Header Bidding: Threat or Savior?

Header bidding is washing over the AdTech ecosystem faster than any other tech, leveling the playing field between pubs and exchanges. Need the basics? Read these primers from Digiday and Adprofs, or our recent blog, for a quick history.

Adoption rates among US publishers are incredibly high – reportedly at 70%+. Big numbers – who are the winners and losers?

Header bidding is exploding because publishers reason (often correctly) that they are getting screwed by the second price auction and the intermediaries who may be rigging the system. Via header bidding, publishers are able to bypass the waterfall of exchanges, which increases overall eCPMs, provides more control over inventory, and relegates exchange(s) – mostly AdX – to sell “remnant”.  

Though there is some disagreement on the stats, header bidding on guaranteed inventory has increased eCPMs by at least 20%. For non-guaranteed inventory, header bidding has seen a 50% increase.

There are two reasons for this, with equal weighting:

  1. Header bidding exposes ALL inventory to bidders, rather than restricting visibility to unsold/remnant/low priority — high-value inventory competes with guaranteed demand.
  2. Bids through the header are passed from DFP to AdX, creating floor pricing. This increases eCPMs for AdX-sold inventory.

Exchanges are struggling to catch up as win rates decline through increased competition. One needs look no further than the recent stock price collapse of Rubicon, who reported that header bidding is the primary culprit in their recent earnings calls (and which resulted in hiring Michael Barrett, a consistently successful CEO with outstanding reputation of selling the companies he walks into.)

PubMatic was also late to the game, resulting in a lull – though they have recently joined the fray and are appearing to be gaining momentum.

AdX, the largest of the primaries, is certainly a short-term loser, at least. Due to the new floors header bidding has created, AdX is able to sell inventory at a higher price. However, the volume of quality inventory has dropped, with the best inventory being snatched-up quickly in the header bidding cycle.

Then there’s Google… who I would never count out. While their response is developing, header bidding is also threatening their core ad-server dominance. But, Google is encouraging publishers to explore competitive ad-servers that have built-in programmatic capabilities, as opposed to DFP, in which the exchanges are separate systems.  

AppNexus seems to have woken up with their open source solution, prebid.org, but it’s too early to be certain how they will factor long-term, although they are clearly gaining steam.

Secondary and tertiary SSPs/Exchanges – traditionally the third, fourth, or fifth calls on the remnant inventory chain – were used to seeing inventory picked-over by AdX, AppNexus, Rubicon… Thanks to header bidding, these smaller SSPs and exchanges can offer the same inventory, at the same time, as the big exchanges, and compete on price and service. Now, it’s the biggest exchanges (with the noted exception of AppNexus) who are scrambling to catch up.

Certain other exchanges, in particular OpenX and Index Exchange, made big bets early on in the header bidding model. SOVRN has also fared well through this upheaval. SOVRN sees 100% of a given publisher’s inventory, and their volumes and eCPMs have increased. And yes, they also incur ‘listing fees’ for 100% of the inventory — but the top line is exploding.

While they encounter significantly higher listening costs to manage the huge volume of increased impressions, DSP’s now see all of a publisher’s inventory. This visibility includes the most valuable impressions, driving up CPMs and overall sales, even as win rates are lower due to the massive amount of visible inventory.

Networks have been in decline for many years – header bidding is not a single, fatal blow. What’s more: a number of networks are still competing successfully, both integrating inventory into exchanges and leveraging data.  

However, header bidding is going to ultimately subsume what is left of the network marketplace. Some will emerge stronger by managing header bidding solutions for smaller publishers, but those who are primarily aggregating inventory will likely be destroyed.  

How will the emergence of server-to-server header bidding impact the adTech landscape?

Short term, it appears to not only help publishers, but also favor smaller exchanges.  

Server-to-server header bidding is, essentially, a publisher selecting one exchange and giving that exchange all of their inventory. The publisher is then not only seeing the “unsold,” but 100% of the inventory (like all header bidding). However by doing so publishers are opening themselves up to many of the same transparency problems of yesterday’s exchanges. Plus, cookie-syncing issues are emerging with server-to-server solutions (not to worry here – these issues will be fixed.)

The biggest publishers with the highest-quality inventory don’t need an exchange. Companies like Purch have already tackled this, and we are seeing the emergence of other companies stepping unto the breach to support publishers, deploying their own server-to-server solution.  

I suspect the biggest and best publishers, used to working with a healthy percentage of media spend, will migrate to a fully-transparent server-to-server model. This will force the exchanges to become more transparent, change their pricing, and provide different levels of service. Publishers will jointly create a cookie-syncing solution, and eventually attract the largest DSPs to bid directly – nary an exchange in sight.   

Exchanges will be forced to provide their services to the mid- and long-tail. While some may survive, many will fail. The exchanges who do survive will likely be those already focussed on the long tail (think: SOVRN) versus those competing for the comScore 200.  

I am left with the thought that perhaps the exchanges and SSPs will (ultimately) win — in the short term with all publishers, but in the long term, perhaps only with smaller publishers. There are many exchanges – some are focussed on a more vertical approach (think: mobile or video) and others on providing higher-quality service, trying to differentiate themselves in other ways. What’s more: The biggest exchanges have always been “display first,” and their business models will come under increased pressure as header bidding tech becomes more ubiquitous.

Plus, we cannot overlook the benefits of deploying one’s own solution, extending further into the market.

Sure, header bidding doesn’t fix many of the other problems with the programmatic marketplace (fraud, walled gardens, viewability, effectiveness…) but this shift is returning some pricing power back to independent publishers.

That can only be good for the industry.

Industry Index is exploring server-to-server v. browser-based header bidding solutions at our upcoming Roundtable, with some of the smartest names in the field. Jonathon Shaevitz will moderate. Get your tickets here.

