means referring brands to other parties that would be better suited for their needs.

There’s always been this rivalry between Silicon Valley and NYC in tech. What are some tangible benefits to being based in NYC?

Silicon Valley may be the tech hub, but New York City has been the advertising capital of the country from the start! We work with advertisers across the country and have team members all over — from Miami to Dallas to San Francisco — but it’s important for us to be here to keep a pulse on what’s going on. Plus, we are an international team, and being on the east coast means we’re only a short flight away from our Berlin headquarters for our annual global department summits.

Name one place in your company’s NYC neighborhood that you and your team just can’t live without.

We just recently moved offices from Flatiron to near the Empire State Building, but one place that we still frequent is the Shake Shack at Madison Square Park. Nothing beats sitting in the park with their burgers and shakes on a sunny afternoon, and we’ve gotten the timing down to avoid the crazy lines.

Learn more about Sociomantic here.

My6sense is a native advertising platform that enables ad networks and media companies to build their own customized ads for mobile and web content. The company was founded by Avinoam Rubinstein, a serial entrepreneur with over 20 years of experience in the industry. He was previously CEO of Atrica (acquired by Nokia), and GM at NiceCom.

We sat down with Avinoam to learn about his company’s startup journey.

Tell us about your company’s beginnings. What did you see (or not see) in the market that led you to launch?

We established my6sense because we believed that digital platforms are best suited to provide users with personalized and relevant content. With the advancements driven by machine learning technology, including our own Digital Intuition® advanced machine learning algorithms and optimization engine, we’re even closer to realizing our technology-driven vision of enabling publishers to offer the right content to the right users at the right time.

Specifically, my6sense’s technology learns user behaviors, publisher patterns, and context in order to match the content with the user. Our Digital Intuition® technology is able to offer users content which is both more relevant and more personal. This enables publishers and supply partners to generate greater revenue as marketers benefit from higher engagement rates.

What were some of the biggest challenges that your team faced at zero stage?

As an engineer, the biggest challenge is always getting the technology right. Once the technology works, everything else falls into place because if you build it ‘right’, they really do come.

Digital publishing is a dynamic market which has evolved over the years, and today, we apply our AI and machine learning technology for our White Label Programmatic Native Ad Platform and Exchange, which enables more than 100 ad serving and media group clients to improve performance and user experience through better optimization, relevancy, and personalization of their native content and ads.

Let’s look at the science behind your product. What makes it different from other offerings in this space?

What sets my6sense apart among the native programmatic solutions is that ours is the only offering which is a fully programmatic native exchange solution for multi-item native ad units with comprehensive organic content recirculation. Only my6sense enables our clients and partners to mix a recommendation widget, like Outbrain or Taboola offer, with any in-feed, in-ad or other custom native unit with any number of ads and units on a given page. And our Digital Intuition® machine learning technology further differentiates our solution by enabling better matching of content to users, resulting in better user engagement metrics for marketers and greater revenue for our supply side partners.

The my6sense white label programmatic native solution provides hierarchical business management tools for ad networks and media & publisher groups as well as comprehensive ad quality classifications and control, performance optimization and advanced policy rules. For our Demand Side Platforms (DSPs), my6sense offers a full native exchange with a built-in direct campaign manager for advertisers and ad-unit & yield manager for publishers. Our partners make use of my6sense’s flexible configurations, including a white labeled native ad network and exchange, owned managed private exchange for group publishers, and cross-network programmatically traded supply and demand.

How do you translate your brand’s message in a way that gets you heard above the noise?

A lot of companies pivot towards what’s hot, so when ‘native advertising’ become hot a couple of years ago, a lot of ad tech companies jumped on the native advertising bandwagon. My6sense’s initial technology was developed to serve more personalized and relevant content to users, so we already had technology which was optimized for native advertising. In that sense, my6sense is a company whose technology is ‘built for’ and not ‘pivoted into’ native advertising. And that’s why our focus is exclusively on native advertising today. This differentiation, coupled with the mix of native ad formats we enable our partners to run and the efficacy of our technology enables my6sense to stand out.

Let’s talk about brand values. What means the most to your company besides industry success?

What means the most to my6sense is satisfying the user/consumer.

We make money by recommending contextually relevant native advertising and content for marketers via our partners, but if users don’t find the content and ads our technology recommends relevant, interesting and engaging, they won’t click. And if they don’t click and engage, our partners will select different technology to power their native advertising and content.

