Despite what might be considered setbacks for the programmatic industry in 2017, like the YouTube ad controversy and the constant battle against “bots” and “ad fraud” – more and more marketers are investing in programmatic advertising. eMarketer estimates nearly four of every five US digital advertising display dollars will have been transacted programmatically in 2017, totaling $32.56 billion. For 2018, programmatic digital display ad spending will climb to $39.46 billion, with 80% of mobile display ads being purchased programmatically — that’s up 21% from 2017.
So marketers can’t afford to not get on the programmatic bandwagon, if they want to be effective in getting their brand out in front of customers and prospects, the Holiday Season is prime-time for getting a running start.
6 Reasons You Should be Buying Programmatically ASAP
1. The world of advertising is moving towards Automation. With more of the advertising display dollars being spent programmatic platforms than any other method, and huge advancements in ad technology, brands who continue to buy ads manually will fall behind their competitors who choose automation.
2. Personalization is now achievable though Programmatic. Personalizing your marketing has always been a goal but now it’s a real thing through programmatic targeting tactics like geolocation, in-depth demographics information and dayparting, for example. And also more consumers are accepting of and are feeling more positively about a brand when their ads are personalized.
3. More Data! With marketers being tasked to analyze and optimize on hundreds of different data points about their users, programmatic platforms can use this data to create detailed behavioral profiles of existing customers and even prospects. This data can then be used to enable tactics like lookalike modeling and contextual targeting which gives advertisers the ability to create a more personalized media plan for their Holiday campaigns.
4.Dynamic Creative Optimization (DCO) really works. DCO technology enables marketers to use programmatic platforms to deliver on the promise of serving relevant and custom advertising to the consumer and capture their attention. This also gives marketers the opportunity to have their best performing creative be served more often. Studies have shown that DCO ads can have up to 50% higher post-click conversion rates over standard display ads – delivering overall better results than non-dynamic creative.
5. Make Storytelling a reality by reaching the right audience. Today’s customer expects a journey, an experience, a story from their advertiser or brand. With the accuracy of programmatic targeting and the sophistication of ad-tech platforms, there is finally the potential to deliver this.
6. More scale equals more opportunity. With more consumers adopting ad blockers, every opportunity to get in front of potential consumers needs to be maximized. Programmatic provides the scale that most marketers need to get in front of the right consumers at the right time, especially during the Holiday season.
Anyone in the marketing role knows that the holidays are a crucial time for ads, which means that the market is flooded with advertising, but not all of it is optimized for the best results. In addition to getting on the programmatic bandwagon, here are some other things marketers should be thinking about:
Creative eye-catching images and well-written ad copy that is most relevant to your target audience.
Your ad should directly link to the product you want to sell, saving time for the customer.
Have a strong call-to-action; make it time-sensitive!
To find out more about programmatic buying tactics and shopping habits this 2017 Holiday season download Digilant’s ‘Holiday and Consumer Shopping Report.’
The rise of digital advertising has given marketers fuel to reach their ultimate marketing goal: connect the actions of users into a meaningful whole. When marketers know a lot about their consumers, advertising is personally relevant and more effective. Personalization of brand experiences is a powerful way to drive conversion – and in digital advertising, personalization is driven by data.
Pre-digital direct marketers relied on research of public records of births, marriages, and property deeds. They bought mailing lists from catalog companies to reach out to potential customers. Audience segmentation and tracking purchase intent are not new strategies, but digital data collection has significantly increased their impact. And online consumers leave a digital data trail behind wherever they go.
Now that there is much more data available for marketers to use, behavioral targeting has become a much more popular tactic for media buying. Most digital advertising still relies on at least some information about individual attributes — like gender, geo-location, and age. But programmatic buyers and also have the ability to collect data related to online behaviors.