3,500 MarTech Companies and Counting…

At Industry Index we’re obsessed with organizing, categorizing, and segmenting the Industry. We’re tracking 5,000+ tech companies across MarTech/Adtech, as we like to call it — MadTech. Our tracking is expansive — e-commerce related companies, social media, chatbots, augmented reality, salestech, marketing automation… the list goes on.    

Meanwhile, there is a lot of great research occurring all around us. One data point that caught our eye was published on Chiefmartec. They recently announced that they now track over 3,500 MarTech companies, up from 2,000 in 2015 and 1,000 in 2014.  

Sure, you can quibble with the exact number, but the pace of growth is undeniably astounding: It doubled from 2014 to 2015, and then grew 87% again between 2015 and 2016. Simultaneously, tremendous consolidation continues. It seems like every week there’s another deal.

Why the tidal wave of growth?

1)It’s the money.
All signs point to the explosion of investment capital, sheer number of startups, and expansion of the MarTech ecosystem. Pick your favorite statistic:

  • MarTech spending is expected to reach 10% of overall budgets for Fortune 500 companies by 2024 (up from 1% in 2014)
  • MarTech spending reached $12B in 2014
  • MarTech spending will reach $120B by 2024

2)There are additional compelling reasons for the proliferation:   

  • It is easier than ever for brands to try and test tech.  
  • Most new tech have APIs that allow faster deployment and integration
  • The SaaS model reduces tech acquisition costs – lower risk to try
  • The proliferation of tech drives more targeted “point” solutions; tech deployments can be for single campaigns or trials
  • Previously siloed data and systems can now be integrated and leveraged with relative ease
  • Most importantly, customers are expecting more and better engagements with companies – Personalized, fast, authentic… IMMEDIATE!

Marketers ultimately need to remember the real reason they’re investing in MarTech: To better understand current and potential customers with the purpose of driving sales. Companies need to make sure that their marketing stack—regardless of the vendors that they work with—provides deep customer intelligence and paints a holistic picture of the customer.


What does this mean for MarTech buyers?

  • First and foremost, the phone will keep ringing, emails will be chirping, LinkedIn messages will fill your inbox.  
  • The market is difficult to understand and sort out. Understanding the differentiation of companies within a category can be agonizing. You need to start with a different perspective:
    • It is incumbent on buyers to start by developing a general understanding of the type(s) of tech that are interesting.
    • You need to focus more attention on developing your own requirements.
    • Finally, consult the data. More and more companies are utilizing research to produce content, and much of this research is extremely useful.  However, you need to be a smart consumer of data/content. There is a BIG difference between research studies, true thought leadership, and long, glorified sales pitches.

What does this mean for MarTech vendors?  

For starters, doesn’t it feel like there is more competition? That’s because THERE IS MORE COMPETITION.

As Industry Index began planning for its website relaunch for this summer, we began with a basic question:  Where are the boundaries of MadTech and how do we organize our data?  

This lead us to explore vast numbers of companies, and where they sit in the ecosystem.  It was immediately apparent that not only were there many more companies, but the boundaries had expanded. And, while many of the new entrants are narrowly targeting a single problem, most companies are now, unlike five years ago, selling solutions that inherently include data, products, and integrations with other technology types as basic table stakes.  

So what does it all mean…

  1. Despite all the M&A activity, the marketplace is growing more crowded.
  2. The lines between tech categories are getting very murky.
  3. More MadTech products are being sold directly to brands – sometimes because the agencies are reluctant to test, but more often because data integration requires direct relationships with brands.
  4. Marketers are increasingly trying/buying tech, but companies’ product lifecycles are shortening.
  5. Most MadTech vendors continue to dance in the dark, not knowing the basics: the whos, whats, and whys of their prospect lists. Vendors are too willing to attempt to stretch their product capabilities in exchange for a few more dollars of revenue.

Ok Everyone, You Missed the Point

Last week Burger King earned significant publicity over their latest ad stunt, in which a TV spot was designed to hijack Google Home devices by asking “OK, Google, what is the Whopper burger?” The hope was that viewers with a Google Home Virtual Digital Assistant (VDA) would hear a list the ingredients back from their device. There has been a lot of news and industry talk about the advertisement itself… the Wikipedia skirmishes… but so far, everyone has missed the point.

This stunt is not about the ad, but about the power of the home-based VDA. Given Google’s insatiable appetite for advertising revenue, Google Home is programmed to use Wikipedia to list Whopper ingredients — a tiny illustration of the power of VDAs. How long will it take for your Google Home, Amazon Echo, or other VDA, to not only link to an advertisement and choose where to direct you, but for Google and Amazon to get paid by brands for your virtual self-space? Imagine you ask for paper towels – let’s say your VDA can choose Bounty or Brawny – what is Amazon’s incentive to pick one brand over the other?

I already say to my Echo, “Alexa, reorder XYZ”, and it does. No price check, no alternative, and when XYZ is a generic item, like sugar, it effectively selects the brand. I know this is the effect of my own laziness, but what I expect to see soon will be nothing short of invasive. Amazon already knows far too much about me. Again, my own choice, but in this “winner take all” economy, our retail choices are going to become limited in an entirely new way. It will not just be the local merchant being pushed out by big boxes and malls. Even they are being shattered as we embrace e-commerce, online price checking, and are swayed by social influencers, changing how we buy. eMarkerter’s recent report on programmatic spending, indicating that 84% of all digital advertising will be programmatic, shows that algorithmically-driven advertising works.  It is coming to TV (already in video) and to every other form of advertising.

What is fascinating about the potential power of VDA as it relates to marketing, advertising, and commerce, is that no one is paying attention. This will be the largest sea change in advertising/marketing and controlled by only a few companies (Google, Amazon, Apple, ???). Both Google and Amazon have reduced the friction of every transaction and are basically selling a BIG EASY BUTTON for shopping. However, the costs of finding alternatives, or actually knowing what the alternatives are, will continue to empower that easy button. This enables yield pricing on every product we buy online.

