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.

3. 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 of 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.

4. 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.

5. 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 investment 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 affects 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.

6. 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.

7. 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.