Therefore, it all goes back to our ability to satisfy the user and in turn our customers and business partners.

There’s always been this rivalry between Silicon Valley and NYC in tech. What are some tangible benefits to being based in NYC?

For my6sense, there are two major benefits to being based in NYC. First, as an advertising technology company, New York City is the center of both the advertising and publishing industries which means that all of our prospective partners and customers are either based in NYC or have a large presence in town. The second major benefit for my6sense is that NYC is closer to Tel Aviv, where our R&D center is located, both in terms of time zones (7 hour difference versus a 10 hour difference between Israel and the West Coast) and in terms of the number and frequency of direct flights.

Name one place in your company’s NYC neighborhood (restaurant, cafe, etc) that you and your team just can’t live without.

Easy: Katz’s Deli. There is nothing else like it anywhere, and yet it’s quintessentially New York. It’s a little out of our neighborhood but worth the effort.

Learn more about my6sense here.

 

Powered by Guardian.co.ukThis article titled “‘A white mask worked better’: why algorithms are not colour blind” was written by Ian Tucker, for The Observer on Sunday 28th May 2017 12.27 UTC

Joy Buolamwini is a graduate researcher at the MIT Media Lab and founder of the Algorithmic Justice League – an organisation that aims to challenge the biases in decision-making software. She grew up in Mississippi, gained a Rhodes scholarship, and she is also a Fulbright fellow, an Astronaut scholar and a Google Anita Borg scholar. Earlier this year she won a $50,000 scholarship funded by the makers of the film Hidden Figures for her work fighting coded discrimination.

A lot of your work concerns facial recognition technology. How did you become interested in that area?
When I was a computer science undergraduate I was working on social robotics – the robots use computer vision to detect the humans they socialise with. I discovered I had a hard time being detected by the robot compared to lighter-skinned people. At the time I thought this was a one-off thing and that people would fix this.

Later I was in Hong Kong for an entrepreneur event where I tried out another social robot and ran into similar problems. I asked about the code that they used and it turned out we’d used the same open-source code for face detection – this is where I started to get a sense that unconscious bias might feed into the technology that we create. But again I assumed people would fix this.

So I was very surprised to come to the Media Lab about half a decade later as a graduate student, and run into the same problem. I found wearing a white mask worked better than using my actual face.

This is when I thought, you’ve known about this for some time, maybe it’s time to speak up.

How does this problem come about?
Within the facial recognition community you have benchmark data sets which are meant to show the performance of various algorithms so you can compare them. There is an assumption that if you do well on the benchmarks then you’re doing well overall. But we haven’t questioned the representativeness of the benchmarks, so if we do well on that benchmark we give ourselves a false notion of progress.

Joy Buolamwini at TED in November 2016.

It seems incredible that the people putting together these benchmarks don’t realise how undiverse they are.
When we look at it now it seems very obvious, but with work in a research lab, I understand you do the “down the hall test” – you’re putting this together quickly, you have a deadline, I can see why these skews have come about. Collecting data, particularly diverse data, is not an easy thing.

Outside of the lab, isn’t it difficult to tell that you’re discriminated against by an algorithm?
Absolutely, you don’t even know it’s an option. We’re trying to identify bias, to point out cases where bias can occur so people can know what to look out for, but also develop tools where the creators of systems can check for a bias in their design.

Instead of getting a system that works well for 98% of people in this data set, we want to know how well it works for different demographic groups. Let’s say you’re using systems that have been trained on lighter faces but the people most impacted by the use of this system have darker faces, is it fair to use that system on this specific population?

Georgetown Law recently found that one in two adults in the US has their face in the facial recognition network. That network can be searched using algorithms that haven’t been audited for accuracy. I view this as another red flag for why it matters that we highlight bias and provide tools to identify and mitigate it.

Besides facial recognition what areas have an algorithm problem?
The rise of automation and the increased reliance on algorithms for high-stakes decisions such as whether someone gets insurance of not, your likelihood to default on a loan or somebody’s risk of recidivism means this is something that needs to be addressed. Even admissions decisions are increasingly automated – what school our children go to and what opportunities they have. We don’t have to bring the structural inequalities of the past into the future we create, but that’s only going to happen if we are intentional.