Many are already familiar with how airlines present different prices to the same person based upon how they search (one price on Kayak, another on the company’s website, and a third price on the company’s app).  When I recently searched Delta for a flight from LaGuardia to St. Louis using these three methods I was simultaneously quoted three different prices (ranging from $171~$187).  In each instance, Delta knew different things about me, and therefor quoted me three different prices. What is to stop Amazon Echo from quoting me a different price? Amazon already changes its pricing in real time – that cookware set you bought yesterday may be cheaper today (and Amazon no longer offers price protection). Why wouldn’t Amazon set pricing based upon willingness to pay? They could tune their margins perfectly.

VDAs are becoming the next narrowing point of the purchase funnel. Limiting selection and actively managing price is simply the next step.

What can we do? The answer is complicated, but it begins with awareness. We professionals in the MadTech world are familiar with how algorithms dynamically bid for impressions, change creative content inside of ads, and generally drive the successful targeting of advertising. But most people don’t know how pricing algorithms discriminate based upon what they know. As these Madtech capabilities continue to migrate to pricing, the most important thing we can do it is not fall into the easy trap by spending a little more time looking for pricing alternatives.

Let Them Come…Consultancies Welcome!

It is hard to ignore the steady drumbeat of warnings that management consultants are coming to challenge agencies. Management consulting firms are often seen as the enemies of agencies – new market entrants that need to be stopped.  Many of them have already won, as Forbes illuminated in a recent article. “According to Ad Age, all the top 3, and 8 of the top-10 ad agencies are not those legacy names that might visit your home nightly with their TV commercials. Instead, they are consultancies like Deloitte, Accenture, KPMG and PwC.” Agencies seems to be responding in-kind, building up their consulting expertise.

This trend is driven by many factors, with two of the key drivers being:

  • Brands are increasingly spending more on MadTech, and technology has always been a core capability of management consultants;
  • Digital transformation is now often driven by customer engagement points (MadTech), and agencies have a long history of driving and managing customer engagement points for brands.  

The old three-martini lunch may have passed, but the agencies’ “trust me” attitude often remained, at least until recently. The ANA’s report on agency transparency, the P&G bombshell at the IAB Leadership conference, and recent cries from some YouTube advertisers speaks to the increasing volume of calls for change. The press points fingers at ‘AdTech’ companies, the programmatic nature of buying, fake news, fraud…

I think it’s something different.

Given all the background noise about transparency, agencies, AdTech companies and others have a vested interest in the ‘media’ pricing model, which hides all the dirty little secrets: fees and recharges with agency trading companies, the hidden costs of SSP’s and Exchanges, and the ‘price included’ fees of data targeting. These (and many other) MadTech fees are structured to be imbedded in the holy ‘media-based’ model.

This model is seriously broken. With many claiming the ‘AdTech tax’ is at least 45%—and some declaring it to be as high as 75%—everything is suspect. Brands are spending more on MadTech than ever before. They know they’re getting screwed, they’re just not sure how.

In march the consultants, with their decades of expertise in supply chain management, and a depth of expertise in getting technologies to work together, that few agencies can challenge.

Large consulting firms have spent decades, if not generations, tearing down supply chains to remove waste and friction, reassembling them for higher efficiency. The typical MadTech supply chain to deliver an impression is primed for the consulting axe:

  1. Data and Targeting
  2. Ad Serving
  3. SSP/Exchange fee
  4. Dynamic Creative
  5. Fraud/Verification/Viewability

    …Et cetera.

Each of these technologies, many of which are invaluable, are bundled by agencies into the ‘price of the media’ and distributed behind closed doors. Management consultants know how to play in this game. They are going to continue to gain market share, particularly against major agency holding companies, until the pricing model changes. And, by the way, it’s not that consulting firms come at a bargain, but they don’t hold the same vested interests that agencies do. They expose problems, are more transparent about their own pricing, and are ruthless in attacking the supply chain.

Management consultants will drive transparency in agency pricing models. However, while they are experts in supply chain management, they are not as good at recognizing how MadTech innovation can improve a brand’s performance, and are likely to pick only the largest tech suppliers as they strive for supply chain efficiency.

Let management consultants drive agencies toward embracing transparency. But technology companies, take note: To maintain an innovation-driven ecosystem, rather than to see a culling of the herd with only the largest companies surviving, will require new pricing models. The onus is on MadTech to create them, and to lead the way.


You Can’t Spell Exchange without Change


Header Bidding – the new black, taking the market by storm, the must have, top of the trends.

So why is it such a threat?

Header bidding shifts the power dynamic away from the SSPs and exchanges, moving it back to the publishers. Publishers who manage their own header bidding have created what exchanges promised to create for the last five years: a highly competitive auction for a publisher’s inventory. Not only are publishers making more money with header bidding, they are gaining a bigger advantage, transparency of demand, and inventory control.  

Who is winning – and who is losing – thanks to header bidding? Why do I believe it ultimately spells the demise of many exchanges?


