Cross-Device and Cross-Platform Targeting

By Jed Wheeler, Director of Solutions Engineering

Some of the enduring sources of pain for digital marketers include associating consumers with their digital devices, and assembling the right data sources to establish those relationships.  Over the past two years, cross-device targeting has become an established product category aimed at alleviating this pain, with several companies specializing in cross-device matching data. RadiumOne is integrated with all of them.

The challenge in using that data is twofold.  First, one must validate its accuracy.  Second, once it’s been applied to recognizable users, contextual data must be layered on to make it meaningful.  

This month, RadiumOne released two significant products that help address these issues.  The first is a cross-device data store, which allows us to to store, correlate, and cross-check third-party data with our proprietary cross-device data.  That’s a big deal because we can now tie together broad site/app usage data from over 95 ad exchanges with data acquired via our deep software integrations with thousands of web sites and apps.  

The second big release is Smart URL, an enhancement to our link shortening tool that enables deep linking.  For a more in-depth look at that tool and how it empowers marketers, check out my recent post on the blog.  The most significant item for this discussion is that, with Smart URL deep linking, marketers can benefit from 1-to-1 matching of mobile web and mobile app interactions – tying cookies and device identifiers together into a single cross-platform user profile using a deterministic (100% accurate) match. This is significant, because many companies that specialize in cross-device data build their so-called device graphs on probabilistic matching — a far weaker way of tying together consumer web and app engagement  

Tying together data from mobile app and mobile web behavior seems like a simple task, but it’s surprisingly difficult.  The problem is that the two systems use parallel forms of anonymous user identification — cookies on web and IDFA/GAID in native mobile apps.  Unless you happen to be lucky enough to have a service that people regularly log into on both platforms (Facebook being the obvious example), there simply hasn’t been a good way to tie these data sets together.  My recent post on protecting end user privacy goes into the nuts and bolts of this in more depth. To summarize, because they use different identifying technology, neither platform can see what’s going on in the other, and data can’t be easily passed back and forth without impacting the end user experience.  Smart URL solves that problem.

So far, so good – identifying users across the three main digital mediums (desktop web, mobile web, and native apps) is a great start, but it’s only the first step.  The real win for marketers is in tying together interest and behavior data by combining the previously platform-dependant data sets.   

RadiumOne is in a unique position here because of the investments we’ve made in audience intelligence software.  All programmatic media-buying solutions can see bidding data from the ad exchanges.  Unlike other solutions, however, we are not limited to it.  RadiumOne’s social analytics tool captures over 250 million desktop and mobile user actions per day across thousands of  websites.  Connect, our full-featured mobile app analytics and push notification tool, captures billions of in-app events from tens of millions of users per month.  So our broadly-deployed audience intelligence software  allows us to see what consumers are interested in and what they do in a way that is simply not available to other programmatic media-buying solutions.  Our analytics software customers get top-of-the-line products for free and we get the anonymized usage data we need to help make your ad campaigns successful.  It’s a win for everyone.

None of the individual pieces here are new, but combining them is a “chocolate in my peanut butter” moment.  Unlike any other solution on the market, RadiumOne now has the data to create comprehensive cross-platform and cross-device user behavior and interest profiles and then take action on that data across all the major ad exchanges.   No other programmatic solution can offer this combination of deep insight and cross-platform targeting.  


The Fight to Keep Personally Identifiable Information Private on Mobile

By Jed Wheeler, Director of Solutions Engineering


One of the fundamental tenants of today’s digital advertising environment is that a line must be drawn between the use of information that is helpful for delivering targeted, personally relevant ad campaigns and the use of information that invades a consumer’s privacy. Over time Cookies have become the standard way to build user interest profiles without personally identifying the user, with the added bonus that end users can easily erase them at any time.  The industry switch to mobile presents new challenges that the industry is still wrestling with.

Most activity on mobile takes place within apps as opposed to web browsers, rendering cookies all but meaningless. Both Google (through GAID) and Apple (through IDFA) have introduced their own versions of mobile identifiers, but if someone wanted to merge IDFA or GAID data with a set of Personally Identifiable Information (PII), all anonymity and privacy would fly out the window. Unfortunately, in a complex ecosystem that involves app developers, ad networks, analytics providers and other platform companies, this scenario happens all too often.