If these systems are based on old data isn’t the danger that they simply preserve the status quo?
Absolutely. A study on Google found that ads for executive level positions were more likely to be shown to men than women – if you’re trying to determine who the ideal candidate is and all you have is historical data to go on, you’re going to present an ideal candidate which is based on the values of the past. Our past dwells within our algorithms. We know our past is unequal but to create a more equal future we have to look at the characteristics that we are optimising for. Who is represented? Who isn’t represented?

Isn’t there a counter-argument to transparency and openness for algorithms? One, that they are commercially sensitive and two, that once in the open they can be manipulated or gamed by hackers?
I definitely understand companies want to keep their algorithms proprietary because that gives them a competitive advantage, and depending on the types of decisions that are being made and the country they are operating in, that can be protected.

When you’re dealing with deep neural networks that are not necessarily transparent in the first place, another way of being accountable is being transparent about the outcomes and about the bias it has been tested for. Others have been working on black box testing for automated decision-making systems. You can keep your secret sauce secret, but we need to know, given these inputs, whether there is any bias across gender, ethnicity in the decisions being made.

Thinking about yourself – growing up in Mississippi, a Rhodes Scholar, a Fulbright Fellow and now at MIT – do you wonder that if those admissions decisions had been taken by algorithms you might not have ended up where you are?
If we’re thinking likely probabilities in the tech world, black women are in the 1%. But when I look at the opportunities I have had, I am a particular type of person who would do well. I come from a household where I have two college-educated parents – my grandfather was a professor in school of pharmacy in Ghana – so when you look at other people who have had the opportunity to become a Rhodes Scholar or do a Fulbright I very much fit those patterns. Yes, I’ve worked hard and I’ve had to overcome many obstacles but at the same time I’ve been positioned to do well by other metrics. So it depends on what you choose to focus on – looking from an identity perspective it’s as a very different story.

In the introduction to Hidden Figures the author Margot Lee Shetterly talks about how growing up near Nasa’s Langley Research Center in the 1960s led her to believe that it was standard for African Americans to be engineers, mathematicians and scientists…
That it becomes your norm. The movie reminded me of how important representation is. We have a very narrow vision of what technology can enable right now because we have very low participation. I’m excited to see what people create when it’s no longer just the domain of the tech elite, what happens when we open this up, that’s what I want to be part of enabling.

The headline of this article was amended on 28 May 2017 to better reflect the content of the interview.

guardian.co.uk © Guardian News & Media Limited 2010

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According to a recent study by Operative, publishers are finding ad tech so confusing and riddled with pitfalls that many are becoming just as disenchanted with programmatic ad buying as advertisers.

That doesn’t mean that advertisers and publishers aren’t still pouring into the ecosystem; automated digital ad sales have risen steadily for years, but the increased spend and inventory shifts appear to be out of necessity rather than any widespread belief that ad tech is a win-win system.

The Operative survey of more than 350 publishers and advertisers revealed that publishers are earning less than 10% of their income through automated buying. Hindered by a lack of operational resources to successfully manage a shift towards ad tech while continuing to support direct sales growth, many publishers remain ill-at-ease with moving full-on towards programmatic until the benefits and risks are clear.

Some of the key sticking points mentioned were an absence of transparency in the “tech” side of ad tech, and some publishers’ lack of in-depth knowledge of how programmatic translates from high concept to day-to-day operations and ROI benchmarks.

According to a study by Optimal in cooperation with Wells Fargo, publishers are deeply concerned with the difficulty of managing attribution, as well as the rise of ad blockers, the use of which is predicted to cost publishers an estimated $12.5 billion in lost revenue globally in 2017.

Publishers’ mounting uneasiness was perhaps inspired by advertisers’ overall mistrust of ad tech as an industry. A recent study by Signal and eConsultancy, reported by The Harvard Business Review, showed that only 12%, from a pool of 350 senior marketing executives, felt “comfortable” with the ad buying ecosystem as it is.

According to another survey of 59 brand advertisers from the World Federation of Advertisers (WFA)– which represents more than $70 billion in ad spend–almost 90% of respondents were reevaluating their media buying budgets because of programmatic’s enduring client-facing problems. Despite a significant rise in brands venturing into programmatic during the past three years, issues such as rampant ad fraud, the difficulty of identifying excessive transaction fees, and the complexity of audience measurement were cited as significant concerns.

While programmatic buys are predicted to account for 73% of digital ad spend this year, approximately 60% of leading ad agency buyers described themselves as “fearful” of the ecosystem’s haphazard range of audience quality, up from 48% in 2015.