  1. Digital advertising was born.
  2. Digital advertising was sold much like TV, print and radio, mostly on a guaranteed basis via phone calls, faxes and emails.
  3. Digital inventory exploded and “remnant” (unsold) was born.  
  4. Remnant was sold via networks, used for house ads, or went unsold.  
  5. Networks figured out how to create vertical networks and other aggregation methods, providing reach and contextual targeting to buyers.
  6. Networks started deploying audience targeting tools and were the first to really leverage data (with the exception of Google, who always knew how to leverage data).
  7. DMPs and other data companies emerged, created huge pools of profiled cookies.
  8. SSPs, Exchanges, and DSPs emerged to create the ability to “real time target and bid” on remnant inventory.
  9. DSPs leveraged the audience data to drive performance and the size of the RTB market exploded.
  10. Publishers were pushed to “be transparent” with their inventory and add higher quality inventory to what was sold programmatically, increasing eCPMs of exchange inventory, but not necessary the overall eCPM of publishers.
  11. Exchanges, and DSPs starting making some serious money (each taking about 15% of the spend) creating the so called “AdTech Tax.”  
  12. Meanwhile, companies like Criteo realized that being in the header gave them first look for all inventory (not just unsold), driving up eCPMs for publishers while cherry-picking inventory.
  13. Technology-learning publishers began to experiment with “header bidding,” often leveraging DFPs’ dynamic allocation tools.
  14. Open source header bidding wrappers and adapters became available and the market exploded.
  15. Header bidding began driving up CPMs for publishers, allowing them to capture top dollar for high-value inventory.


Header bidding is exploding because publishers reason (often correctly) that they are getting screwed by the second price auction and the intermediaries who seem to be rigging the system. With header bidding, publishers are able to bypass the the waterfall of exchanges, increase their overall eCPMs, gain more control of their inventory and only use their exchange(s) (mostly AdX) to sell what is truly now “remnant”.  

Why are the exchanges doomed? First, they’re not all screwed. Some were losing under the “exchange daisy chain market.”  They were the third, fourth, or fifth call on the chain and saw lousy inventory that had been picked over by AdX, AppNexus, Rubicon… Certain companies, in particular OpenX and Index Exchange, made early big bets on the header bidding model.  All of a sudden, they were seeing 100% of a given publisher’s inventory, and their volumes and eCPMs increased. (Yes, they also incurred a “listening fee” for 100% of the inventory, but top line exploded.) AppNexus jumped on the bandwagon a little later, with their open source solution, prebid.org. However Rubicon was late to the party, as was Pubmatic.  

Rubicon has reported header bidding as the primary culprit in their recent earnings calls. One need look no further than the recent stock price collapse of Rubicon. It has been blaming header bidding for its sinking performance for the last few quarters, but was overwhelmed with bad news with its recent reporting (which resulted in hiring Michael Barrett, a consistently successful CEO (successful at selling the companies he walks into).

Most importantly, publishers, particularly the comScore 150, were figuring out how this was all working, and began taking control of the process. Now everyone is talking about server-to-server integration for header bidding. This seems to overcome the real technology problems of header bidding by creating a single header bidding call and having someone else then manage the bidding process. Usually this “someone else” is the exchange. They have the technology infrastructure needed to manage the extraordinary volume created by this system.  

Server-to-server also creates a new problem related to cookie matching, but let’s assume this will get resolved over time. The biggest part of the challenge is exchanges’ unwillingness to cookie sync.  

Shenanigans, deception, and more of the same-old-same-old.  

While server-to-server integration clearly solves most of the problems associated with the speed and load times of header bidding, it leaves publishers exposed to different problems.  One traditional complaint of publishers regarding exchanges was that the actual fees charged by such intermediaries were less than transparent. Also, publishers suspected that, in some cases, exchanges were front running their inventory, creating additional spread within auctions, adding or subtracting data for their own benefit. Publishers felt cheated, but were not certain whether it was true.  

Over the last few years, as more bid stream data has become available, these suspicions have sometimes been confirmed. Certainly, some deceptive practices have been identified.  As with most things, transparency is the greatest disinfectant.  

The problem with header bidding managed by the exchange is that it opens the ecosystem back up to the suspicions of self dealing. In one instance recounted by multiple publishers, some exchanges seemed to win a disproportionate amount of inventory when they were the “wrapper” compared to when they were only an “adapter” inside someone else’s wrapper (i.e., when they manage the whole auction they win too much, compared to when they are just another bidder).

Simply put, server-to-server, at least as most people are discussing, is basically a publisher selecting one exchange and giving them all their inventory. Now they are not just seeing the “unsold,” but 100% of the inventory (like all header-bidding). However publishers are opening themselves up to many of the same transparency problems of yesterday’s exchanges.

Why is this a threat to the exchanges? Simple – the biggest publishers with the highest quality inventory don’t need to use an exchange. Companies like Purch have already tackled this themselves, and we are seeing the emergence of other companies stepping into the breach to either support publishers deploying their own server-to-server deployment, or creating new pricing models so they do not have an incentive to play with the auction.  

I suspect the biggest and best publishers will migrate to a fully-transparent server-to-server model, which will force the exchanges (who are used to working of a healthy percentage of the media spend) to become more transparent, change their pricing, and provide different levels of service. Publishers will jointly create a cookie-syncing solution, and eventually attract the largest DSPs to bid directly, and not through an exchange at all.  

Exchanges will be forced to provide their services to the mid- and long-tail. While some can survive, many will fail. The winners will likely be the exchanges already focussed on the long tail (think SOVRN) versus those competing for the comScore 150.  

There are many exchanges in the market, some focused on a more vertical approach (think mobile or video) and others providing higher-quality service and trying to differentiate in other ways. However, the biggest exchanges were and are “display first,” and their business models will come under increasing pressure as header bidding technologies become more ubiquitous, and as the expertise to deploy one’s own solution extends further into the market.

These trends don’t fix many of the other problems with the programmatic marketplace (fraud, walled gardens, viewability, effectiveness…) but this shift is going to return some of the pricing power back to independent publishers. That can only be good for the industry.

7 Deadly Sins of MadTech Marketing 

It may be obvious, but most MadTech companies don’t market, they do lead generation and demand generation and call it marketing.