One particularly dangerous scenario is brands piping data from their analytics solutions to their advertising tools to target consumers based on the goldmine of data these solutions collect, without first sanitizing the data and removing PII. Using app analytics to drive mobile advertising makes a lot of sense. Analytics tells us a lot about user behavior and therefore can help deliver better, more targeted ads, but we have to respect user privacy in the process. Unfortunately, most analytics solutions were never intended to be used to power advertising, and therefore they don’t have proper measures in place to control the flow of PII to parties that might not treat it with the respect it deserves.

For example, at a recent industry conference, a C-level executive at a major analytics company spoke at length about how advertisers should get over their “fear” of PII and just use it — apparently unaware that what he was advocating was illegal. Even in cases where there is no overt intent to share customer PII, it is far too easy for Brands to accidentally include it in data exports from common analytics tools.  This is a problem.  

RadiumOne is clear on this point.  We do not collect PII and we do not allow clients or their agencies to send it to us.  We’ve built our entire global data infrastructure around the EU standards — the strictest in the world — to make sure that we are fully compliant with privacy laws everywhere.

As an industry, it is imperative that we protect PII. Consumers don’t mind sharing their data with an app or service if they get something of value in return, but they don’t expect their personally identifiable data will end up in some anonymous third party’s data warehouse as a result, and they definitely expect that data to be treated with respect.  We hope our peers in the mobile analytics world will follow our lead.  

Why Visibility and Communication are Keys to Success in Programmatic Campaigns

By Lauren Magistro, Head of Account Management


Programmatic marketing can be confusing to those just catching on. More than understanding the technology ins and outs, clients often assume that success rests squarely on their agency’s shoulders.

In truth, a successful programmatic campaign has a lot of moving parts and mutual responsibilities. Ensuring satisfaction and renewed business comes down to making sure media planners and clients are able to agree on what goes into achieving success: 

Success starts on day one.

Feelings of excitement, relief and eagerness accompany every campaign launch. Launches represent a huge effort on the part of many and everyone is anxious to see the results start rolling in. But clients first need to be able recognize that the programmatic relationship isn’t the next leg of a race, but rather a partnership they will be part and parcel of throughout the life of the campaign.

Key to this partnership is establishing open and honest communication between parties. Though some clients arrive with a very solid plan in mind, it’s important that they be open to new ideas and responsive to future requests surrounding the campaign. Data accuracy runs on timely, true response, not vague answers and unopened emails. Besides setting a positive, collaborative tone, being sure to take this first step can ensure that client revenue potential is maximized.

Success and visibility go hand in hand.

The importance of being able to see what the client sees, in real-time, is another cornerstone of success. Any lag-time in discovering places for optimization decreases the ability of those on the other side (the programmatic third party) to act effectively. Visibility into all data generated during a campaign, together with client input, brings critical insights to light that clients who are not well-versed in programmatic don’t yet recognize. Transparency can be thought of as three pronged, meaning:

  • A continuous feedback loop to gauge performance relative to expectation.
  • Access to real time data through pixel placement.
  • Direct access to client’s 3rd party reporting to see how optimizations translate to performance.

Visibility improves conversion attribution accuracy.

Access to third-party reporting data not only helps the programmatic partner understand how their actions are being reflected in the data that the client sees, it also improves the ability to better attribute conversions to the right channel–very important to a client who is figuring out where to invest their money and time.

Success means thinking bigger.

Programmatic success depends on data—a lot of it, though sometimes clients lean towards limiting it. It’s a delicate thing to tell a client who comes prepared with demographic data and other campaign expectations that they don’t know best (another reason for setting those day-one expectations for open-mindedness).

Media planners can position it like this: the more data available, the more the programmatic partner has to work with. The very value of the predictive analytics involved in programmatic marketing is the ability to mine campaign-boosting directives from the overwhelming amount of big data out there. In order to give programmatic room to experiment with the data, the client must be open to widening the pass. Where the client may see nothing, predictive analytics may find responsive audiences a client would have missed had they remained rigid.

Open communication. A dotted line between your information and theirs. Lots of data. All points media planners should make upfront when talking programmatic success. After that, delivering on expectations is as easy as swimming downstream.

Read our white paper “A Pocket Guide to Programmatic Buying” to learn everything you need to know to get the most out of investing in media through programmatic ad buying.

