The 7 Most Common Errors Programmatic Media Buyers Should Avoid

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.

  1. Vague or overambitious campaign goals.

    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.

  2. 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.

  1. 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.

  1. 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.

  1. 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.

  1. 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.

  1. 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

Summary 

  • 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.

How to Make Programmatic Advertising Not Fail for You?

The metaphors are all real: Digital marketing is the Wild West, the final frontier, the Game of proverbial Thrones. But how do you win?

Original post by: Every Market Media
By using quality data to custom craft targeted profiles for programmatic advertising. At least, that’s one way.
Listen to Rick Holmes interview Alan Osetek, CEO of Digilant, a global programmatic solutions provider, and find out how not to fail when the stakes are almost as high as the competition is fierce.

One-to-one programmatic

When you’re a provider using first, second, and third party data to reach consumer prospects online, you hear a lot of buzzwords around “programmatic.” But one that’s not an exaggeration is the level of competition in a digital market.

Osetek, who explains programmatic to end user marketers in terms of a war to reach consumers, knows it really is a war to reach anyone in a highly competitive, noisy market. And whether you’re trying to sell toothpaste or data as a service, you’re going to need to use data to give yourself a serious advantage in finding and keeping customers.

1:1 programmatic
“So in the war to reach consumers in a B2B environment, we use the analogy of the HBO show Game of Thrones,” Osetek explains. The simple fact is that social and programmatic are quickly becoming the mainstay of how you reach people online.

“We’ve moved from a world where digital and, specifically, data was the way to reach mass audiences through TV or radio, to a world of segmented search audiences,” he says. “Now, you search for clusters or segments of people and to build custom personas and profiles.”
It’s no good to market to just anyone, because that’s a huge waste of time and money. You need to have an ideal customer in mind and use programmatic to create a profile of real people who match up the most closely.

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Part art, part science

Programmatic is moving to a one-to-one world online where digital will look a lot like what direct mail intel marketing has been in the last 50 years. Smart people use first, second, and third party data sets, merge them together, and build a profile.

You could be trying to build a B2C profile, say, a soccer mom. Or it could be a B2B profile, a data scientist working in the pharma industry. Either way, you start with a premise and look for different data sets that will help you meet that criteria.

he best profiles, the ones made at Digilant, are custom created for each client. So two different clients, like the B2C or B2B, will get totally custom approaches to those groups.

Every marketer is looking to reach a different audience, so every solution to digital marketing problems should be different, too. Digilant builds behind the scenes modules with algorithms that may use the same process or methodology to craft a profile, but the data input into the system is completely unique for each customer.
“The data world now is still the Wild West,” Osetek says. “You have some large established players of third party data sets, but you also have all sorts of private marketplace deals going on. These aren’t as well-known but are very high quality.”

The science part of programmatic is the programming, obviously.

The art part, however, is finding those niche data sets and making the private marketplace deals with publishers or third party data marketers that drive straight to the heart of the customer profile.

Data sets in programmatic

In contextual marketing, “data set” means the visitors to a given internet piece of content.

Like people who visit a forum to read about a vehicle. If you sell a part for that vehicle, the data of who goes to that site will be super valuable to your company, because the people in that data set already want what you have.
contextual targetingUsing targeting display ads and building context for data sets can be very hard. (As in, if everyone could do it, there wouldn’t be a marketing war.)

How do you make contextual marketing not arduous? Mining the right keywords.

To build a good data set, you have to index many sites—4 or 5 million sites—daily to look for keywords that relate to something (toothpaste, cars, chips, wind energy, whatever).

In B2B, for example, there can be hundreds of thousands of keyword generated by search engine marketing. It would be a royal waste of time to comb through all those, but what happens if you take the most relevant 10 or 15 keywords?

Then you can examine those keywords used in the last two months and use that to create a precise persona. Actually, this way, Digilant can look at both positive or negative sentiment built in for marketers.

“So we do retargeting and remonetizing people who have been at a site,” Osetek explains. “It’s a list building technique, a keyword search in reverse.”

Most B2B and B2C marketers are spending a lot of money in search. How do people coming from a search background successfully bring search and programmatic together?

A word of advice: It’s way better to get your own keywords and contextual targeting in programmatic so you aren’t reliant on the keywords or modifications made up by some other company’s data scientists.

Programmatic helps sales marketers extend search by doing search keyword retargeting using an audience extension technique. Digilant takes keyword search techniques and extends them out to reach a new audience—to go find other sites that are contextually linked to those keywords.

This is the whole beauty of programmatic—not having to market even to a segment but to an individually crafted group of consumers attuned exactly to your profile.

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