There are many reasons for this:

  • Most MadTech founders are engineers and don’t like the squishy metrics of marketing
  • The prospect list is limited and often known, so why do a big marketing campaign when there are only 500~1,000 prospects? Let’s go sell them!
  • Brands are viewed as unimportant in MadTech, so why invest?
    • Maybe they are unimportant since most have names that sound alike and almost all use the same language including “optimize,  reach your audience, performance, unified, programmatic,” etc.
  • Budgets for start-ups and young companies are limited, so better to invest in a feature/function that a prospect or customer has requested
  • Most digital advertising is focussed on performance, so it is what we know
  • MadTech products are impossible to differentiate through marketing because they require a presentation or demonstration to understand.

These are all valid reasons. So what to do? First, what do MadTech companies do? They spend their “marketing” budgets on:

  1. Hiring sales people who have a great “list”
  2. Attending trade shows and conferences
  3. Sponsoring trade shows and conferences
  4. Email campaigns
  5. Running ads in industry publications
  6. Running ads on LinkedIn, Facebook, Twitter
  7. Spitting out some content



Hiring sales people who have a great “list”.

There is no doubt that a great sales person is worth their weight in gold.  And a great salesperson not only has a great list, but also understands how to talk about the technology itself (they may not understand how it does what it does, but they are able to describe the benefits in language a prospect can digest).

It is also true that great sales people are few and far between.  The model of converting a media sales person to MadTech sales person is littered with great lists and no sales. So, most companies play salesperson roulette, swapping the same 300 people (thanks Andrew Kraft), in and out, and paying ever hirer prices.

Alternatively, companies are beginning to hire from outside the industry or people simply interested in tech and starting to invest in training them. This works, but takes time.

Attending trade shows and conferences.

These range from awesome to awful.  From one year to the next the same conference can differ vastly, or simply be picked over, but attending trades shows and conferences works.  The right ones are target rich environments and people are there to meet, network, and do business.

The emerging challenges with trade shows and conferences include:

  • Real prospects, brands, agencies, publishers, are becoming like gazelles on the prairie, they blend in well and travel in herds to protect themselves from technology vendors quietly stalking them.  When separated, they tend to be bounced on by predators from all sides.
  • There seems to be an industry conference almost every day, so deciding what to attend is challenging.
  • Content tends to be broad and shallow.  The people who most benefit from the “content” are end users (brands, agencies, and publishers) and, as noted above, are hesitant to attend.
  • Content is often “pay to play.” Who needs to hears another pitch?

But, to reiterate, conferences work!  People are there to learn and do business. It’s just picking the right ones.

Email campaigns

Email marketing works, if you have a good list, are careful and treat your recipients with respect.

The problem is, few MadTech companies are very good at email marketing.  They track their open rates but not their ROI.  They fail to customize content, and much of their content is overly self-serving.  Also, MadTech companies tend to think in shorter terms. As mentioned in a previous post, the most important factors to email marketing are:

  1. Play the long game. Build a relationship.
  2. Don’t buy lists, build them. Find real people with real connections to your brand.
  3. Humans + Automation is the most powerful combination. It’s not one or the other.
  4. Relevance is critical.

Running ads in industry publications

We all know who raised a fresh round of financing, not by reading Crunchbase, but by reading Digiday, AdExchangerMediaPost, etc.  We know because their ads cover the pages for a couple of weeks.  Other companies use these channels as part of an ongoing branding strategy.  I have done the same myself, with Maxifier, Upfront Digital Media (formerly Legolas Media), Adomik, and many companies on whose boards I sat.  It is hard to know whether this worked.

These campaigns clearly help communicate the companies’ existence. But most of the readers are inside the MadTech echo chamber, so the advertising may work to sell to agencies and publishers, but probably not to brands we are also desperately trying to reach.  Given the industry we are in, it is surprising there is not more online advertising.  Part of the problem is that these campaigns tend to be short-lived and to focus on a feature function approach, not a problem solution.  Any brand manager worth their salt will identify key attributes they want their company to stand for and reinforce those attributes over many years.


Running ads on LinkedIn (Facebook, Twitter)

These promoted posts and native ad units clearly work for many companies.

While these data cross all industries, when selling B2B, the ability to target finely in these channels is clearly effective.  The key once again is to invest in these strategies over an extended period of time, which is difficult in an ecosystem that seems to changes every six months.

Spitting out some content

Content works.  Thought leadership REALLY works. However, for content to work it has to serve the interest of the reader not the author.  Most content is glorified sales pitches wrapped up in article.

A 2016 study by The Economist Group and Hill+Knowlton Strategies reported:

The qualities executives most associate with compelling thought leadership are

  • Innovative 40%
  • Big Picture 36%
  • Transformative 36%
  • Credible 35%

The qualities executives associate with unimpressive thought leadership are

  • Superficial 34%
  • Sales driven 31%
  • Biased 28%

Credibility is based on the quality of research, not the brand; nearly half of executives would consider a new source of content if it were a “source of hard facts”

  • Quality or nature of research analysis 55%
  • Credible data 55%
  • Expert opinion 33%
  • Evident or declared interest by the provider 14%
  • Secondary data validation 13%
  • The brand plays an active role 7%
  • The media / public profile of the provider 5%
  • No branding at all 3%
  • Other, please specify 1%
  • I do not trust thought leadership 1%

Much of the content written by MadTech companies is poorly thought out, and driven by the desire to quickly stand out in the market.  It so often rarely does, that people often blame the medium instead of the message.  We all know that the world has changed and we are competing for attention.  Consumers, whether trying to pick a movie or purchase  a $1 million piece of software, are selecting what they choose to consume, pulling that information to their screen, and quickly engaging or passing based upon their perception of the quality, credibility, and insight.