Recently, leading industry standards organizations such as The Internet Advertising Bureau (IAB) have begun offering educational programming and analytics tools– such as a free CPM calculator released in 2016– which were designed to make the ad buying process more transparent for advertisers.

“There is a lack of communication between buyers and sellers about the ad technologies being used by each side, as well as the fees that are removed in the bidding process before publishers’ net CPMs are realized,” the accompanying IAB report read. “This creates a discrepancy between buy and sell side inventory valuations, which has the potential to erode trust in the marketplace and reduce inventory liquidity.”

 

Tom Phillips was CEO of Dstillery in 2014. This story originally appeared in The Advertising Technology Review in 2014.

Advertising technology company Dstillery, formerly Media6Degress, has raised $26 million in funding and worked with more than 400 leading brands across the globe. CEO Tom Phillips and Chief Scientist Claudia Perlich discussed key principles marketers need to keep in mind when looking at Big Data in a post-cookie world.

There’s been a lot of talk about a post-cookie world.  How likely is it that this would occur sooner rather than later? How will it impact marketers?

The post-cookie world is already here, and is evident by the rise of apps, as well as browsers that limit the use of third-party cookies. Companies have already started deploying alternative approaches that use a “recipe” of tactics to find and target audiences. In addition, numerous companies are looking to provide a true multi-screen marketing solution for advertisers trying to engage with consumers, who are moving seamlessly between devices wherever they go. The cookie represents a declining part of the recipe, as other tactics such as statistical IDs, registered user data and location-based targeting gain traction. However, as much as most people think in terms of absolutes i.e., the “death of the cookie,” the reality is that the cookie will be around for a long time. The biggest challenge for marketers and ad tech vendors is to get non-cookie-based identifiers synched with the tools that measure performance of advertiser campaigns. If analytics providers and ad servers measure only cookie-based conversions, the impact of non-cookie-based targeting technology will be understated. For instance, today’s ad servers measure post-view conversion results using cookie-based technology. In most cases, post-view conversions on a Safari browser go uncounted. This problem has been recognized but considered on the fringe for some time now given the low penetration of Safari. Consumer adoption of non-cookie-based devices and digital media is making this an issue that needs to be addressed more urgently.

We hear so much about data these days, many marketers have become data-blind, believing that any data is good data. What do marketers need to look for when determining which data is relevant to crafting strategy? How should they address the data quality issue?

Claudia Perlich, Chief Scientist, Dstillery

There is an overload on the term ‘data.’ In the world of data science, data is the beginning, the raw ingredient. Imagine making a cake. Data is simply one ingredient — the flour. In order to turn the flour into a cake, you need a baker -a data scientist- and a recipe, which is the algorithm along with other ingredients. The marketer’s strategy is to offer your future mother-in-law a cake. Now it is true that if the flour, the data, is bad, the cake won’t be great. But the right cake may require a whole different recipe. Raw data is just a recording of facts about the world. For instance, did someone go to a website, did they click on an ad, etc. And as such, data is not good, bad, clean or dirty; it simply is. When it turns out that the data doesn’t lead to the results we expected, we consider it low-quality. For instance, what technically might qualify as a click, may not actually be a person that deliberately clicked on the ad in order to check out the offer. It may just be that the computer system recorded something that by technical definitions was a click. Software that has infected the browser could have generated that click, giving someone far away with no interest in the ad power to control the browser.

That relates to what we actually mean by “data,” it seems.

Most often when non-data scientists question the quality of the ‘data,’ it is really a question about something derived from the raw data, something considered an ‘insight.’ When we move to insights, or more generally any form of derived data, things start to get really tricky. At this point a lot more manipulation has gone into it, typically done by someone else. Now you have to figure out whether that means what you think it does. For instance, if someone gives you a number and tells you it’s the average of the age of your customers’ cookies taking action on your site, the number they’ve shared almost surely doesn’t mean what you think it does. It depends on many factors like the percentage of traffic coming from a specific device or browser, the percentage of cookies disabled, whether one removes the zero ages or not, etc. Any number between one hour and 90 days is plausible, but only one is consistent with what you think it means. So the only solution is a strong push for data literacy. Everyone using data has to really know what it means and buying data or getting data from a third-party makes this nearly impossible.