While a lot of privacy-conscious consumers delete cookies or use the “limit ad tracking” features on mobile devices, advertisers aren’t interested in personally sensitive information – like cheating on taxes or a romantic partner. They are more interested in behavioral data signals that indicates whether consumers are in the market for a car, house, or coffee maker. Social media sites or other login-based services have access to personal identifiable information (PII), but tying it to other data points would drive away customers. The ongoing stream of “shares”, “tweets”, “likes” — or other “reactions” — is revealing enough info to be worth a lot to advertisers – even without names and emails addresses.
Online activity allows data providers to identify specific audience segments, These segments can be defined by variables like (1) geolocation, (2) device type, (3) marital status, (4) income level, (5) profession, (6) shopping habits, (7) travel plans and a variety of other factors. These valuable segments can be sold to the highest bidder wanting to reach segments as specific as men in trouble or burdened by debt: small-town singles.
There are many players in the data game – and some play multiple roles.
Brands collect informationabout their customers, such as email addresses and purchase history, which is helpful when tailoring their experience through product recommendations or incentive offers.
Publishers sell data about readers who visit their site, which is valuable to advertisers purchasing ad space on their site – but can also be used to track their site visitors in other places online.
Other data collectors who may sell data may not be thought of as “ad industry” types at all, such as:
1. Political campaign groups often rent out their lists to firms as a fundraising strategy
2. Credit-card companies issued directly or through banks sell anonymized data to advertising companies – in cases where cards are issued directly, customers can be cookie’d whenever they login then go elsewhere online.
3. Online auctions offer a huge amount of user info, again anonymized, but revealing.
4. Any company, site or service that requires a login can collect data. For example, social media sites garner huge amounts of data as users “like” “tweet” and “share” about their interests.
The data game players are defined by how they collect and use data – either as first-party or third-party. First-party data is any information that’s collected by a company that has a direct relationship with the consumer. First party data tends to be considered as more valuable because it usually is more accurate and is free for the advertiser.
If we take the fictional example of Heart and Sole shoes, they would like collect data about customers’ style preferences and shoe size through the user’s’ purchase history.
If we look at a fictional online publisher, say Knitting News Weekly, they may associate an ID to anonymously track the articles that their visitors read and share
Another fictional example, like Gloria’s Games App might use an API to gather data themselves, for example, the most common geographic locations where the mobile app is used.
Some apps also use external SDKs — or a software development kits — from a technology provider that will track user data. In this scenario, the technology provider is a 3rd party data collector. And third party data is any data collected by platforms or services that do not have a direct relationship with the consumer. These service providers obtain data in many different ways, such as:
Paying a publisher to collect data about their visitors.
Or piecing together behavioral or interest profiles and audience segments to be sold to advertisers.
Let’s not forget the new comer to the data party – 2nd party data, which is essentially first-party data that you are getting directly from the source. Buyers and sellers can arrange a deal in which the first-source party offers specific data points, audiences, or hierarchies to the buyer. The sharing of high-quality, first-party data gives marketers access to many hard-to-find audiences they may not have been able to reach. Whether first-party or third-party, data is often housed and managed for programmatic buyers by a Data Management Platform – or DMP. DMP’s give marketers — and sellers of data — a centralized way to:
Create target audiences, based on a combination of in-depth first-party and third-party audience data;
Accurately target these audiences across third-party ad networks and exchanges,
Many brands still don’t take advantage of all the possibilities offered by programmatic advertising, preventing them from increasing the profitability of their media buy and maximizing their ROI.
Instead, if brands leveraged the potential of programmatic advertising they could broaden their audience, reaching twice as many unique users, increasing conversions by more than 36%, and reducing CPA vs. traditional online media buying methods.
Analyzing Campaign Errors
Digilant analyzed nearly 500 programmatic advertising campaigns and identified the seven most common mistakes made by media buyers that hinder performance of their campaigns.
Although digital marketing has become increasingly precise in its targeting, it’s still very common for advertisers to want to cover too many goals or KPIs at once with their programmatic investment. Advertisers should be clear in setting their KPIs to whether for example they are looking to increase brand awareness in a new market, drive online conversions or in-store traffic, or other goals. That starting point is imperative, the advertiser’s target must be aligned with the most appropriate programmatic tactics, which will ultimately improve campaign performance and ROI.