Buyers are also increasing influenced by high quality content.  The study by The Economist Group and Hill+Knowlton Strategies further reported:

76% of senior executives are influenced in their purchasing decisions

67% would be willing to advocate for that brand or organization externally

83% would be influenced in their choice of business partner


So, in summary.  MadTech marketing is confused.  It is most driven by demand-  and lead generation, not traditional marketing, and almost never brand building. Many of these decisions are logical and make sense given the different pressures in the MadTech ecosystem.  All 7 of typical responses:

  1. Hiring sales people who have a great “list”
  2. Attending trade shows and conferences
  3. Sponsoring trade shows and conferences
  4. Email campaigns
  5. Run ads in the industry publications
  6. Run ads on LinkedIn, Facebook, Twitter
  7. Spitting out some content

All these methods can and do work.  Some maybe better than others, but the strategy to employ is often driven by the stage of the company and the maturity of the team.

However, the world is changing.  Success and consolidation have forced many companies to change their strategies. The young and new technologies will continue to be driven by the feature/function, and marketed based upon delivering the next key event in the company’s life. But many of what were “new” tech segments of 3~5 years ago are now established.  Think of the key technologies that were exploding on the scene: SSPs, exchanges, DSPs, DMPs, video, cross-device, etc.  These have all become established parts of the ecosystem, with multiple companies generating hundreds of millions of dollars of business (some much more).  It is now time for these companies to slow down in order to succeed in the next round of growth.

So, in summary.  MadTech marketing is confused.  It is most driven by demand- or lead generation, not traditional marketing, and almost never brand building.  Many of these decisions are logical and make sense given the different pressures in the MadTech ecosystem.  All seven typical responses…

  1. Hiring sales people who have a great “list”
  2. Attending trade shows and conferences
  3. Sponsoring trade shows and conferences
  4. Email campaigns
  5. Running ads in industry publications
  6. Running ads on LinkedIn, Facebook, Twitter
  7. Spitting out some content

… can and do work.

What I Learned at IAB Leadership

If your goal is to meet with senior people in the industry, the IAB Leadership Conference  is among the best of the year.  The conference draws mainly senior people, has fairly good content (high praise for MadTech conferences), and everyone is under one roof (unlike CES, Mobile World Congress, SXSW, etc.)

It does suffer from a common problem, however: There are more vendors than buyers. But ratios are better and the people who attend – including publishers, agencies, and brands – are senior and engaged.


  • MadTech is capable of solving the #FakeNews problem. We helped create it, therefore we have to own our portion of the solution.
  • Transparency is the new watchword for 2017:
    • Procter & Gamble have thrown the gauntlet down, calling on the digital media industry to become transparent in the face of “crappy advertising accompanied by even crappier viewing experiences.”
  • Mobile continues to grow and is making life more complicated and evermore “real time.”
  • Storytelling still matters (organizers could recycle this talk every year — it will not change).
  • Measurement and attribution are going to be top industry focuses in 2017.
  • Google, our personal misgivings aside, continues to push ideas, tools, and commitments to an “open web.”
  • Data is getting smarter and performing better. It is also consolidating quickly, creating new challenges, particularly if everyone is using the same targeting data.
  • Content is still king, but the good publishers have valued short term revenue over their readers and viewers, and have let Facebook and other walled gardens dis-intermediate them from their community.
  • Consumers have the all the power to select which content they choose.


Observations from outside of the formal conference presentations:

  • Around 1,000 people paid to attend; another 200 showed up to hang out in the bar.
  • Attendees are getting older – far fewer people are staying out until 4AM.
  • I still had to get on an airplane to meet with people who work within just a few miles of me.
  • It remains a male-dominated industry, but the signs of change are definitely clear. This change needs to move along a little faster.
  • Diversity. Why is #IABSoWhite ? And it doesn’t stop there.
  • This industry is still driven by geeks, nerds, and misfits (thank goodness)!

WTF is MadTech

Industry Index began using the term “MadTech” as opposed to AdTech or MarTech, as these technologies began to converge and overlap. We think of MadTech as the intersection of AdTech and MarTech. So first some definitions:

The term “AdTech, which is short for advertising technology, broadly refers to different types of analytics and digital tools used in the context of advertising. Discussions about AdTech often revolve around the extensive and complex systems used to direct advertising to individuals and specific target audiences.”  Techopedia

MarTech is the blending of marketing and technology. Virtually anyone involved with digital marketing is dealing with MarTech, since digital by its very nature is technologically-based.” MarTech Today

AdTech was borne by Google. Yes, there were other companies earlier, but Google really created the category.  They figured out how to make gobs of money by leveraging their proprietary technology to sell advertising (via paid search results).  Many others have followed in their wake, but AdTech companies  make money one of two ways:

  1. They sell media married with a proprietary technology. Their income statements have a huge top line, but the next line is an expense, their Cost of Media, and usually runs 60%~90% of total revenue.  This includes DSPs, exchanges, SSPs, ad networks, retargeters and publisher optimization tools.
  2. They sell a technology based upon the number of impressions served (the CPM model).  This started with ad serving and has continued to evolve to include DMPs, creative optimization, rich media, ad verification, measurement and analytics.  (A lot of publisher-centric technologies — which we also cover under MadTech — also follow this model, sometimes counting “pageviews” or “visitors” rather than impressions.)

MarTech meanwhile is traditionally sold under a software or service contract and recently adapted to a SaaS model. It’s offered directly to brands rather than through  agencies and other intermediaries.

Another way to differentiate AdTech from MarTech is that AdTech typically targets anonymous audiences, while MarTech targets known customers.

It’s All Melding Together

Today, the distinctions among AdTech and MarTech are no longer clear.

MarTech companies are moving into the realm of AdTech.  They are actively engaging with unknown customers  (think HubSpot and Marketo, who are actively engaging in tracking anonymous website visitors while also managing known visitors). Equally importantly, MarTech is often initiating the decision to target a known or unknown user.

Retargeting, which was traditionally AdTech and therefore anonymous, is now partnering with companies that translate cookies to users, emails, and sometimes names and addresses. AdTech companies, in which we’ll include publishers, are also rapidly trying to move their business models from “media” to “technology.”