How will the possibility of more screens, increased privacy regulations and the growing importance of content marketing impact traditional models of behavioral targeting? What is Dstillery’s value proposition in reference to the changing needs of marketers in an uncertain ecosystem?

Dstillery CEO Tom Phillips

Traditional models of behavioral targeting help bring scale and relevance to campaigns, regardless of the screen. Traditional advertising models use estimates to try to get a message in front of appropriate audiences. And while mass communication is one tool for building brand awareness, intelligent use of data can create much more efficient solutions for marketers, who are looking to build brands and drive sales. Whether it is television, print, radio or digital, marketers have focused on content as a proxy for trying to find the right audience. Fragmentation of media has helped push endemic advertising. But there is still a huge amount of content consumption, where marketers are looking to hit high compositions of an audience because it’s the best that they can do. In other words, if you’re trying to reach cooks, it’s a lot easier to hit your target audience by advertising on The Food Network rather than American Idol. Understanding consumer intent through tracking and then deploying advertisements through digital means allows marketers to connect with the right prospects for their brand more effectively. This has been done in the desktop space for some time now. Mobile efforts are growing rapidly, and soon we’ll see significant growth in digital TV, radio and outdoor. This shift is resulting in more data, and with it a more complete window into the consumer beyond anything that previously existed. At Dstillery, what we have built for the past five years allows us to capitalize on this shift and effectively activate the data on behalf of marketers. We find ourselves at an exciting time in marketing, one that is great for the marketer. And with the right balance of innovation and respect for consumer privacy, it will be great for the consumer as well.

 

Brian Kane was COO of LiveRail in 2012. This story originally appeared in The Advertising Technology Review in 2012

Brian Kane is the new COO of video advertising technology company, LiveRail. Mr. Kane was formerly COO at Admeld, and Google’s Director of Publishing Services prior to joining Admeld. Mr. Kane spoke with The Advertising Technology Review about LiveRail’s standing in the video advertising field, the risks of adopting the GRP and his belief that the infamous ad tech bubble might just be a myth.

Are we truly in an ad tech bubble? How far does ad tech have to go to convince the masses that it can deliver enough value to justify shifting more ad spend online?
First, as it relates to the idea of a bubble, I don’t necessarily think that we’re – meaning ad tech as a whole- in a bubble. It does seem that there are a number of companies which appear to be a bit more focused on their valuations, their raises and planning for their exits versus providing solutions to the market. The number of companies which are placing a value in excess of $1 billion on their companies is staggering. The fact is that those companies are talking about their exits, raises and valuations before they talk about sustainability of operations, and the value they are bringing to their customers. That’s the interesting piece. So that’s my definition of a bubble; it’s the state you’re in when you start worrying more about the exit then about creating something of real value. I’m pretty sure many would’ve said that at the time of Google’s acquisitions of Youtube or DoubleClick – that they were indicative of “bubble-like” conditions. Certainly not in retrospect. Increased numbers of acquisitions doesn’t equate to a bubble. Players were focused on exits rather than solutions; those are the cases where individual companies may be in a bit of a bubble. As for what we need to do to demonstrate to brands that there’s justification for moving more spend online, I think that as an industry its obviously important to continue to provide them with interesting and actionable sets of data to enable them to understand the ways in which their campaigns are impacting consumers. Online holds significant advantage in this area over every other medium, and our ability to educate brands on this is still – all these years later – central to our work. More importantly, we are recognising that as an industry we’re driving a huge amount of change in how things have been done for a long time. It’s not just “flick-a-switch” kind of change, but cultural change – the kind that takes longer to work through – the kind that causes people to do things and look at things very differently than they have in the past. I think it’s critical that in ad tech we recognise that we’re still moving people along a very rapidly moving continuum of deep change. Serving as trusted partners to these organisations, enabling them to make sense of technology which is complex and changing so quickly, has to remain core to what we do.


Video advertising is far more effective than traditional banner ads. Is this arena the next frontier for innovation in ad tech?