Failure to segment audience data using programmatic technology.
When provided with large volumes of user data, the possibilities of different types of audience segmentation are endless. There are about 200 individual data points associated with each online user, and by using dynamic programmatic reporting, marketers can create profiles that allow for real-time segmentation and thus increased performance. To capitalize on this enhanced campaign performance, the audience must be segmented at several levels. With each layer, the objective is to filter and eliminate users that do not fit the target audience for that brand.
Ranking users without considering their value.
By applying machine learning and using data from advertisers and third party data providers, it’s possible to determine the appropriate user profiles for the advertiser to target in real time that are most likely to convert. Skipping this step puts campaigns at risk for failure. After identifying users’ behaviors, predictive algorithms can be applied to determine the value of each profile and user in real time. Knowing the value of the user will allow the audience to be segmented efficiently and effectively, by focusing the campaign on the right users and increasing the investment on users who will be more prone to make a purchase.
After executing a campaign it’s important to reexamine consumer conversion data to optimize the effectiveness of future media buying actions, as brands can exponentially enhance the returns on their programmatic campaigns by knowing more about their user behaviors and attributes.
Delivering the same creatives to customers and leads.
One of the great strengths of programmatic advertising is its predictive ability. It is possible to apply data science algorithms to find potential “new consumers”, not just recycle the same users gained through retargeting.
But it would not make sense to send the same message to the every user. It is necessary to personalize the messages directed to the different profiles that the campaign wants to impact, using technologies like Dynamic Creative Optimization (DCO) to optimize the ad investment. This level of customization is not done as often as it could be for programmatic campaigns, which can negatively impact performance.
Low investment in attribution.
Insights gleaned from programmatic KPI metrics allow marketers to understand campaign performance at a level that is unmatched by other traditional channels such as print advertising or television. The added invested in attribution gives media buyers the opportunity to analyze the results beyond last click, which is a one dimensional view of online marketing and doesn’t allow for full funnel analysis.
Attribution allows you to understand how the media really affect results. For example, actions in the media may be linked to loyalty data or to credit card transactions; So by using attribution technology it is possible to measure the impact of a campaign or a channel on the final conversion of a new customer. In addition, advertisers can also analyze the impact of a campaign on the brand and the perception of users.
Campaign reports are not optimized for future strategies.
Programmatic ad buying provides more metrics, information and data than any other advertising medium. Taking advantage of these real-time stats can help brands and agencies discover ideas that are not always intuitive to them and guide the strategy of their next campaign.
For example, a sportswear retailer may be focussed on targeting a totally male audience. However, a programmatic campaign using intelligence gained through data science could reveal that its highest performing audience is actually in the segment of women aged 25-34.
Using the wrong marketing channels.
There are many ways to reach an audience programmatically — desktop, mobile, apps, video, native advertising, audio and traditional television, for example.
Each channel offers potential advantages and drawbacks that marketers need to carefully weigh when deciding where to allocate their ad spend. If the priority is to take a low-cost action with a quick return on advertising investment, it’s best to invest your budget in display. Video and audio justify the highest CPM if you pursue better brand recognition.
It is also important to keep cross-device segmentation in mind, as the average consumer connects to the Internet through five or more devices daily.
Programmatic ad buying relies on advanced data science solutions to provide marketers with a comprehensive understanding of their respective marketplace and at the same time gives them the tools they need to set out more precise guidelines for optimize advertising campaigns and increasing their ROI. However, many companies still treat their target audience as one large segment, often employing obsolete tactics without analyzing the consumer’s behaviors, interests and attitudes, to find the right segments within that large audience to target.
Advanced segmentation, especially adaptive segmentation allows you to identify the most essential existing audiences for a brand and uncover new key segments. It is as important to spend time with your media buyer to find the right tactics and channels for a programmatic campaign, as it is to learn from the results. The flexibility provided by programmatic advertising allows a continuous optimization during and after a campaign. The analysis and strategy prior, during and after the campaign will ensure that future media buys will have better results for the investment made
Too many campaigns are executed without having properly analyzed the value of each user, which is essential to effectively segment the audience, thus improving performance: investment should be increased in clients more prone to conversion.