Using Sankey Diagrams to Visualize Better Ad Placement

By Nicole Romano, Data Scientist at RadiumOne

A Sankey diagram depicting one week of testing for a single campaign. The nodes of the Sankey diagram show membership, in this case a snapshot of the web domains in the testing, holding, and highly targeted strategies on each day. The links between nodes show how these web domains are moved amongst the testing, holding, or performant strategies as we get more information about their active performance.


How do you use data to decide where to advertise? At RadiumOne, we spend a lot of time on that question. Considering that there are a vast number of websites that sell advertising space, and that different ads will perform better with different audiences, it can get to be pretty complicated. We recently developed a new visualization tool to help make sense of advertising performance data. As you can see from the chart above, we can easily track the performance of our ad testing platform as it shuffles advertising domains between three buckets: Test, Performant, and Holding. This tool came out of our participation in Insight’s Data Visualization Lab.

Dynamic testing pipeline

At RadiumOne, we use proprietary data sources to identify high-performance advertisement opportunities in the Real-Time Bidding (RTB) Marketplace. Our Data Science team leverages this data to build algorithms that identify users who are likely to convert for a particular advertiser. Because RadiumOne evaluates over 800,000 advertisement opportunities per second, we also build operational tools that provide automated feedback on the success of our algorithms and engineered features in real time.

When we participated in the Visualization Lab in May, our team had just finished building a dynamic testing pipeline that evaluates the performance of our web placement algorithms. These algorithms comb through millions of web domains to find contextually relevant places to display advertisements for a particular brand. At full scale, a false positive prediction — predicting an ad will perform well where it will not — for even one web domain could mean thousands of wasted advertising dollars. Our new testing platform evaluated the actual performance of these domains, using statistical tests to identify false positives with high certainty and minimal wasted ad impressions.

Our new testing platform targets the most promising web domains for a limited number of ad impressions. Once the number of testing impressions is reached, the domain is shuffled to either a holding area to await feedback (‘Holding’), or a highly targeted list (‘Performant’) if the feedback was positive. Domains can be shuffled back to the testing area (‘Test’) if more information is statistically necessary. Over the course of an ad campaign, a domain may be shuffled hundreds of times.

We chose to visualize the activity on this testing platform to see if any large-scale patterns were emerging that could inform future web domain algorithms. The platform was shuffling thousands of web domains amongst the testing environment, a holding area, and a highly targeted environment for performant domains (above). Each web domain could be shuffled hundreds of times in one test, its path regulated by feedback latency, performance goals, and statistical power. Visualization of such a complex and unique system was a daunting task, so we turned to Insight’s Data Visualization Lab.

Visualization tool

After a series of talks and exercises on effective visualization, I was introduced to Silvia, a data engineer from SVDS with a Ph.D. background in data visualization. Silvia looked at my use case and recommended the Sankey Diagram, a type of flow diagram usually used to depict the transfer of energy or money in systems. This suggestion was the first in a series of breakthroughs during the Lab that demonstrated to our team the practical value of the Visualization Lab.

Using the Lab’s visualization resources wiki, I rapidly identified several open-source tools that would allow me to build a Sankey Diagram. The visualization expert talks had introduced me to several concepts, such as tooltips and cross-filters, which allowed me to build a visualization interface that was both simple and powerful. After consultation with the Visualization Labs experts, I chose to work with Google Charts’ wrapper for d3.js.

Insight Data Labs had invited Shelby Sturgis, a Visualization Engineer at Elastic and d3.js expert, to give us hands-on help with our projects. As Shelby and other visualization experts worked their way around the room, I wrote a python script to wrangle my data into the proper format for d3. Shelby helped me navigate the d3.js library and Google Charts API, pointing me to valuable resources and code blocks along the way. Effective visualizations are rarely built from out-of-the-box solutions, and my project was no different. Because this visualization required me to circumvent some of the design characteristics of Google Chart’s Sankey diagram wrapper, Shelby’s advice was crucial to the success of my project. The fact that I could build this visualization using an unfamiliar Javascript library in under a day is a testament to the expertise available at the Visualization Lab.

I returned to my team with a visualization product, a new familiarity with open source tools for visualization, and a catalog of code blocks that I could use for other visualization products in the future. Perhaps more importantly, I returned with new insights into our testing platform, which have informed a new model for ad placement algorithms. With every iteration of this algorithm, we can easily visualize emergent patterns using the Sankey tool built in Insight’s Visualization Lab.