There are a handful of factors at play that make video advertising a particularly important area of ad tech innovation. In the early days of online advertising, one of the largest gating factors to bringing advertisers online was their relative lack of comfort in creating compelling creative in the absence of video. On the buy side of the ecosystem, all these years later, video still remains the format that advertisers gravitate towards and understand best. On the supply side, the number of video- enabled impressions has grown exponentially, and there’s a good amount of recent data that suggests that the proliferation of connected devices and tablets is going to have a substantial impact on the numbers of these impressions that will become available over the next few years. Equally important though are the technology solutions that have come to the market recently which have given advertisers and publishers really powerful tools to transact programmatically, at scale. Advertisers now have the ability to buy video placements via RTB leveraging really rich audience data – and publishers can now feel more confident and comfortable in selling their video inventory through these channels while maintaining tight control over who can buy and at what price. The advent of private exchanges has also brought a new buying model to bear, enabling premium publishers to lob off slices of inventory which are sold in programmatic fashion to a select pool of buyers. This innovation is the here and now. The next phase, which I think is really most interesting, is what will take place as more televisions become connected, and as tablet usage continues to explode. While it certainly is not the most scientific study, I’ve got 3 kids between ages of 5 and 7. Their first screen is their iPad, their second screen is their iMac, and the TV is last on their list. We’ve got a bit to go, but this trend will press our industry to create new ways for advertisers to connect with audiences and new ways to measure the success of those engagements. This has been substantiated recently in studies from Nielsen which found some significant shifts over the last few years as to the reduced importance of TV as the primary media consumption device. This is, to me, an exciting not-so-distant future state.

LiveRail manages more than 3 billion impressions per month, about 25 percent of all video ads. Based on your knowledge of the what major brands want, what trends do you see emerging in video ads?
I think there are two significant trends that are substantially shaping the video advertising industry today. The move today is towards audience-buying via real-time-bidding and the continued shift of consumers to devices apart from the television. This is prompting advertisers to focus significant effort on multi-platform buying. As real-time bidding and programmatic buying technologies advance, we’re seeing more large publishers and buyers adopt this technology. For publishers, the appeal of RTB has typically been the creation of more efficient ways to manage the non-guaranteed sales channel, in video, we believe that we are going to see more and more guaranteed deals executed via this new technology as agency trading desks build their video businesses, and as publishers begin to implement new models like private exchanges, for exposing this video inventory to buyers. Multi-platform is the other significant trend that’s driving substantial change across the video advertising space. As more content being delivered and consumed via tablets, and to a lesser degree, connected TVs, publishers and advertisers are looking for more efficient ways to manage advertising across these platforms. The other thing that is getting a good amount of attention is the focus on gross rating points (GRP), and whether this traditional media metric can be brought over into the online world as a measurement tool. As more TV buyers transition to the online space, GRP represents a familiar and useful metric for both planning and measurement, but the fear is that it doesn’t capture many of the nuances that differentiate online from other formats. The concern is that if our industry fully embraces GRP, we risk devaluing much of what makes online advertising unique. There are merits to both sides here. Stepping back from the granular details, development of an appropriate set of standards that deliver effective cross-platform insights to traditional TV buyers, while still respecting many of the unique aspects of online, would be a positive step forward for the industry.

Privacy and data are two big concerns for consumers and brands. How does LiveRail tackle these issues for clients?
Since we work with participants across the entire ecosystem– publishers, ad networks, DSP’s, trading desks, and agencies) we understand the complexities and concerns that come with privacy compliance and audience data from various perspectives.  Earlier this year, we worked with the leading technology vendors that specialise in these areas and created the Video Brand Safety Alliance. All members have native integrations in our platform and with one click, our clients can use TRUSTe and Evidon to address privacy and Exelate, Proximic, comScore, and AdSafe, and DoubleVerify to address audience data.


Brian Kane was Chief Operating Officer for LiveRail, a leading video advertising company.

This story originally appeared in The Advertising Technology Review in 2013.

Despite the fact that Lifestreet is in social media and apps, its worth is not based on a jargon-fueled valuation, buoyed by advertising technology’s ebuillent army of publicists. LifeStreet is making ads that work for brands. How do we know this? Because the company is making money from its business model and paying its developer partners, to the tune of $100 million, having driven more than 200 million app installs. LifeStreet’s advertising technology approach focuses on relevancy in its advertising, using its method of “iterative high velocity testing” to find the most effective elements of an advertisement and it seems that investors are backing its methods. The Advertising Technology Review spoke with Lifestreet Media CEO Mitchel Weissman about his company and its data-driven approach to advertising technology.