The second most costly error: do not apply algorithms or look alike models to find potential “new consumers” by recycling users gained through retargeting. The messages are not targeted to the different profiles that the campaign wants to impact, and the investment is therefore not optimized.
Unclear objectives, mistaken marketing channels, inability to identify adequate data layers, poor measurement of objectives and not optimizing the information obtained are other frequent mistakes.
Properly using the potential of programmatic advertising allows advertisers to broaden their audience, reaching twice as many unique users, increasing conversions by more than 36%, and reducing CPA versus traditional online methods.
Back to School (BTS) season is the longest shopping event of the year. A 2016 survey from eMarketer found that 66% of shoppers planned on doing their back to school shopping between July 4 and Labor Day and 17% said that they plan on shopping on an “as-needed” basis.
College students start doing BTS searches while they are still at the beach. It’s important for marketing teams to understand the types of messages and call to actions customers would be most receptive to before planning their programmatic advertising campaigns so that they can get the biggest return on their investments. That’s why Digilant dove into the data to find out when and how marketing dollars should be spent.
BTS shoppers are now using all their devices to do their searches, so a cross-platform media buying strategy is absolutely necessary. Parents are browsing their desktops and iPads with their children, looking for BTS items but also shopping around for the best price. They are also using their mobile devices when they are in store, price-checking items and looking for coupons to download. Most buyers are not relying solely on brick-and-mortar stores anymore. Some buyers will rely solely on using online stores for their BTS shopping like Amazon.com and most others will shop at stores like Walmart, Macy’s and even CVS who offer a combination of online shopping and in-store returns, which has totally changed the Back to School shopping dynamic.
According to a RetailMeNot survey, top predicted days for BTS shopping in 2017 are:
Monday, 9/4/17 (Labor Day)
Digilant also discovered the following information about BTS shoppers:
Best Call to Actions:
88% of parents use coupons
Parents are also receptive to: promotional emails, promo codes and brands they already know
Programmatic media buys via DSPs usually materialize as a checklist of targeting tactics and bidding parameters pushed through a platform using an algorithm. When heralded as the power of machines over people, DSP-based programmatic buying can appear to be sterile and isolated from other channels of media delivery, such as search and social. The “human element” of programmatic buying usually refers to optimizations and analysis, when in reality, it is how a campaign is serviced that also makes the process human.
Too often, marketing goals dictate media plans that rely on dated programmatic tools, tech, and thinking. While there is a time and place for coloring within the lines and relying on those plans and approaches that have worked in the past, we need to sharpen our focus on creativity and experimentation and apply new data strategies within marketing plans.
The pre-planning process is not the only proper place for creativity! Programmatic media professionals are also creative thinkers and explorers on the front lines of innovation. How can we inject a new creative sensibility into programmatic? By prioritizing the human element of media buying. In short, we need to anticipate.
The case study of the Semmering Railway offers us a roadmap for what I’ll call Anticipation-Driven Creativity. Between 1848 and 1854, about 20,000 workers laid 41 kilometers of train tracks across the Semmering Pass in the Austrian Alps.a This was not an easy feat, as the mountains held especially steep grades with challenging turns, making them uniquely difficult to traverse. Neither surveying tools nor locomotive design available at that time could accommodate travel on the newly-laid tracks. In short, the Semmering Railway Project was laying tracks for a train that didn’t yet exist. They built the tracks knowing that one day, the train would come.
A competition asked entrants to design trains that would achieve what had been previously impossible. While none of the original four entrants were successful, “trials for a suitable locomotive led to a number of developments in this field of engineering, and in the end resulted in the invention of the Engerth locomotive.”bIn this case, the “thing” that was anticipated (a train that could make this unprecedented trip) forced the process to create the very thing they were anticipating when they laid the tracks.