What Success Metrics Should You Care About

by RadiumOne Optimization Team


Ask anyone what metric they use to size up campaign success and it’s likely you’ll Purchase this image at a few different answers. There are, in fact, numerous ways you can run the numbers to make sense of how well a campaign is doing and help pinpoint areas for optimization. This wealth of metrics is alluring to clients, many of whom get started too quickly and become overwhelmed in metrics they weren’t ready for.

Spending too much time processing too many metrics can cloud the path to campaign success. There’s no golden metric lighting the way, but zeroing in on just what a client is trying to achieve is a key starting point. When talking about the “right” metrics, first consider what kind of ad campaign is being run and the intention of users impacting the numbers:

Direct response campaigns include people at both the bottom and top of the funnel of intent. At the bottom are users contemplating an imminent purchase or subscription. At the top, users are more easily swayed and open to brand messages to drive them closer to action. Within these types of campaigns COST Per Action is the standard metric for success—giving advertisers a sense of cost-efficiency in their messaging efforts.

Because brand-oriented campaigns target users who are not expected to convert or make a purchase within the next few days, the purpose—and most relevant success metrics—is different. Measuring success in brand-awareness campaigns often falls to an old, but well-recognized standard: the Click-Through Rate or CTR which quickly reflects the increase in traffic to your brand page.

After considering the above the number of available programmatic KPIs (key performance indicators) blows up quite a bit in terms of technology options third party vendors offer to help you make the most of your client’s campaign. A few of these include:

  • Viewability: an online advertising metric that aims to track only impressions that can actually be seen by users.
  • Brand Safety: refers to practices and tools allowing to ensure that an ad will not appear in a context that can damage the advertiser’s brand
  • In demo verification: (interchangeable with the below)
  • Audience verification: measurement by a third party validating that the audience (demographic or psychographic) of the campaign is in line with that requested by the advertiser
  • Brand studies: independent research conducted by a third party to measure the effectiveness of campaign in increasing brand awareness or favorability

The digital advertising space is extremely dynamic and becoming increasingly complex. Evaluating too many metrics at a time can get in the way of accomplishing your initial goals.

There’s no one “golden” metric for measuring success, but being thoughtful about the metric you choose can take you a long way. In short, before you or your client jump off the KPI deep-end, stick one toe in the water in terms of asking yourself just what you are trying to achieve. Contact RadiumOne for more information on how to get started with your campaign!

2016 Election Strategies Trump High School Locker Tactics

by Stephanie Schepp, Account Director

We’ve all endured at least one class president campaign. They mostly went like this: candidates rallied friends and invested resources into poster board and personalized swag. The savviest among them often boosted visibility by slipping campaign literature into all the lockers—the one place students would certainly see it.

Skip ahead to the 2016 Election and similar tactics remain—rallying voters, preparing literature and printing a bumper sticker or two. But the process of placing the issues close to prospective voters has become a great deal more complicated and exact.

Today’s digital platforms have added a level of sophistication to campaign strategy unseen since the marriage of politics and television. The first televised debates beamed the images of two presidential candidates out to more people, directly to where constituents were found (their living rooms), faster than any medium previous. Today, digital has quickly eclipsed this early example in several ways.

  • Digital is increasing campaign efficiency and scale.
  • Digital is helping strategists render and place messaging more relevantly.
  • Digital is ensuring political participants, strategies, and messages are mobile-ready.

How do today’s digital campaigns differ from earlier years?

Not only does digital allow candidates to engage with hundreds of thousands of voters instantly over email, social media and other platforms, digital is giving campaign strategists and data analysts immediate feedback so that they can tailor messaging and retarget voters on-the-go.

Digital is increasing efficiency in campaign spending.

In terms of monetary efficiency, digital is allowing campaign finance to rest a little easier at night because digital data insight is now at their fingertips. Before digital, it might have taken months to see the effect of precious political ad dollars. And the ability to adjust to the results was equally as slow. Today, strategists can quickly gauge if their dollars did well in one market over another, with one message versus another, or across one particular platform or another—and make near real-time adjustments to save ad dollars.

What strategic elements of political campaigns are being impacted the most by digital?  

Programmatic media buying services have a handle on helping people and parties target their political advertising audience down to a science—a science that is becoming increasingly sophisticated as more big data on prospective voters (like where they travel, what they wear and what brands they are loyal to) is made available.