Large vendors like Adobe and Oracle have acquired AdTech companies and integrated their technologies into their other marketing technologies and built a marketing and advertising stack, effectively consolidating these categories into a unified offering.

AdTech is beginning a massive transition and likely consolidation. Some of the change is due to the preference equity investors place on “technology” over “media,” but much is due to the frustration of buyers over the lack of transparency and the clearer opportunity to create value for their clients with a “technology” sale. Of course some players, particularly publishers, still seem to prefer the “media” model, but these preferences will also evolve as publishers experience the value and increased revenue opportunities of transparent pricing.

Also, the boundaries among silos within a company are fading as new technologies are deployed. Delineation between call centers, marketing and sales used to be clear. But with a persistent user ID that follows a customer across websites, phone calls and advertisements, companies are forced create far more overlap among these formerly disparate groups.

AdTech and MarTech are becoming interchangeable terms used to describe an assortment of technologies, data sources and tools that  fundamentally focus on reaching the right audience with the right message at the right time and place.
For this reason, Industry Index has decided to call all of this technology MadTech. Now our challenge is to appropriately categorize and organize these different companies into a structure that is understood, searchable, and provides knowledge to our community.

BIG DATA–The New Monopoly

mo-nop-o-ly (noun) –the exclusive possession or control of the supply or trade in a commodity or service.

Generally speaking, monopolies are considered bad for the economy and the consumer.  Two of the most easily remembered monopolies are the original AT&T and Standard Oil.  AT&T was given its monopolistic status by the government, whereas Standard Oil, achieved it through business practices. In both cases, the government eventually broke up these monopolies, and innovation, lower prices, and competition thrived.

Data is the new and most leverageable monopoly commodity!  Big Data companies are successfully creating barriers to entry that stifle competition and create a new type of moat around their success.  Unlike traditional analog monopolies, the marginal cost of a new customer is effectively zero.  No new plants to build, no distribution costs, no new staff to hire (yes, there is a real cost to building and running these data centers, but the costs of that technology continues to drop rapidly).

Today, it appears that some of the largest consumer data aggregators — Google, Amazon, Apple, Facebook, etc. — have emerged as near-monopolies in their ability to collect data and insights about consumers.  Facebook, as one example, built its business on an advertising model, but its real value is data targeting.  It has more and better data about most people (at least in the U.S.)  than almost anyone else.  The more users Facebook engages, the lower Facebook’s data acquisition costs and the higher their value. Amazon has a similarly unique data set as the largest online retailer in the U.S., Google as the dominant search engine, video platform (YouTube) mobile OS (Android), and ad platform (DoubleClick). Apple, through iOS. The other two companies that might be thrown in the mix are AT&T Wireless (thanks to Apple, by the way) and Verizon Wireless (along with its acquisitions of AOL and Yahoo), which have the two largest databases of mobile IDs in the country.

However, our governmental institutions today are ill-equipped to respond to the challenges of global companies growing at exponential rates. Traditionally, the value of a company was built on a combination of intellectual property and physical assets (plants, trucks, machines, etc.). The physical assets were often developed and acquired based upon the underlying intellectual property (think patents).  Today, it still takes around three years to get a patent, but companies’ ability to leverage intellectual property can happen in a few years or even months.  As an example, Uber burst on the scene with its founding as Uber Cab in 2009, and reached a valuation at $3.5 billion in 2013. Had they waited for a patent approval, they would have missed the market opportunity.

Does It Matter?

Each of the big data competitors has emerged with a unique opportunity to collect more and better data and then sell that data to advertisers. Does it matter?

The short answer is yes, it matters. These giant data aggregators are already dominating the ability to leverage data to more effectively to target an ad.  But the insidious part is their ability to disaggregate a supplier from a buyer.  Companies like Amazon or Facebook know (or infer) not just who you are but what you are like. They know not only where you are but they can guess where you are going. They don’t just know what you are doing right now — they have a pretty good idea why you are doing it. And they make excellent guesses about what you will do next, guesses that grow more accurate as you go about your daily life while being carefully observed by the data giants. Amazon is already adjusting its pricing algorithm in real time. Amazon can charge one individual a different amount than another. Since the acquisition costs of many products are pre-negotiated, when it chooses to increase a price, the incremental margin remains with Amazon. Additionally, Amazon knows more about the value of a product than the manufacturer.  Therefore, Amazon can negotiate the price for every item and drive down manufacturers’ margin.

They have users’ shopping data, now married to zip code (which tends to indicate income levels) and to family members (if you set up “sub-accounts” on Prime). Amazon acquires age and demographic information, and if they want to, Amazon can purchase your credit score and other available data to provide a fuller view of a consumer. They can successfully charge you more than the next buyer for something they’re confident you want, like that “soon to obsoleted” piece of technology.

In the narrow confines of online advertising and commerce, combining some of these data clearly makes marketing more efficient by improving targeting, and by identifying and eliminating the famed half of the marketing budget that is wasted. As HBR noted:

“Marketers have trained their big-data telescopes at a single point: predicting each customer’s next transaction. In pursuit of this prize marketers strive to paint an ever more detailed portrait of each consumer, memorizing her media preferences, scrutinizing her shopping habits, and cataloging her interests, aspirations and desires. The result is a detailed, high-resolution close-up of each customer that reveals her next move”.

We have reached an inflection point.  Data are ubiquitous, and the marriage of data from multiple sources is commonplace. We are witnessing the transition from from data improving efficiency, to data becoming a strategy, to data becoming a barrier to entry (monopoly)!

Today, data is a strategy, and we need to start thinking about it as one. While scale is always a source of leverage for a supplier, with data the marginal acquisition cost is near zero and the benefit to data aggregators grows exponentially with each incremental data element. Data should adhere to the same competitive standards as other business strategies. Data monopolists’ ability to block competitors from entering the market is not markedly different from that of the oil monopolist Standard Oil or the telecommunications monopolist AT&T.