Solutions-based partnerships ultimately fail without anticipation and human creativity. In fact, creativity needs to take its place at the very center of programmatic buying – to anticipate where tech could potentially go, and help us get there. To be better at what we do, we need to lay the metaphorical tracks, which will help us design the train fit to travel on them.
First, we need to build a level of trust that offers us the freedom to not only present new ideas, but more importantly, present new ideas for which there is no currently established proof that the idea will work. We need some leeway to be risk takers. Many will say, “What? That sounds like you want to allocate client spending to a leap of faith!” To which I would respond, “brands take risks in their creative processes all the time.”
Innovation is based on risk, but calculated, rooted in experience, information, and intelligence (should sound familiar to those working in the programmatic media buying space). The proliferation of think tanks within brands, like Nike’s Innovation Kitchen, helps break through the innovation clutter.c Additionally, the title “Chief Innovation Officer” within agencies and brands also indicates the value placed on calculated risk and innovation within the “creators” of media strategies and plans. Let’s inject this same approach into the practice of programmatic!
To do that, we need to transform programmatic’s “test and learn” mentality into an incubation mentality.Programmatic incubation fosters freer conversations about new capabilities and allows for greater risk in leading the technology where our clients’ marketing objectives need it to go.
If we were to generate programmatic “think tanks,” similar to our brand and agency colleagues and partners, we’d see a dramatic increase in programmatic innovation and creative thinking at the DSP-level. Not all of our ideas will work as originally designed (much like the 4 locomotive entrants in the Semmering Trials), but having designed them will allow us to push our programmatic thinking forward.
Let’s avoid making programmatic a rote exercise. We need to own programmatic creativity. We, as an industry, need to experiment more. Digilant has made the shift toward a more custom offering that is unique to the buyer, uncovering new data and audiences they wouldn’t have know about. The beauty of programmatic is its ability to make quick pivots; let’s use this to our advantage.
The Train Will Come
We, as an industry, should make anticipation a part of our daily approach to media buying. To that end, we should activate programmatic think tanks to innovate as the “human layer” on top of the programmatic tech layer. And with enough focused anticipation and experimental fearlessness, in every case, the train will come.
Personalization is the challenge that the majority of marketers face in the marketplace today. But the many providers out there competing for your marketing dollars are still only offering a selection of off-the-shelf solutions, as they attempt to keep their own costs down.
Everyone has access to the same data and the ad-tech ecosystem is overgrown with platforms that offer no great distinctions. The savviest of advertisers have advanced and are demanding control and customization from their programmatic advertising campaigns and they expect their suppliers to make the same leap.
Until now, the focus has been on developing advertising technology in silos in order to sell media services. But, as the technology efficiencies are maximized and commoditized, the focus shifted to unlocking value by leveraging assets that go beyond core capabilities. The best ingredient that is often left unexplored is the advertiser’s own data.
1st and 2nd Party Data
The most import and recent evolution in programmatic is the ability to use 1st party data (connecting CRM data to an advertiser’s media buy). To do this, independent data on-boarding service providers like LiveRamp and DataLogix are used to translate offline data signals to a digital user ID, so that programmatic companies like Digilant can now use off-line data in online media campaigns.
2nd party data, acquired through exclusive relationships with data providers, who do not sell their data in the open market, have also opened new opportunities for marketers who don’t want to buy the same 3rd party segments as their competitors. Programmatic providers can enrich an advertiser’s 1st party data or directly activate 2nd party data. Companies like Digilant are in a unique position to provide data intelligence to help advertisers make that data actionable.
With all the effort, platforms, people and cost involved in executing data driven programmatic advertising, the recipe for success is not pre-packaged. Marketers now expect that every aspect of programmatic can be customized — from funnels and segmentation to AI models, creative, and cross-channel messaging strategies. Instead of pushing products, platforms and data – the future for programmatic companies is personalization, resulting in a solution for marketers that is Customatic.
Like what you see? Join the 500+ clients that have partnered with Digilant.