The ability to layer geomarketing techniques including geotargeting and geofencing on top of other telling digital data like voter registration details has dramatically increased both the relevancy of campaign messaging and the pace and scale at which political marketers can promote across hyper targeted audiences and platforms. This applies both to a campaign’s ability to target messages to their own party members and to cross-target messages across party lines.

Political campaigns are also leveraging the growing value of video to reach voters where they are and to tactically stir and steer the direction of campaign issues. Here, too, programmatic advertising enables campaign strategists to use social media as a way to get voters and non-voters alike to listen, share and interact with campaign messaging across multiple platforms, geographies and other campaign-critical demographics.

Applying best practices, analytics tools and other cross-platform solutions, digital consultants can work with campaigns to create a branded content experience, drive donations, recruit donors, promote personal fundraising and ensure rapid compliance.

Campaigns are given access to tools that manage offline outreach, create targeted lists of decision-makers, create and deliver petitions and connect campaign efforts to social media.

To top it all off, in-depth analysis helps campaign staff search constituent records, share data with other systems, optimize fundraising efforts and track what efforts supporter have taken from sign-ups to donations to sharing.

Digital data means getting feedback—all the time.

Digital is a tool that allows for continuous feedback to happen between the political campaign and the environment outside of them. It’s this very feedback that is allowing marketers and advertisers in both the political and corporate world to inch closer to their conversion goals. Constituent and consumer…to voter and buyer.

Programmatic Takes the Lead as Political Candidates Look to Add More Fizz

by Caitlin Borgman, Director, Strategic Accounts

When Coca-Cola answered the personalization trend with its “share a Coke” campaign – replacing the familiar cursive logo on its soda products with namesakes and common nouns – another branding rule went out the window. Not just any company could pull that off.

Giving up prime ad real estate takes a lot of guts, especially when finding the most valuable place to park your brand is becoming so sophisticated—most noticeably when it comes to digital advertising.

Political parties and their candidates have begun paying more attention to the value of digital and how big data intelligence can help them reach their ideal voter when they are most receptive. What impression should they place and where? Powerful analytics is giving them just that.

What is it that’s turning political heads towards sophisticated media buying practices like programmatic advertising?

According to Borrell and Associates research, digital media spend on political advertising will break the $1 billion level for the first time in 2016. Political strategists are turning to programmatic as an efficient and effective way to expand their digital presence. Taking a more personalized approach to political ad impressions will get a candidate more attention (like the increased consumer interest spawned by customized Coke cans).

Just a few years ago, campaigns were targeted to generalized voter segments. Today, programmatic buying makes it easier to find the best times, places and platforms to reach potential voters with targeted messaging. For example, political camps wanting to get campaign-winning insight on how the country feels about certain healthcare issues could leverage programmatic to quickly deliver a poll to the most relevant, receptive audience across desktop, mobile, apps email, video and more. In the case of the healthcare poll, the best programmatic strategy might be delivering 20,000 impressions of the poll to people currently engaging with popular healthcare site, WebMD.

This recent CNBC story helps explain how ad tech firms are leveraging big data insight–like what political party is associated with buying one juice brand over another–to point their clients to the best media buys.

Programmatic and the Politics of Tomorrow
Growth in online political ad spending is expected to increase dramatically over the next five years with $3.3 billion estimated to be spent in the 2020 election.

To find out more about programmatic advertising and how RadiumOne can find your next customer, contact us today.

Top 5 Myths of Programmatic: A Programmatic Primer Part 3


by Maryam Motamedi, Director of Marketing 

(This is part 3 of a 3 part series. Read part 1 and part 2.)

Having a solid understanding of programmatic marketing principles (what it does, how it works and why you need it) is hard enough. Try tackling the public vs. private debate on top of all this and you’re likely to run yourself in circles.

Below are just a few of the common myths about public and private exchanges circulating within the industry right now:

Myth 1. You must pick a side.
A common programmatic misstatement you’ll find is that publishers and advertisers have to choose what side to stand on: public or private. But, says Kevin Dalias, Product Solutions Consultant for RadiumOne, “You can’t think of public vs. private as two different camps. They are simply two ways to reach users.” So why the strong debate over which one is better? Many  automated media buying agencies prefer one exchange over the other and target their content accordingly, others, like RadiumOne prefer to be “exchange agnostic”.