The real problem is that our institutions are still moving at the speed of analog while our economy is literally moving at the speed of light. The actions and behaviors of these companies is rational and so far seemingly legal, but left unchecked they will become egregious. Data corrupts and absolute data corrupts absolutely.

Where Has All the VC Gone?


The drumbeat about the dearth of VC funding for AdTech has been growing louder recently.  Alternatively, MarTech funding has been growing rapidly and continues to accelerate.  So why has AdTech underperformed and why is MarTech so attractive to VCs?

The challenges of AdTech for VCs?

  1. No Exits.  AdTech companies cannot exit, so why invest?
  2. No Growth. Google, Facebook and a few other monsters are sucking all the revenue growth so everyone else is fighting over scraps.
  3. No Innovation. The only companies looking for funding are “me too” DSPs, SSPs and the like.

Each argument has merit if you narrowly define “AdTech” as technology companies who make money off of media spend:

No Exits.  With few exceptions, the IPO market has not been kind to AdTech. The exceptions, TradeDesk, Criteo and YuMe, are overshadowed by the dire stock performance of Rocket Fuel, Rubicon, and TubeMogul (before its sale to Adobe last November). But this not really a fair analysis. The interesting exits have come from the M&A side: NeuStar, Sizmik, Smaato, StickyAds, AddThis, ConvertMedia, ReachLocal, etc.  But since most of these deals are private, the exact terms, particularly the originally invested equity, are difficult to find.  Suffice it to say, VCs are generally not drooling.

No Growth: It’s difficult to argue this point. Depending upon who’s counting, Google and Facebook accounted for 75 percent or more of all new online ad spending. Whatever number is correct, these two companies are capturing a disproportionate share of new digital ad spend. The other 3,000+ AdTech companies are fighting over the remaining 25%~35% at most.

No Innovation:  Here is the interesting area. Hundreds and hundreds of AdTech firms were funded from 2009~2013. With few exceptions, they were all variations on similar themes:

  • Automate the selling of media (SSP’s, exchanges, publisher tools, networks, etc.)
  • Automate the buying of media (DSP’s, exchanges, trade desks, creative optimization, measurement, etc.)
  • Data (DMP’s, data aggregators, offline/online conversion, etc.)

Again, the revenue model for all these companies is based upon a percent of media spend or, in a few cases, a CPM charge.

The challenge for most of these companies is in proving they add value. For almost all the technologies developed within AdTech, scale trumps innovation.  Once one company achieves a minimal level of scale within a technology segment, the incremental value of a better black box is usually trumped by the reach opportunities of scale.  Second, where hundreds of AdTech companies have focused on optimization technology in one shape or form, it turned out the better data was what won. Facebook’s success is based upon the best data.  It has far from perfect data, but it is the richest, broadest, and certainly deepest data available.

Also, let’s not forget that the AdTech community has wounded itself by burying its technology inside of black boxes with promises of “better performance” but with almost no ability to compare one solution to another.  Hence, high churn, higher customer acquisition costs, and declining margins.

It’s no wonder that the VC money has been steadily migrating away from AdTech.  According to Results International , “The number of AdTech deals completed is down slightly year-on-year, a 10.4% decrease from 67 transactions in H1 2015 to 60 in H1 this year. The total value of those deals fell from $7.6bn in H1 last year to $3.7bn in H1 2016. The H1 2015 figures were skewed by Verizon’s $4.4bn acquisition of AOL in June 2015.”

By comparison, “the number of MarTech deals rose from 132 in H1 2015 to 158 in H1 this year – an increase of almost 20%. MarTech deal value rose from $1.5bn in H1 last year to $7.8bn in H1 2016. However, this year’s figures are skewed by a number of acquisitions in excess of $1bn: Demandware by Salesforce ($2.8bn), Marketo ($1.6bn) and Cvent ($1.7bn) by Vista Equity Partners, and Sitecore by EQT ($1.1bn).”

Why is MarTech winning?  Besides being shiny and new, the business model of most MarTech companies is a true SaaS model.  In order to sell SaaS, companies need to provide a way to measure ROI and deliver real value to customers.  Also, the customer base is different.  AdTech’s business model, built of media spend and buried in black boxes couldn’t be more different.

MarTech is generally sold directly to the enterprise, as opposed to fickle agencies.  While these sales cycles may be longer, customer loyalty is real and, maybe most importantly, enterprises are willing to share the right data and measurements to create a partnership, whereas agencies either don’t possess, or choose to withhold such data as a negotiating club (“No, you didn’t really perform well…”).

According to Lola Alford  from Thumbtack Technology the MarTech segment set records in global venture capital funding in the second quarter of 2016 at more than $5.05 billion. That’s already 72 percent of the $7 billion MarTech firms netted over all of 2015.  A large portion of that funding, some $3.5 billion, was invested in May alone. In comparison, VC-backed FinTech funding in Q2 reached only $2.5 billion, down 49 percent from Q1 funding for this year and down 52 percent from Q2 of 2015, according to data from KPMG and CB Insights.

So what does this all mean?

  1. Raising VC money for traditional media-driven AdTech is extremely hard.  It can be done, but valuations are down and only the strong, with unique offerings, are raising money.
  2. AdTech companies that are selling a true SaaS model will do much better with VCs.  In general, this means companies selling directly to enterprises are better positioned, but the SaaS model is also well accepted by publishers, so PubTech tools (header bidding, SSPs, data capture, user engagement, etc.) are proving more adept at proving long-term value.
  3. MarTech should continue to win for the next few years. All B2B technology companies are well served to think through their business model.  When you sell something, whether a recurring revenue or a one time software sale, you have to prove to the buyer your ROI which forces you to deconstruct your technology and how that value is created.  Burying software costs within a larger media budget is helpful in winning a deal, but severely challenging when trying to keep a customer.