Your company recently received a $66 million investment, ostensibly because your business model is that strong. What are you doing differently with social and mobile in-app advertising that is different than the rest of the industry?
The industry is chock full of ad networks which are not adding any value and are just playing matchmaker between advertisers and publishers. LifeStreet is completely different. As a technology company, not an ad network, we actually create and optimize the ads and the many factors that drive revenue for those ads. This means that LifeStreet’s technology goes way beyond matchmaking. We literally create revenue for each thousand impressions. We’ve invested over $25 million into inventing a brand new type of technology, called universal object serving, with which we’ve constructed a transformative optimization platform called RevJet. RevJet applies Iterative High Velocity Testing to any digital revenue driver – where each revenue driver is modeled and served as an object. For example, should the background color of this ad be blue, green, red or black? These are visual objects and definite revenue drivers– we test them all. Should the copy say “click here,” “click now,” “click,” “learn more,” or “learn”? These are visual objects and definitely impact revenue – so we test all of these too.

What about logical objects, such as targeting algorithms, which also impact revenue?
Using universal object serving technology, RevJet is able to apply Iterative High Velocity Testing not only to visual objects, but also to logical objects such as targeting algorithms. Here’s an example: suppose we have an opportunity to serve an ad into a leaderboard inside App 123 to a user located in San Francisco at 8PM at night. Which campaign will generate the most revenue? Sounds like a simple question with a simple answer: just “look at your data” and “see what performs best,” right? Wrong! Which data should we look at? Should we look at “the last 3 days of data from ads served in San Francisco?” Or maybe we should look “only at evening data for the last 7 days from ads served in San Francisco?” Or perhaps recency and daypart are both more important than geography? In that case, maybe we should look at the whole United States rather than just San Francisco? That, of course, would preserve daypart and recency. Because we would have so much more data we would be able to look only at data from the evening daypart instead of the full day for the most recent 2 days of data, rather than for 7 days or more. So if an object is both digitally instantiated and impacts revenue, definitive revenue maximization is achieved only by true field-testing- and it has to be rapid, iterative, perpetual, and definitive field-testing in order to work. That’s what Iterative High Velocity Testing is all about. Before LifeStreet came along and invented universal object serving technology, this sort of testing wasn’t possible. Now, with RevJet, it’s happening in the marketplace as we speak.

Exactly what is the opportunity for in-app advertising?
The in-app advertising opportunity is enormous. There are nearly 9 million apps and websites integrated with Facebook and nearly 1 million mobile apps for Android and iOS. Many of these apps are free and need avenues to help them monetize. We help apps make money by placing banner ads within them. These are our publishers, and we’ve paid out $100 million to them so far. Similarly, all of these apps need to be discovered before they can be used. We help apps become hits, and we’ve completed more than 225 million app installs on behalf of our advertising customers. Borrell Associates expects the mobile in-app advertising opportunity to reach $8 billion by 2015, and eMarketer predicts that social advertising will reach $8 billion this year. It’s a great time to be an app developer, and we’re happy to play a vital role in helping them achieve success.

There are a few voices out there saying that apps are great initially but then they don’t deliver value consistently, or in the long term. How do you respond to the critics of the app space?

Obviously we’re a big believer in apps – both in social apps and in mobile apps. It’s the app ecosystem that has helped Facebook reach astronomical engagement levels, and it’s apps that drive mobile engagement levels. ComScore found that 4 out of every 5 mobile media minutes are spent with apps based on 2012 data.The numbers tell a very clear story: Americans spend 16 percent of their time online on Facebook according to MarketBeat (2011) and Statista calculated Americans’ engagement with Facebook to equate to 100K years per month (2012). Americans spend on average 50 minutes a day on mobile devices, equal to the combined time spent with magazines and newspapers according to eMarketer (2011). Social and mobile apps are here to stay. The strong ones will continue to deliver value for users, and the weak ones present an opportunity for savvy developers eager to create the Next Big Thing.

What does LifeStreet have planned for the future?
We started this company to free the industry from conventional ad serving technology, which we consider to be outdated, overly rigid, and unable to produce the kinds of results advertisers and publishers deserve. Right now we’re focused on social and mobile in-app advertising, but it’s extremely clear that applications for RevJet and universal object serving technology extend well beyond digital advertising. That said, LifeStreet’s charter today is to serve as an app developer’s “best friend.” We seek to be their partner of choice to help them drive customers and monetization, so it’s exciting to us to think about applying RevJet and Iterative High Velocity Testing to other areas of developers’ businesses. For example, we could help optimize in-game user experiences and virtual good sales within social and mobile gaming apps. In fact, we’re having early discussions with large industry players about doing just this — applying RevJet to in-game revenue optimization. We see this as a fantastic opportunity to use universal object serving technology to help developers make even more money from their apps.