Myth 2. Premium programmatic is a new animal.
The concept of leveraging private exchanges to house premium content and command higher revenues isn’t entirely new, despite all the fanfare. Historically, publishers put together “ad networks” by bundling selected sites and selling brands access to these handpicked networks at a premium. Private networks are simply the automated answer to an already-established ad buying/serving model.

Myth 3. Public exchanges carry more risk than private.
The answer is: It depends. Public exchanges are as clean as you keep them. “[RadiumOne] invests a huge amount of time in making sure our inventory  is clean and that we are serving impressions to human beings in the right times and places,” says Dalias. In the case of RadiumOne guarding its clients against fraud, the company uses their own, proprietary algorithms and have integrations with several third-party protection providers.

Myth 4. Private exchanges are the “best place” to see and be seen.
In the old world advertising model, “where” you reached users was paramount. Buying and serving ad impressions in a select setting, after all, comes with certain guarantees as to brand strength and eyeball count. But delivering a relevant ad experience with the intent of increasing conversions isn’t just about reaching customers in the right place…it’s also about reaching the right customers at the right time. The right user may be surfing a news publication and then a shoe store. In this context, private exchanges are limiting in terms of reach as you are taking the gamble that the right customer will happen to exist within the confines of that private space with limited reach.

Myth 5. Automated ad buying eliminates the need for human interaction.
Though automation is helping make the ad buying process more efficient and effective, it can’t replace the relationships that have to be built and maintained in order to ensure,that campaigns are being run in a way that is aligned with the advertisers’ expectations.  It’s shortsighted to assume that all you need from a programmatic solutions provider is good technology. You need good people too.

If you’d like to find out how RadiumOne can help you make more sense of the public vs private debate while helping you reach the right people at the right place and time, contact us.

Weighing in on Private Marketplaces: A Programmatic Primer Part 2

by Tony Biel, Account Director


This is part two in our programmatic primer series focusing on RTB public and private marketplaces. You can read part one here.

Today programmatic marketing is a well-oiled, fast moving machine. But it wasn’t always that way. The growth of digital advertising has seen the ad buying process evolve from person-to-person ad negotiation to a complex technology-driven configuration of traders, advertisers, publishers and targets.

From the first year digital advertising took off until now, the number of ads, clicks and impressions available has continued to grow exponentially. New marketplaces or “exchanges” were the industry’s answer to the need to centralize quickly rising digital ad inventory. Out of these original “public” exchanges arose the eventual implementation of publisher-created, private marketplaces. These public and private marketplaces make up the Real Time Bidding (RTB) arm of programmatic marketing.programmatic_activate graphic

In Part 2 of this RTB primer we define “private” exchanges, who uses this exclusive method of buying and selling digital inventory, its benefits and what place it holds in the future of programmatic advertising.

Private Marketplaces Defined

A private marketplace is one created by the publisher, made public to select clients, and represents their premium inventory. As opposed to awarding impressions to the highest bidder (as is the case with a public exchange), private marketplaces are closed systems. It’s up to the publisher who they want to invite to make purchases on their platform. Also unlike public exchanges where real-time market competition is driving rates, private marketplaces include pre-negotiated terms like flight dates, floor prices, auction types and budget.

Though the debate continues as to which type of marketplace is truly the better place to invest digital advertising dollars (public vs. private), publisher-created private marketplaces attempt to elevate the quality of their content and draw a crowd that values service and singular relationships over price.. Though several recent articles are predicting interest in private marketplaces will eventually overtake public exchanges in terms of popularity, as of 2015, private marketplaces only accounted for 23% of the total RTB market spend.

The benefits of private marketplaces are the following:

  • More control on pricing policy
  • Not tied to an underlying system.
  • Publisher has the chance to be more creative.
  • Publisher has more control over brands and products represented.

As discussed in Part 1 of our programmatic primer, public exchanges also have a wealth of benefits all their own:

  • Equal access to any impression.
  • Massive amounts of inventory.
  • Widest campaign coverage possible.
  • Meets full range of advertising goals.

Public vs. Private? The Jury is Still Out.

So is one format better than the other? Are private marketplaces elitist or do they really add value? If so, where?
Maybe you’re mulling over your options. Public? Private? Both?? Maybe you have so much on your marketing plate you can’t seem to see the forest for the trees? Either way, our next primer will include in depth insider discussion about public vs. private marketplaces that you won’t want to miss.