Mitchell Weisman is a co-founder and CEO of LifeStreet Media.

Ramsey McGrory was CEO of AddThis in 2012. This story originally appeared in The Advertising Technology Review in 2012.

There are voices which claim, with a barely shrouded hint of indignation, that social media is a Wild West of unfiltered interactions of varied importance, and not a substitute for traditional online advertising. Social data, nonetheless, has begun to redefine the digital publishing landscape and social media’s role has become inextricable from that of advertising technology as a preferred method of brand messaging.

Ramsey McGrory, CEO of AddThis (formerly Clearspring), believes that social content publishing is fundamentally transforming the way brands and their marketers connect with audiences across multiple platforms, supplanting the old ideas about the role of advertising technology. “Social media is a horizontal force that connects with all of the vertical elements that we create, such as mobile, display, search and traditional publishing,” said Mr. McGrory in an interview with The Advertising Technology Review. “Social is a layer that is forcing advertisers to become publishers and publishers to become advertisers”, Mr. McGrory asserts.

The AddThis social sharing technology has been installed by publishers on 14 million websites and loads 90 billion times per month. The day that AddThis decides to create a new model of content or data management for brands, it may dwarf some of the America’s largest advertising technology companies simply by default. AddThis gains much of its value from its data and its ability to turn that data into enriched portraits of consumer behavior for brands and publishers.

Aggregating its data, AddThis has the largest interest and sharing graph on the open web. There is also the possibility that AddThis, by virtue of its scale and the intrinsic value of content-derived consumer data, may be able to turn the publishing and advertising technology industries inside out.

“Traditionally, if you wanted to read content, you went to the publisher’s domain, now, that content is increasingly being distributed through many channels,” said Mr. McGrory. “Publishers are now thinking of ways to get consumers to become content distribution channels,” Mr. McGrory believes. The key determinant of publisher success, according to Mr. McGrory, is how well publishers are able to use powerful content to win loyal consumer fans whom willingly integrate their content choices into their interactions with their social graph.

Content sharing and the rich data that accompanies it has changed the way brands look at the very definition of engagement, speeding an industry-wide shift from click-based metrics to a model which promotes lasting consumer-brand connections. The role of AddThis in this shift is, according to Mr. McGrory, not only to facilitate content sharing for consumers, but also to serve as a reservoir of rich data.

No one shares banner ads, but content shares are rich in “organic” data, giving clues to a consumer’s psychographic landscape in a way that a banner click simply cannot. The genius of AddThis is its simplicity as a channel to bring consumer content preferences closer to social data in a logic-driven way, allowing brands to use valuable data to personalize consumer’s online experiences. “A lot of marketers spend a lot of time at the top of the funnel, attempting to gauge and inspire awareness, interest, and intent,” said Mr. McGrory. “If you can leverage the power of social across paid, owned and earned media you can accelerate consumer brand awareness and action.”

The AddThis suite of social tools maps the content and social connections of its 1.3 billion users, allowing brands to use site, search and social data to create customized content and ad experiences in real time. This combination of data sources, when joined with the ability to graph connections on such a large scale, creates an effective fail-safe for marketers interested in amplifying the value of their own audience data, even data derived outside of the AddThis suite.

“The world of anonymous data has collided with the world of the personal, allowing marketers to connect the dots between content sharing and online behavior while still respecting privacy,” stated Mr. McGrory. “There is a powerful gush of data that marketers and publishers have not had access to; nor have they had the tools to leverage that data,” said Mr. McGrory. “Creating social tools leveraging big data allows publishers to create deeper engagement experiences and marketers to create better campaigns,” Mr. McGrory believes.

Social data is bringing an end to the shotgun approach to advertising, causing advertisers to think more critically about how to enable consumer engagement experiences, and how those experiences may be shared in a way that multiplies their impact across numerous audiences. Mr. McGrory highlighted several new social tools that AddThis launched recently which expand beyond sharing, and hinted that the company has plans that to venture much further into the territory of social technology and data. “The question that we ask every day is,” quipped Mr. McGrory, “when we have a data set this large and the DNA to build social technology, what do we build? “Imagine how many areas into which you can drive value for publishers and advertisers with intelligence that leverages the power of the open web.”

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